Datasets:

TomTBT

/

pmc_open_access_xml

like 5

[ "<title>Introduction</title>", "<p>Protein deamidation occurs spontaneously in proteins at level of unstable Asn residues, which are flanked, on the α-carboxyl side, by small non-bulky residues, such as Gly, Ala, Ser or Thr ##REF##7887885##[1]##, ##REF##12726775##[2]##. The deamidation mechanism entails the nucleophilic attack of the peptidyl nitrogen of the Asn+1 residue onto the β-carbonyl carbon of the Asn, leading to the formation of an aspartyl succinimidyl (ASU) intermediate, with the elimination of the ammonia moiety. (##FIG##0##Fig. 1##). ASU itself is unstable and its ring can open on either side of the nitrogen atom, yielding either a normal peptide or an atypical isopeptide containing a β-linked isoaspartyl residue (isoAsp) ##REF##11158575##[3]##, ##REF##10708396##[4]## the latter form being generally prevalent ##REF##10708396##[4]##. The occurrence of such an abnormal residue can significantly alter protein structure and function, as it has been demonstrated for epidermal growth factor, calmodulin, tubulin, synapsin, eye lens crystallins, Alzheimer's β-amyloid, tissue plasminogen activator ##REF##12943218##[5]## collagen type-I ##REF##14729060##[6]##, Protein Kinase A ##REF##10684253##[7]## and others.</p>", "<p>Protein isoaspartyl carboxyl <italic>O</italic>-methyltransferase (PCMT; 2.1.1.77) is a S-adenosylmethionine (AdoMet)–dependent methyltransferase, which specifically recognizes and methyl esterifies the free α-carboxyl groups of the isoaspartyl residues, raising from asparaginyl deamidation. This enzyme, hence, promotes the conversion of the abnormal L-isoAsp residue into L-aspartyl, eliminating the isopeptide bond which alters protein conformation, thus preventing the accumulation of dysfunctional proteins. This methylation-dependent repair activity has been demonstrated <italic>in vitro</italic>, with synthetic isoAsp-containing peptides as well as with deamidated purified proteins. Various <italic>ex vivo</italic> studies confirmed that a PCMT activity is related to the processing of deamidated-isomerized proteins. For example in the erythrocytes from patients with spherocytosis ##REF##8611472##[8]## or with a G6PD deficiency ##REF##11985579##[9]## the increase in membrane protein isomerization, associated with the disease, could be monitored <italic>ex vivo</italic> by an increase in methyl ester formation in the intact erythrocytes. On the other hand, in chronic renal failure, where PCMT is inhibited by the intracellular accumulation of S-adenosylhomocysteine, membrane proteins tend to accumulate isomerized aspartyls within the red cell membrane ##REF##8514862##[10]##. Further <italic>in vivo</italic> studies provided evidence on the role of this enzyme in preventing the accumulation of potentially harmful damaged proteins. In <italic>PCMT</italic> knockout mice isomerized proteins increased 4–8 fold compared with the levels detected in the wild-type mice, and the knockout animals exhibited brain damage and fatal epileptic seizures ##REF##9177182##[11]##.</p>", "<p>A number of cell stress conditions have been linked to an increased propensity of proteins to undergo deamidation. Oxidative conditions have been considered as a way through which proteins become more susceptible to deamidation. The underlying mechanism is still unclear, although the evidence suggests that oxidative conditions may induce an increased flexibility of the polypeptide backbone or a transient unfolding of proteins, allowing Asn deamidation and enhancing the formation of L-isoAsp residues. In this respect it has been shown that erythrocytes from glucose-6-phosphate dehydrogenase (G6PD)-deficient patients display a higher propensity to deamidation at membrane protein level ##REF##11985579##[9]##. Moreover, UV irradiation, which causes an increased formation of reactive oxygen species, leads to an increased protein deamidation in cultured melanoma cells ##REF##11425484##[12]##. On the other hand, analysis of the <italic>PCMT</italic> gene provided interesting clues about the regulation of this enzyme. This gene contains several motifs, as potential regulation sites in response to different stress conditions ##REF##8914929##[13]##.</p>", "<p>It has been proposed that protein methyl esterification, catalyzed by PCMT, may be able to mediate protection from apoptosis induced by Bax in a neuronal cell line ##REF##10580153##[14]##. This interpretation relies upon the evidence that cotransfection with a <italic>PCMT</italic> carrying vector prevents apoptosis induced by Bax, in this system. More recently it has been shown that Bcl-x_L, an antiapoptotic member of the Bcl2 protein family, contains two labile asparaginyl sites which are deamidation-prone (i.e. positions 52 and 66) ##REF##12372300##[15]##. The deamidated Bcl-x_L is not more able to block the action of pro-apoptotic proteins thus leading to cell death. A transient intracellular alkalinization has been related to Bcl-x_L isomerization during cell stress ##REF##17177603##[16]##. It is worth noting in this respect that general alkaline pH conditions increase the tendency of labile asparaginyl residues to form ASU. Consistent with these observations the rate of Bcl-x_L deamidation was found to be significantly reduced in hepatocellular carcinomas compared to normal liver tissue and this has been linked to a resistance of the transformed cells to undergo apoptosis ##REF##12810626##[17]##.</p>", "<p>We report here that PCMT, when overexpressed in endothelial cells, is able to prevent apoptosis induced by an oxidative treatment. Experiments using PCMT negative dominants show that the enzymatic activity must be preserved in order to exert its antiaptotic effect. In order to identify molecular mediators of apoptotic cascade involved in this mechanism, and specifically recognized and modified by PCMT, we have employed the human recombinant enzyme as a specific ligand. We thus identify in our experimental system, a number of methyltransferase targets, also including Bcl-x_L. We could therefore infer the role of protein methylation in apoptotic cell death and its underlying implications.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Materials</title>", "<p>The plasmid encoding the GFP was from Stratagene (USA). <italic>E. Coli</italic> strain DH5a was used as a host for the plasmids and cloning procedures, and BMH71-18 <italic>mut</italic>S was used in the mutagenesis step (Clontech, Palo Alto, CA, USA). Bl21, Sulfo-SBED and Immunopure immobilized monomeric avidin beads were purchased from Pierce (Rockford, IL, USA). DTT, ACTH, Renin, and Angiotensin I were from Sigma (St. Louis, MO, USA). DMEM, RPMI and FBS were purchased from Life technologies (Invitrogen S.R.L., Milan, Italy). Trypsin sequencing grade (Product number V5111) was from Promega (Madison, Wisconsin, USA). Protein standards and Iodoacetamide were from BioRad laboratories (Milan, Italy). Water and Acetonitrile were HPLC grade (Sigma). S-adenosyl-L-[methyl-¹⁴C]Met [specific activity (sp. act.) 50 mCi/mmol] was purchased from Amersham International (Buckinghamshire, UK). <italic>S</italic>-adenosyl-L-[methyl-³H]Met (sp. act. 500 mCi/mmol) and S-adenosyl-L-[methyl-¹⁴C]Met (sp. act. 50 mCi/mmol) were purchased from Amersham International (Little Chalfont, Buckinghamshire, UK). All standards and reagents were from Sigma Chemical Co. and were of the purest grade available.</p>", "<title>PCMT clone</title>", "<p>The pBluescript II SK-based plasmid construct pDm2X, containing human PCMT isoform II cDNA, and polyclonal antibodies against the C-terminal dodecapeptide of PCMT were generously provided by Dr. Steven Clarke (Department of Chemistry and Biochemistry and the Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA).</p>", "<title>Cell Culture and Transient Expression</title>", "<p>PAEC were grown on 24–well plates, in DMEM supplemented with 10% FCS and 1× penicillin/streptomycin. Cells were maintained at 37°C in humidified air with 5%CO₂ atmosphere. For transient transfection by electroporation, PAEC growing in 150 cm² flasks were tripsinized before confluence, collected by centrifugation, washed with PBS and resuspended in 20 mM HEPES buffer at pH 7.4, containing 137 mM NaCl, 5 mM KCl, 0.7 mM NaH₂PO₄ 6 mM glucose, at 4°C.</p>", "<p>HUVECs from American Type Culture Collection were maintained in RPMI 1640 with 10% FCS and 2 mM glutamine, and were used at passages 5 to 10. Co-transfections were performed by mixing 15 µg of each pcDNA3.1 construct and 2 µg EGFP control. Cells were exposed to a pulsed electric field that corresponded to a field strength of 0.75 kV/cm and a duration ranging from 9 to 12 ms using electroporation cuvette and Gene Pulser II (Bio-Rad Laboratories, Hercules,. CA, USA). Samples were incubated on ice for a further 5 min, then transferred to a 10 cm diameter tissue culture dish and incubated at 37°C under standard growth conditions. After transfection, cells were plated for 16 h in DMEM supplemented with 10% FCS. Medium was replaced after 24 h.</p>", "<title>Mutagenesis</title>", "<p>Mutagenesis was performed by Transformer Site-Directed Mutagenesis kit from Clontech (Palo Alto, CA). Of the three highly conserved methyltransferase sequence motifs we chose to perform mutagenesis of the invariable aspartyl site within sequence motif I (<named-content content-type=\"gene\">AL<underline>D</underline>VGSGSGI</named-content>), involved in the AdoMet binding site ##REF##2684970##[18]##, ##REF##8179327##[19]##. The mutagenesis primer was <named-content content-type=\"gene\">5′-ggagctaaagctcttttcgtaggatctgg-3′</named-content>, (Asp replaced by Phe); <named-content content-type=\"gene\">5′ ggagctaaagctcttgtcgtaggatctgg3′</named-content> (Asp mutated into Val). The selection primer was <named-content content-type=\"gene\">5′-caggaaagaagatctgagcaaaag-3′</named-content>. A unique restriction site (<italic>Afl</italic>III) was replaced with a new unique restriction site (<italic>Bgl</italic>II). Sequencing of double-stranded plasmid DNA by the Sanger method was used to confirm the desired nucleotide substitution.</p>", "<title>Characterization of PCMT plasmid <italic>constructs</italic>\n</title>", "<p>PCMT activity in endothelial cells transfected with vectors carrying <italic>PCMT</italic> sense or antisense or either mutants, was detected by means of the radiochemical assay described by Macfarlane, using ovalbumin as a standard methyl-accepting substrate ##REF##6198323##[41]##. One enzyme unit is defined as 1 pmol methyl groups transferred×min⁻¹.</p>", "<title>Plasmids</title>", "<title>pcDNA3.1 wild type</title>", "<p>Construction of mammalian expression plasmid encoding human PCMT was subcloned from construct pDM2X used for mutagenesis, into pcDNA3.1, using the <italic>Kpn</italic>I and <italic>Hind</italic>III restriction sites.</p>", "<title>pcDNA3.1 antisense</title>", "<p>The cDNA was subcloned from pcDNA3.1 wild type.</p>", "<title>pcDNA3.1 mut phe</title>", "<p>pcDNA3.1 encoding for mutated PCMT Asp83→Phe was subcloned from construct pDM2X mut Phe into pcDNA3.1 using the <italic>Kpn</italic>I and <italic>Hind</italic>III restriction sites.</p>", "<title>pcDNA3.1 mut Val</title>", "<p>pcDNA3.1 encoding for mutated PCMT Asp83→Val was subcloned from construct pDM2X mut Val into pcDNA3.1 using the KpnI and HindIII restriction sites.</p>", "<title>Apoptosis Assay</title>", "<p>Endothelial cells were grown to 70% to 80% confluence and incubated for 18 h in the absence or the presence of 0.1, 0.2, 0.3, 0.4 or 0.5 mM H₂O₂. Parallel samples were treated with 35 mM Cisplatin for 18 h as a positive apoptosis control. The optimal active H₂O₂ concentration and exposure time were selected by determining dose-response and time curve. Under these conditions, the assay was linearly dependent on H₂O₂ concentration and incubation time. Longer incubation periods or higher H₂O₂ concentrations resulted in massive cell death. Apoptosis was assayed <italic>in vitro</italic> by a combination of three distinct approaches on endothelial cells transfected with vectors carrying <italic>PCMT</italic> sense or antisense or either mutants.</p>", "<title>Caspase-3 activity and PARP cleavage</title>", "<p>After oxidative injury, cells were collected and lysed in the appropriate buffer. Total cell extracts (30 to 50 µg) were electrophoresed onto a 12.5% SDS-PAGE gel system and transferred onto polyvinylidene difluoride membrane (Millipore S.p.A, Milan, Italy). Blots were incubated with a polyclonal anti-caspase-3 antibody (BD-PharMingen Milan, Italy), or mouse polyclonal antipoly (ADP-ribose) polimerase (PARP). Total active caspase-3 and PARP bands were revealed by chemiluminescence (Amersham-Pharmacia Biotech).</p>", "<title>DNA ladder</title>", "<p>Cells treated as above were harvested and DNA was extracted using the Apoptotic DNA ladder Kit (Roche Diagnostics S.p.A., Monza, Italy). DNA Ladder profiles were detected upon electrophoresis on 2% agarose gel.</p>", "<title>FACS scan analysis</title>", "<p>Six hours after the removal of the stimulus, apoptosis was checked by detected fluorescence microscopy. FACS analysis (FACSCalibur; Becton-Dickinson, San Jose, CA, USA) was performed after treating cells pellets (approx 10⁶ cells) with 50 µg/ml propidium iodide (PI) in 0.1% sodium citrate, in the presence of 0.1% Nonidet P40 and 100 µg/ml Dnase-free RNase A (Boeringer Mannheim, Milan Italy). Integration of area under the pre-G0 peak was measured to quantify percentages of apoptotic cells.</p>", "<title>Human recombinant PCMT purification</title>", "<p>\n<italic>E. Coli</italic> strain DH5a was used for cloning and propagation of plasmid constructs. For <italic>PCMT</italic> overexpression, <italic>E. Coli</italic> strain BL21 (DE3) was transformed with pDM2x expression plasmid and grown in Luria-Bertani medium, in the presence of 100 mg/mL ampicillin. PCMT was purified from transformed bacteria basically as described by MacLaren and Clarke 1995 ##REF##7756844##[42]##, except that the original DEAE-cellulose chromatography final step, under non-equilibrium conditions, was replaced by Q-Sepharose HP chromatography, using a Hiload 26/10 column (Pharmacia, Uppsala, Sweden). Column was equilibrated with buffer A (20 mM Tris-HCl, 0.2 mM EDTA disodium salt, 10% wt/vol glycerol, 15 mM beta-mercaptoethanol, 25 mM phenylmethylsulfonyl fluoride, 0.1 M NaCl, pH 8.0). After sample loading (10 mL, 6 mg/mL protein concentration), the column was washed with 10 volumes of buffer A (at 1 mL/min flow rate), followed by a linear gradient from 0.1 to 0.7 M NaCl over 210 minutes.</p>", "<title>Quantitation of isoaspartyl residues in cells lysates after oxidative stress</title>", "<p>Cells transfected with PCMT wild type (sense), antisense PCMT, PCMT mutants (Asp₈₃ →Phe and PCMT Asp₈₃→Val) and untransfected endothelial cells were stressed with 0.3 mM of H₂O₂. Deamidated proteins were detected in each lysate preparation by an in vitro assay using recombinant PCMT. Damaged residues were specifically recognized and methyl esterified by PCMT, using radiolabeled AdoMet as the methyl donor, under conditions designed to insure complete labeling, on a 1∶1 molar ratio, of accessible damaged residues in proteins. This method has proven highly sensitive, specific, reproducible, and particularly suitable when analysis of deamidated protein mixtures is to be carried out ##UREF##2##[43]##.</p>", "<title>Identification of PCMT substrates</title>", "<p>In order to identify specific PCMT substrates, HUVEC were infected with PCMT antisense and stressed with 0.1 mM H₂O₂. Cell lysates were prepared as above and analyzed by 2D-gel electrophoresis according to Zhu et al ##REF##16959769##[44]##.</p>", "<title>Generation of the retrovirus</title>", "<p>An 800-bp genomic sequence including either <italic>wild type PCMT</italic> or its antisense counterpart was cloned upstream from the IRES of the MSCV-IRES-GFP (MIGR) (murine stem cell virus-internal ribosome entry site-green fluorescent protein) retrovirus. Infectious defective virions were transiently produced by transfection of the 293 FT cell line with 3 plasmids: pCMV gag-pol, pCMV-VSV-G (vesicular stomatite virus envelope glycoprotein). Briefly, 293 FT cells were seeded at a concentration of 10⁶ cells per well in 6-wells plates. The next day, 0.5 µg of each plasmid was cotransfected using Exgen reagent (Euromedex, Mundolshein, France) according to the manufacturer's recommendations. Supernatants were collected after 48, 72, and 96 h and concentrated 20-fold over an amicon membrane (Centricon Plus-80; Millipore, St-Quentin en Yvelines, France). Viral titers were determined by limiting dilution assay on NIH 3T3 cells. GFP fluorescence was analyzed by flow cytometry. Virus stocks containing 10⁷ infectious particles per milliliter or more were used to infect HUVEC (ATCC- CRL-1730).</p>", "<title>Quantitative real-time -PCR</title>", "<p>RNA was extracted from the antisense PCMT-transduced cells and non-transfected HUVEC by a double Trizol- chloroform treatment and precipitated in isopropanol. Total RNA. 250 ng, was reverse transcribed using the Superscript II (Invitrogen), where the reaction mixture contained forward primer for <italic>PCMT</italic> (<named-content content-type=\"gene\">5′- TTAAAGCCCGGAGGAAGATT3′</named-content>) and, as the reverse, the oligodT examer included in the kit.</p>", "<p>The specific <italic>PCMT</italic> cDNA was then amplified in the presence of 1× SYBR green by for quantification by real time PCR. using an iCycler iQ machine (BiorRad, inc.); primers pairs used were <named-content content-type=\"gene\">5′-TTAAAGCCCGGAGGAAGATT3′</named-content> and <named-content content-type=\"gene\">5′-ATCACTTCCACCTGGACCAC-3</named-content>, designed to amplify 169 bp region of <italic>PCMT</italic> cDNA.</p>", "<p>Relative expression was calculated using the ΔCt method. To determine the quantity of <italic>PCMT</italic> transcript present in the antisense-<italic>PCMT</italic>-infected HUVEC, relative to uninfected ones, their respective Ct values were first normalized by subtracting the Ct value obtained from the evaluation of the <italic>GAPDH</italic> transcript, chosen as an housekeeping gene (ΔCt = Ct<italic>_PCMT</italic>−Ct<italic>_GAPDH</italic>). The relative abundance of <italic>PCMT</italic> transcript in the infected HUVEC compared with uninfected cells was calculated by subtracting the normalized Ct values obtained for uninfected cells from those obtained from antisense-<italic>PCMT</italic> infected cells (ΔΔCt = ΔCt_infected−ΔCt_uninfected; the relative expression was then determined (2^−ΔΔCt). The the value of 2^−ΔΔCt&gt;1 reflects increased expression of the target <italic>PCMT</italic> gene, and a value of 2^−ΔΔCt&lt;1 points to a decrease in the gene expression ##UREF##3##[45]##.</p>", "<title>Crosslinking reaction</title>", "<p>PCMT was dissolved at 1 mg/mL in phosphate buffer (0.1 M phosphate, 0.18 M Na, pH 7.5). 1.12 mg of SulfoSBED was weighed and dissolved in DMSO under subdued light immediately before use. PCMT and sulfoSBED solutions were combined and maintained under subdued light with aluminum foil wrapping for 30–60 min at room temperature and nonreacted SulfoSBED was removed from solution by dialysis using Slide-A-Lyzer Dialysis Cassette (Pierce). 5 mg of proteins extracted from HUVEC cells line after infection with PCMT antisense carrying retrovirus and treated for 24 h with 0.1 mM H₂O₂, were dissolved in 0.5 ml PBS and incubated at room temperature for 3–5 minutes with the biotinylated complex. A 365 nm UV lamp (Rad-Free Model RF UV-365, Schleicher and Schuell, Keene, NH, USA), held at 5 cm distance from sample solutions, was used to activate the arylazide portion of the crosslinker. Samples were reduced by adding DTT to a final concentration of 50 mM and incubating for 1 h at room temperature.</p>", "<title>Binding biotinylated proteins</title>", "<p>Avidin affinity capture of biotinylated species was performed using immobilized monomeric avidin. Small batches (typically 100 µl) of beads in 50% aqueous suspension (MagPrep Streptavidin Beads purchased from Novagen, Merck chemicals Ltd, Nottingham, UK) were prepared for use into a clean 1.5 ml microcentrifuge tube and placed in magnetic tube rack, following wash with 400 µl of 0.1 M phosphate buffer (pH 7.5, 0.18 M Na) and the aqueous supernatant removed. The beads were washed twice and resuspended to their original volume then incubated for 30 min at RT with purified biotinylated target protein. After the binding, the excess of protein was taken away by magnetizing the beads and removing the aqueous phase.</p>", "<title>2D analysis and MALDI-TOF</title>", "<p>Gels were stained with Coomassie blue and spots of interest were identified by comparing gel images as appropriate. Spots of interest were then cut and submitted to the Proteomics Core. The samples were transferred to the MassPrep station for automated in-gel protein digestion, following the protocol included with the WinPREP Multiprobe II software (WinPREP Multiprobe II; Perkin Elmer, Massachussets, USA). Briefly, gel pieces were de-stained with ammonium bicarbonate/acetonitrile and reduced with dithiothreitol. The reducing mixture was removed and iodoacetamide in ammonium bicarbonate added and incubated for 20 min at 37°C. The alkylation solution was removed, followed by washing with ammonium bicarbonate/water and dehydration with acetonitrile. In-gel digestion of the extracted proteins was carried out with 6 ng/µL trypsin in 50 mM ammonium bicarbonate for 5 h at 37°C. The digested peptides were extracted in a mixture of 1% formic acid/2% acetonitrile and applied onto a stainless steel MALDI plate (Micromass). Mass spectra of the resulting peptides were recorded on the MALDI-TOF spectrometer in reflectron mode (Perkin Elmer Mass Prep Station; Micromass Maldi-TOF RL). Prior to data collection, calibration was performed with Angiotensin I (Average molecular mass 1296.5 Da), Renin (Average molecular mass 1759.0, Da), and ACTH 18–39 clip (adenocorticotropic hormone clip 18–39, average molecular mass 2465.199 Da). Sofware MassLynx 4.0 (Micromass); ProteinLynx 2.0 (Micromass) was used for processing, background subtraction, and some supplemental analysis. Resulting peptides were matched with their corresponding proteins with XProteo (XProteo: fast, reliable protein identification), by searching the non-redundant database maintained at the NCBI (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www3.ncbi.nlm.nih.gov/\">http://www3.ncbi.nlm.nih.gov/</ext-link>). In order to produce a putative protein identification and score, the following parameters were used for search: mass tolerance 0.07 Da, incomplete cleavages allowed, alkylation of Cys and oxidation of Met were considered as possible modifications. Percentage of sequence coverage (%) was indicated for each protein assignment. Z-score is defined as the distance to the population mean in unit of standard deviation. It also corresponds to the percentile of the search in the random match population (according to ProFound - Peptide Mapping Version 4.10.5 - The Rockefeller University Edition).</p>" ]

[ "<title>Results</title>", "<title>Characterization of PCMT plasmid constructs</title>", "<p>Porcine aortic endothelial cells (PAEC) were transfected with plasmid constructs carrying the <italic>PCMT</italic> sense or the antisense genes or either negative dominant mutants (Asp83→Phe and Asp83→Val), as described under “<xref ref-type=\"sec\" rid=\"s4\">Methods</xref>”. The site of mutagenesis, which affects a conserved residue in sequence motif I, involved in AdoMet binding ##REF##2684970##[18]##, ##REF##8179327##[19]##, was chosen on the basis of the information available on PCMT structure and on its catalytic mechanism.</p>", "<p>PAEC extracts were then used as a PCMT source to check whether transfection successfully produced the overexpression of the proper protein species (wild type or mutant) or, in the case of antisense, silenced the endogenous <italic>PCMT</italic>. Methyltransferase activity was assayed, according to the vapor diffusion assay procedure, in the presence of saturating concentrations of both the methyl donor AdoMet and ovalbumin, a common <italic>in vitro</italic> methyl accepting substrate.</p>", "<p>Results in ##FIG##1##Fig. 2 panel A## show that PAEC transfected with the sense <italic>PCMT</italic> gene displayed an increased methyltransferase activity, compared either with the antisense <italic>PCMT</italic> transfectants or with both negative mutants.</p>", "<p>The same cell extracts were then analyzed by SDS-PAGE and Western blot, using a PCMT antipeptide antibody. All transfectants carrying <italic>PCMT</italic> sense (wild type or mutants) over-expressed the relevant protein, while the protein signal was almost undetectable in those carrying the antisense counterpart (##FIG##1##Fig. 2, panel B##). These results demonstrated that PAEC, transfected with either PCMT Asp83→Phe or Asp83→Val plasmids effectively overexpress the relevant mutant proteins, where the conserved Asp83 residue in the consensus region I is substituted by a residue with a non polar side chain. As the result, the mutant proteins are devoid of catalytic activity. Transient transfection of PAEC with a plasmid carrying the antisense <italic>PCMT</italic> significantly lowers the activity of the endogenous methyltransferase, by critically reducing its expression. Consequently PAEC transiently transfected with plasmids carrying various <italic>PCMT</italic> constructs, can be used as a model system to study the role of PCMT on apoptosis induced by an oxidative stress.</p>", "<title>PCMT overexpression prevents apoptosis induced by H₂O₂ treatment in endothelial cells</title>", "<p>PAEC transfected with plasmids carrying <italic>PCMT</italic> wild type, mutants or antisense, were exposed to an oxidative stress brought by H₂O₂ treatment, as described in the experimental section. Apoptosis was monitored by the occurrence of DNA fragmentation, according to the typical DNA ladder pattern. In addition, caspase 3 activation was detected in cell extracts by SDS-PAGE Western blot analysis using an anti-caspase 3 antibody, which specifically recognizes the cleaved (activated) form of this enzyme. The activation of the apoptosis cascade was further confirmed by checking PARP cleavage, as a typical caspase 3 substrate.</p>", "<p>\n##FIG##2##Fig. 3 column A## shows the results of the DNA fragmentation (ladder) detection assay. Treatment with 0.1 mM H₂O₂ was fully effective inducing apoptosis in PAEC cells transfected with the antisense <italic>PCMT</italic> plasmid, compared with the cells overexpressing the catalytically active “sense” <italic>PCMT</italic>. The latter transfectants were in fact resistant to H₂O₂ treatment, up to a concentration of the oxidant in between 0.3 and 0.4 mM. As for the mutants, cells overexpressing either Asp83→Val or Asp83→Phe PCMT showed a sensitivity to H₂O₂ comparable with that observed in the antisense <italic>PCMT</italic> transfectants, since 0.1 mM H₂O₂ is sufficient to generate an evident DNA fragmentation.</p>", "<p>The enhanced sensitivity to the proapoptotic stimulus revealed by the DNA ladder assay was further confirmed by SDS-PAGE Western blot experiments, aimed at the detection of caspase-3 activation and poly (ADP-ribose) polimerase (PARP) cleavage (##FIG##2##Fig. 3 column B##). In cells transfected with antisense <italic>PCMT</italic>, indeed, apoptosis was apparent even at 0.1 mM H₂O₂ concentration. A similar behavior was observed in cells transfected with either <italic>PCMT</italic> mutants, in which apoptosis markers appeared already at 0.1 mM H₂O₂ concentration. Conversely, in the sense <italic>PCMT</italic> transfectants both markers of apoptosis were detected only at a H₂O₂ concentration in between 0.3 and 0.4 mM.</p>", "<p>These results, as a whole, demonstrated that PCMT overexpression is able to raise the threshold of cell sensitivity to apoptosis induced by oxidative stress up to a H₂O₂ concentration approaching 0.4 mM.</p>", "<p>In order to quantitate the effects of the oxidative treatment on the induction of apoptosis, cells were also analyzed by flow cytometry. PAEC samples transfected with plasmids carrying wild type or antisense or negative dominant mutants of <italic>PCMT</italic>, were subject to oxidative, pro-apoptotic treatment using 0.3 mM H₂O₂. This value, indeed, represented a clear cut off concentration which was able to induce apoptosis only in the negative dominants (<italic>PCMT</italic> antisense or mutants), according to the markers so far employed. Results of the FACS analysis basically confirmed that overexpression of wild type <italic>PCMT</italic> prevents apoptosis induced by an oxidative stress, as judged by the appearance of a pre-G₀ peak in both the antisense and mutant <italic>PCMT</italic> cell samples, upon H₂O₂ treatment (##FIG##2##Fig. 3 column C##). The evaluation of the area under the peaks allowed a quantitative assessment of the different cell subpopulations. Results showed that overexpression of wild type <italic>PCMT</italic> renders cells resistant to apoptosis, while a high percentage of cells transfected with antisense or either negative mutants undergo apoptosis upon H₂O₂ treatment.</p>", "<title>Accumulation of deamidated isoaspartyl-containing proteins in PCMT negative dominants</title>", "<p>It is conceivable that the reduced PCMT activity in PAEC transfected with antisense or <italic>PCMT</italic> mutants may determine a significant build up of isoaspartyl-containing damaged proteins. Therefore we attempted: a) to establish whether or not <italic>PCMT</italic> overexpression was able to prevent the accumulation of deamidated-isomerized proteins, in PAEC upon oxidative pro-apoptotic treatment; b) to quantitatively evaluate the amount of isoAsp sites in proteins extracted from these cells. To this end an <italic>in vitro</italic> assay, using recombinant PCMT, was employed.</p>", "<p>Results showed that transiently transfected PAEC were all characterized by a high content of deamidated proteins, except those overexpressing the wild type <italic>PCMT</italic> gene (##FIG##3##Fig. 4##). Therefore, the ability of PCMT to prevent apoptosis upon oxidative treatment was strictly dependent on the retention of its catalytic activity. In fact negative dominants, carrying a point mutation involving the catalytic site of the enzyme, accumulated isomerized-damaged proteins and, hence, were more sensitive to the pro-apoptotic stimulus. These results led us to exclude that PCMT may prevent apoptosis though a direct interaction of the enzymatic protein with members of the apoptotic cascade. Such a direct interaction mechanism is instead operative in <italic>E. Coli</italic>, where <italic>PCMT</italic> overexpression improved heat shock survival by a mechanism independent of its methyltransferase activity ##REF##14527954##[20]##.</p>", "<p>More remarkably, our results demonstrate that some molecular mediators, involved in apoptosis induced by pro-oxidant conditions, are deamidated proteins, which can be methylated by PCMT, since they contains the unique feature recognized by this enzyme: the isoaspartyl residue. We were then prompted to search for substrates of PCMT whose deamidation could be favored under oxidative pro-apoptotic conditions and which could no longer be “repaired” in the negative dominants.</p>", "<title>Identification of PCMT substrates</title>", "<p>In order to identify specific methyl accepting substrates involved in apoptosis, the purified human recombinant PCMT was cross-linked with sulfo-SBED, a trifunctional reagent containing a biotin, a sulfonated N-hydroxysuccinimide (Sulfo-NHS)active ester and a photoactivatable aryl azide. The moiety containing the active ester also exhibits a cleavable disulfide bond. A PCMT-interacting substrate is then captured by the photoreactive aryl azide moiety. The interacting complex is then isolated and the disulfide bond subsequently reduced. Upon reduction of the disulfide bond, PCMT is released and biotin is “transferred” onto the methyltransferase substrate (Label Transfer Method) ##REF##15144972##[21]## (##FIG##4##Fig. 5 panel A##). The biotinylated PCMT substrates can then be purified exploiting streptavidin-biotin interactions as described under “<xref ref-type=\"sec\" rid=\"s4\">Methods</xref>” and subject to proteomic analysis. As an expression system, we chose human umbilical vein endothelial cells (HUVEC) infected with retrovirus carrying antisense-<italic>PCMT</italic> at a moi of 100. The retroviral transgene was expressed in nearly 100% of the cells, as assessed by confocal microscopy of GFP fluorescence. We used real time-PCR to analyze the silencing of <italic>PCMT</italic> gene in the cells infected with antisense-<italic>PCMT</italic> carrying virus. <italic>PCMT</italic> was effectively hypoexpressed in the antisense PCMT-transduced cells Relative expression of <italic>PCMT</italic> in the HUVEC infected with the vector carrying the antisense PCMT was 0.012 fold (±0.0035; standard deviation) compared to what detected in the uninfected HUVEC. HUVEC infected with retro-<italic>PCMT</italic> antisense were then treated with 0.3 mM H₂O₂ for 24 h. In order to identify PCMT substrates, protein extracts from these cells were incubated with biotinylated human recombinant PCMT, as above described. In order to discriminate the specifically PCMT-interacting proteins from a background of non-interacting proteins, a parallel assay was run, as a negative control, by incubating cell extracts with sulfo-SBED not cross-linked with PCMT. The resulting protein samples, enriched in PCMT substrates, were analyzed with 2D gel (##FIG##4##Fig. 5 panel B##). Protein spots, differentially expressed between sample and negative control, were considered for MALDI-TOF mass spectral analysis. Good matches were found for eight spots that were analyzed by mass spectrometry. All of them produced a good Z score, high sequence coverage and had molecular weights and isoelectric points consistent with the location of the protein on 2D gel. Several spots could not be identified, since relevant mass data did not yield a match with a high Z score or good sequence coverage (##TAB##0##Table 1##).</p>", "<p>Previous work amply demonstrated that two structural features are essential for PCMT function: a) presence of an isoAsp residue; b) recognition by the methyltransferase. As for the first feature, the most deamidation-susceptible residues are asparagines followed by non bulky residues ##REF##7887885##[1]##, ##REF##12726775##[2]##, ##UREF##0##[22]##. As for substrate-PCMT interaction, negative structural requirements are the presence of Cys or charged residues immediately following isoAsp ##REF##2303443##[23]## as well as N-terminal isoAsp residues ##REF##3181156##[24]##. Based on these criteria we therefore carefully reviewed published sequences of all proteins substrates we had identified. Results confirmed that all proteins indeed contained at least one deamidation site, thus allowing us to predict the position at which the actual methylatable isoaspartyls may occur. Protein disulfide isomerase (accession no P30101) displays one theoretically deamidation-susceptible site at Asn199Gly, another at Asn272Ala, plus two adjacent AsnThr sites at position 88. Molecular chaperone HSP70 [accession number (AN) NP_005338.1] contains several theoretical deamidation sites including: five Asn-Ala (at position 59, 280, 367, 515, 619), two Asn-Ser (407, 646), Asn62Thr. Asn41Ser occurs in HSP90 (AN NP_031381.2). Ferrochelatase (AN NP_000131.1) displays three of such features (Asn153Thr; Asn204Ala; Asn372Gly). As for mitochondrial import receptor (AN NP_064628.1) the only theoretical deamidation site is Asn124Thr. Actin (AN P63261) contains the following theoretically deamidation-susceptible asparagines: Asn12Gly, Asn-Thr at positions 128 and 296, Asn280Ser. In addition, we identified, as a PCMT substrate, the cleaved form of the antiapoptotic protein Bcl-x_L\n##REF##9771973##[25]##. Bcl-x_L deamidation sites have been experimentally and unambiguously identified by previous work, as discussed below. It is now clear that this protein undergoes deamidation at two (Asn52 and Asn66) of the three Asn-Gly sequences, which are theoretically sensitive hot spots for this post-biosynthetic modification. Present results demonstrate that this protein actually is recognized by the repair methyltransferase PCMT.</p>" ]

[ "<title>Discussion</title>", "<p>Our data demonstrate that PCMT overexpression confers resistance to apoptosis, induced by oxidative stress, in endothelial cells. Conversely, under conditions in which PCMT was suppressed, cells accumulated isoaspartyl-containing, deamidated proteins, upon oxidative stress. The identification of isoaspartyl-containing derivatives as the actual target-substrate for this protection was made possible by the utilization of PCMT as a specific enzymatic probe, which selectively recognizes the isoaspartyl moiety in deamidated proteins. In fact we were able to show that isomerized proteins increase significantly in the cells committed to apoptosis as the result of oxidative treatment. To clarify the mechanism involved in this resistance we employed a proteomics approach using, again, PCMT as a specific ligand to isolate deamidated-isomerized protein substrates. We can conclude that all the proteins we were able to isolate act as endogenous substrates for PCMT, under conditions in which cells undergo apoptosis. These substrates include various stress proteins (HSP70, HSP90, mitochondrial import receptor, protein disulfide isomerase), the cytoskeletal component actin (a long-established substrate for PCMT), ferrochelatase and Bcl-x_L. The role in apoptosis of some of these proteins has been well established, in particular regarding chaperone HSP70 and HSP90 ##REF##16200196##[26]##. As for HSP70, this protein prevalently exerts antiapoptotic activity, both in the intrinsic and in the extrinsic pathways, according to a complex pattern throughout the apoptosis cascade ##REF##17536179##[27]##, ##REF##16407317##[28]##. As for HSP90, this component, as well, is endowed with antiapoptotic activity through a multifaceted mechanism ##REF##17536179##[27]##, ##REF##15169835##[29]##. Bcl-x_L is perhaps the most interesting protein we were able to isolate, for at least two reasons: first it exerts powerful and direct antiapoptotic activity. Second, and more relevant to our aim, Bcl-x_L undergoes deamidation in relation with cell damage, giving rise to its isoaspartyl derivative, and this process has profound implications on its functional antiapoptotic role. In fact it has been previously reported in the literature that Bcl-x_L deamidation is critical in the signaling pathway leading from DNA damage to apoptosis. Data accumulating over the last few years led to the notion that Bcl-x_L deamidation induces a profound structural modification, which, in turn, hampers the antiapoptotic function of this protein. In particular Deverman and coworkers used constructs where Asn52 and Asn66 in the wild type form of Bcl-x_L, the two critical deamidation-susceptible asparagines, are replaced ##REF##12372300##[15]##. Results, as rediscussed subsequently, were consistent with the view that Asn deamidation to isoaspartate, as the real product, results in the loss of Bcl-x_L function (Erratum for ##REF##12372300##[15]## in ##UREF##1##[30]##. The mechanism for generation of the isoaspartyl derivative of Bcl-x_L has been finally elucidated, as it involves an increase of the intracellular pH, consequent to cell injury, and transcriptional activation of a Na/H antiport, which constitutes a favorable microenvironment for asparaginyl deamidation through ASU formation ##REF##17177603##[16]##.</p>", "<p>It is worth noting that an oxidative stress, as the means we used to induce apoptosis, also represents a protein deamidation-favoring microenvironment. In this respect, it has been previously shown that a) human erythrocytes treated with either <italic>t</italic>-BHP or H₂O₂ accumulate deamidated isomerized proteins in the cell membrane, which are methyl esterified <italic>ex vivo</italic> by PCMT ##REF##10880963##[31]##; b) human erythrocytes from G6PD-deficient subjects are particularly prone to undergo deamidation at membrane protein level, upon oxidative stress, compared to normal red cells ##REF##11985579##[9]##; c) melanoma cells also accumulate PCMT substrates upon UV irradiation, according to a mechanism which is mediated by an oxidation ##REF##11425484##[12]##. Finally, we detected increased isoaspartyl formation in the erythrocytes from patients with Down Syndrome, a condition which is characterized by increased oxidative stress ##REF##17892495##[32]##.</p>", "<p>Now a more general question arises: is the occurrence of isoaspartyls upon deamidation a built-in destruction device or, rather, a fine tuning system acting in concert with methylation? The presence of deamidation-susceptible Asn in proteins appears to be selected against during evolution ##REF##1678690##[33]##. Some early experimental evidence ##REF##4371091##[34]##, ##REF##3198655##[35]## supports a “Molecular Clock” hypothesis. According to this model, the presence of such deamidation-susceptible Asn may account for the occurrence of time-dependent structural modifications of functional meaning. For example, in the case of triosephosphate isomerase and serine hydroxymethyltransferase, deamidation of labile asparagines residues may represent specific signals for commitment of protein to degradation.</p>", "<p>On the other hand, it has been suggested that the non-random distribution of such labile residues in proteins may not only be related to their degradation. It has been argued that although deamidation could be actually considered as a “structural alteration”, at least in some instances, the persistence of such deamidation hot spots during evolution may otherwise serve to certain functions ##REF##12943218##[5]##. According to this view, deamidation may be interpreted as a molecular switch that regulates partitioning over time between two molecule subpopulations of a certain protein, which are also functionally modified. The existence of PCMT, as an enzyme involved in the “repair” of the isopeptide bond resulting from Asn deamidation, is also in agreement with the latter mechanism. In this respect protein deamidation to isoaspartyl-containing products, which are susceptible to recognition and repair by PCMT, has been found to occur in the extracellular matrix ##REF##9188066##[36]##, ##REF##9188065##[37]##. More recently it has been reported that deamidation of susceptible proteins in the extracellular matrix may also serve as a molecular signal to unravel new integrin binding sites ##REF##17015452##[38]##. Deamidation of Bcl-x_L, with consequent abolishment of its antiapoptotic function, thus represents a further example of such a molecular device to change functional properties of those proteins in which it occurs. Based on present results we then propose that PCMT is involved in the modulation of the apoptotic process, by regulating the balance, within the cell, between the isoaspartyl-containing and the repaired aspartyl form of Bcl-x_L (##FIG##5##Fig. 6##). The repair mechanism, as it has been shown on various models, does not consist in the restoration of the asparaginyl residues, but, rather, in the conversion of the isopeptide bond at the level of the isoAsp into a normal α–peptide bond ##REF##7887885##[1]##, ##REF##12726775##[2]##.</p>", "<p>Present results allow us to speculate on the possible implications of deamidation and methylation in the modulation of programmed cell death, under conditions in which this process is altered, such as in cancer. Some of the proteins we thus identified as PCMT substrates, which are known to be involved in apoptosis, have been implicated in pathogenesis of tumors, with particular regard to the acquisition of resistance by the transformed cell phenotypes. In this respect, it has been recently reported that HSP70 increases tumorigenicity and inhibits apoptosis in pancreatic adenocarcinoma ##REF##17234771##[39]##. Data also showed the role of HSP90 in the mechanism of metastasis ##REF##17645779##[40]## about the involvement of apoptosis in cancer, Bcl-x_L perhaps provides the best example of how methylation of deamidated proteins may play a role in maintaining full functioning antiapoptotic proteins (##FIG##5##Fig. 6##). These latter, in turn, may contribute to the resistance of transformed, tumor cells, which otherwise would undergo programmed death. In line with this interpretation are previous results showing a significant reduction in the deamidation rate of Bcl-x_L hepatomas, compared to normal liver tissue ##REF##12810626##[17]##. Our present results, on the ability of PCMT to recognize and methylate Bcl-x_L, thus preserving the antiapoptotic features of this protein, in fact suggest a role of this methyltransferase as a potential target for anticancer intervention.</p>" ]

[]

[ "<p>Conceived and designed the experiments: PG DI. Performed the experiments: AC RC FM IS LM. Analyzed the data: VZ. Contributed reagents/materials/analysis tools: MR MLDB SD. Wrote the paper: PG DI.</p>", "<title>Background</title>", "<p>Natural proteins undergo <italic>in vivo</italic> spontaneous post-biosynthetic deamidation of specific asparagine residues with isoaspartyl formation. Deamidated-isomerized molecules are both structurally and functionally altered. The enzyme isoaspartyl protein carboxyl-<italic>O</italic>-methyltransferase (PCMT; EC 2.1.1.77) has peculiar substrate specificity towards these deamidated proteins. It catalyzes methyl esterification of the free α-carboxyl group at the isoaspartyl site, thus initiating the repair of these abnormal proteins through the conversion of the isopeptide bond into a normal α-peptide bond. Deamidation occurs slowly during cellular and molecular aging, being accelerated by physical-chemical stresses brought to the living cells. Previous evidence supports a role of protein deamidation in the acquisition of susceptibility to apoptosis. Aim of this work was to shed a light on the role of PCMT in apoptosis clarifying the relevant mechanism(s).</p>", "<title>Methodology/Principal Findings</title>", "<p>Endothelial cells transiently transfected with various constructs of <italic>PCMT</italic>, <italic>i.e.</italic> overexpressing wild type PCMT or negative dominants, were used to investigate the role of protein methylation during apoptosis induced by oxidative stress (H₂O₂; 0.1–0.5 mM range). Results show that A) Cells overexpressing “wild type” human PCMT were resistant to apoptosis, whereas overexpression of antisense <italic>PCMT</italic> induces high sensitivity to apoptosis even at low H₂O₂ concentrations. B) PCMT protective effect is specifically due to its methyltransferase activity rather than to any other non-enzymatic interactions. In fact negative dominants, overexpressing PCMT mutants devoid of catalytic activity do not prevent apoptosis. C) Cells transfected with antisense <italic>PCMT</italic>, or overexpressing a <italic>PCMT</italic> mutant, accumulate isoaspartyl-containing damaged proteins upon H₂O₂ treatment. Proteomics allowed the identification of proteins, which are both PCMT substrates and apoptosis effectors, whose deamidation occurs under oxidative stress conditions leading to programmed cell death. These proteins, including Hsp70, Hsp90, actin, and Bcl-xL, are recognized and methylated by PCMT, according to the general repair mechanism of this methyltransferase.</p>", "<title>Conclusion/Significance</title>", "<p>Apoptosis can be modulated by “on/off” switch partitioning the amount of specific protein effectors, which are either in their active (native) or inactive (deamidated) molecular forms. Deamidated proteins can also be functionally restored through methylation. Bcl-xL provides a case for the role of PCMT in the maintenance of functional stability of this antiapoptotic protein.</p>" ]

[]

[ "<p>The authors wish to thank Dr Vincenzo Nigro, Professor of General Pathology at S.U.N., for helpful hints and for kindly reviewing the manuscript.</p>" ]

[ "<fig id=\"pone-0003258-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g001</object-id><label>Figure 1</label><caption><title>Mechanism for deamidation of asparaginyl residues in peptides.</title><p>(Step 1): the nitrogen of the Asn+1 residue (a Gly in the example) attacks the β-carbonyl carbon of the Asn, thus forming the succinimidyl derivative of the peptide (ASU) with the ammonia elimination. The ASU ring can open spontaneously on either side of the nitrogen atom. In one case the α-aspartyl peptide is formed (Step 2). In the other case the β-isoaspartyl peptide does occur (Step 3).</p></caption></fig>", "<fig id=\"pone-0003258-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g002</object-id><label>Figure 2</label><caption><title>Characterization of <italic>PCMT</italic> plasmid constructs.</title><p>Panel A) Plasmids were transfected into endothelial cells and 48 h later methyltransferase activity was assayed using a methanol diffusion assay in the presence of saturating concentrations of the methyl donor AdoMet and ovalbumin as a methyl accepting protein. Results are given as the mean of three experiments. Error bars indicate standard deviation; (*) refer to statistically significant differences (p&lt;0.05), as evaluated by <italic>t</italic>-test. Panel B) Cells transfected were then processed for immunoblotting with PCMT antibody. The immunoblot was reprobed for actin as a loading control. The sample “PCMT” is authentic human recombinant enzyme as a positive control. PAEc = PAE transfected with void plasmid.</p></caption></fig>", "<fig id=\"pone-0003258-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g003</object-id><label>Figure 3</label><caption><title>Effect of PCMT expression levels and mutants on apoptosis induced by oxidative stress on PAE cells.</title><p>Column A: <underline>Apoptotic DNA ladder in cells overexpressing PCMT constructs and subject to oxidative treatment</underline>. Apoptotic DNA ladder patterns, of transfected endothelial cells stimulated with different concentrations of H₂O₂, were detected after transfection with plasmid void (control) or carrying <italic>PCMT wild type</italic> (sense); antisense <italic>PCMT</italic>; <italic>PCMT</italic> Asp₈₃ →Phe₈₃ Mut and PCMT Asp₈₃ →Val₈₃ Mut. Column B: <underline>Caspase-3 activation and PARP cleavage in cells overexpressing PCMT constructs and subject to oxidative treatment</underline>. Immunoblot developed with a polyclonal antibody against caspase-3 and PARP (a final effector of various apoptotic pathways) on transfected endothelial cells stimulated with different concentration of H₂O₂ after transfection with plasmid void (control) or carring PCMT <italic>wild type</italic> (sense), antisense PCMT, PCMT Asp₈₃ →Phe₈₃ Mut and PCMT Asp₈₃ →Val₈₃ Mut. CP is a positive control obtained by treating a parallel cell sample with cisplatin. Column C: <underline>Flow cytometry analysis of cells overexpressing PCMT constructs and subject to oxidative treatment</underline>. Cells stimulated with 0.3 mM of H₂O₂ after transfection with void plasmid (control), <italic>PCMT wild type</italic> (sense), Antisense <italic>PCMT</italic>, PCMT Asp₈₃ →Phe₈₃ Mut. PCMT Asp₈₃ →Val₈₃ Mut. PI: propidium iodide.</p></caption></fig>", "<fig id=\"pone-0003258-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g004</object-id><label>Figure 4</label><caption><title>Quantitation of the extent of protein deamidation in cells lysates after oxidative stress.</title><p>Cells transfected with <italic>PCMT</italic> wild type (sense), antisense <italic>PCMT</italic> (anti), PCMT mutants [Asp₈₃ →Phe₈₃ (Phe) and Asp₈₃→Val₈₃ (Val)] and endothelial cells transfected with void plasmid (PAE) were stressed with 0.3 mM of H₂O₂. Deamidated proteins were quantitated in each lysate preparation using recombinant PCMT. Standard deviation error bars are included for each analysis.</p></caption></fig>", "<fig id=\"pone-0003258-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g005</object-id><label>Figure 5</label><caption><title>Identification of PCMT substrates.</title><p>Panel A: <underline>Experimental strategy for isolation and characterization of PCMT substrates</underline>. Step 1: human recombinant PCMT, purified to homogeneity, was immobilized onto sulfoSBED by <italic>N</italic>-hidroxysuccinimide chemistry; Step 2: cell extracts as a source of substrates were added and Step 3: proteins interacting with PCMT were immobilized upon UV photoactivation; Step 4: PCMT was released and biotin “transferred” onto the methyltrasferase substrate (Label Transfer Method); Step 5: purification was accomplished by exploiting streptavidin-biotin interactions. Panel B: <underline>2D gel electrophoresis imaging of comparative proteomics</underline>. HUVEC were infected with antisense <italic>PCMT</italic> carrying retrovirus and then stressed with 0.3 mM of H₂O₂. Cells lysates were reacted with Sulfo-SBED previously cross-linked with recombinant PCMT (Panel B). Arrows indicate the protein spots which have been characterized as reported in ##TAB##0##Table 1##. Background noise due to aspecific binding was subtracted by comparison with the 2D image obtained from a parallel sample reacted with non-cross-linked Sulfo-SBED.</p></caption></fig>", "<fig id=\"pone-0003258-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.g006</object-id><label>Figure 6</label><caption><title>Proposed role of Bcl-x_L deamidation and methylation in apoptosis.</title><p>Deamidation-isomerization of two critical Asn residues of Bcl-x_L abolishes its antiapoptotic function. Methylation of the same residues can restore the functional integrity of Bcl-x_L through repair of the isopeptide bonds. Regulation of apoptosis toward antiapoptosis is gained through fine balancing of Bcl-x_L deamidation and methylation.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003258-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003258.t001</object-id><label>Table 1</label><caption><title>PCMT substrates identified in endothelial cells.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Spot no</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Protein Information and Sequence Analysis Tools (T)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">%</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">kDa</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Est'dZ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Function</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|2507461|pir||P30101 protein disulfide-isomerase (EC 5.3.4.1) ER60 precursor - human</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">57.06</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Thioreductase/isomerase activity</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|16507237|ref|NP_005338.1| heat shock 70 kDa protein 5 (glucose-regulated protein, 78 kDa); Heat-shock 70 kD protein-5 (glucose-regulated protein, 78 kD); heat shock 70 kD protein 5 (glucose-regulated protein, 78 kD) [Homo sapiens]</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">72.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chaperone</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|20149594|ref|NP_031381.2| heat shock 90 kDa protein 1, beta; heat shock 90 kD protein 1, beta; Heat-shock 90 kD protein-1, beta [Homo sapiens]</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">83.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chaperone</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|4557593|ref|NP_000131.1| ferrochelatase [Homo sapiens]</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">48.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ferrochelatase activity</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>T</bold> gi|9910382|ref|NP_064628.1| mitochondrial import receptor Tom22 [Homo sapiens]</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">receptor activity</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CAA80661 Homo sapiens Bcl-x_L\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">anti-apoptosis</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S 14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|54036678|pir|P63261| gamma-actin [Homo sapiens]</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cytoskeletal structure and dynamics</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">S18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">T gi|229674|pdb|1ALD| Aldolase A (E.C.4.1.2.13)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Energy metabolism</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><p>HUVEC cells were infected as described under “<xref ref-type=\"sec\" rid=\"s4\">Methods</xref>”. The antisense negative dominants were treated with 0.3 mM H₂O₂. PCMT ligands were isolated by means of human recombinant methyltransferase immobilized onto SulfoSBED. Purification, 2D separation and MS analysis were accomplished as detailed in the online supplemental material.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work was supported in part by Grant 2005062199_003 from M.I.U.R.-P.R.I.N. to D. Ingrosso and by Grant 2004057129_003 from M.I.U.R.-P.R.I.N. to P.Galletti.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003258.g001\"/>", "<graphic xlink:href=\"pone.0003258.g002\"/>", "<graphic xlink:href=\"pone.0003258.g003\"/>", "<graphic xlink:href=\"pone.0003258.g004\"/>", "<graphic xlink:href=\"pone.0003258.g005\"/>", "<graphic id=\"pone-0003258-t001-1\" xlink:href=\"pone.0003258.t001\"/>", "<graphic xlink:href=\"pone.0003258.g006\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>In mammals, the widely studied second messenger cAMP can be generated by two types of enzymes: G protein-regulated transmembrane adenylyl cyclases (tmACs) and bicarbonate-regulated soluble adenylyl cyclase (sAC). Nine distinct genes encode a family of tmAC isoforms which display differential tissue distribution and responsiveness to calcium. Each tmAC isoform is modulated by heterotrimeric G proteins in response to hormones and neurotransmitters (reviewed in ##REF##16786220##[1]##). In contrast, a single sAC gene ##REF##9874775##[2]## generates multiple isoforms by alternative splicing ##REF##15659711##[3]##, ##REF##11423534##[4]## whose activities are directly stimulated by bicarbonate and calcium ions ##REF##16250004##[5]##–##REF##12609998##[8]##. A second sAC-related locus present in human, dog and other mammalian genomes, but not detected in mouse or rat genomes, appears to be a pseudogene ##UREF##0##[9]##.</p>", "<p>The sAC protein was initially purified from rat testis cytosol, and two independent cDNAs, which were subsequently shown to represent alternatively spliced isoforms ##REF##11423534##[4]##, were cloned from a rat testis cDNA library ##REF##9874775##[2]##. These two transcripts were termed full-length (sAC_fl), encoding a 187 kD protein, and truncated (sAC_t), encoding a 53 kD protein (##FIG##0##Fig. 1A##). The protein originally purified corresponds to sAC_t. This isoform is highly active but of relatively low abundance. We required approximately 1000 rat testis to recover sufficient material to obtain sequence information ##REF##9874775##[2]##, ##REF##11665644##[10]##, and detecting sAC_t in testis cytosol from wild type mice by Western blotting required an initial enrichment step; i.e., immunoprecipitation with a different sAC-specific monoclonal antibody ##REF##16054031##[11]##. The majority of immune reagents generated, protein biochemistry and kinetics, and the design of a knockout mouse have been based on the knowledge of the sAC_t and sAC_fl isoforms.</p>", "<p>Historically, ‘soluble’ adenylyl cyclase activity had only been detected in testis cytosol ##REF##1055368##[12]##, ##REF##670231##[13]##. Initial Northern blot data confirmed that sAC message is abundant in testis ##REF##9874775##[2]##, and that it is specifically enriched within the developing male germ cells ##REF##10737962##[14]##. But more sensitive methods of mRNA detection, including RT-PCR ##REF##10737962##[14]## and multiple tissue expression arrays ##REF##11932268##[15]##, revealed sAC mRNA to be universally expressed. For example, the NCBI Gene Expression Omnibus database chronicles sAC expression in a number of somatic tissues, including brain. Finally, the GNF gene expression Atlas and in situ analysis performed by the Allen Brain Institute identified sAC message throughout the nervous system including dorsal root ganglia, spinal cord, cerebellum, hypothalamus, and thalamus ##REF##17151600##[16]##.</p>", "<p>To examine sAC protein expression, we and others, have raised various polyclonal antisera and numerous monoclonal antibodies against sAC ##REF##15659711##[3]##, ##REF##11423534##[4]##, ##REF##10915626##[6]##, ##REF##15958523##[17]##, ##REF##12475901##[18]##. These immune reagents predict sAC to also be expressed in a large number of cell lines ##REF##15659711##[3]##, ##REF##12475901##[18]## and a variety of somatic tissues ##REF##10915626##[6]##, ##REF##15958523##[17]##, ##REF##14512417##[19]##–##REF##14769862##[24]## However, the sAC protein identified in cells and tissues tends to be associated with intracellular organelles ##REF##12475901##[18]##, ##REF##14769862##[24]##, ##REF##14697363##[25]## or vesicles ##UREF##1##[20]##, implying that somatic sAC is not a soluble protein but could require detergent extraction.</p>", "<p>Somatic functions for sAC are predicted by both genetic and pharmacologic experiments. The human sAC locus was implicated in familial absorptive hypercalciuria (AH) ##REF##11932268##[15]##, a syndrome of calcium homeostasis defects in intestine, kidney and bone. Pharmacological methods taking advantage of sAC-selective versus tmAC-selective inhibitors have identified a role for sAC as a cellular sensor of pH_i in epididymis ##REF##14512417##[19]## and kidney ##UREF##1##[20]##, a CO₂/HCO₃ sensor in airway cilia ##REF##17591988##[21]##, a mediator of oxidative burst in response to tumor necrosis factor in human neutrophils ##UREF##2##[26]##, and a modulator of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) in corneal endothelium ##REF##12519749##[22]## and in human airway epithelium ##REF##15958523##[17]##. In certain isolated primary cells and cell lines, we have been able to use sAC-specific RNAi mediated knockdown to confirm results obtained with sAC- and tmAC-selective pharmacological inhibitors. Using these more stringent criteria, we have elucidated additional roles for sAC in neuronal responses to the guidance cue Netrin-1 ##REF##16964251##[23]## and in cellular responses to the neurotrophin, Nerve Growth Factor (NGF) ##REF##16627466##[27]##, ##REF##17680672##[28]##.</p>", "<p>These numerous putative somatic functions for sAC are inconsistent with the initial descriptions of a very specific germ cell phenotype in the existing sAC knockout (Sacy^tm1Lex/Sacy^tm1Lex) mouse ##REF##16054031##[11]##, ##REF##14976244##29##, ##REF##18400890##30##. These mice were generated by homologous recombination with an exon trapping, IRES-lacZ expression cassette replacing the 2^nd through 4^th coding sequence exons present in both sAC_t and sAC_fl isoforms ##REF##14976244##[29]##. In mice with the Sacy^tm1Lex locus, lacZ expression was only detected in testis, suggesting that at least the promoter and exon 1 are specific to male germ cells. More importantly, homozygous male knockout mice are sterile; their sperm are immotile, do not undergo capacitation, and are unable to fertilize an egg <italic>in vitro</italic>\n##REF##16054031##[11]##, ##REF##14976244##[29]##. A more extensive phenotypic analysis revealed that female Sacy^tm1Lex/Sacy^tm1Lex mice display increased circulating cholesterol and triglyceride levels and both male and female homozygous knockout animals have slightly elevated heart rates [as deposited in the Mouse Genome Database ##REF##15608240##[31]##]. And even though knockout phenotypes are often muted or absent due to compensation, such subtle somatic phenotypes are unexpected considering the variety of physiological functions demonstrated or predicted for sAC. For example, even though we demonstrated that sAC is essential for Netrin-1 induced axonal outgrowth in commissural axons ##REF##16964251##[23]##, Sacy^tm1Lex/Sacy^tm1Lex mice do not exhibit the pronounced structural brain defects ##REF##16964251##[23]##, ##REF##18400890##[30]## seen in Netrin-1 knockout animals ##REF##8978605##[32]##.</p>", "<p>Moe and co-workers cloned human sAC cDNAs from somatic cells whose open reading frames do not contain exons deleted in Sacy^tm1Lex/Sacy^tm1Lex mice ##REF##15659711##[3]##. If such cDNAs represent the predominant species of sAC in mammalian somatic tissues, it would explain how the Sacy^tm1Lex knockout could exhibit exclusively a germ cell phenotype. Here we use immunological and molecular methods to confirm the existence of previously unknown somatic isoforms of sAC. These somatic sAC isoforms derive from a unique mRNA start site which “escapes” the design of the Sacy^tm1Lex mouse.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Animals</title>", "<p>2–4 month old wild type or Sacy^tm1Lex/Sacy^tm1Lex mice ##REF##14976244##[29]## were euthanized with CO₂, and brains, kidneys, or testis were immediately dissected, flash frozen in liquid N₂ and stored at −80°C until processing. All animal work was performed with approval from the Institutional Animal Care and Use Committee of Weill Cornell Medical College (IACUC Protocol #0604-487A).</p>", "<title>Immunoprecipitation from detergent extracts</title>", "<p>Brains or kidneys were thawed and homogenized in detergent lysis buffer in the presence of protease inhibitors (50 mM Tris, 150 mM NaCl, 0.4 mM EDTA, 0.1 mM DTT, 1 M PMSF, 10 μg/ml aprotinin, 10 μg/ml leupeptin, 1% NP40) (1∶10 w/v). All steps were performed on ice (or at 4°C) unless specified. Homogenates were centrifuged at 45,000xg for 50 minutes. The protein concentration of the supernatant fraction was determined (BioRad) and an aliquot saved at 4°C for Western analysis (‘pre-IP lysate’). Equivalent protein amounts from different supernatants were precleared by incubation with protein G beads (Amersham Pharmacia) (100 μl beads/100 mg total protein) overnight at 4°C. Samples were centrifuged at full speed in an Eppendorf centrifuge for 10′, and the supernatant was collected into fresh tubes. Clarified lysates were incubated with specific anti-sAC antibodies (R37 or R40) or control, mouse IgG at a concentration of 20 μg antibody/mg protein for 4 h at 4°C. Immune complexes were collected on Protein G beads (50 μl/100 mg total protein) and incubated for 1 h. Beads were collected by centrifugation, and an aliquot of the supernatant was collected for Western analysis (post-IP supernatant). Beads were washed three or four times in detergent-free lysis buffer.</p>", "<p>For Western analysis, beads were incubated in SDS/PAGE sample buffer (BioRad) containing 5% β-mercaptoethanol for 5′ at room temperature, briefly spun, and an aliquot used for SDS/PAGE. Proteins were transferred to PVDF membranes, which were blocked in 5% milk (BioRad) for 1 hour at room temperature, rinsed once with TBST and incubated with biotinylated mAbs, R21 or R37 (1∶500 in TBST) overnight at 4°C. Control blots to examine streptavidin binding proteins were incubated in TBST alone. Membranes were rinsed in TBST (4×15′) and incubated with a HRP-conjugated streptavidin (1∶5000 in TBST) for 1 hour at room temperature. Bands were visualized using enhanced chemiluminescence (Pierce Co.)</p>", "<p>For activity assays, beads were incubated in 100 μl reaction buffer containing 200 mM Tris pH 7.5, 100 U/ml phosphocreatine kinase, 20 mM creatine kinase, 2.5 mM ATP, and 10 mM MgCl₂ for 30 minutes at 30°C. Where indicated, reactions contained 10 μM forskolin or 100 μM 4-hydroyestradiol (Steraloids, Inc.) or equivalent volumes of vehicle. Reactions were terminated by adding reaction supernatant into 100 μl 0.2 M HCl, samples were neutralized according to manufacturers protocol and cAMP quantitated using Correlate-EIA Direct Assay (Assay Designs, Inc).</p>", "<p>\n<bold>Antibody epitope mapping</bold>\n</p>", "<p>sAC_t sequence was first divided into 11 fragments, and primers were designed to amplify all 11 fragments, with forward primer 5′CACC overhang for cloning into pENTR/D-TOPO entry vector (Gateway System, Invitrogen) followed by ATG, where necessary. The entry clone was subsequently recombined with pDEST15 vector to create 11 sAC sequence fragments with N terminal GST tag. The N terminal tag was necessary to monitor protein expression and to increase fragment size to facilitate analysis by SDS-PAGE. Clones were shuttled into BL21-AI cells, and expression induced by addition of final concentration of 0.2% L-arabinose (Sigma) for 3–4 hours. Pelleted bacteria was resuspended in Laemmli sample buffer, run on SDS-PAGE and immunoblotted with each monoclonal antibody of interest. To narrow down the antibody epitope, forward and reverse complimentary primers encoding 14–17 amino acid stretches were designed to cover each of the recognized fragments. Each large fragment was covered by 5 overlapping smaller fragments. Forward primers contained CACC overhangs and N terminal ATG for cloning into pENTR/D-TOPO vector. Complimentary oligomers were annealed by incubation in cooling water in the presence of buffer containing 50 mM NaCl, 10 mM Tris-HCl pH 8, 10 mM MgCl₂, 1 mM DTT, cloned into the entry vector, and recombined to generate GST-fusion proteins. Proteins were expressed and epitopes were defined by Western blotting using each monoclonal antibody.</p>", "<title>RNA production, and RT-PCR amplification of sAC products</title>", "<p>Tissues harvested from wild type or Sacy^tm1Lex/Sacy^tm1Lex mice were immediately placed in Trizol and either stored at −80°C or processed for total RNA according to manufacturer's protocol. Total RNA was quantified spectrophotometrically, and at least 2 mg of total RNA was used to generate polyA⁺ RNA using the Micro Poly(A) Purist Kit according to manufacturer's protocol (Ambion). Purified polyA⁺ RNA was resuspended in DEPC-treated water and treated with amplification grade DNase I according to the manufacturer's protocol (Invitrogen). DNase-free polyA⁺ RNA was stored at a final concentration of approximately 100 ng/mL at −80°C until use.</p>", "<p>Approximately 500 ng of polyA⁺ RNA was used to generate first strand cDNA using Invitrogen's Platinum Taq PCR kit according to manufacturer's instructions. Briefly, RNA was incubated with 50 mM oligo(dT)₂₀, (or 10 mM gene specific primer), 10mM dNTP and DEPC-treated water in a volume of 10 μl for 5 minutes at 65°C. An equal volume of cDNA Synthesis Buffer was added, yielding final concentrations of 1× Reverse Transcriptase Buffer (Invitrogen), 10 mM DTT, 125 mM MgCl₂, 40U RNaseOUT, 200U SuperScript III Reverse Trancriptase, and the reaction was incubated for 60 minutes at 50°C. The reaction was terminated by incubation at 85°C for 5 minutes, and placed on ice. 1μl of RNase H (2 U/ml) was added, and incubated at 37°C for 20 minutes. This first strand was stored as single use aliquots at −80°C until use.</p>", "<p>Routinely, PCR reactions used a standard three step protocol using Platinum Taq (Invitrogen, Inc.) with an initial denaturation step at 93°C for 3 minutes, followed by 35 or 40 cycles of 93°C for 20 seconds, 60°C for 20 seconds, and 68°C for 1 minute, followed by a final step at 68°C for 10 minutes. In wild type somatic tissues, 35 cycles was sufficient to detect sAC amplified products, but Sacy^tm1Lex/Sacy^tm1Lex somatic tissues routinely required 40 rounds of amplification to detect fragments.</p>", "<p>Primers used to amplify from exons 1 to 5:</p>", "<p>Forward: LRL1127: <named-content content-type=\"gene\">5′-ATGAGTGCGCGAAGGCAGGAAT-3′</named-content>\n</p>", "<p>Reverse: LRL1511: <named-content content-type=\"gene\">5′-CTGCTCTCTGATCTGGAATCCTC-3′</named-content>\n</p>", "<p>Primers used in to amplify from new mRNA start site to exon 16:</p>", "<p>Forward: Up5: <named-content content-type=\"gene\">5′-ACCCAGAATGTGTTGTGCAAAC-3′</named-content>\n</p>", "<p>Reverse: LRL1519: <named-content content-type=\"gene\">5′-CTTGTCCCGGATTTCCTGAGGCTG-3′</named-content>\n</p>", "<p>Primers used in to amplify from exons 15 to 16:</p>", "<p>Forward: LRL1518: <named-content content-type=\"gene\">5′-CAGAAGCAACTGGAAGCCCTG-3′</named-content>\n</p>", "<p>Reverse: LRL1519: <named-content content-type=\"gene\">5′-CTTGTCCCGGATTTCCTGAGGCTG-3′</named-content>\n</p>", "<p>Primers used to amplify the βGal/Neo cassette:</p>", "<p>Forward: LRL 1276: <named-content content-type=\"gene\">5′-GGAACTAACAGAGATCTATCTGC-3′</named-content>\n</p>", "<p>Reverse: LRL 1277: <named-content content-type=\"gene\">5′-GGATGGACCATCTAGAGACTGCCA-3′</named-content>\n</p>", "<p>Primers used to amplify β-actin:</p>", "<p>Forward: BF: <named-content content-type=\"gene\">5′-GGAGAAGATCTGGCACCACAC-3′</named-content>\n</p>", "<p>Reverse: BR: <named-content content-type=\"gene\">5′-GGTGACCCGTCTCCGGAGTCC-3′</named-content>\n</p>", "<p>\n<italic>5</italic>′ <italic>Rapid Amplification of cDNA Ends (5</italic>′<italic>RACE)</italic>\n</p>", "<p>5′RACE was performed on 500 ng of polyA⁺ RNA from brains of sACy^tm1Lex/sACy^tm1Lex mice using 5′RACE Kit (Invitrogen) according to the manufacturer's protocol.</p>", "<p>5′RACE Primers used from Exon 5:</p>", "<p>Ex5GSP1: <named-content content-type=\"gene\">5′-CTGCTCTCTGATCTGGAATCCTC-3′</named-content>\n</p>", "<p>Ex5GSP2: <named-content content-type=\"gene\">CAATTTCAATCATGCTCCGATCACAG</named-content>\n</p>", "<p>Ex5GSP3: <named-content content-type=\"gene\">CAGCAGTTTGGTGACAAAATAACGTCG</named-content>\n</p>" ]

[ "<title>Results</title>", "<title>sAC-specific antibodies identify isoforms unaffected in Sacy^tm1Lex ‘knockout’</title>", "<p>We used two sAC-specific monoclonal antibodies recognizing distinct, non-overlapping epitopes to examine the molecular nature of sAC proteins expressed in brain. R21 is a monoclonal antibody recognizing an epitope in coding sequence exon 5 (within amino acids 206–216) of sAC_fl while R37 is a monoclonal antibody recognizing an epitope in exon 11 (within amino acids 436–466) (##FIG##0##Fig. 1##). Due to compelling evidence for a function of sAC in neuronal signaling ##REF##16964251##[23]##, ##REF##16627466##[27]## and because we previously demonstrated we could recover sAC activity (i.e., it was inhibited by the sAC-specific inhibitor, KH7, and it was insensitive to the tmAC activator, forskolin) by R37 immunoaffinity purification from detergent extracts of rat brain ##REF##16964251##[23]##, we first focused on the sAC proteins present in mouse brain. Western blots using R21 revealed a number of immunoreactive bands. Surprisingly, none of these putative sAC bands were altered in the Sacy^tm1Lex/Sacy^tm1Lex mice (##FIG##1##Fig. 2A##, first two lanes).</p>", "<p>We also examined the sAC activity immunoprecipitated by R37 from wild type and Sacy^tm1Lex/Sacy^tm1Lex brains (##FIG##2##Fig 3##). We previously showed the adenylyl cyclase activity immunoaffinity purified from wild type mouse brains was insensitive to forskolin and inhibited by sAC-specific inhibitor ##REF##16964251##[23]##. Preliminary analysis suggests that there is considerably less sAC adenylyl cyclase activity immunoprecipitated from a single wild type brain (77 pmol cAMP/ml) than from wild type testis (at least 254 pmol cAMP/ml) (##FIG##2##Fig. 3A##). This is not surprising considering sAC mRNA expression in testis is greater than in any somatic tissue, including brain ##REF##10737962##[14]##, and because testis expresses the highly active, sAC_t isoform ##REF##16250004##[5]##, ##REF##16054031##[11]##. Equivalent amounts of adenylyl cyclase activity were immunoprecipitated from wild type or Sacy^tm1Lex/Sacy^tm1Lex brains (##FIG##2##Fig. 3B##), and the activity from Sacy^tm1Lex/Sacy^tm1Lex brains was confirmed to be sAC by its insensitivity to forskolin (no statistically significant difference in the presence or absence of 10 μM forskolin) and its sensitivity to the sAC-selective inhibitor, 4-hydroxyestradiol. The sAC-selective catechol estrogen, 4-hydroxyestradiol ##REF##14512417##[19]##, ##REF##1970182##[33]##, ##UREF##3##[34]##, was used to inhibit the immunoprecipitated activity from Sacy^tm1Lex/Sacy^tm1Lex brains because it is unaffected by the detergents used during immunoprecipitation. The immunoprecipitated activity from Sacy^tm1Lex/Sacy^tm1Lex brains was inhibited by approximately 50% in the presence of catechol estrogen (##TAB##0##Table 1##). These data suggested that the sAC protein(s) in brain was unaffected by the deletion of exons 2-4, and would therefore represent novel, previously uncharacterized isoforms.</p>", "<p>To determine whether the immunoreactive bands were recognized by both antibodies, which would provide a compelling argument that they are <italic>bona fide</italic> sAC isoforms, we immunoprecipitated using R37 followed by Western blotting with R21 (biotinylated R21 was used for Western blotting to prevent detection of the immunoprecipitating R37 IgG). Western blotting the R37 immunoprecipitates reveals that at least two of the immunoreactive bands, at approximately 50 kDa, are recognized by both sAC-specific monoclonal antibodies (##FIG##1##Fig. 2A,B##). These two proteins are also diminished in the brain extracts following specific (R37) immunoprecipitation, but remain in brain extracts following immunoprecipitation with control (isotype-matched IgG) antibody. Thus, we have identified two proteins of approximately 50 kDa proteins, which are recognized by distinct sAC-specific monoclonal antibodies and are correlated with sAC-like adenylyl cyclase activity. Yet, both isoforms are unaffected in brains from Sacy^tm1Lex/Sacy^tm1Lex mice.</p>", "<p>If these brain sAC isoforms were unaffected by removal of exons 2-4, they should not be recognized by antisera directed against this region. One of our monoclonal antibodies, R40, recognizes an epitope which spans exons 2 and 3 (##FIG##0##Fig. 1A##). Using R40, we were able to immunoprecipitate a 50 kDa protein from wild type mouse testis cytosol, which was absent in testis cytosol from Sacy^tm1Lex/Sacy^tm1Lex mice (##FIG##3##Fig. 4##, top). This 50 kDa isoform is presumably sAC_t. Not only was this isoform not detectable in brain, but this exon 2-3 directed monoclonal antibody did not immunoprecipitate any detectable sAC isoforms from wild type or Sacy^tm1Lex/Sacy^tm1Lex brains (##FIG##3##Fig. 4##, bottom). The testis cytosolic isoform, sAC_t, and one of the newly identified detergent extractable, brain isoforms run together at ∼50 kDa and are not easily distinguished on SDS/PAGE (compare ##FIG##1##Fig. 2## and ##FIG##3##4##). We believe this coincidence has contributed to previous confusion about the molecular identity of sAC isoforms identified by Western blotting.</p>", "<p>We next asked whether the detergent extractable, 50 kDa isoforms present in brain could be found in other somatic tissues. In kidney, sAC has been proposed to form a complex with the vacuolar proton ATPase to regulate renal distal proton secretion ##UREF##1##[20]##. Western blots (using R21) of R37 immunoprecipitates from detergent extracts of wild type and Sacy^tm1Lex/Sacy^tm1Lex kidneys revealed a ∼50 kDa sAC isoform, which once again, was unaffected by removal of exons 2-4 (##FIG##1##Fig. 2C##). These data suggest that at least one of the two ∼50 kDa brain isoforms represents a widely distributed, somatic isoform of sAC.</p>", "<title>sAC transcripts in brain use an alternate start site</title>", "<p>We used the knowledge that brain sAC isoforms must contain the epitopes recognized by R21 (amino acids 206–216) and R37 (amino acids 436–466) to explore the nature of brain sAC cDNAs. Using primers specifically recognizing these sequences and 35 cycles of amplification, we detected a fragment in brain mRNA from wild-type mice; with forty rounds of amplification, we amplified fragments from both wild type and Sacy^tm1Lex/Sacy^tm1Lex brains (##FIG##4##Fig. 5##). In each case, nucleotide sequencing confirmed the amplified fragment contained a single product corresponding to the complete sequence (i.e., contained all known exons) between exons 5 and 11. The need for greater than 30 rounds of amplification to detect sAC message in somatic tissues is consistent with the recently published identification of sAC mRNAs in specific neuronal cell types ##REF##18400890##[30]##. PCR amplification of the LacZ/Neo cassette confirmed the identity of Sacy^tm1Lex/Sacy^tm1Lex tissues, but it is unclear why knockout brains and testis appear to express equivalent LacZ/Neo message.</p>", "<p>Consistent with the facts that R40 did not detect any sAC isoforms in brain and the isoforms we do detect in brain are unaffected by removal of exons 2-4, we were unable to amplify a product using exon 1, 2, 3, or 4 sense primers to exon 5 antisense primers from either wild type or knockout brain mRNA (##FIG##5##Fig. 6## and data not shown). As control, the exon 1 sense and exon 5 antisense primers amplified the expected size product using testis mRNA from wild type and Sacy^tm1Lex/+ heterozygous mice (##FIG##5##Fig. 6##). These primers also amplified a smaller product (of 200 base pairs) from Sacy^tm1Lex/+ heterozygous and Sacy^tm1Lex/Sacy^tm1Lex homozygous knockout mice which nucleotide sequencing confirmed to be an in-frame, exon1:exon5 spliced product arising exclusively from the Sacy^tm1Lex allele. It is possible this uniquely spliced product in testis from knockout mice is responsible for the residual adenylyl cyclase activity identified in sperm from Sacy^tm1Lex/Sacy^tm1Lex mice ##REF##16842770##[35]##. It is also possible this aberrant, testis-specific product diminishes splicing into the LacZ/Neo cassette, explaining why the level of LacZ/Neo message in testis is not much higher than the levels found in brain (##FIG##4##Fig. 5##).</p>", "<p>To test whether brain sAC mRNAs use an alternate start site, we performed 5′ Rapid Amplification of cDNA Ends (RACE) starting in exon 5. We obtained two 5′ RACE products, which extended beyond the intron/exon boundary of exon 5 into the sequence previously thought to be intron. The two fragments were contiguous; the larger fragment simply extended further (344 nucleotides) into the intron upstream of coding exon 5 (##FIG##6##Fig. 7##; GenBank Accession #EU478437). Neither fragment extended into sequences removed in the Sacy^tm1Lex locus, and these upstream sequences did not correspond to any of the alternatively spliced transcripts identified in human tissues ##REF##15659711##[3]##. Thus, sAC mRNAs in mouse brain appear to utilize a unique start site, which would not be deleted in Sacy^tm1Lex/Sacy^tm1Lex mice (##FIG##0##Fig. 1B##).</p>", "<p>We had first concluded that sAC is widely distributed in mammals based upon an RT-PCR experiment using primers in exons 15 and 16 ##REF##10737962##[14]##. Reed <italic>et al</italic>. reached a similar conclusion using an overlapping region as probe in a multiple tissue array blot ##REF##11932268##[15]##; therefore, exon 16 is likely included in somatic isoforms of sAC. Using a sense primer corresponding to the newly identified 5′ end and an antisense primer in exon 16, we amplified a single product, from both wild type and Sacy^tm1Lex/Sacy^tm1Lex mouse brain mRNA, which extended from the newly described start site through exons 5 to 16 (##FIG##0##Fig. 1B##). This cDNA was amplified in both wild type and Sacy^tm1Lex/Sacy^tm1Lex brains. While we still do not know the true 3′ end of brain sAC cDNAs, we expect them to be significantly shorter than sAC_fl because the encoded protein isoforms are only ∼50 kDa. Consistent with this, we were unable to amplify a product from the new start site to exon 32 (data not shown). This new mRNA start site, outside the region deleted in the Sacy^tm1Lex locus, predicts a previously unappreciated promoter used for expression of sAC in mouse brain. Because sAC proteins in mouse brain derive from this alternate promoter, downstream from the deleted exons and inserted IRES-lacZ cassette, one would not expect to find LacZ expression in brain nor a neuronal defect in Sacy^tm1Lex/Sacy^tm1Lex mice.</p>" ]

[ "<title>Discussion</title>", "<p>These findings reveal the sAC locus to be more complex than previously appreciated. The biochemically characterized sAC_t and sAC_fl isoforms may ultimately prove to be predominantly, if not exclusively, expressed in male germ cells, explaining the relatively specific male sterile phenotype of Sacy^tm1Lex/Sacy^tm1Lex mice ##REF##16054031##[11]##, ##REF##14976244##[29]##. In contrast, the presumptive promoter identified here, which directs expression of brain mRNAs initiating upstream of coding exon five, is likely to direct expression of sAC in many somatic tissues. Thus, the relatively subtle somatic phenotypes reported for Sacy^tm1Lex/Sacy^tm1Lex mice ##REF##15608240##[31]## may be due to altered expression of a somatic sAC isoform instead of loss of sAC_t or sAC_fl. Consistent with this hypothesis, we routinely required increased rounds of PCR amplification to detect sAC messages from Sacy^tm1Lex/Sacy^tm1Lex tissues (##FIG##4##Fig. 5##).</p>", "<p>Somatic isoforms encoded by transcripts from this promoter will possess only the second (C2) of the two identified catalytic domains ##REF##9874775##[2]##. Heterologous expression of C2-only containing isoforms has thus far failed to result in adenylyl cyclase activity ##REF##15659711##[3]##, so how these isoforms produce cAMP remains an open question. By possessing only the C2 catalytic domain, somatic sAC isoforms will differ from the previously characterized, C1-C2 containing isoforms which may be exclusively expressed in male germ cells. Thus, it would be possible to design safe and effective contraceptive strategies by identifying inhibitors selective for C1-C2 containing sAC isoforms.</p>", "<p>The evolutionary conservation of bicarbonate-mediated cAMP generation across many kingdoms ##REF##10915626##[6]##, ##REF##12829712##[36]##–##REF##16400172##[39]##, including from the earliest known forms of life, Cyanobacteria ##REF##10915626##[6]##, ##REF##12829712##[36]##, suggests that this signal transduction pathway should be fundamentally important in biology. For example, multiple physiological processes, in addition to sperm function, are modulated by CO₂ and/or HCO₃\n⁻ (i.e., diuresis, breathing, blood flow, cerebrospinal fluid and aqueous humor formation) ##UREF##4##[40]##. In most cases, the effects of CO₂/HCO₃\n⁻ have been ascribed to as yet undefined chemoreceptors ##UREF##4##[40]##–##UREF##5##[42]##, but potential links to cAMP signaling, such as in carotid body ##REF##12163513##[43]##, suggest additional, somatic roles for a bicarbonate regulated adenylyl cyclase, such as sAC. With our identification of novel isoforms of sAC in somatic tissues, such additional roles remain possible.</p>" ]

[]

[ "<p>Conceived and designed the experiments: LSR LRL JB. Performed the experiments: JF LSR MT MK. Analyzed the data: JF LSR MT LRL JB. Contributed reagents/materials/analysis tools: MK. Wrote the paper: JF LRL JB.</p>", "<title>Background</title>", "<p>Mammalian Soluble adenylyl cyclase (sAC, Adcy10, or Sacy) represents a source of the second messenger cAMP distinct from the widely studied, G protein-regulated transmembrane adenylyl cyclases. Genetic deletion of the second through fourth coding exons in Sacy^tm1Lex/Sacy^tm1Lex knockout mice results in a male sterile phenotype. The absence of any major somatic phenotype is inconsistent with the variety of somatic functions identified for sAC using pharmacological inhibitors and RNA interference.</p>", "<title>Principal Findings</title>", "<p>We now use immunological and molecular biological methods to demonstrate that somatic tissues express a previously unknown isoform of sAC, which utilizes a unique start site, and which ‘escapes’ the design of the Sacy^tm1Lex knockout allele.</p>", "<title>Conclusions/Significance</title>", "<p>These studies reveal increased complexity at the sAC locus, and they suggest that the known isoforms of sAC play a unique function in male germ cells.</p>" ]

[]

[ "<p>We thank the members of the Levin-Buck laboratory and Dr. Samie Jaffrey for critical reading of the manuscript.</p>" ]

[ "<fig id=\"pone-0003251-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g001</object-id><label>Figure 1</label><caption><title>Schematic organization of (A) previously identified, testicular sAC transcripts and (B) the newly identified somatic sAC transcript.</title><p>Boxes denote exons. C1 and C2 refer to the two catalytic domains. Red exons contain stop codons. (A) sAC_fl is encoded by all known coding exons (32), and sAC_t is generated by skipping exon 12. Yellow exons (2-4) are removed in the Sacy^tm1Lex allele. Arrows indicate approximate locations of epitopes for the indicated monoclonal antibodies (R40, R21, and R37). (B) Somatic sAC transcripts derive from a unique start site upstream of exon 5 and continue through at least exon 16 to an unknown stop.</p></caption></fig>", "<fig id=\"pone-0003251-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g002</object-id><label>Figure 2</label><caption><title>Somatic sAC isoforms unaffected in Sacy^tm1Lex locus.</title><p>Immunoprecipitations (IP) using mAb R37 or IgG control antibody from detergent solubilized whole cell extracts (lysates) of brains (A,B) or kidney (C) from wild type or Sacy^tm1Lex/Sacy^tm1Lex mice were subjected to Western analysis using (A,C) biotinylated R21 mAb (R21B) or (B) biotinylated R37 mAb (R37B). White circles denote nonspecific bands detected with streptavidin (no primary antibody) alone. The smear at ∼50 kDa in the R37 IP from brain resolves to at least two bands when less of the IP is loaded for Western blotting (inset).</p></caption></fig>", "<fig id=\"pone-0003251-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g003</object-id><label>Figure 3</label><caption><title>Somatic sAC activity in brain is lower than activity in testis, but it is not diminished in brains from Sacy^tm1Lex/Sacy^tm1Lex mice.</title><p>(A) Adenylyl cyclase activity (in pmol cAMP formed per ml) in mouse IgG or R37 IP from detergent extracts from a single mouse brain or mouse testis from wild type mice. Activity from testis may be under-represented; we did not confirm antibody was in excess. MM is adenylyl cyclase reaction conditions alone (no IP added). Control IgG activity is derived from pooled brain and testis detergent extracts. Values represent averages of duplicate determinations. (B) Adenylyl cyclase activity in R37 IPs from wild type (WT) or Sacy^tm1Lex/Sacy^tm1Lex (KO) mice. MM is adenylyl cyclase reaction conditions alone (no IP added). Extracts were precleared through mouse IgG prior to immunoprecipitation. Values represent quadruplicate determinations from two wild type and two knockout brains with error bars indicating S.E.M.</p></caption></fig>", "<fig id=\"pone-0003251-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g004</object-id><label>Figure 4</label><caption><title>Sperm sAC isoforms are not detected in brain.</title><p>Immunoprecipitations (IP) using mAb R40 or isotype-matched IgG control antibody from detergent solubilized whole cell extracts (lysates) of testis (top) or brain (bottom) from wild type or Sacy^tm1Lex/Sacy^tm1Lex mice were subjected to Western analysis using biotinylated R21 mAb. The sharp band at ∼50 kDa in the R40 IP from wild type testis is distinct from the faint, background bands found in Sacy^tm1Lex/Sacy^tm1Lex mice and in the control IgG IP.</p></caption></fig>", "<fig id=\"pone-0003251-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g005</object-id><label>Figure 5</label><caption><title>RT-PCR of cDNA from testis and brain from wild type (WT) and Sacy^tm1Lex/Sacy^tm1Lex mice (KO).</title><p>(A) PCR across exons 15-16. (B) PCR across exons 5-11. (C) PCR for β-actin loading control. (D) PCR for LacZ/Neo. (−) is a no template control. The number in the lower right corner of each panel is the number of cycles used in each experiment.</p></caption></fig>", "<fig id=\"pone-0003251-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g006</object-id><label>Figure 6</label><caption><title>PCR from Exons 1 through 5 from WT and knockout mouse tissues.</title><p>(A) and (C) PCR across exons 1-5. (A) Testis first strand from WT (+/+), Sacy^tm1Lex/+ heterozygote (+/−), and Sacy^tm1Lex/Sacy^tm1Lex homozygous knockout (−/−) mice. (C) First strand cDNA from brain (B), heart (H), kidney (K), or liver (Li) from Sacy^tm1Lex/Sacy^tm1Lex homozygous knockout (−/−) mice; (−) indicates no template control. (B) and (D) β-actin controls. The number in the lower right corner of each panel is the number of cycles used in each experiment.</p></caption></fig>", "<fig id=\"pone-0003251-g007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.g007</object-id><label>Figure 7</label><caption><title>Sequence of 5′ RACE product defining new mRNA start site from mouse brain.</title><p>Sequence in bold is the newly defined 5′UTR which corresponds to the region previously assigned to be the intron between Exons 4 and 5.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003251-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003251.t001</object-id><label>Table 1</label><caption><title>sAC activity from Sacy^tm1Lex/Sacy^tm1Lex brains</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">cAMP<xref ref-type=\"table-fn\" rid=\"nt101\">*</xref> (pmol/mL)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Standard Deviation (pmol/mL)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Basal activity</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20.472</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.138</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4-hydroxyestradiol (100 μM)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11.223</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.726</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><label>*</label><p>Average of quadruplicate determinations.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work was supported by grants from the National Institutes of Health [NS55255 (LRL) and GM62328 (JB)], American Diabetes Association, and the Hirschl Weil-Caulier Trust (LRL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003251.g001\"/>", "<graphic xlink:href=\"pone.0003251.g002\"/>", "<graphic xlink:href=\"pone.0003251.g003\"/>", "<graphic id=\"pone-0003251-t001-1\" xlink:href=\"pone.0003251.t001\"/>", "<graphic xlink:href=\"pone.0003251.g004\"/>", "<graphic xlink:href=\"pone.0003251.g005\"/>", "<graphic xlink:href=\"pone.0003251.g006\"/>", "<graphic xlink:href=\"pone.0003251.g007\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Many organs are composed of sheets or tubes of epithelial cells. Epithelia create a diffusion barrier and at the same time mediate selective transport of substances within organs. These functions depend on proper apical-basal polarization of epithelia. In the case of tubular organs, such as the lungs or kidneys, the apical epithelial surface faces the tube lumen, and the basal side forms the outside of the tubes ##REF##12526790##[1]##. It is of key importance for organogenesis and for proper function of the mature organ that secreted proteins and membrane material are transported to their correct (apical or basal) destinations at the right time. Thus, the spatiotemporal control of secretion plays a crucial role in organ development and physiology. Yet, these processes have been studied mainly using <italic>in vitro</italic> tissue culture models, and functional studies <italic>in vivo</italic> have thus far been rare ##REF##17681133##[2]##–##REF##17179093##[4]##.</p>", "<p>The <italic>Drosophila</italic> tracheal system, a network of gas-filled epithelial tubes, has emerged as a powerful model to study the cellular and molecular basis of tubular organ development <italic>in vivo</italic>\n##REF##14570584##[5]##–##REF##12791296##[7]##. Tracheal tubes originate from segmentally repeated clusters of epidermal cells that invaginate and subsequently branch out to form a network of interconnected tubes that supply oxygen to target tissues. Importantly, tracheal morphogenesis occurs in the absence of cell division and relies entirely on coordinated changes in cell shape and cell rearrangements. Several steps of this morphogenetic program were recently shown to critically depend on apical protein secretion. First, secretion of two Zona Pellucida (ZP)-domain proteins, Piopio (Pio) and Dumpy (Dp), into the luminal space was shown to be critical for proper cell rearrangement during branch elongation ##REF##12973360##[8]##. In the absence of Pio or Dp, branches disconnect from each other and form cyst-like structures. Second, when adjacent tracheal metameres fuse to give rise to interconnected tubes, pairs of specialized cells at the tips of neighboring branches contact each other and form new apical lumens that grow towards each other and eventually fuse, resulting in a continuous lumen ##REF##8951068##[9]##–##REF##9012491##[10]##. The formation of the fusion cell lumen was shown to depend on targeted exocytosis and local plasma membrane remodeling ##REF##11880359##[11]## mediated by the Arf-like 3 small GTPase ##REF##17919535##[12]##–##REF##18083504##[13]##. It was suggested that the exocyst complex controls the assembly of the specialized fusion cell lumen. Third, upon completion of tracheal tube fusion in the embryo, the initially narrow lumen expands to its final size to allow for efficient gas transport in the larva. Tube expansion occurs rapidly within a few hours. During this process, the apical (luminal) surface of tracheal cells grows selectively, while the basal surface shows little change, thus resulting in an expansion of luminal diameter and a flattening of tracheal cells ##REF##10887083##[14]##. This expansion phase is temporally coupled with a peak in secretory activity of tracheal cells ##REF##17681133##[2]##. Just before and during expansion, large amounts of proteins are secreted into the lumen, where they form an apical extracellular matrix (aECM). This matrix, which contains the polysaccharide chitin in addition to secreted proteins, plays important roles in controlling the shape and size of tracheal tubes. The aECM components Serpentine (Serp) and Vermiform (Verm) are predicted chitin-binding proteins required for limiting tracheal tube elongation ##REF##16431371##[15]##–##UREF##1##[17]##. In contrast, chitin forms a luminal scaffold that appears to be required for uniform expansion of tube diameter ##REF##16139230##[18]##–##REF##16277981##[20]##. Components of the COPII vesicle traffic machinery (the GTPase Sar1 and the COPII coat proteins Sec13 and Sec23), which exports proteins from the Endoplasmic Reticulum (ER) to the Golgi complex, were shown to be required for apical secretion of certain aECM components ##REF##17681133##[2]##. However, the precise function of the secretory apparatus in tube expansion, as well as the identity of the secreted factors required for proper tube morphogenesis, are not yet known.</p>", "<p>The COPI coatomer complex is involved in membrane traffic of small vesicles. Coatomer is trafficking primarily from the early Golgi to the ER and is found on vesicles derived from Golgi cisternae ##REF##17041781##[21]##–##REF##16956762##[22]##. Other intracellular routes have also been proposed ##REF##17041781##[21]##, ##REF##9714721##[23]##–##REF##17023067##[24]##. For example, COPI coated vesicles have been proposed to play a role in peroxisome biogenesis and peroxisome to ER transport ##REF##17023067##[24]##. In addition, coatomer is directed to the nuclear membrane by the nuclear pore protein Nup153 at mitosis ##REF##12967567##[25]##.</p>", "<p>COPI coatomer was characterized as a large heptameric complex, conserved from yeast to mammals ##UREF##2##[26]##. It contains the α, β, β', γ, δ, ε and ζCOP subunits. β, γ, δ and ζCOP share a distant homology with AP clathrin adaptor subunits ##REF##10229581##[27]##. αCOP and β'COP are WD40 proteins ##REF##15261670##[28]##. Cytosolic coatomer is recruited to membranes <italic>en bloc</italic> upon stimulation by the membrane-associated, GTP-bound form of the small myristoylated G protein ARF (adenosine-diphosphate-ribosylation factor). Coat disassembly is triggered by an ARF-GTPase activating enzyme (GAP) ##REF##16956762##[22]##, ##UREF##2##[26]##. In addition to ARF, the p23 and the p24 type I membrane proteins play a role in coat formation and in cargo selection ##REF##17041781##[21]##. Coatomer is recruited to membranes through interaction of ARF with the β− and the γCOP subunit and also through interaction of the γCOP subunit with p23 or p24, which are also involved in ARF recruitment ##REF##17041781##[21]##. COPI coatomer-coated vesicles contain cargo indicative of both forward and retrograde transport. Thus, there must be mechanisms determining the content and the various destinations of different COPI coated vesicles. Coating vesicles with distinct combinations of different isotypic coatomer subunits may assist sorting to various destinations and may also be involved in specific cargo recruitment; e.g. there are two γCOP homologues in higher organisms, γ1 and γ2, as well as two ζCOP subunits, ζ1 and ζ2 ##REF##17041781##[21]##, ##REF##17023067##[24]##, ##REF##14729954##[29]##. With the exception of <italic>εCOP (SEC28)</italic>, yeast COPI components are strictly required for viability and inter-compartmental traffic ##REF##9714721##[23]##, ##REF##1461285##[30]##–##UREF##3##[31]##; therefore, the formation of a functional COPI coat requires all the main subunits. Furthermore, the coatomer activity appears to be adapted to cell-type specific requirements. Secretion and Golgi functions are compromised in zebrafish mutants deficient for <italic>α, β</italic> and <italic>β'COP</italic>. In these mutants, the development of chordamesoderm cells proceeds abnormally ##REF##15469843##[32]##.</p>", "<p>Previously, we found that most COPI components are ubiquitously expressed during <italic>Drosophila</italic> development, as expected for proteins required for cell viability. They are expressed at higher levels in cells with secretory function, such as the salivary gland cells. During embryonic tracheal development, most coatomer subunits are expressed at elevated levels in tracheal cells ##REF##16169286##[33]##. These elevated tissue-specific expression levels might represent an adaptation to the increased needs for membrane recycling in secretory cells or cells undergoing morphogenesis and shape changes.</p>", "<p>To find out more about the function of COPI-mediated membrane traffic during <italic>Drosophila</italic> development, we generated null mutations in the <italic>γCOP</italic> locus starting from a previously isolated <italic>P</italic>-element insertion into the <italic>γCOP</italic> locus ##REF##16169286##[33]##. In this study, we present the isolation of <italic>γCOP</italic> loss-of-function mutants and an analysis of the role of <italic>γCOP</italic> in the development of epithelial organs in the embryo. We show that <italic>γCOP</italic> null mutants die late in embryogenesis with a poorly differentiated cuticle, indicative of difficulties in secreting cuticle components. These mutants display defects in luminal secretion of several key proteins, which are required for the coordinated cell rearrangements and cell shape changes during tracheal tube morphogenesis. As a consequence, <italic>γCOP</italic> mutants show defects in cell rearrangements, in branch elongation, in tube dilation, as well as in tube fusion. We present genetic evidence that a specific subset of the tracheal defects in <italic>γCOP</italic> mutants is due to the reduced secretion of the Zona Pellucida protein Piopio because over-expression of this critical target rescues the tracheal branch elongation defects of <italic>γCOP</italic> mutants.</p>" ]

[ "<title>Materials and Methods</title>", "<title>\n<italic>Drosophila</italic> strains</title>", "<p>\n<italic>P{lArB}A383.2M3</italic> is described in ##REF##16169286##[33]##. The <italic>rucuca</italic> chromosome (<italic>roughoid¹ (ru¹)</italic>, <italic>hairy¹ (h¹)</italic>, <italic>thread¹ (th¹), scarlet¹ (st¹), curled¹ (cu¹), stripe¹ (sr¹) ebony^s (e^s) claret¹ (ca¹)</italic>) was isogenized before use in a standard meiotic recombination experiment; likewise the <italic>P{neo⁺ FRT}82B</italic> chromosome. The TMS <italic>P{ry⁺ Δ2-3}99B</italic> stock was a gift from Ulrich Schäfer. The <italic>ry⁵⁰⁶ Sb P{ry⁺ Δ2-3}99B</italic>/TM6 was a gift from Bill Engels. To balance the jump-out deletions a <italic>Lyra (Ly) rosy (ry)</italic>/TM3 Balancer was used. <italic>UAS-pio</italic> is described in ##REF##12973360##[8]##; <italic>breathless (btl)-Gal4 UAS-αCatenin (αCat)-Green Fluorescent Protein (GFP)</italic> is described in ##REF##15620646##[45]##. The Golgi maker <italic>P{sqh-EYFP-Golgi}3</italic> is described in ##REF##15152597##[36]## and was obtained from the Bloomington stock center. The following genotypes were used in ##FIG##0##Figure 1:##\n<italic>ry⁵⁰⁶, ry⁵⁰⁶ γCOP^{P{lArB}A383.2M3}</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP⁵</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP¹²</italic>/TM3 Ser, <italic>ry⁵⁰⁶ γCOP⁶</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP⁸</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP¹⁰</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP⁵⁷⁷</italic>/TM3 <italic>Ser</italic>, <italic>ry⁵⁰⁶ γCOP⁶⁷⁷</italic>/TM3 <italic>Ser</italic>. In ##FIG##1##Figure 2##, the following lines were used: <italic>y w</italic>, TM2<italic>/γCOP^kg06383</italic>, TM2/<italic>Df(3R)pygo11-3</italic>, TM2/<italic>P{neo⁺ FRT}82B γCOP⁵</italic>, TM2/<italic>P{neo⁺ FRT}82B γCOP⁶</italic>, TM2/<italic>P{neo⁺ FRT}82B γCOP⁸</italic>, TM2/<italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic>, TM2/<italic>γCOP⁶⁷⁷</italic>.</p>", "<title>Single fly PCR</title>", "<p>Genomic DNA from different candidate deletion lines was obtained using the method described by ##REF##8224830##[46]##. PCR analysis was carried out with different primer pairs amplifying smaller or bigger fragments spanning the original <italic>P</italic>{lArB} insertion site. For these “diagnostic” PCR reactions mainly the Red Taq DNA polymerase (Sigma) was used. The PCR strategy was similar to the one outlined below (determination of breakpoints), but adapted for the Red Taq polymerase.</p>", "<title>Determination of breakpoints</title>", "<p>To amplify the deletion breakpoint of the <italic>γCOP⁶</italic> allele, the breakpoint sequence was amplified from genomic <italic>γCOP⁶</italic> DNA using either primers cop15 and cop6rev or cop14 and cop11rev together with the Advantage HF 2 PCR Kit (Clontech) and the following cycling conditions: 94°C for 1 min, then 35 cycles as follows: 94°C for 30 s, 60°C for 30 s, 68°C for 2 min. Cycling was ended with one round of incubation at 68°C for 5 min and then cooled to 4°C. Three PCR reactions were carried out in parallel and the products were gel-purified. Then they were pooled and directly sequenced using the nested primer cop14 for the first amplicon and primer cop6rev for the second. The breakpoint sequence of the other <italic>γCOP</italic> excision alleles was determined in a similar fashion; (sequencing primers cop14 for deletion <italic>5</italic>, <italic>8</italic>, <italic>6</italic>, <italic>12</italic>, <italic>677</italic>, primer cop15 for deletion <italic>577</italic>, primer cop6rev for deletion <italic>10</italic>); details are available upon request. Sequence data from this article have been deposited with the EBI/EMBL Data Libraries under accession numbers: AM398208 (<italic>γCOP⁵</italic>), AM398209 (<italic>γCOP¹²</italic>), AM398210 (<italic>γCOP⁶</italic>), AM398564 (<italic>γCOP⁸</italic>), AM503089 <bold>(</bold>\n<italic>γCOP¹⁰</italic>), AM398563 (<italic>γCOP</italic>\n⁶⁷⁷), AM398565 (<italic>γCOP</italic>\n⁵⁷⁷), EU447785 (<italic>Df(3R)pygo ^11-3</italic>).</p>", "<title>Southern Analysis</title>", "<p>Genomic DNA was isolated from different lines using a modification of the method described ##REF##6410077##[47]##; details are available upon request. It was digested using <italic>Eco</italic>RI and <italic>Hind</italic>III. Roughly 15 fly equivalents per slot were loaded on a 0.8% agarose gel and transferred onto a Hybond N⁺ Nylon membrane (Amersham) by the Alkali blotting procedure suggested by the manufacturer. Digoxigenin (DIG)-labeled probes were generated using the PCR DIG Probe Synthesis Kit (Roche); a fragment from cDNA LP01484 amplified using primers cop5 and cop11rev was used for the Southern Blot shown in ##FIG##0##Figure 1C##. For the Southern Blot shown in ##FIG##0##Figure 1D##, a fragment amplified with primers 3prime1 and 3prime2rev on genomic DNA, was used as a probe. The Southern blots were probed with the DIG-labeled fragments according to the instructions of the DIG Easy Hyb Granules manual (Roche) and developed according to the instructions of the CDP-Star manual (Roche). For a standard, the DIG-labeled DNA Molecular Weight Marker VII (Roche) was used.</p>", "<title>Oligonucleotides</title>", "<p>R1 3'UTR (<named-content content-type=\"gene\">CGGAATTCTAAGACAGCGAGCCATGCA</named-content>), 3'BamHI (<named-content content-type=\"gene\">CGCGGATCCCCTCCAATGGCCGCCGTTATCA</named-content>), gm4 (<named-content content-type=\"gene\">GCGTGCGCCGACGTCTCAACTCTTG</named-content>), cop2rev (<named-content content-type=\"gene\">CGATGATGACGTCCTCGGCAATGG</named-content>), cop5 (<named-content content-type=\"gene\">GACCAGAGGATCTCTAAAGAGTCC</named-content>), cop6rev (<named-content content-type=\"gene\">AAGCTCCTCAGAGGGAATGTCC</named-content>), cop11rev (<named-content content-type=\"gene\">CACAGAGCGCAAATGGCCTGC</named-content>), cop14 (<named-content content-type=\"gene\">ACAACATCGGAGCTATCGATAC</named-content>), cop15 (<named-content content-type=\"gene\">CATCGCATTGATCAGCCTTCGC</named-content>), 3prime1 (<named-content content-type=\"gene\">GCGGACTGTGCAGAGGAGGAGGAC</named-content>), 3prime2rev (<named-content content-type=\"gene\">GACTACCGCCGCATATGAATCACG</named-content>), 100 (<named-content content-type=\"gene\">GACTAGTGTCGACAAAACTCGGAGAGCCG</named-content>), 101 (<named-content content-type=\"gene\">ACGCGTCGACCTCGAGCTTGCAATCATTAAAAT</named-content>).</p>", "<title>Transgenes</title>", "<p>Using the expand long Template PCR system (Roche), the genomic region of <italic>γCOP</italic> and a ∼5.8 kb region between <italic>γCOP</italic> and the proximal gene <italic>CG1499</italic> (ending at a <italic>Sal</italic>I site 3′ of the <italic>CG1499</italic> gene) was amplified from <italic>ry⁵⁰⁶</italic> flies according to the manufacturer's cycling conditions, using primer 100 for the 5′ end and primer 101 for the 3'end. This PCR product was subcloned into pCR 2.1 TOPO (Invitrogen). A <italic>Sac</italic>I fragment of the γCOP cDNA LP01448 was used to replace the sequences 3′ of the <italic>γCOP</italic>-internal <italic>Sac</italic>I site to the end. In this way, the entire rescue construct was framed by two <italic>Not</italic>I sites, which were used to retrieve this genomic-cDNA-hybrid rescue construct and to clone it into the <italic>Not</italic>I site of pPCaSpeR4 ##UREF##5##[48]## resulting in p<italic>P</italic>{<italic>w⁺</italic> γCOP Ω35} (or <italic>Ω35</italic> for short notation). To create the monomeric Red Fluorescent Protein (mRFP)-tagged rescue construct p<italic>P</italic>{<italic>w⁺ γCOP-mRFP Ω38</italic>}, a <italic>Bam</italic>HI-<italic>Eco</italic>RI fragment containing <italic>mRFP</italic>\n##UREF##6##[49]## was subcloned into pCR 2.1 TOPO; An <italic>Eco</italic>RI site was introduced into the γCOP-3'UTR by PCR (primer R1 3'UTR and T7); this amplicon was cut with <italic>Eco</italic>RI and the <italic>γCOP</italic>-3'UTR was introduced into the <italic>Eco</italic>RI site of the <italic>mRFP</italic> clone. The stop codon of γCOP was changed to a <italic>Bam</italic>HI site by PCR: Using primer 3'BamHI and primer cop5, the 3'part of the γCOP coding region was amplified, cut with <italic>Nar</italic>I and <italic>Bam</italic>HI and cloned into the <italic>Nar</italic>I-<italic>Bam</italic>HI site of pKS-γCOP. To generate the γCOP-mRFP-γCOP 3'UTR-fusion, mRFP-γCOP 3'UTR was introduced as a <italic>Bam</italic>HI-<italic>Xba</italic>I fragment into the newly generated <italic>Bam</italic>HI site, which replaced the γCOP stop codon. The C-terminal γCOP-mRFP-γCOP 3'UTR fragment was introduced as a <italic>Sac</italic>I fragment (similar as in construct <italic>Ω35</italic>), into the γ<italic>COP</italic>-internal <italic>Sac</italic>I site of the genomic γ<italic>COP</italic> clone in pCR 2.1 TOPO. A 2 kb fragment containing the FRT-Flip-out casette ##REF##8440019##[50]##, was introduced as <italic>Asp</italic>718 fragment into pPCaSpeR4-γCOP; subsequently one of the <italic>Asp</italic>718 sites and the γ<italic>COP</italic> insert were removed by <italic>Xho</italic>I restriction and religation, leaving the FRT-Flip-out cassette in pPCaSpeR4. Finally, the <italic>mRFP-</italic>tagged<italic>-γCOP</italic> transgene containing the genomic upstream region was recovered from pCR 2.1 TOPO as a <italic>Not</italic>I fragment and cloned into the internal <italic>Not</italic>I site of the FRT-cassette giving rise to rescue construct <italic>Ω38</italic> (see ##FIG##0##Figure 1E##). For the pP{<italic>w⁺</italic> UASp-γCOP Ω31} construct, γ<italic>COP</italic> cDNA LP01448 (Research Genetics, ##REF##16169286##[33]##) was recovered as an <italic>Eco</italic>RV-<italic>Ssp</italic>I fragment und subcloned into the <italic>Eco</italic>RV site of pBluescript to add an <italic>Asp</italic>718 site at the 5′ end and a <italic>Bam</italic>HI site at the 3'end. Subsequently, the γ<italic>COP</italic> cDNA was cloned as an <italic>Asp</italic>718-<italic>Bam</italic>HI fragment into pPUASp ##REF##9858703##[51]##. All the <italic>P</italic>-element-based constructs were introduced into <italic>y w</italic> flies by <italic>P</italic>-element transformation ##REF##6289435##[52]##.</p>", "<title>Whole mount <italic>in situ</italic> hybridization</title>", "<p>The whole mount double <italic>in situ</italic> hybridization protocol and the probes are described ##REF##16169286##[33]##.</p>", "<title>Cuticle preparation</title>", "<p>Cuticle preparations of embryos were made essentially as described ##REF##7926775##[53]##. The <italic>γCOP</italic> mutations were balanced over a TM2 <italic>Ubx</italic> balancer chromosome to identify homozygous mutant embryos by the absence of the dominant <italic>Ubx</italic> phenotype, displayed by TM2 balancer chromosome carrying embryos.</p>", "<title>Antibody staining</title>", "<p>Whole mount antibody staining was essentially carried out as described ##REF##16169286##[33]##. The rabbit anti-Pio antibody ##REF##12973360##[8]## was used at a dilution of 1∶200, the mouse monoclonal anti β−Galactosidase (anti-β−Gal; Promega) at 1∶500, rabbit anti-Serp and rabbit anti-Verm antibodies ##REF##16431371##[15]## were used at 1∶100. FITC- and Rhodamin-conjugated Chitin-binding probes (NEB Biolabs) were used at 1∶300.</p>", "<title>Quantification of tracheal fusion defects</title>", "<p>Lumen fusion was analyzed in <italic>γCOP¹⁰</italic> homozygous embryos and heterozygous siblings by scoring the number of successful fusion events per ten tracheal metameres in stage 15 embryos stained for Chitin. Anti-β-Gal staining was used to genotype embryos.</p>", "<title>Live imaging</title>", "<p>For live-imaging, embryos expressing <italic>αCat-GFP</italic> in the tracheal system under the control of the <italic>breathless</italic> promoter (<italic>btl</italic>-GAL4 <italic>UAS−αCat-GFP</italic>) were collected overnight, dechorionated in 4% bleach, and mounted in 400-5 mineral oil (Sigma Diagnostic, St Louis, MO, USA) between a glass coverslip and a gas-permeable plastic foil (bioFOLIE 25, InVitro System and Services, Göttingen, Germany). They were imaged either on a Leica TCS SP5 scanning confocal microscope or a Leica TCS SP scanning confocal microscope. Z stacks were collected every 2 min with optical sections at 1 µm intervals. Image processing was made with ImageJ (W Rasband; <ext-link ext-link-type=\"uri\" xlink:href=\"http://rsb.info.nih.gov/ij/\">http://rsb.info.nih.gov/ij/</ext-link>) and house made ImageJ plugins. Z stacks were projected to get flat images. Salivary glands were dissected from third instar larvae in Grace's insect tissue culture medium (GIBCO) and were transferred to welled immunofluorescence slides (Polysciences), covered by a coverslip and analyzed by confocal microscopy.</p>" ]

[ "<title>Results</title>", "<title>Isolation of <italic>γCOP</italic> alleles</title>", "<p>To investigate the function of <italic>γCOP</italic> during development, we determined the cellular and developmental defects of <italic>γCOP</italic> mutants. We previously identified a <italic>P</italic>-element insertion line within the <italic>γCOP</italic> locus, which maps to the haplo-insufficient region close to 100C (<italic>γCOP^{P{lArB}A383.2M3}</italic>; ##REF##16169286##[33]##). <italic>P{lArB}A383.2M3</italic> was homozygous viable, weakly fertile and the flies were smaller than wild type. We considered the <italic>P{lArB}A383.2M3</italic> allele a weak hypomorphic allele of <italic>γCOP,</italic> as we expected a <italic>γCOP</italic> deletion to have more severe phenotypes (##REF##1461285##[30]##; supporting information ##SUPPL##0##Text S1##). We generated stronger <italic>γCOP</italic> mutants through remobilization of the <italic>P</italic>{lArB}A383.2M3 element, which is inserted within the 5'UTR of the <italic>γCOP</italic> transcription unit (##REF##16169286##[33]##; ##FIG##0##Figure 1A, E##; Supporting Information ##SUPPL##0##Text S1##). By screening through a large number of embryonic lethal lines generated in the remobilization experiment using a PCR assay, we identified a few <italic>γCOP</italic> mutants harboring small deletions as well as others harboring larger deletions, which also remove parts of the neighboring gene <italic>pygopous (pygo)</italic> (##REF##12015286##[34]##–##REF##11955446##[35]##; Supporting Information ##SUPPL##0##Text S1##). These seven lines were further investigated. Southern blot analyses confirmed the existence of physical deletions in all the different <italic>γCOP</italic> alleles (##FIG##0##Figure 1B–D##). Through sequence analysis, we determined the deletion breakpoints (<xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>, Supporting Information ##SUPPL##0##Text S1##). In the case of deletion <italic>5</italic>, <italic>12</italic>, <italic>6</italic>, <italic>8</italic> and <italic>677</italic>, a few base pairs of the 5'<italic>P</italic> inverted repeat sequence and in the case of deletion 6 also a few base pairs of unknown origin had stayed behind after the imprecise excision of the <italic>P</italic>{lArB}. In the case of <italic>10</italic> and <italic>577,</italic> the entire <italic>P</italic>{lArB} element, along with 5′ and 3′ adjacent sequences were excised (##FIG##0##Figure 1E##; Supporting ##SUPPL##1##Figure S1##). We named these mutants <italic>γCOP⁵, γCOP¹², γCOP⁶, γCOP⁸, γCOP¹⁰, Df(3R)γCOP⁵⁷⁷</italic> and <italic>Df(3R)γCOP⁶⁷⁷</italic> (for more details see Supporting Information ##SUPPL##0##Text S1##). Whereas in <italic>γCOP¹², γCOP⁵</italic> and <italic>γCOP⁶</italic> mRNA from the <italic>γCOP</italic> locus is still transcribed (##FIG##0##Figure 1F##; data not shown), no <italic>γCOP</italic> transcripts can be detected in homozygous embryos of the <italic>γCOP¹⁰</italic> allele (##FIG##0##Figure 1G##). Thus, we have not only identified deletions of the entire <italic>γCOP</italic> locus (<italic>Df(3R)γCOP⁵⁷⁷</italic> and <italic>Df(3R)γCOP⁶⁷⁷</italic>), but also a single mutant <italic>γCOP</italic> null allele (<italic>γCOP¹⁰</italic>), in addition to hypomorphic <italic>γCOP</italic> alleles (<italic>γCOP¹², γCOP⁵, γCOP⁶, γCOP⁸</italic>; Supporting Information ##SUPPL##0##Text S1##). The <italic>γCOP</italic> null allele (<italic>γCOP¹⁰</italic>) and the deletions removing the entire <italic>γCOP</italic> transcription unit (<italic>Df(3R)γCOP⁵⁷⁷</italic> and <italic>Df(3R)γCOP⁶⁷⁷</italic>), are embryonic lethal; complementation assays between the <italic>γCOP</italic> deletions (<italic>6, 8</italic> and <italic>10</italic>) and the <italic>Df(3R)pygo^11-3</italic>\n##REF##12015286##[34]## or the independent <italic>γCOP^kg06383</italic> allele, which had become available in the meantime (Flybase), also confirmed that <italic>γCOP</italic> is indeed a gene essential for viability (data not shown). Thus, <italic>γCOP</italic> null mutations are recessive embryonic lethal, indicating that the <italic>γCOP</italic> locus does not represent the haplo-insufficient locus close to 100C on chromosome 3.</p>", "<p>In the course of our deletion analysis, it became clear that there were additional mutations present on the <italic>γCOP</italic> deletion chromosomes, which could disturb a functional analysis of the <italic>γCOP</italic> mutants. Therefore, theses mutations were removed by meiotic recombination. Only cleaned chromosomes (e.g. <italic>FRT82B sr¹ e^s γCOP¹⁰</italic> or <italic>FRT82B e^s γCOP¹⁰</italic>) were used in our further analyses (<xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>; Supporting Information ##SUPPL##0##Text S1##).</p>", "<title>\n<italic>γCOP</italic> zygotic mutants are embryonic lethal</title>", "<p>We first wanted to verify that the embryonic lethality and the associated phenotypes were indeed a consequence of the absence of <italic>γCOP</italic>. Therefore, we aimed to rescue the lethality of the different <italic>γCOP</italic> alleles using <italic>γCOP</italic> rescue constructs (<italic>γCOPΩ35</italic> and <italic>γCOPΩ38)</italic>. <italic>γCOPΩ35</italic> contains the entire <italic>γCOP</italic> coding sequence and also ∼5.8 kb of upstream sequence (##FIG##0##Figure 1E##). The first <italic>γCOP</italic> intron (which is only spliced out in the <italic>γCOP-RA</italic> mRNA) is present, whereas otherwise all introns are lacking in <italic>γCOPΩ35</italic> (##FIG##0##Figure 1E##; <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>). In our tests, several independent insertions of this <italic>γCOP</italic> rescue construct <italic>Ω35</italic> were found to rescue lethality of different <italic>γCOP</italic> alleles (e.g. <italic>γCOP⁸</italic> and <italic>γCOP¹⁰</italic>) to different extents (##FIG##1##Figure 2##). For example, the insertion <italic>Ω35</italic>-i8 on chromosome 2 fully rescued the lethality associated with <italic>γCOP¹⁰</italic>, when present in two copies (##FIG##0##Figure 1H##, ##FIG##1##Figure 2##), while a single copy of insertion <italic>Ω35</italic>-i17 conferred a rescue activity of 76%. A similar rescue construct, which was tagged with mRFP at the C-terminus of <italic>γCOP (Ω38),</italic> was fully able to rescue the lethality of <italic>γCOP</italic> null mutants (##FIG##0##Figure 1E##, ##FIG##1##Figure 2##). These experiments showed that <italic>γCOP</italic> fully accounts for the lethality associated with the deletion mutants and indicate that the associated phenotypes are due to the absence of <italic>γCOP</italic>. In addition, the mRFP-tagged rescue construct <italic>(Ω38)</italic> allowed us to inspect the sub-cellular localization of γCOP. Analyzing living salivary glands carrying both the mRFP-tagged construct <italic>Ω38</italic> and an EYFP-Golgi marker (##REF##15152597##[36]##, <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>) showed that γCOP predominately localizes to punctate structures, which correspond to the Golgi; such a subcellular localization of COPI components has also been observed in other organisms ##REF##16956762##[22]##.</p>", "<title>\n<italic>γCOP</italic> is required for cuticle development</title>", "<p>To determine the lethal phase of <italic>γCOP</italic> mutants and the defects associated with a lack of zygotic <italic>γCOP</italic> function, we made cuticle preparations of the different <italic>γCOP</italic> alleles (##FIG##2##Figure 3##; <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>). All <italic>γCOP</italic> mutants die in late stages of embryogenesis. Presumably, the presence of maternal <italic>γCOP</italic> gene products ##REF##16169286##[33]## allows them to survive to such late stages. While embryonic patterning was rather normal in <italic>γCOP</italic> mutant embryos (see also below), they were smaller than wild type embryos and displayed weakly pigmented cuticles with poorly differentiated denticles (##FIG##2##Figure 3##); some of the mutants also displayed a partial dorsal open phenotype. The strongest phenotype was present in the embryos homozygous for the null allele <italic>γCOP¹⁰</italic>, which showed almost transparent cuticles and only weakly visible denticles (##FIG##2##Figure 3G, I##). The deletion alleles <italic>γCOP⁵</italic>, <italic>γCOP⁶</italic> and <italic>γCOP⁸</italic> are significantly stronger than the <italic>γCOP^kg06383</italic> allele, but in comparison to the null allele, are hypomorphic for the cuticle phenotype, suggesting that these deletion alleles retain partial <italic>γCOP</italic> function (##FIG##2##Figure 3B, D–F##). It is conceivable that N-terminally truncated proteins are made from the RNAs of these hypomorphic deletion alleles (see Supporting ##SUPPL##1##Figure S1##). Such truncated proteins might confer residual γCOP activity or a dominant negative activity, which would complicate the interpretation of the phenotypes of these alleles. Thus, they were not included in our subsequent investigation of tracheal development in <italic>γCOP</italic> mutants (see below). The phenotype of the homozygous <italic>Df(3R)pygo^11-3</italic> allele, in which the C-terminal part of <italic>γCOP</italic> is missing, was also hypomorphic for the cuticle phenotype (##FIG##0##Figure 1E##; ##FIG##2##Figure 3C##); it is conceivable that a 573 amino acid (aa) long γCOP protein is made in <italic>Df(3R)pygo^11-3</italic> mutants (Supporting ##SUPPL##1##Figure S1##). Notably, yeast mutants carrying a <italic>γCOP</italic> allele with a similar C-terminal deletion (579 aa) are not viable; expression of this truncated protein may also exert a dominant negative activity. Remarkably, a yeast strain expressing a slightly longer γCOP mutant protein (676 aa) shows temperature-sensitive lethality ##REF##14527408##[37]##.</p>", "<title>\n<italic>γCOP</italic> is required for tracheal development</title>", "<p>Since we have previously observed that <italic>γCOP</italic> and most other coatomer subunits are expressed at elevated levels in tracheal cells, we analyzed tracheal development in <italic>γCOP</italic> mutants using live imaging and immunostaining (##FIG##3##Figures 4## and ##FIG##4##5##). We observed a number of defects, shown in detail in ##FIG##3##Figure 4## and the corresponding supporting movies. While the branching pattern was similar or identical to wild type embryos, the dorsal branches were often disrupted and formed cyst-like structures rather than extended branches linked up to the dorsal trunk (DT; ##FIG##3##Figure 4A##, Supporting ##SUPPL##2##Movie S1##). These defects were rescued using the genomic rescue construct <italic>Ω35</italic> (##FIG##3##Figure 4B##; Supporting ##SUPPL##3##Movie S2##) as well as upon trachea-specific expression of <italic>γCOP</italic> (##FIG##3##Figure 4C##, Supporting ##SUPPL##4##Movie S3##, <italic>UAS</italic>-<italic>γCOP</italic>). The disruption of dorsal branches and the formation of cyst-like structures are reminiscent of the defects seen in <italic>pio</italic> and <italic>dp</italic> mutant embryos ##REF##12973360##[8]##, suggesting that a lack of Pio and/or Dp might be the cause for these defects in <italic>γCOP</italic> mutants. To find out whether Pio was indeed reduced in <italic>γCOP</italic> mutants, we analyzed its expression using an anti-Pio antiserum (##FIG##4##Figure 5##; ##REF##12973360##[8]##). In wild type embryos, Pio protein accumulates in the tracheal lumen beginning at stage 13. Indeed, we found that the levels of Pio protein were slightly diminished in <italic>γCOP^kg06383</italic> (##FIG##4##Figure 5B, B##'); reduction was more prominent in <italic>γCOP¹⁰</italic> homozygotes (##FIG##4##Figure 5C, C##'). These observations suggest that the reduced levels of Pio accumulation in the tracheal lumen in <italic>γCOP</italic> mutants cause the disruption of dorsal branches. To test this hypothesis, we over-expressed Pio specifically in the developing tracheal system in <italic>γCOP</italic> mutant embryos, and found that the cyst-like structures were not observed anymore; instead, all dorsal branches extended as they do in wild type embryos (Supporting ##SUPPL##5##Movie S4##; ##FIG##3##Figure 4D##; see also ##FIG##4##Figure 5D##). Thus, reduced accumulation of Pio in the tracheal lumen in <italic>γCOP</italic> mutants causes a <italic>pio</italic>-like defect in dorsal branch formation.</p>", "<p>Closer inspection of the tracheal system in <italic>γCOP</italic> mutant embryos revealed that the dorsal trunk lumen was much narrower than in wild type embryos (see ##FIG##3##Figure 4A##, and compare to ##FIG##3##Figure 4B##). Since lumen expansion has been shown to rely on the secretion of a number of proteins into the luminal space ##REF##17681133##[2]##, and since this additional tracheal phenotype was not rescued by Pio expression (and thus not due to the lack of Pio; see ##FIG##3##Figure 4D##), we analyzed the expression of other luminal markers in <italic>γCOP</italic> mutants. In wild type embryos, the soluble secreted protein Serp accumulates in the tracheal lumen, where it associates with the luminal chitin cable (##FIG##5##Figure 6A, B, G, H##; ##REF##16431371##[15]##). While high levels of Serp are detectable in the tracheal lumen in wild type embryos, Serp protein is predominantly retained inside tracheal cells in <italic>γCOP¹⁰</italic> mutants (##FIG##5##Figure 6E, K##). Interestingly, Serp protein behaves differently from Pio protein; Pio is apparently secreted at lower levels, but is not detectable intracellularly in <italic>γCOP</italic> mutants (##FIG##4##Figure 5C, C##'). Chitin, which forms a cylindrical cable-like structure inside the lumen, is still found in the lumen in <italic>γCOP</italic> embryos, although at slightly reduced levels (##FIG##5##Figure 6D, J##). Taken together, <italic>γCOP</italic> is required for the accumulation of two secreted proteins, Pio and Serp, but not of the polysaccharide chitin, inside the tracheal lumen. To address the effects of reduced secretion at the morphological level, we analyzed tracheal morphology in more detail in <italic>γCOP</italic> mutants. In addition to the narrow lumen, <italic>γCOP¹⁰</italic> embryos displayed defects in DT lumen fusion, noticeable as interruptions in the luminal chitin cable in the DT (arrowheads in ##FIG##5##Figure 6F, L##). These defects were variable in frequency (on average 3 DT lumen interruptions per side in <italic>γCOP¹⁰</italic> homozygotes (n = 45) compared to 0.2 interruptions in <italic>γCOP¹⁰</italic>/+ heterozygotes (n = 33); ##FIG##5##Figure 6M##) and most frequently occurred in posterior segments. We also observed defects in lateral trunk (LT) fusion (##FIG##5##Figure 6F, M##). Together, these phenotypes are reminiscent of the tracheal fusion defects described for <italic>Arl3/dead end</italic> (<italic>dnd</italic>) mutants ##REF##17919535##[12]##–##REF##18083504##[13]##, suggesting that Arl3-mediated membrane remodeling during DT fusion is compromised in <italic>γCOP</italic> mutants. Thus, lack of <italic>γCOP</italic> causes defects in three distinct processes during tracheal development: dorsal branch elongation, lumen expansion and tube fusion.</p>" ]

[ "<title>Discussion</title>", "<p>In this study, we present the isolation of <italic>Drosophila melanogaster γCOP</italic> null mutations and the analysis of their effect on embryonic development. To obtain deletions within the <italic>γCOP</italic> locus, we remobilized a <italic>P</italic>-element insertion within the <italic>γCOP</italic> locus. Among the imprecise-excision deletions, we found a null mutant, which abrogates transcription from the <italic>γCOP</italic> locus, as well as two complete deletions of the <italic>γCOP</italic> CDS, which remove, in addition, parts of the distal neighboring gene <italic>pygo.</italic> Like in other organisms, the zygotic absence of <italic>γCOP</italic> is lethal ##REF##9714721##[23]##, ##REF##1461285##[30]##. <italic>γCOP</italic> mutant embryos survive until late stages of embryogenesis, as was also shown recently in an independent study ##REF##18398480##[39]##, likely due to the perdurance of maternal <italic>γCOP</italic> gene products, which are deposited in the egg during oogenesis ##REF##16169286##[33]##. These <italic>γCOP</italic> mutant embryos display defects in the formation of the embryonic cuticle; denticles are barely made. Judged by the severity of the cuticle phenotype, we classified the different mutations. As expected, the strongest defects were associated with the null allele <italic>γCOP¹⁰</italic>. Weaker mutant cuticle phenotypes were observed for the 5′ and 3′ deletions; this suggested to us that N-terminal or C-terminal truncated proteins may be made in these mutants, which retain residual <italic>γCOP</italic> activity. Studies in other organisms have shown that <italic>γCOP</italic> is an essential subunit of the COPI complex, which is involved in inter-compartmental traffic of small vesicles ##REF##17041781##[21]##–##REF##16956762##[22]##. In the presence of truncated <italic>γCOP</italic> proteins, the heptameric COPI complex might still form and provide minimal, but not sufficient coatomer activity to the mutant cells. We expect that no COPI activity remains in cells harboring the <italic>γCOP</italic> null mutation alleles once they have run out of their maternal products, because the COPI complex most likely does not form in the absence of <italic>γCOP</italic>\n##REF##14527408##[37]##. Furthermore, <italic>γCOP</italic> does not only interact with several of the other COPI subunits ##REF##14527408##[37]##–##REF##10921873##[38]##, it also represents one of the key interaction partners of coat assembly and disassembly regulators. It interacts with ARF1 and also p23/p24, which recruit coatomer to membranes ##REF##17041781##[21]##. <italic>γCOP</italic> also interacts with an ARF-GAP required for Golgi to ER retrograde trafficking vesicles ##REF##10921873##[38]##. Several different trafficking routes for the COPI complex have been proposed, which may be mediated through different isotypes of COPI subunits, including <italic>γCOP</italic>\n##REF##14729954##[29]##. By mutating <italic>Drosophila γCOP,</italic> we expect to affect all the major coatomer-dependent traffic routes: <italic>γCOP</italic> is present as a single gene in <italic>Drosophila melanogaster</italic> and our N-terminal deletions remove the only alternative splice site known, which is not conserved in higher organisms ##REF##17041781##[21]##, ##REF##16169286##[33]##. The cuticle phenotype of the <italic>γCOP</italic> mutants is similar, although stronger, than those described for mutants in other secretory pathway genes, <italic>e.g</italic>., <italic>sec13</italic>\n##REF##15901661##[40]##. Sec13 is a component of the COPII complex involved in anterograde transport of small vesicles from the ER to the Golgi ##REF##15901661##[40]##–##REF##15473836##[41]##. Therefore, a primary effect of removing <italic>γCOP</italic> functions from the embryo might be the inability to secrete proteins. Although coatomer has been predominantly implicated in retrograde transport of small vesicles, blocking retrograde transport should also affect anterograde transport. Membranes and the machinery required for vesicle formation and fusion are recycled back to the ER by means of the COPI-mediated vesicle transport from the ER-Golgi-Intermediate-Compartment (ERGIC), which is targeted by anterograde-moving, COPII complex-coated vesicles (see ##REF##15473836##[41]##–##UREF##4##[42]## and references therein). Indeed, in mutants of the yeast <italic>γCOP</italic> homologue <italic>sec21,</italic> ER to Golgi transport is affected ##REF##1461285##[30]##. Coatomer has also been implicated in transport of vesicles derived from Golgi cisternae ##REF##17041781##[21]##. Interestingly, Golgi functions are slowed down but not prevented in yeast mutants defective in COPI vesicle assembly ##REF##16699523##[43]##–##REF##16791181##[44]##. Thus, COPI mutations could affect secretion in two ways: on the one hand, by slowing down the movement of cargo through the Golgi and on the other by blocking COPII-mediated transport due to the lack of recycling of proteins back to the ER, which are required for functions within the ER.</p>", "<p>The idea that protein secretion is blocked in <italic>γCOP</italic> mutants is corroborated by our findings, as well as by recently published data ##REF##18398480##[39]##, showing that several secreted proteins fail to accumulate to normal levels in the tracheal lumen of <italic>γCOP</italic> mutants. Serp protein levels in the tracheal lumen are severely reduced. Serp protein accumulates within the tracheal cells and the ZP-domain protein Pio is not present at normal levels in the tracheal lumen. Although small amounts of Pio protein are still found in the tracheal lumen of <italic>γCOP</italic> mutants, these residual amounts of protein appear to be insufficient to provide enough Pio function for proper epithelial tube morphogenesis. In the absence of <italic>γCOP</italic>, the dorsal tracheal branches are often disrupted, defects that are strikingly similar to those described for <italic>pio</italic> mutants ##REF##12973360##[8]##. Restoring function with a <italic>γCOP</italic> transgene in <italic>γCOP</italic> mutants rescues Pio secretion and DB migration, indicating that these defects are due to the lack of <italic>γCOP</italic> function. Interestingly, we were also able to restore DB integrity by over-expressing Pio specifically in tracheal cells in <italic>γCOP</italic> mutants. Thus, the requirement for <italic>γCOP</italic> in DB migration can be overcome by raising Pio protein levels, which presumably leads to increased levels of luminal Pio protein sufficient for normal cell intercalation. Importantly, this result suggests that Pio protein is the critical target whose reduced secretion in <italic>γCOP</italic> mutants is responsible for the specific DB defects observed in <italic>γCOP</italic> mutants. Thus, we were able attribute a specific subset of the defects in <italic>γCOP</italic> mutants to the failure in apical secretion of a distinct protein (Pio). This result was surprising, given that at least one additional protein (the ZP protein Dumpy) was previously shown to be required for DB cell intercalation along with Pio. However, Pio protein is required for luminal accumulation of Dp ##REF##12973360##[8]##. This suggests that the two ZP proteins are mutually dependent on each other for efficient transport through the secretory apparatus. Thus, raising the level of Pio protein in <italic>γCOP</italic> mutants may not only lead to increased secretion of Pio, but presumably also of Dumpy. Interestingly, a recent study using different, independently generated <italic>γCOP</italic> alleles ##REF##18398480##[39]## showed both by light and electron microscopy that <italic>γCOP</italic> is required for ER and Golgi structure, as well as for epithelial protein secretion. In addition, these authors showed that tracheal tube expansion is affected in <italic>γCOP</italic> mutants, while tracheal migration and fusion defects were not reported (see also below).</p>", "<p>It was recently shown that targeted membrane remodeling in tracheal lumen fusion is dependent on the function of the exocyst complex ##REF##18083504##[13]##. Our finding that lumen fusion is also defective in <italic>γCOP</italic> null mutants raises the question whether the lumen fusion process is indirectly affected due to <italic>γCOP's</italic> general effect on luminal protein secretion, or whether the proper functioning of the exocyst complex and the lumen fusion process are affected more directly by the absence of COPI-mediated vesicle trafficking. We favor the latter scenario, because a general defect in COPII-dependent secretion in <italic>sar1</italic> mutants was shown to result in tracheal tube expansion defects similar to those observed in <italic>γCOP</italic> mutants, whereas tracheal lumen fusion was not reported to be affected in COPII component mutants ##REF##17681133##[2]##. Also, none of the secreted luminal proteins identified so far are required for lumen fusion. Thus, we argue that <italic>γCOP</italic> plays a more direct role in lumen fusion, maybe by affecting the function of the ARL3/Dnd G-protein ##REF##17919535##[12]##–##REF##18083504##[13]##. <italic>arl3</italic> is expressed specifically in tracheal fusion cells, suggesting that it plays a dedicated role in membrane trafficking in the highly specialized tracheal tube fusion process. In contrast, <italic>γCOP</italic> and other components of the COPI complex are broadly expressed and are presumably generally required for COPI-dependent vesicle formation. Here, we show that the tracheal defects in <italic>γCOP</italic> mutants can be genetically dissected into (i) defects due to a general requirement for <italic>γCOP</italic> in all tracheal cells (luminal protein secretion, tube expansion) and (ii) defects due to a specific requirement in distinct cell types (dorsal branch cells, fusion cells).</p>" ]

[]

[ "<p>Conceived and designed the experiments: NCG EC MA SL. Performed the experiments: NCG EC SL. Analyzed the data: NCG EC MA SL. Contributed reagents/materials/analysis tools: NCG EC DP KC MA SL. Wrote the paper: NCG MA SL.</p>", "<p>Current address: NIH/NICHD, Bethesda, Maryland, United States of America</p>", "<title>Background</title>", "<p>There is increasing evidence that tissue-specific modifications of basic cellular functions play an important role in development and disease. To identify the functions of COPI coatomer-mediated membrane trafficking in <italic>Drosophila</italic> development, we were aiming to create loss-of-function mutations in the <italic>γCOP</italic> gene, which encodes a subunit of the COPI coatomer complex.</p>", "<title>Principal Findings</title>", "<p>We found that <italic>γCOP</italic> is essential for the viability of the <italic>Drosophila</italic> embryo. In the absence of zygotic <italic>γCOP</italic> activity, embryos die late in embryogenesis and display pronounced defects in morphogenesis of the embryonic epidermis and of tracheal tubes. The coordinated cell rearrangements and cell shape changes during tracheal tube morphogenesis critically depend on apical secretion of certain proteins. Investigation of tracheal morphogenesis in <italic>γCOP</italic> loss-of-function mutants revealed that several key proteins required for tracheal morphogenesis are not properly secreted into the apical lumen. As a consequence, <italic>γCOP</italic> mutants show defects in cell rearrangements during branch elongation, in tube dilation, as well as in tube fusion. We present genetic evidence that a specific subset of the tracheal defects in <italic>γCOP</italic> mutants is due to the reduced secretion of the Zona Pellucida protein Piopio. Thus, we identified a critical target protein of COPI-dependent secretion in epithelial tube morphogenesis.</p>", "<title>Conclusions/Significance</title>", "<p>These studies highlight the role of COPI coatomer-mediated vesicle trafficking in both general and tissue-specific secretion in a multicellular organism. Although COPI coatomer is generally required for protein secretion, we show that the phenotypic effect of <italic>γCOP</italic> mutations is surprisingly specific. Importantly, we attribute a distinct aspect of the <italic>γCOP</italic> phenotype to the effect on a specific key target protein.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>NCG thanks Walter J. Gehring for his generous support to initiate and carry out the presented work on the function of <italic>γCOP</italic> in the embryo in his laboratory and Marc Neumann for his initial investigation of <italic>γCOP</italic> mutant embryos. NCG thanks Jennifer Lippincott-Schwartz for the possibility to complete this manuscript while working in her laboratory. SL and MA thank Christos Samakovlis for exchange of unpublished information. SL thanks Christian Lehner for support and discussions. We thank Kristina Armbruster for critical reading of the manuscript. We thank the Bloomington stock center for sending us numerous fly stocks. We thank Lydia Michaut and Makiko Seimyia for sharing their experience with DIG Southerns with us. We thank Makiko Seimyia for antibody stainings. We thank Konrad Basler and R. Tsien for plasmids. We thank Konrad Basler, Bruno Bello, Bill Engels, Roger Karress, Urs Kloter and Ulrich Schäfer for fly stocks. We are grateful to Karin Mauro, Gina Evora and Bernadette Bruno for providing us with excellent fly food.</p>" ]

[ "<fig id=\"pone-0003241-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g001</object-id><label>Figure 1</label><caption><title>Structure of the <italic>γCOP</italic> locus and generation of <italic>γCOP</italic> mutations.</title><p>(A) Strategy to generate <italic>γCOP</italic> jump out excision alleles from <italic>γCOP^{P{lArB}A383.2M3}</italic>, which carries <italic>ry⁺</italic> as a selection marker. In the parental generation P, the <italic>γCOP^{P{lArB}A383.2M3}</italic> line was crossed to any one of the <italic>P</italic>-element transposase lines, marked with <italic>Sb</italic>. In the F1 generation, single males undergoing <italic>P</italic>-element excision events were crossed to virgin <italic>Ly ry⁵⁰⁶</italic> females in order the chromosome, from which the <italic>P</italic>{lArB} has jumped out (marked }{ ), can be discriminated in the following generations from the homologous chromosome 3. The individual excision events were balanced in the F3 generation (TM3, <italic>Ser</italic>). (B) In lanes 1–8 PCR amplification products using primers gm4-cop6rev on genomic DNA of control and deletion lines was loaded; primers gm4-cop6rev amplify a fragment of 2305 bp from the <italic>γCOP</italic> locus of wild type or <italic>ry⁵⁰⁶</italic>. (1) <italic>ry⁵⁰⁶</italic>, (2) <italic>γCOP^{P{lArB}A383.2M3(iso6)}</italic>/TM3 <italic>Sb</italic> (3) <italic>γCOP⁵</italic>/TM3 <italic>Ser</italic> (4) <italic>γCOP¹²</italic>/TM3 <italic>Ser</italic> (5) <italic>γCOP⁶</italic>/TM3 <italic>Ser</italic> (6) <italic>γCOP⁸</italic>/TM3 <italic>Ser</italic> (7) <italic>γCOP¹⁰</italic>/TM3 <italic>Ser</italic> (8) <italic>ry⁵⁰⁶</italic>. Standard molecular weights are indicated in lane s. (C, D) <italic>Hind</italic>III, <italic>Eco</italic>RI digested gDNA from control and deletion lines was probed with a DIG-labelled cop5-cop11rev fragment in (C) and with a 3prime1-3prime2rev fragment in (D) (see <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>); Standard molecular weights of DIG VII are indicated in lane s. The following genotypes were loaded and blotted in (C): <italic>ry⁵⁰⁶</italic> (1), <italic>γCOP^{P{lArB}A383.2M3}</italic>/TM3 <italic>Ser</italic> (2), <italic>γCOP⁵</italic>/TM3 <italic>Ser</italic> (3), <italic>γCOP¹²</italic>/TM3 Ser (4), <italic>γCOP⁶</italic>/TM3 <italic>Ser</italic> (5), <italic>γCOP⁸</italic>/TM3 <italic>Ser</italic> (6), <italic>γCOP¹⁰</italic>/TM3 <italic>Ser</italic> (7). In (D) <italic>γCOP⁵⁷⁷</italic>/TM3 <italic>Ser</italic> (1), <italic>γCOP⁶⁷⁷</italic>/TM3 <italic>Ser</italic> (2). (E) Map of <italic>γCOP</italic> locus and the <italic>γCOP^{P{lArB}A383.2M3}</italic> deletions. Chromosome 3R is indicated as a red line. <italic>P</italic>-element insertion of <italic>γCOP^{P{lArB}A383.2M3}</italic> is indicated in black, <italic>γCOP^kg06383</italic> insertion in red. Extent of the two alternative <italic>γCOP</italic> transcripts is shown, yellow boxes denote non-coding regions, blue boxes coding regions. cDNA LP01448 was used for cloning experiments (<xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>). The 3'end of the neighboring gene <italic>CG1499</italic> is indicated above the red line. The 3'end of the neighboring gene <italic>pygo</italic> is indicated below the red line. The DNA present on the deletion chromosomes is indicated as black lines; the missing DNA in comparison to the original chromosome is a blank space; small red triangles indicate the parts of the <italic>P</italic>-element inverted repeat which stayed behind after P-element excision. In deletion <italic>γCOP¹⁰</italic> and <italic>Df(3R)γCOP⁵⁷⁷</italic> no P-element derived sequences have stayed behind. Constructs for transgenic flies are shown. The extent of the upstream genomic region present in rescue construct <italic>Ω35</italic> and <italic>Ω38</italic> is shown as a pink box; <italic>Ω38</italic> is tagged with mRFP (red box) and the <italic>γCOP</italic> 3'UTR (yellow box); in addition this construct is flanked by FRT sites (purple arrows); in <italic>UASp-γCOP</italic> the full length <italic>γCOP</italic> cDNA is present (see <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>). (F, G) Deletion alleles (balanced over TM3-<italic>lacZ</italic>) were analyzed for <italic>γCOP</italic> transcription with a DIG-labeled <italic>γCOP</italic> probe and a FITC-labeled βGal probe, to discriminate heterozygous (red and blue) from homozygous <italic>γCOP</italic> mutant embryos. Whereas deletion mutant <italic>γCOP⁵</italic> (marked with asterisk in (F)) still expresses <italic>γCOP</italic> (red staining), deletion mutant <italic>γCOP¹⁰</italic> (marked with asterisk in (G)) shows no <italic>γCOP</italic> transcripts. (H) Fly rescued with <italic>γCOP</italic> rescue construct (marked with asterisk) and heterozygous sibling fly (unmarked) are shown. (I) PCR amplification of primer gm4 and cop6rev on five rescued flies confirming the presence of the original deletion in the rescued viable adults; in the PCR reaction only the short amplicon of the deletion breakpoint is visible; Lane (s) shows standard sizes. The amplicon of <italic>γCOP</italic> mutant flies (<italic>γCOP¹⁰ (1,2) γCOP⁶</italic> (3)), rescued with insertion <italic>Ω35-i7</italic> (2) <italic>or</italic> insertion <italic>Ω35</italic>-<italic>i8</italic> (2, 3).</p></caption></fig>", "<fig id=\"pone-0003241-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g002</object-id><label>Figure 2</label><caption><title>\n<italic>γCOP</italic> rescue constructs rescue lethality of <italic>γCOP</italic> mutants.</title><p>Crossing different insertions of rescue construct <italic>Ω35</italic> or the <italic>mRFP</italic>-tagged rescue construct <italic>Ω38</italic> (<italic>Ω35-i8, Ω35-i17, Ω35-i20, Ω38-4, Ω38-12, Ω38-15</italic>) into the background of the <italic>γCOP</italic> null allele <italic>γCOP¹⁰</italic> (or other alleles) rescued the embryonic lethality of the <italic>γCOP</italic> mutants to different extents, depending on the line used. The different strength of the different insertion sites is likely due to position effect. (A) Columns: (I) rescue line used; (II) Parental genotype of the virgin; (III) Parental genotype of the male; (IV) Number of F1 flies, heterozygous and (V) number of F1 flies, homozygous for a given <italic>γCOP</italic> allele; (VI) Expected number of homozygous F1 flies if rescue was 100%; (B) Rescue activity for all crosses (column VII) is displayed as a bar chart. Line <italic>Ω35-i17</italic>, which was used in the tracheal rescue experiment (##FIG##3##Figure 4##, ##FIG##4##5##), shows already a significant rescue activity if paternally provided in one copy. The <italic>mRFP</italic>-tagged rescue construct <italic>Ω38</italic> rescues lethality of the <italic>γCOP¹⁰</italic> null allele even to 100%. (C, E) The <italic>mRFP</italic>-tagged rescue construct <italic>Ω38</italic> shows a punctate subcellular localization in living salivary gland cells, predominantly to the Golgi apparatus as visualized by an EYFP-Golgi marker (D, E <xref ref-type=\"sec\" rid=\"s4\">Materials and Methods</xref>).</p></caption></fig>", "<fig id=\"pone-0003241-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g003</object-id><label>Figure 3</label><caption><title>\n<italic>γCOP</italic> is required for cuticle development.</title><p>Cuticle preparations of the following genotypes are shown: (A) <italic>y w/y w</italic>, (B) <italic>γCOP^kg06383</italic>/<italic>γCOP^kg06383</italic>, (C) <italic>Df(3R)pygo^11-3</italic>/<italic>Df(3R)pygo^11-3</italic>, (D) <italic>P{neo⁺ FRT}82B γCOP⁵/P{neo⁺ FRT}82B γCOP⁵,</italic> (E) <italic>P{neo⁺ FRT}82B γCOP⁶</italic>/<italic>P{neo⁺ FRT}82B γCOP⁶</italic>, (F) <italic>P{neo⁺ FRT}82B γCOP⁸</italic>/<italic>P{neo⁺ FRT}82B γCOP⁸</italic>, (G) <italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic>/<italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic>, (H–I) close-up of wt (H) and <italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic>/<italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic> (I) cuticle showing ventral side of the embryo (denticles).</p></caption></fig>", "<fig id=\"pone-0003241-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g004</object-id><label>Figure 4</label><caption><title>\n<italic>γCOP</italic> is required for tracheal tube morphogenesis.</title><p>Live imaging of embryonic tracheal development in mutant and rescued embryos. Tracheal development was followed in live embryos using an <italic>αCat-GFP</italic> transgene specifically expressed in the tracheal system under the control of <italic>btl</italic>-<italic>Gal4</italic>. Pictures of late stage embryos were taken from movies (see supporting material) of the following genetic makeup: (A) <italic>btl-Gal4 UAS-αCat-GFP; γCOP¹⁰</italic>/<italic>γCOP¹⁰</italic>. (B) <italic>btl-Gal4 UAS-αCat-GFP</italic>; Ω35-17 <italic>sr¹ e^s γCOP¹⁰/</italic> Ω35-17 <italic>sr¹ e^s γCOP¹⁰.</italic> (C) <italic>btl-Gal4 UAS-αCat-GFP/UASp</italic>-<italic>γCOP</italic>; <italic>γCOP¹⁰</italic>/<italic>γCOP¹⁰.</italic> (D) <italic>btl-Gal4 UAS-αCat-GFP</italic>; <italic>UAS-pio γCOP¹⁰</italic>/<italic>γCOP¹⁰.</italic> Strikingly, the dorsal branches are frequently disrupted in <italic>γCOP¹⁰</italic> mutants (see arrows in A and ##SUPPL##2##Movie S1##), similar to the phenotype observed in <italic>pio</italic> and <italic>dp</italic> mutants ##REF##12973360##[8]##. Dorsal trunk fusion defects are also observed in mutants (arrowhead in A). Both defects were rescued either by expressing a genomic <italic>γCOP</italic> rescue transgene (B), or by expressing <italic>γCOP</italic> specifically in the tracheal system using the UAS/Gal4 system (C). Tracheal-specific expression of Pio protein rescues the dorsal branch defects; however, dorsal trunk fusion defects are still visible (arrowhead in D).</p></caption></fig>", "<fig id=\"pone-0003241-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g005</object-id><label>Figure 5</label><caption><title>\n<italic>γCOP</italic> mutants are defective in Pio secretion.</title><p>Pio levels are diminished in <italic>γCOP¹⁰</italic> mutants. Secretion of Pio into the lumen of the developing embryonic tracheae in control <italic>y w</italic> embryos (A, A' blow up). In the hypomorphic mutation <italic>γCOP^kg06383</italic> there is only a mild effect on Pio secretion (B, B' blow up of homozygous <italic>γCOP^kg06383</italic> mutant embryo of (B)). Only low levels of Pio staining are detectable in the lumen of <italic>γCOP¹⁰</italic> mutant embryos (C, C' blow up of homozygous <italic>P{neo⁺ FRT}82B sr¹ e^s γCOP¹⁰</italic> mutant embryo of (C)); Secretion of Pio into the tracheal lumen is restored by <italic>γCOP</italic> expression from the Ω35 rescue construct (D', blow up of homozygous <italic>Ω35-17 sr¹ e^s γCOP¹⁰</italic> embryo shown in (D)). In the hypomorphic mutation <italic>γCOP^kg06383</italic> there is only a mild effect on Pio secretion (B, B' blow up of homozygous <italic>γCOP^kg06383</italic> mutant embryo of (B)). Note that the gain in (C) was increased compared to (A, B, D) in order to show Pio signals (compare background yolk signals)).</p></caption></fig>", "<fig id=\"pone-0003241-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003241.g006</object-id><label>Figure 6</label><caption><title>\n<italic>γCOP</italic> is required for apical protein secretion and tracheal lumen morphogenesis.</title><p>(A–F): Chitin and Serp protein accumulate in the tracheal lumen of stage 16 wild type embryos (A–C). In contrast, Serp protein is retained in tracheal cells in <italic>γCOP¹⁰</italic> mutants, while luminal accumulation of chitin is not affected in the mutants (D–F). Note that the tracheal lumen marked by chitin staining in <italic>γCOP¹⁰</italic> embryos (D) is narrower than in wild type embryos (A). In addition, <italic>γCOP¹⁰</italic> embryos display interruptions in the DT lumen and in the LT (arrowheads in F) and stunted dorsal branches (asterisks in F) in posterior metameres. Also note that <italic>γCOP¹⁰</italic> embryos are developmentally delayed compared to wild type embryos, as indicated by gut morphology (green gut autofluorescence is visible in C, F). (G–L): Close-ups of wild type (G–I) and <italic>γCOP¹⁰</italic> (J–L) embryos. DT lumen fusion defects (arrowheads) and DB migration defects (asterisk) are indicated in (L). (M): Quantification of DT and LT fusion defects in <italic>γCOP¹⁰</italic> embryos (light grey bars) compared to heterozygous siblings (dark grey bars). 100% corresponds to nine successful fusion events in the ten tracheal metameres on one side of the embryo. Error bars indicate standard deviation. (A–F) are wide field fluorescent micrographs, (G–L) are single confocal sections taken at identical settings.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s001\"><label>Text S1</label><caption><p>Identification of mutations and removal of background mutations.</p><p>(0.09 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s002\"><label>Figure S1</label><caption><p>Map of <italic>γCOP</italic> jump out deletions. Genomic sequence of the <italic>γCOP</italic> locus; position 1 has been chosen arbitrarily. <italic>γCOP</italic> transcripts LP01448 (for <italic>γCOP</italic>-RA) and the breakpoints of different <italic>γCOP</italic> jump out deletions are aligned. Exons are highlighted in bold. LP01448 starts at position 1086 and γCOP-RB starts at position 1067. Translation starting ATG sequences are displayed in capital letters and in red. The gt/ag consensus splice sites sequences are highlighted in red. It is notable that the first intron is spliced out only in the LP01448 transcript (highlighted in purple), therefore, the translation start site of the shorter transcript is present on the longer transcript (<italic>γCOP</italic>-RB) and seems to be ignored for the production of γCOP-PB. The protein sequence of both γCOP-PA and γCOP-PB are displayed below the genomic DNA sequence; the alternative N-terminus of γCOP-PB is highlighted in blue; Amino acid numbering is in black for PA and in blue for PB. The stop codons in all three frames in the 3'UTR are highlighted in red. In the deletion <italic>γCOP¹⁰</italic> positions 74 to 1974 are deleted (first and last present and deleted nucleotides are displayed as capital letters). In deletions <italic>γCOP⁵</italic>, <italic>γCOP¹²</italic>, <italic>γCOP⁶</italic> and <italic>γCOP⁸</italic> a short fragment of the P-element IR (magenta) and the transcription start site are still present. In <italic>γCOP⁶</italic> 28 bp of unknown origin are also present. The beginnings of the presumptive <italic>γCOP</italic> transcripts made in these deletions (starting with either the <italic>γCOP</italic>-RA or RB transcription start sequence) are shown in line with the genomic sequence at both breakpoints. The 5′ breakpoint for the deletions <italic>γCOP⁵</italic>, <italic>γCOP¹²</italic>, <italic>γCOP⁶</italic>, <italic>γCOP⁸</italic> is at position 1092, the 3′ breakpoint for the deletion <italic>γCOP⁵</italic> is at position 1568, the 3′ breakpoint for the deletion <italic>γCOP¹²</italic> is at position 1776, the 3′ breakpoint for the deletion <italic>γCOP⁶</italic> is at position 2139, the 3′ breakpoint for the deletion <italic>γCOP⁸</italic> is at position 2166. It is conceivable that a short peptide (MMK) is encoded on the IR sequence. However, it is also conceivable that a shortened γCOP protein is synthesized starting from the second AUG sequence present on these presumptive transcripts because in all deletions the second AUG is in frame with the coding frame and preceded by sequence motifs satisfying the requirements for a translation start site ##REF##3822832##[54]##–##REF##12165842##[55]##. For all transcripts positions -1 to -4 (corresponding to the presumptive Shine-Dalgarno sequence) in respect to a potential translation starting AUG are underlined (red for wt <italic>γCOP</italic> transcripts, pink for the transcripts of mutant <italic>γCOP</italic> loci); nucleotides identical with the <italic>Drosophila</italic> consensus sequence as defined by Cavener ##REF##3822832##[54]## are displayed in capital letters. The deletion breakpoint of the <italic>Df(3R)pygo^11-3</italic> allele is at position 3187 of the <italic>γCOP</italic> gene. Through the deletion, three new aa and a new stop codon are introduced; the <italic>pygo^11-3</italic> locus gives potentially rise to a 570 aa <italic>γCOP</italic> protein ending with the sequence IMV (in total 573 aa).</p><p>(0.12 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s003\"><label>Movie S1</label><caption><p>Development of the tracheal system in a homozygous <italic>γCOP¹⁰</italic> mutant embryo. Anterior is to the left and dorsal to the top. The tracheal cells express <italic>αCat-GFP</italic>. The images were acquired at 2 min intervals. Several dorsal branches break. The dorsal trunk shows a fusion defect. Dorsal closure is incomplete.</p><p>(2.26 MB MOV)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s004\"><label>Movie S2</label><caption><p>Development of the tracheal system in a homozygous <italic>γCOP¹⁰</italic> mutant embryo carrying the genomic rescue construct <italic>Ω35-i17</italic>. Anterior is to the left and dorsal to the top. The tracheal cells express <italic>αCat-GFP</italic>. The images were acquired at 2 min intervals. Tracheal system development is normal. There is no dorsal closure defect.</p><p>(2.28 MB MOV)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s005\"><label>Movie S3</label><caption><p>Development of the tracheal system in a homozygous <italic>γCOP¹⁰</italic> mutant embryo expressing the <italic>γCOP</italic> cDNA LP01448 by means of the Gal4/UAS system in tracheal cells (UAS-<italic>γCOP</italic>). Anterior is to the left and dorsal to the top. The tracheal cells express <italic>αCat-GFP</italic>. The images were acquired at 2 min intervals. Tracheal system development is normal. However, dorsal closure is incomplete.</p><p>(2.29 MB MOV)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003241.s006\"><label>Movie S4</label><caption><p>Development of the tracheal system in a homozygous <italic>γCOP¹⁰</italic> mutant embryo expressing <italic>pio</italic> by means of the Gal4/UAS system in tracheal cells (UAS-<italic>pio</italic>). Anterior is to the left and dorsal to the top. The tracheal cells express <italic>αCat-GFP</italic>. The images were acquired at 2 min intervals. The dorsal branches extend without breaking. The dorsal trunk still shows a fusion defect and does not expand normally. Dorsal closure is incomplete.</p><p>(2.28 MB MOV)</p></caption></supplementary-material>" ]

[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work was supported by grants from the Kantons Basel-Stadt and Basel-Land (MA), the German Research Foundation (SL), The Swiss National Science Foundation, an EMBO long term fellowship (EC), a FEBS fellowship (EC), the Treubel-Fonds, Basel (NCG) and the NIH grant RO1 GM082994 (KC).</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003241.g001\"/>", "<graphic xlink:href=\"pone.0003241.g002\"/>", "<graphic xlink:href=\"pone.0003241.g003\"/>", "<graphic xlink:href=\"pone.0003241.g004\"/>", "<graphic xlink:href=\"pone.0003241.g005\"/>", "<graphic xlink:href=\"pone.0003241.g006\"/>" ]

[ "<media xlink:href=\"pone.0003241.s001.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003241.s002.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003241.s003.mov\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003241.s004.mov\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003241.s005.mov\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003241.s006.mov\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>1. INTRODUCTION</title>", "<p>Genomics is playing a growing role\nin almost any biological experimentation. Based on presently available\ncommercial expression array technologies, an investigator is given almost\nfull-genome coverage of transcriptional changes that provides for novel methods\nfor gene identification and validation. However, exhaustive data mining from\ngenomics datasets is cumbersome, and to a large extent is outside the expertise\nof the individual experimenter. The greatest strength in genomics data analysis\nstems from multidimensional analysis, as such orthogonal comparison can bring\nout biologically relevant information not extractable from the individual\ndatasets alone. However, such multidimensional querying is often advised\nagainst, as individual genomics experiments are performed in different\nlaboratories, using dissimilar methodologies. Such array data should not be\nuploaded and analyzed concomitantly in the available software data analysis\nprograms commonly used. Prudent analysis of multiexperimental results would\ntherefore call for individual data analysis of experimental sets, and only\nparse for intersections/exclusions within the resulting gene lists. This is\npossible through genomics analysis platforms using separate gene list saving.\nHowever, the process is burdened by the fact that the analysis of a relevant\ndataset for orthogonal querying requires the identification of the existence of\nthe data, upload, normalization, and scaling of individual DNA chip scan files\nand thereafter selecting and executing a valid analysis for the particular\ndataset, followed by results storage. In practice, this is time consuming, and\ntoo overwhelming, for most biologists.</p>", "<p>In the islet and islet\ndevelopmental biology research fields, a continuously growing set of public\ngenomics data is becoming available. Also, initial problems in both genomics\nchip design and experimental execution are gradually being overcome. It is\ntherefore appreciated that a large, generally untapped resource is provided by\ngenomics analyses performed in islet-focused laboratories around the world. Two\nonline databases, T1dbase [##REF##17169983##1##] and EpconDb [##REF##17071715##2##], contain genome data\nrepository components within their sites. However, they do not provide advanced\nmultiexperimental querying options that would allow generation of gene lists\nbetween experiments. Acknowledging this, we set forth to create a resource that\nwould consolidate diabetes-research relevant genomics data and allow rapid\nmultidimensional analysis between such datasets. To do this, we created an\nonline genomics data repository, which we term GeneSpeed Beta Cell. This was\ndeveloped as an additional component of the GeneSpeed resource [##REF##17132830##3##], see \n##FIG##0##Figure 1##. GeneSpeed Beta\nCell (<ext-link ext-link-type=\"uri\" xlink:href=\"http://genespeed.ccf.org/betaCell/\">http://genespeed.ccf.org/betaCell/</ext-link>) contains two forms of \ndata: normalized and similarly scaled genomics data relevant for the islet or pancreatic \ndevelopmental biologist. Secondly, it contains precalculated analyses, which include pairwise\nand self-organizing neural network clustering results applied to relevant data\nseries. On the analysis side, GeneSpeed Beta Cell provides “My Gene Workspace”\nwhere gene list overlap can be evaluated. It also provides access to any search\nparameter in the GeneSpeed environment, including precalculated data on tissue\nspecificity (Shannon entropy) and wide-tissue\nbatch expression queries. Together, the unified environment within the\nGeneSpeed database provides for some unique capacities not found elsewhere. We\nhere describe the use of GeneSpeed Beta Cell by addressing a set of novel, and biologically\nrelevant, questions appealing to the islet biologist.</p>" ]

[ "<title>4. METHODS</title>", "<title>4.1. Genomics data incorporation and analysis</title>", "<p>The “GeneSpeed Beta Cell” environment was developed using the J2EE platform on a Linux\nserver. For Affymetrix-type genomics data, we compiled the CEL files (raw data)\nassociated with different experiments from different sources and normalized\nthem locally using MAS5.0 algorithm, using an identical scaling factor of 500,\nto ensure optimal comparability in a cross-experimental setting.</p>", "<p>The microarray experiments\ncurrently available can be grouped, and hence analyzed, according to\nexperimental design type. For time-series experiments (and drug-effect studies),\nan SOM neural network clustering algorithm was applied. The number of clusters\nselected is empirically based on individual results, selecting the minimal\nnumber adequately describing the data complexity. A graphical presentation is\nprovided of the log-transformed expression averages of genes within the\ncluster. Also, the total number of gene number contained/cluster is provided. R\nand Bioconductor [##REF##16939789##7##] were used to accomplish this\ntask.</p>", "<p>For multicomponent analysis, which also\nincludes single pair-wise analysis, ANOVA testing was performed. For\nmultiple-condition datasets, several pair-wise analyses are provided. These\nresults are depicted through volcano plots. A false discovery rate (FDR) test\ncorrection on the ANOVA result at 10% significance is provided for each plot as\nthe default <italic>P</italic>-value setting. On the volcano plots, the boxed areas\noutlining a 10% FDR corrected <italic>P</italic>-value and the −2 to +2 fold regions of\nchange are shown.</p>", "<title>4.2. Account functionality</title>", "<p>There are two account types in\nGeneSpeed: “guest” and “registered user.” In order to use the workspace\nenvironment registration is required. A “registered user” can log back into\ntheir account to gain access to saved studies. Establishing a registered\naccount is free and can be done on the GeneSpeed registration page (<ext-link ext-link-type=\"uri\" xlink:href=\"http://genespeed.ccf.org/loginReq.php\">http://genespeed.ccf.org/loginReq.php</ext-link>).\nAn automated password will be sent to the newly registered user. The\nconfidentiality of all registration information is strictly maintained and we\nwill only use such information to notify our users of any disruptions or\nmodifications of the GeneSpeed service. At present, only registered users are\nallowed to use the GeneSpeed Beta Cell database.</p>", "<p>The GeneSpeed account allows\nregistered users to save gene lists into a private account that is permanent\nand may only be viewed by the owner. The “My Gene Workspace,” on the other\nhand, maintains gene lists temporarily during the current login session; upon\nlogging out the content of the “workspace” will be deleted.</p>", "<title>4.3. Functional implementation of “My Gene Workspace”</title>", "<p>The “My Gene Workspace” logic was\ndeveloped using J2EE and sql-type queries. Facilitating cross-platform\ncomparisons, the workspace utilizes Unigene cluster Ids (UID). Consequently,\nthe probeset identification through the experimental analyses is translated\ninto corresponding UID upon transfer to the workspace. As a result, if more\nthan one probeset is detected for a given gene in the analysis, these probesets collapse into\nthe UID of that gene. Secondly, upon selection of the content of a gene list in\nthe workspace, followed by showing the content in the expression space, all probesets corresponding to the\nselected Unigene will be displayed. To reduce ambiguities, we update the system\ncontinuously upon the availability of updated mapping files from NetAffx Analysis Center\nserver. Given that the NCBI Unigene dataset is constantly evolving, updated\nmapping to the most recent UID is done every 6 months.</p>" ]

[]

[ "<title>3. DISCUSSION</title>", "<p>Of the current available places for\ngenomics data reposition, the NCBI GEO (gene expression omnibus, [##REF##17099226##5##]) is presently the most\nexhaustive. The development of GEO proceeds to include data analysis of public\narray-type experiments, which also include those deposited on islets, or\ndeveloping pancreas. The tools are currently limited to analyses performed\nwithin individual experiments, and data results cannot be ported between experiments.\nHowever, no other resource exists with a similar exhaustive compilation of DNA microarray-type datasets,\nand as such, GEO represents a growing and increasingly important pillar for\narray data compilation. In contrast to the more universal user-base that GEO\nseeks to cover, certain resources have also been made available and dedicated\nto the islet community. T1Dbase (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.t1dbase.org/\">http://www.t1dbase.org/</ext-link>)\nwas specifically developed to catalogue information on the genetics of type-I\ndiabetes, and contains extensive information on candidate gene regions [##REF##17169983##1##]. It also contains a\nmicroarray repository and a recently developed <italic>Gene Atlas</italic> search\nfunction, aimed at providing a rapid visualization of gene expression in\nislets. The strength of the environment lies in the use of Gaggle [##UREF##1##6##], which is a Java-based\ncommunicator interface to several bioinformatics tools. However, to use this\nrequires a significant knowledge of the Gaggle-implemented tools such as the\nTIGR tmev (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.tm4.org/mev.html\">http://www.tm4.org/mev.html</ext-link>) or R\n(<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.r-project.org/\">http://www.r-project.org/</ext-link>),\nnotwithstanding a rather complicated data upload scheme. Despite its strength,\nthis may therefore represent a time-consuming and intellectual barrier to most\nbiologists using the resource irregularly. Another comparable resource, the\nEpconDb (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.cbil.upenn.edu/epcondb42/\">http://www.cbil.upenn.edu/epcondb42/</ext-link>)\n[##REF##17071715##2##], originally generated by the\nEndocrine Pancreas Consortium and funded through the NIH Beta Cell Biology\nConsortium (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.betacell.org/\">http://www.betacell.org/</ext-link>), also\nprovides microarray chip repository support. Recently, precalculated analysis\nresults for select experiments are also provided. The structure of the EpConDb\nresource centers on the GUS (genome unified schema), which includes the DOTS\ndatabase. DOTS shares significant similarities to the NCBI-devised Unigene EST\ndatabase, but extend to include splice site data, as well as promoter\ndefinition.</p>", "<p>The GeneSpeed Beta\nCell site seeks to complement these resources on particularly two fronts: to\nprovide more extensive orthogonal analysis between array experiments and to\nprovide a functional gene list operator workspace, which neither the T1dbase\nnor Epcondb sites allow. To achieve the former, we focused on providing a\nlarger degree of relevant precomputed analyses of array experiments providing\nthese in an easy-to-query format. To achieve the latter, we developed a gene\nlist workspace that would allow for platform-to-platform compatibility using\nthe common Unigene denominator, which is the nexus of the GeneSpeed MySQL\ndatabase. The current version of the database provides certain features not\nfound elsewhere, some of which has been addressed through the demonstration\ncases. Yet, the database is a currently developing structure that in its\npresent form is useful, but easily imagined improved. Therefore, we are\ncurrently focusing on key aspects for the further development of the GeneSpeed\nenvironment. These include the identification of additional relevant microarray\nexperiments; filling out “missing links” by performing stop-gap-type microarray\nexperiments for populating critical, but missing, areas of the pancreatic\nexpression space; improving the search and query formats for user-friendliness;\nand finally developing an export/import interface for pathway analysis programs\nsuch as Ingenuity Pathway Analysis (IPA).</p>", "<p>The usefulness of GeneSpeed\nBeta Cell database is dependent on the amount of available genomics data\ncontent. A linear increase in number of available datasets and accompanying precomputed\nanalyses translates into an exponentially growing set of query combinations.\nThere are obvious gaps in the available datasets, as multiple null mutations\nhave been created for several key developmental regulators during pancreatic\ndevelopment, and several mutant models resulting in diabetes due to beta-cell\ndysfunction have also been reported, all of which would represent valuable data\nin the present environment. Therefore, we are asking the islet research\ncommunity to share available datasets for multidimensional analysis. Also, we\nwill continue to upload publicly available datasets from the GEO environment.</p>", "<p>For a wet-biology laboratory like our own, the present\nincarnation of the database has provided means of moving forward in otherwise\ndifficult-to-execute bioinformatics-based questions. We hope that the same\nappreciation may pioneer gene identification challenges in other laboratories\nhereby helping the diabetes research community.</p>" ]

[]

[ "<p>Recommended by Ulf Eriksson</p>", "<p>\n<italic>Objective</italic>. We here describe the development of a freely available online database resource, GeneSpeed Beta Cell, which has been created for the pancreatic islet and pancreatic developmental biology investigator community. <italic>Research Design and Methods</italic>. We have developed GeneSpeed Beta Cell as a separate component of the GeneSpeed database, providing a genomics-type data repository of pancreas and islet-relevant datasets interlinked with the domain-oriented GeneSpeed database. <italic>Results</italic>. GeneSpeed Beta Cell allows the query of multiple published and unpublished select genomics datasets in a simultaneous fashion (multiexperiment viewing) and is capable of defining intersection results from precomputed analysis of such datasets (multidimensional querying). Combined with the protein-domain categorization/assembly toolbox provided by the GeneSpeed database, the user is able to define spatial expression constraints of select gene lists in a relatively rigid fashion within the pancreatic expression space. We provide several demonstration case studies of relevance to islet cell biology and development of the pancreas that provide novel insight into islet biology. <italic>Conclusions</italic>. The combination of an exhaustive domain-based compilation of the transcriptome with gene array data of interest to the islet biologist affords novel methods for multidimensional querying between individual datasets in a rapid fashion, presently not available elsewhere.</p>" ]

[ "<title>2. GENESPEED BETA CELL DATABASE STRUCTURE\nAND NAVIGATION</title>", "<title>2.1. Multiexperimental viewing</title>", "<p>“GeneSpeed Beta Cell” is a gene\narray data repository linked to the GeneSpeed environment. For a more detailed\ndescription of the domain-based gene categorization afforded by GeneSpeed,\nplease refer to [##REF##17132830##3##] and the online background and\ntutorials. GeneSpeed Beta Cell consists of a central “experiment selector page”\n(##FIG##1##Figure 2##), listing experiments by relevance to embryonic development, adult\nislet studies, adult whole pancreas studies, experiments using cell lines, and\nsolid tumor data. Currently, the site is being expanded with gene chip data of\ndeveloping nonpancreatic endoderm. For each group, experiments are separated\ninto human and mouse studies. At current, Affymetrix-type data is supported,\ngiven that the body of relevant genomics data is the largest on this particular\nplatform; but as the parent GeneSpeed database is not platform-specific, we\nhave also made it capable of operating with the Illumina BeadChip type datasets.\nAll current Affymetrix-type datasets in the repository were obtained as\nunnormalized raw cel files, and were normalized using MAS5.0 using identical\nsettings and similarly scaled for cross-experimental comparisons (see methods).\nThe available data can be viewed through multiexperimental viewing. Any saved\ngene list can be viewed for any of the available datasets. This is a fast and\nconvenient way to display the normalized expression values of defined gene\nlists between independent experiments performed in different laboratories. The\nresulting display page is constructed to facilitate horizontal glancing of expression\nvalues, while maintaining the individuality of experiments. As there is no\nlimit as to the number of genes shown or number of experiments selected, the\nresulting page view can be quite large. To assist the identification of the\nrespective column (tissue type/experimental condition) and row (gene symbol), a\nhovering tool supplying this information was implemented. Also, for quick\nanalysis of the gene ID, each cell is hyperlinked to the respective Unigene\npage for that gene. If a gene within a gene list does not contain a respective\nprobeset, the cell content is displayed as N.A. The multiexperiment viewer\nfacilitates table sorting based on each component in selected datasets. This\nprovides, for example, quickly arranging genes in a larger gene list according\nto expression levels for any tissue/condition selected (e.g., ##FIG##2##Figure 3## shows a\nlist of homeodomain-class genes sorted based on expression at the E12.5\ngestational time point in pancreatic development).</p>", "<title>2.2. Multidimensional analysis in “My Gene Workspace”</title>", "<p>To enhance online capabilities, we\ndeveloped tools for multidimensional analysis. The multidimensional analysis\ntool operates within a “My Gene Workspace” environment (##FIG##3##Figure 4##), which is\narray-platform independent as it stores genes by Unigene identifier. “My Gene\nWorkspace” allows for temporary storage of gene lists, naming such, and\nselecting individual lists to be combined using the Boolean operators AND or\nOR. Hereby, intersections (AND), or additive combinations (OR) can be performed\non the selected gene lists, for further logical operations or visualized using\nthe multiexperimental viewer. Several means of populating the workspace is\npossible. The user is provided with a “permanent list” account, in which work\nbetween sessions can be saved. Lists can here be grouped according to project\nname. Gene lists from the permanent account can be ported to the workspace or\ngene family choices from a concurrent GeneSpeed query that can be directly imported. In addition,\ngene list results from precalculated analyses based on the available datasets\ncan be added. The final option provides a highly useful method to dynamically aggregate\nand compare results from individual experimental data that was not initially\ndesigned for a combined analysis. Such comparisons can be highly scientifically\nrelevant, and examples are provided later.</p>", "<p>As this latter method is based on\nprecalculated analysis of available datasets, a certain level of a priori\nchoice has been necessary to implement, as all permutations of possible data analysis\ncould not be practically implemented. Consequently, depending on the underlying\nexperimental conditions, the precomputed analysis is restricted to pairwise\nanalysis (although multiple pairwise comparisons are often provided for a given\ndataset), or a self-organizing cluster analysis (for series-type data such as\nexperimental time, drug concentration, or developmental time). Graphical\npresentation of each analysis is provided to help the user gauge gene numbers\ngiven the conditions chosen. For pairwise analysis, a volcano plot (plotting\nsignificance (<italic>p</italic>-value) versus fold-change) of the pairwise analysis result is\nshown. The default cutoff for gene selection is set at a false discovery rate\nof 0.1, but can be changed to the user's preference. Similarly, the fold-change\nrange can be freely set, allowing the user to port, that is, &gt;2-fold\nupregulated genes in a given condition into the workspace. The graphical\npresentation of cluster analyses contains a cluster number, and number of genes\nwithin the cluster. The user is free to\nselect any number of clusters and port to the workspace. In this manner,\nvarious experimental conditions can be continuously ported to the workspace,\nand the experimental multi-intersectional analysis occurs there. There is no\nlimit to the number of gene lists present in the workspace. We should note that\nfor both the multidimensional viewing page, and for the multidimensional query\nform in the workspace, individual datasets are always kept separate (viewer),\ntreated as such (query page), and are never pooled. Cross-experimental pooling\nis not tolerable due to varying conditions in different laboratories during\ndata generation.</p>", "<title>2.3. Current experimental content of GeneSpeed Beta Cell</title>", "<p>As the available datasets and analyses grow on a daily basis, users should visit the site for a list of\ncurrently available datasets and analyses.</p>", "<title>2.4. GeneSpeed Beta Cell use-case scenarios</title>", "<p>Some biologically relevant use-case\nscenarios for the islet cell biologist are described in the following. Each of\nthese is available also as online tutorials at GeneSpeed Beta Cell at <ext-link ext-link-type=\"uri\" xlink:href=\"http://genespeed.ccf.org/betaCell/tutorial.jsp\">http://genespeed.ccf.org/betaCell/tutorial.jsp</ext-link>.\nAs for any bioinformatics-based method application, the results are provided as <italic>candidate</italic> gene lists, corresponding to genes/probesets fulfilling input\ncriteria. The further validation of such lists using noninformatics-based techniques is a\ngeneral requirement. In the following demonstrations, the end-result gene lists\nare often supported by previous published data from other sources, hereby\nproviding the validation required for the particular demonstration scenarios.</p>", "<p>\n<statement id=\"ex1\"><title>Example 1</title><p>(Compiling lists of islet-expressed transcription\nfactors (online tutorial 1)). We wish to address the issue of\ndefining islet-expressed transcription factor (TF) encoding genes. To do this,\nwe will utilize the predefined transcription factor categorization provided by\nthe GeneSpeed database, assemble a nonredundant list of TF encoding genes, and\nfind those reduced in <italic>Ngn3</italic> null pancreas. First, we select “new search,”\nand desired species “mouse” from the drop-down menu. Next, we select “search by\ntranscription factor classification” within the GeneSpeed search options. As 5\nmajor domain family groupings exist for the transcription factor type genes, we\nwill need to iterate the following procedure for each, but will here limit the\nfamilies to the “Basic,” “Beta-Scaffold,” and “HTH” superfamilies. These\nfamilies contain, for example, the leucine zipper, bHLH, and homeodomain\ntranscription factor families, but not the Zn-finger class. Selecting “Basic”\nas the first type, we ctrl-select all the subfamily members of the basic TF\nsuperfamily. Displaying the result provides 685 hits. These correspond to every\ninstance where the Unigene database of the mouse contains a homology hit for\nany of the domain types associated the “basic” superfamily. However, as the\ndatabase has no preset lower E-score cutoff, several false positives exist in\nthis list (see discussion of how to set an E-score cutoff on the description\npages at GeneSpeed for a full explanation). To eliminate low-scoring similarity\nhits, we set the E-score cutoff at E10-6, and redo the search. Now, a resulting\nlist of 167 genes is detected. We save these to the user account under an\narbitrary name (All_TFs). This process is repeated for the TF superfamilies\nmentioned above, where the individual results is added to the All_TF's list,\nconsequently providing a list of &gt;1600 individual Unigenes. These are next\nimported into the “My Gene Workspace.” To extract genes unique to pancreatic\nislets in the developing pancreas, we will take advantage of the available\ndataset for Ngn3-null embryonic pancreas, which is listed under the experiment\nlisting page of GeneSpeed Beta Cell. A pair-wise analysis is provided comparing\nE15.5 Wt and E15.5 <italic>Ngn3</italic> Null pancreas. The <italic>Ngn3</italic>-deficient\npancreas is excellent to define endocrine-specificity, as the organ is devoid\nof endocrine cells. Selecting genes upregulated &gt;1.5 fold, <italic>P</italic> &lt; .25,\na second list is imported into the workspace as <italic>Down_in_Ngn3</italic>. This list\ncontains 114 genes. Obtaining the intersection between the <italic>TF_ALL</italic> and <italic>Down_in_Ngn3</italic> lists provide a total of 8 transcription factor encoding genes lost in Ngn3\nmutant E15.5 pancreas: <italic>Ngn3, NeuroD, Isl1, Pax6, Arx, MafB, Nkx2.2, Insm1</italic>, and <italic>HIF1a</italic>.</p></statement>\n</p>", "<p>\n<statement id=\"ex2\"><title>Example 2 </title><p>(Multidimensional intersection analysis to\ndefine developmentally regulated expression of protein\nkinase-encoding genes (online tutorial 2)). We here will seek\nto discover kinase-encoding genes that are enriched in either early or late\npancreatic development. A similar study has not been done before. To perform\nthis task, we first need to compile a list of all protein kinase-type genes in\nthe mouse transcriptome. Using a text-search for a gene known as a protein\nkinase (e.g., insr), we obtain two hits: <italic>Insr</italic> and <italic>Insrr</italic>. Both of\nthese are receptor tyrosine kinases, and display the presence of the\nTyr_pkinase domain (IPR001245) with an E-score at 1E10⁻¹⁴⁵. We also\nnote that the generic kinase domain (IPR000719) is detected in both at 1E10⁻²⁴.\nBy checking the “InterPro\nsub-search” box for the IPR001245 domain, and execute the search:\n“refine by subsearch,” we obtain a nonredundant list of Unigene clusters having\nsimilarity to the IPR001245 domain. This provides 480 hits, covering all\nkinase-domain forms (S/T as well as Y-kinase types). To curate against low-similarity\nhits, we manually set the E-score threshold at &lt;1E-6. The resulting list\ncontains bona-fide 432 kinase-containing genes, which we subsequently save as “<italic>Kinase_all</italic>”\nto our account. Many of these genes represent genes with no previous annotation\nas being of the kinase-domain containing type, and may not have been named yet.\nNext, we wish to identify which of these kinase-encoding genes display a\ndownward trend during pancreatic development. To do this, we move to the\n“search GeneSpeed Beta Cell,” and expand the “Embryonic studies” dataset tab.\nSelecting the “kinetic series of mouse pancreatic development 1” precomputed\ncluster analysis, we are provided with the results of a Kohonen's\nself-organizing cluster analysis in a graphical format. Gene clusters with a\ndownward trend during pancreatic development are selected (cluster\n3,4,5,8,9,15,20) and combined using the selection tool provided. The results\nare saved as <italic>Genes_Trend_Down</italic> to the workspace. Within the workspace the\nintersection between the Genes_<italic>Trend_Down</italic> and the <italic>Kinase_all</italic> lists are obtained using the Boolean operator AND. The resulting list contains\n138 kinase-type genes. The list can be saved, or gene expression of the\nparticular genes can be displayed in some or all mouse array experiments in the\nGeneSpeed Beta Cell database. The latter may provide important clues as to\ntissue-specific expression of individual members. Finalizing this demonstration,\nwe wish to address the identity of kinase-encoding genes that are upregulated\nover time in the developing pancreas. By repeating the above method for\nkinase-type genes displaying upregulation (Cluster 6,11,16,17,21,22, generating\nlist <italic>Gene_Trend_Up</italic>), only 27 genes are identified. We can conclude that\nmore kinase signaling diversity exists prior to rather than after the secondary\ntransition in the mouse pancreas.</p></statement>\n</p>", "<p>\n<statement id=\"ex3\"><title>Example 3</title><p>(Defining human islet-specific expression using\nShannon Entropy with exocrine elimination (online tutorial\n3)). This example uses the available\ndataset on human tissues, as provided by the Novartis Genomics Institute (<ext-link ext-link-type=\"uri\" xlink:href=\"http://symatlas.gnf.org/SymAtlas/about.jsp\">http://symatlas.gnf.org/SymAtlas/about.jsp</ext-link>).\nA tissue set consisting of 79 human tissues and 61 different mouse tissues, mostly\nadult solid organs, has been generated in duplicate using the Affymetrix GNF1\nplatform. To provide a measure of tissue expression selectivity, we adopted the\nmethod of Shannon entropy determination, as previously described by Schug et\nal. [##UREF##0##4##]. Shannon entropy provides quantitative measures of expression using a bit-rate scale.\nFor each gene, the Shannon entropy (<italic>H</italic>\n_gene)\ndefines the degree of ordered expression; as a rule, the lower the <italic>H</italic>\n_gene,\nthe fewer tissues in the total set express the gene in question. To identify\nthose tissues showing uniqueness in expression, the measure <italic>Q</italic>\n_tissue can be used. Again, as a rule, the lower the <italic>Q</italic>\n_tissue value, the more\nspecific the gene is expressed in that particular tissue. A rank order of the\nlowest <italic>Q</italic>\n_tissue values thus provides a list of those genes that have\nthe highest selectivity for the tissue in question. Shannon entropy computations were performed for all tissues in the above datasets. As\nthe human, but not the mouse, datasets contain array data for islets, the present\nexample is currently limited to human. From the GeneSpeed search query, we\nselect species “homo sapiens,” and thereafter “search by expression.” We select\nthe human GNF1A chip, and “calculated Shannon entropy” using the drop-down boxes. The following page contains selector boxes\nfor each tissue in the set. For pancreatic islets, we select a <italic>Q</italic>\n_tissue value of &lt; 1.7 × <italic>H</italic>\n_gene. The user should have experiment with the <italic>Q</italic>\n_tissue setting; the lower values (approaching <italic>H</italic>\n_gene) provide smaller\nnumbers, but more tissue-specific genes. Relaxing the value towards a value of\n2 × <italic>H</italic>\n_gene provides more exhaustive, albeit less selectively\nexpressed genes. At <italic>Q</italic>\n_islet at 1.7 × <italic>H</italic>\n_gene, we identify 96\nprobesets (as more than one probeset may exist for each gene, the actual number\nof genes identified is often slightly lower). Selecting to show all Shannon entropy values, we next copy the entire table\ninto Excel, in order to rank-order the hits. Not surprisingly, the\ntop of this list consists of Glucagon (<italic>GCG</italic>), Insulin (<italic>INS</italic>), <italic>IAPP</italic>,\nbut we also notice that not far from the top, some nonendocrine-type genes, such as <italic>PNLIPRP1</italic> and <italic>CPA2</italic> are present. The reason for this is due to exocrine\ncontamination. The majority of such genes are easily removed by eliminating all genes in which\n<italic>Q</italic>\n_panc &lt; <italic>Q</italic>\n_islet. Ranking the resulting genes provides a\nlist of genes showing the highest selectivity for pancreatic islets compared to\n78 other human tissues (the 30 top-ranked genes of this list is shown in ##TAB##0##Table\n1##). The results include the complement of endocrine terminal products (<italic>Ins, Gcg, Sst, Ppy</italic>), four Reg-type genes\n(<italic>Reg1b, Reg3g, Reg3a, Regl</italic>), several\nwell-known endocrine transcripts (<italic>Pcsk1</italic> (PC1/3), <italic>Iapp, Slc30a8</italic>), secretogranins\n(<italic>Scgb2a1, Scgn, Scg5, Scg2, Scg3</italic>),\nand transcription factors known to function in the islet (<italic>FoxA2, Nkx2.2, Isl1</italic>).</p></statement>\n</p>", "<p>\n<statement id=\"ex4\"><title>Example 4</title><p>(Pituitary versus pancreatic islets: finding common\nneuroendocrine properties (online tutorial 4)). It is known that neuroendocrine\ncell types shares certain characteristics related to production and release of\nsecreted products. The pituitary and islets are highly enriched in cells\nproducing polypeptide hormones. Using Shannon entropy, we will here ask what are the genes that may be in common between pituitary and\npancreatic islets and not expressed widely elsewhere. Similar to above,\nwe select Shannon entropy query in GeneSpeed,\nand input a slightly relaxed <italic>Q</italic>\n_tissue value of 1.8 for both pituitary\nand pancreatic islets. Individually, <italic>Q</italic>\n_Islet &lt; 1.8 × <italic>H</italic>\n_{<italic>g</italic>} and <italic>Q</italic>\n_pituitary &lt; 1.8 × <italic>H</italic>\n_{<italic>g</italic>} identify 292 and 222\nprobesets, respectively. The intersection is 21 probesets, corresponding to 19\nindividual genes (##TAB##1##Table 2##, 3 probesets for <italic>GNAS</italic>, guanine nucleotide\nbinding protein were identified). Three genes encode known granule-type\nproteins (<italic>ChgrA</italic>, secretogranin 2 (<italic>SCG2</italic>), secretogranin 5 (<italic>SCG5</italic>)).\nTwo transcription factors are found: InsM1 and ZNF91. The proprotein convertase\nsubtilisin/kexin type-1 inhibitor (<italic>PCSKN1</italic>) and the peptidylglycine\nalpha-amidating monooxygenase are also present. Other products include <italic>CACNA1F</italic> (Calcium channel, voltage-dependent, alpha 1F), <italic>CNGA3</italic> (Cyclic nucleotide\ngated channel alpha 3), the transmembrane protein <italic>TMEM30</italic> as well as\nseveral uncharacterized genes. Many of these genes represent expected hits, and\nshow the value of combining parameters such as tissue uniqueness and\noverlapping gene expression to derive a meaningful candidate repertoire for\nfurther scrutiny.</p></statement>\n</p>" ]

[ "<title>ACKNOWLEDGMENTS</title>", "<p>Nick Robertson, MPT (Louisville, Colo, USA) is thanked\nfor helping develop GeneSpeed. The development of GeneSpeed Beta was conceptually\nan offspring of the Chicago project (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.thechicagoproject.org/\">http://www.thechicagoproject.org/</ext-link>):\nan international effort for a functional cure of diabetes and funding for\nsoftware development was obtained from there. Specifically, Dr. Jose Oberholzer\nis thanked for ongoing comments and critique helping to improve the resource\nduring its development. Additional funding for the project which includes\ngenomics data acquisition was provided by the American Diabetes Association\n(Career Development Award, J.J) and the Children's Diabetes Foundation at\nDenver (J.J), the Diabetes and Endocrine Research Center (NIH P30 DK57516,\nJ.C.H.), the Beta Cell Biology Consortium (NIH U19 DK61248 (J.J, J.C.H), and\nNIH U19 DK072495-0 (G.G)).</p>" ]

[ "<fig id=\"fig1\" position=\"float\"><label>Figure 1</label><caption><p>GeneSpeed and GeneSpeed Beta Cell comparison.</p></caption></fig>", "<fig id=\"fig2\" position=\"float\"><label>Figure 2</label><caption><p>Web-page view of the GeneSpeed Beta Cell experiment selection window.</p></caption></fig>", "<fig id=\"fig3\" position=\"float\"><label>Figure 3</label><caption><p>Example output page of homeodomain-class\ngenes expressed in pancreatic development from E12.5 to E18.5. The list was\nordered based on expression levels in E12.5 pancreas. As examples, Mrg1 and\nAdnp are expressed at high levels throughout pancreatic development. Several\ngenes such as Pitx2 and multiple Hox-family members decrease abruptly after\nE14.5, and are only expressed significantly during early organ development.</p></caption></fig>", "<fig id=\"fig4\" position=\"float\"><label>Figure 4</label><caption><p>Web-page view of “My Gene Workspace” selection window.</p></caption></fig>" ]

[ "<table-wrap id=\"tab1\" position=\"float\"><label>Table 1</label><caption><p>Results, use-case scenario 3. Genes defined as most specific for\nhuman islets as based on Shannon Entropy calculations.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">Gene</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Symbols</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Entropy <italic>H</italic>\n_{<italic>g</italic>}\n</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">\n<italic>Q</italic>\n_Islets\n</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">\n<italic>Q</italic>\n_Pancreas\n</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.516494</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GCG</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.32</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.65</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.22</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.89832</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">INS</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.74</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.04</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.46835</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">IAPP</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.95</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">2.33</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.63</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.4158</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">REG1B</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">2.82</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.91</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.48</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.447084</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">REG3G</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.61</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.46</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.89</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.567312</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">REG3A</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.45</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.65</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.41</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.584797</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">REGL</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.61</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.91</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.59</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.12409</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SST</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.15</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.27</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.558368</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PPY</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.28</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.36</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.82</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.78977</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PCSK1</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.31</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.72</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.8</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.97644</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCGB2A1</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.17</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.83</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.14</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.204238</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">LCN2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3.95</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.24</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.34</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.612083</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.23</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.51</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.43</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.73923</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PNLIPRP1</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.69</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.57</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.05</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.489786</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CFTR</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.8</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.85</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.29</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.116428</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCGN</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.03</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.89</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.34</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.76452</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CRP</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.18</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.21</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.66</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.156540</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCG5</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.92</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.62</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.53985</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GP2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.23</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.71</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">7.72</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.516726</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCG2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4.96</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.3</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.7</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.232618</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCG3</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.12</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.49</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.534458</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CGI-38</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.02</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.51</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.37</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.125898</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GNAS</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.64</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.6</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.81</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.8364</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PDK4</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.72</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.62</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">10.84</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.592742</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">ELL2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.54</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.63</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.26</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.2256</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">MMP7</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.7</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.7</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.14</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.123072</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">RAB3B</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.13</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.78</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.24</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.155651</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">FOXA2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.45</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8.95</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.62</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.516922</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">NKX2-2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.45</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.17</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.68</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.558519</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">ERO1LB</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.63</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.18</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.22</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.491232</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SLC39A14</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.55</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.18</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">10.11</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.260720</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">DNAJC12</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.69</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.25</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.76</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.82071</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CITED2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.58</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.36</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.37</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.503733</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">LOC653275</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.88</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.38</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.61</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.203699</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GOLPH3L</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.59</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.41</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.95</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.479602</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">APBB2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.76</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.45</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.23</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.109590</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GENX-3414</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.89</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.79</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">13.27</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.89655</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PTPRN</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6.01</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.84</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.71</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.532270</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SLC30A8</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">5.97</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.87</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">12.33</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hs.505</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">ISL1</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">9.9</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">11.7</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"tab2\" position=\"float\"><label>Table 2</label><caption><p>Results, use-case scenario 4. Genes specific for both pancreatic islets and pituitary.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">\n</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Unigene ID</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Symbol</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Gene name</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.6790</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">DNAJB9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DnaJ (Hsp40) homolog, subfamily B, member 9</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.156540</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCG5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Secretogranin V (7B2 protein)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.516726</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">SCG2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Secretogranin II (chromogranin C)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.389378</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">MON2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MON2 homolog (S. cerevisiae)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.150793</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CHGA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chromogranin A (parathyroid secretory protein 1)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.152944</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">LOH11CR2A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Loss of heterozygosity, 11, chromosomal region 2, gene A</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.631626</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">ZNF91</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Zinc finger protein 91</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">8</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.89584</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">INSM1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Insulinoma-associated 1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.234785</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CNGA3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cyclic nucleotide gated channel alpha 3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.632799</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">CACNA1F</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Calcium channel, voltage-dependent, alpha 1F subunit</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.369430</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PAM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Peptidylglycine alpha-amidating monooxygenase</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.146180</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">TMEM30B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Transmembrane protein 30B</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.125898</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">GNAS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GNAS complex locus</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">14</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.459183</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">ALPK3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Alpha-kinase 3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">15</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.87295</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">FAM18B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Family with sequence similarity 18, member B</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">16</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.522640</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">PCSK1N</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Proprotein convertase subtilisin/kexin type-1 inhibitor</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">17</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.496542</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">RNF128</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ring finger protein 128</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.444459</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">C9orf135</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chromosome 9 open reading frame 135</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">19</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">Hs.503733</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">LOC653275</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Similar to cryptic/cripto</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"EDR2008-312060.001\"/>", "<graphic xlink:href=\"EDR2008-312060.002\"/>", "<graphic xlink:href=\"EDR2008-312060.003\"/>", "<graphic xlink:href=\"EDR2008-312060.004\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[ "<title>METHODS</title>", "<title>National Health Survey of Pakistan</title>", "<p>Cross-sectional data were collected during the NHSP over four years (1990–1994) by the Pakistan Medical Research Council (PMRC) under the technical guidance and support of the US National Center for Health Statistics (NCHS). The overall design of the survey was a modification of the Third National Health and Nutrition Examination Survey (NHANES III) conducted by the NCHS, tailored to the needs of Pakistan. The details of the sampling, design, components, survey instrument and quality control have been previously reported.##UREF##0##16## Briefly, the survey was conducted on a nationally representative sample of 18 135 individuals aged 6 months to 110 years from 2400 urban and rural households after obtaining informed consent. A two-stage stratified design was used. The urban and rural areas of each of the four provinces of Pakistan were taken as strata. There were 80 urban or rural primary sampling units. A total of 30 households were drawn into the sample from each unit, and all residents of the household were included in the study. The overall individual response rate was 92.6%. The total number of individuals aged 5 years or above was 15 083. Out of these, subjects aged under 15 years were classified as children (n = 5641) in the NHSP.</p>", "<p>Data on demographic, lifestyle, socioeconomic and health-related variables were collected using a questionnaire validated in local languages. Physicians at mobile examination centres performed a standardised physical examination. Mothers were proxy respondents for children aged under 12 years. Trained technicians performed anthropometric examinations.</p>", "<p>Weight and height were recorded to the nearest 0.1 kg and 0.1 cm, respectively, for each child in light clothing without shoes. The BMI was calculated as weight in kilograms divided by height in metres squared. Quality control for the survey included a visit to the field by expert consultants, duplicate examination by field supervisers, calibration protocols and retraining exercises.##UREF##0##16##</p>", "<p>Urban and rural areas were classified according to the definition used by Federal Bureau of Statistics, where thinly populated, largely agricultural areas (fewer than 5000 people) with poor availability of basic amenities (eg, sewerage system, telephone lines) are considered rural.##REF##17060656##13##</p>", "<title>Karachi survey</title>", "<p>This survey was conducted in the urban city of Karachi, Pakistan, during 2004–2005 as part of the baseline data for the trial of a community intervention for the control of hypertension. Ethical approval was obtained from the Aga Khan University Ethics Review Committee.</p>", "<p>Twelve geographical clusters were randomly chosen from among the 72 low-to-middle-income clusters in Karachi. There were approximately 250 households in each cluster. In each household with children between the ages of 5 to 14 years, one child was randomly chosen, and informed consent was obtained from the parent and child for those over the age of 9. A total of 1675 children between the ages of 5–14 years were enrolled in the study.</p>", "<p>Information was collected for each child on their age, gender and educational status. Children under 9 years of age were interviewed in the presence of their parent or guardian. Information on physical activities was collected through questions related to the amount of time in the past 7 days the child had spent in organised and other strenuous physical activity at school, if the child was at school during that period, and the amount of time they spent in similar activities out of school. Diet was measured by a limited food-frequency questionnaire that measured the number of servings of fruits and vegetables a child ate per day and whether they ate sweets. Weight and height measurements were obtained in the same way as in the NHSP (described above).</p>", "<title>Statistical analysis</title>", "<p>Anthropometric indicators of nutritional status were used. Underweight was defined as having a weight-for-age below −2 SD from the World Health Organization/National Centre of Health Statistics (WHO/NCHS) reference, and stunting as having a height-for-age below −2 SD from the WHO/NCHS reference. Overweight and obese were defined as a BMI-for-age at the 85th percentile or greater from the 2000 Center for Disease Control growth charts##UREF##1##17## ##REF##11773541##18## The overall and age-specific prevalence of nutritional status was computed in the urban and rural populations of those who participated in the NHSP and in the Karachi survey. All results were standardised for age and gender according to the NHSP.</p>", "<p>We also performed a sensitivity analysis for the overall estimates of overweight or obese children using the International Obesity Task Force (IOTF) standard, equivalent to a BMI&gt;25 kg/m##REF##15687460##2##.##REF##10419414##19##</p>", "<p>The relationship between physical activity and being overweight or obese was assessed through logistical regression analysis using proc surveyfreq. SAS version 8.0. Survey design methods (clustering) were accounted for in all analyses.</p>" ]

[ "<title>RESULTS</title>", "<title>NHSP 1990–1994</title>", "<p>In the NHSP data, a total of 5641 subjects were aged between 5 to 14 years. 2074 children surveyed for NHSP were from urban areas. Of these, data on height and weight were available for 1972 children (95.0%), 1023 (51.9%) boys and 949 (48.1%) girls. Their mean age (SD) was 9.1 (2.8) years and their mean BMI was 15.0 (2.6) kg/m².</p>", "<p>In the urban areas, 29.7% (27.7–31.7%) of children were underweight: 32% boys and 28% girls, and 16.7% (15.1–18.3%) had stunted growth (both boys and girls). The prevalence of both being underweight and having stunted growth remained fairly constant until the age of 11–12 years old, but decreased for those aged 13–14 years old from 19% to 15% overall (##TAB##0##table 1##). Boys of all ages tended to have a higher prevalence of low weight and stunting. The overall prevalence of being overweight or obese was about 3.0% (2.2–3.8%) among both boys and girls. This prevalence increased with age, reaching 4% and 5% by 13–14 years in boys and girls, respectively.</p>", "<p>Using IOTF standards, the prevalence of overweight or obese children in urban NHSP was 2.7%.</p>", "<p>Overall, only 15% of children reported daily consumption of fruit: 11% in rural and 19% in urban areas, and 28% reported daily consumption of vegetables, both in rural and urban areas.</p>", "<title>Karachi survey</title>", "<p>We interviewed 1675 children of whom 855 (51%) were boys and 820 (49%) were girls. Measurements of weight and height were recorded in all cases. The mean age (SD) of children was 9.4 (2.8) years, and the mean BMI was 15.4 (3.0) kg/m².</p>", "<title>Nutritional status in Karachi survey</title>", "<p>About 27.9% (95% CI) (26–30%) of children were underweight: 29% boys versus 27% girls (p = 0.39), and 14.6% (13–16%) were stunted: 15.5% boys versus 13.8% girls (p = 0.36). The pattern with age was similar to that seen in the NHSP, remaining fairly stable until the age of 11–12 years (prevalence of 16%) and then decreasing with a prevalence of underweight and stunted children among those aged 13–14 years, respectively (prevalence of 9%) (##TAB##1##table 2##). The overall prevalence of overweight and obese children was 5.7% (4.4–6.0%): 4.6% boys versus 6.4% girls (p = 0.13). The number of overweight and obese children increased with age, reaching 7% and 11% in boys and girls aged 13–14 years, respectively.</p>", "<p>Using IOTF standards, the prevalence of overweight or obese children in the Karachi survey was 5%.</p>", "<p>No child reportedly ate the recommended 4–5 daily servings of fruit and vegetables. Approximately one fifth of children (19.8%, 95% CI 12.9% to 26.6%) stated that they ate no fruits and vegetables. The majority of children ate chocolate or other sweets at least once a day (71.2%, 95% CI 66.2% to 76.2%).</p>", "<p>A comparison of nutritional trends between the two urban surveys is illustrated in ##FIG##0##figure 1##. The overall prevalence of being underweight was 29.7% versus 27.3% (p = 0.12), stunting was 16.7% versus 14.3% (p = 0.05), and the prevalence of being overweight or obese was 3.0 versus 5.7 (p&lt;0.001) in the NHSP versus the Karachi survey, respectively. Among boys, the prevalence of being underweight was 31.5% versus 29.0% (p = 0.26), stunting was 16.8% versus 15.5% (p = 0.45), and prevalence of being overweight or obese was 2.9% versus 4.6% (p = 0.06) in the NHSP versus the Karachi survey, respectively.</p>", "<p>Among girls, the prevalence of being underweight was 27.7 % versus 26.9% (p = 0.75), stunting was 16.6% versus 13.8% (p = 0.12), and prevalence of being overweight and obese was 3.2% versus 6.4% (p = 0.002) in the NHSP versus the Karachi survey, respectively.</p>", "<title>Physical activity in the Karachi survey</title>", "<p>Data on physical activity were collected for 1669 children (##TAB##2##table 3##). The median daily amount of time when children were physically active in Karachi was just over half an hour, with boys being more than twice as active as girls (55 minutes (IQR 13, 120 minutes) versus 25 minutes (IQR 0,60 minutes) respectively). Over 20% of children (boys 16% (95% CI 13% to 20%) and girls 27% (95% CI 21% to 32%)) did no exercise either in or out of school.</p>", "<p>About 66% (95% CI 52% to 80%) of school-attending children reported participating in no organised sport within school, and for those that did, it was usually for 30 minutes or less per school day (33% (95% CI (20% to 47%) of children). Although 65% (95% CI 58% to 72%) of children reported other exercise in school, the majority (58% (95% CI 52% to 64%)) did less than 30 minutes of this type of activity.</p>", "<p>Overall 29% (95% CI 25% to 36%) of children did no exercise out of school (boys 21% (95% CI 17% to 26%), girls 36% (95% CI 31% to 41%)), and only 24% (95% CI 20% to 28%) did more than 1 hour of out of school exercise (boys 30% (95% CI 25% to 36%), girls 17% (95% CI 14% to 20%)).</p>", "<p>The amount of physical activity decreased with age, particularly after the age of 9 for girls and 11 for boys. The median time spent watching television was 120 minutes per day, interquartile range (60,180 minutes). There is little variation by age or gender, 5–6 year olds watched somewhat less television (median 60 minutes (IQR (30,120)), whereas girls aged 13 to 14 years watched somewhat more (median 150 minutes (IQR (90, 240 minutes)).</p>", "<p>The results of regression analyses revealed that those engaged in more than 30 minutes of physical activity had significantly lower odds (OR, 95% CI 0.51, 0.32–0.80) of being overweight or obese than those who participated in less than 30 minutes’ activity. The relationship between being overweight or obesity and physical activity at various age groups shows an inverse relationship between the amount of exercise and the prevalence of obesity, especially in girls (##FIG##1##fig 2##).</p>" ]

[ "<title>DISCUSSION</title>", "<p>This is the first report of the nutritional status of the Indo-Asian children of Pakistan, based on a sound, nationally representative epidemiological survey. It is also the first trend analysis in urban Pakistan. Using normative data from children in the United States as a reference, over a 10-year period in urban areas, there was a slight reduction in the prevalence of underweight children and those with stunting, and a marked increase in overweight and obese children 3.0 versus 5.7% (p&lt;0.001). Physical activity was inversely correlated with being overweight or obese (odds ratio, 95% CI, 0.51, 0.32–0.80 for those engaged in 30 minutes or more physical activity compared with those who engaged in less that 30 minutes’ activity).</p>", "<p>In both surveys, the prevalence of undernutrition decreased whereas the number of overweight or obese children increased with age. Our study therefore highlights the unique challenge faced by school-aged children in Pakistan: a rapid increase in the proportion of children with overnutrition in the presence of a persistently high burden of undernutrition.</p>", "<p>The high prevalence of undernutrition in terms of macronutrient as well as micronutrient deficiencies is a well-recognised problem among children under 5 years of age in the Asian developing countries, ranging from 16.0% in the People’s Republic of China to 64.0% in Bangladesh.##REF##15024783##6## The etiologies of these conditions are multi-factorial and are often attributed to poor maternal nutritional, poor access to healthcare and low birth weight. Adequate feeding, however, can lead to catch-up growth, which negates some of these adverse influences.##REF##11061819##20##^–##REF##8383208##22## Our analyses show that a substantial proportion of the population is still underweight even during school years and adolescence in Pakistan. Moreover, the relatively static nature of these estimates from the recent Karachi survey indicates that no substantial improvement in nutritional status has been made. In part, this could be attributed to poor sanitation and the associated frequent diarrhea and an inability to properly digest food, which are consistent with other reports from Indo-Asia.##REF##12493270##7## ##REF##15542535##23## Our findings emphasise the need to implement evidence-based strategies for improving nutritional indicators in this region.##REF##14726158##24## ##REF##16235389##25##</p>", "<p>At the same time, our results highlight the alarmingly rapid rise in the number of overweight and obese school-aged children in urban Pakistan. An almost twofold increase was observed in the estimated levels over a decade, regardless of whether the WHO/NCHS (from 3% to 5.5%) or the IOTF (from 2.7% to 5.0%) criteria were used as a reference. These patterns are consistent with global trends in childhood obesity observed in developed countries such as the United States, where the prevalence of overweight and obese increased from 14% to 17% over 4 years (NHANES 1999–2000 and 2003–2004) and in other emerging countries such as Brazil where a 2.5-fold increase in overweight and obesity children (from 4 to 14%) over the past three decades has been reported.##REF##12036801##12## ##REF##16595758##26##</p>", "<p>The age-related rise in overweight and obese children in Karachi was associated with a parallel decline in physical activity, suggesting that alteration in the energy balance is one of the major contributing factors. We found that only 7% of girls and 30% of boys aged 13–14 years do the recommended physical activity of 1 hour per day.##REF##14692604##27## The benefits of increasing physical activity for reducing obesity as well as other health benefits are well established.##REF##7936854##28## ##REF##17142523##29## Thus, special efforts are needed to engage children, particularly girls, in sports and related activities as they approach puberty. These efforts will include policy-level changes that will help create safe environments for exercise.##UREF##2##30## In addition, family-based, culturally relevant behavioural interventions that have been shown to be effective in weight management elsewhere need to be tested and implemented in developing-country settings.##REF##15995079##31## ##REF##16923855##32##</p>", "<p>At the same time, it must be kept in perspective that up to about 30% of the school-aged children still fall into the underweight category, although this proportion decreases with age (##TAB##1##table 2##). Moreover, micronutrient deficiencies also continue to be a challenge.##REF##17235055##33##</p>", "<p>The US Department of Health and Human services, and the American Heart Association, along with other similar organisations recommend at least five servings of fruits and/or vegetables per day.##REF##17383556##34## We found that the dietary habits of children were unhealthy in Karachi, with the vast majority consuming grossly inadequate amounts of fruits and vegetables. The consumption of fruits and vegetables continues to be inadequate in the United States and United Kingdom as well.##REF##17383556##34## ##REF##10967615##35## Thus, population-wide measures are needed worldwide for improving healthy dietary habits among children. Such measures should include ensuring the affordability of these choices. The promotion of physical activity in these children should also be encouraged.</p>", "<p>Our study has limitations. First, the NCHS/WHO references for school-aged children and adolescents have a number of methodological and practical problems, which may be magnified in Indo-Asian populations. It is important to underscore that the definition for being overweight and obese in our study used references based on Western populations. Our analysis of the NHSP data in adults suggested lower BMI thresholds than those recommended for Western populations for defining being overweight and obese children on the basis of their association with chronic disease outcomes.##REF##17060656##13## These findings have been confirmed by others.##REF##17420343##36## This is thought to be due to greater central fat deposition and insulin resistance in Indo-Asians compared with Europeans, the risk of which probably begins in utero.##REF##14985484##37## Although our previous work has shown higher BMI-adjusted blood pressure in Pakistani children compared with white children in the United States, corresponding thresholds of Asian-specific BMI in children for defining who is overweight and obese are not available.##REF##15769771##38## There is a need to develop appropriate yardsticks for measuring these risks in Indo-Asian populations. Furthermore, this downward shift in the relationship between obesity and adverse outcomes would suggest lowering the current operational thresholds for defining being underweight and having stunted growth for this population as well.##REF##15069915##39## In that light, our analyses might have overestimated and underestimated the true burdens of undernutrition and overnutrition, respectively. Cohort studies of function and disease outcomes are needed to develop and validate appropriate thresholds in this population. However, our analyses provide robust evidence of the high magnitude of the double burden of this problem and, more importantly, of a steep rise in the percentage of overweight and obese children. Furthermore, it is becoming evident that an accelerated rate of weight gain in childhood, regardless of the threshold, is a powerful indicator of future risk of chronic disease.##REF##14985484##37## Disturbingly, our analyses show that this phenomenon is being experienced in urban Pakistan, and possibly in neighbouring countries.</p>", "<p>Second, of the two surveys that were compared, the NHSP was nationally representative whereas the Karachi survey was representative of an urban city in the province of Sind. This is because follow-up data at a national level or even representative data from rural areas are not available. Only urban parts of the NHSP, however, were considered for trend analysis with the Karachi survey, and both the surveys employed similar multistage cluster-sampling strategies and measurement protocols. Moreover, no major differences in estimates of nutritional status among provinces were noted in urban NHSP (unpublished data). Therefore, we believe the surveys are comparable and that the findings of Karachi would be generalisable to other urban cities in Pakistan. Thus, the trends in childhood obesity highlighted in our study are robust.</p>", "<p>Although analysis of the Karachi survey sheds light on the relationship between the level of physical activity and the percentage of children who are overweight and obese, which does seem to track inversely with age, in-depth studies of dietary factors and sociodemographical associates of under- and overnutrition are needed. Finally, a modified International Physical Activity Questionnaire (IPAQ) was used for assessment of physical activity in the Karachi survey. Although this measure is considered adequate for adults, it has been shown to be non-reproducible for all but strenuous physical activity for those aged under 14 years.##REF##12900694##40##</p>", "<p>In conclusion, the rapidly rising burden of obesity with persistent levels of undernutrition among Indo-Asian children is a unique and complex challenge and represents a major threat to the healthcare services. Thus, there is a clear need to focus health policies on combating this rising epidemic of energy imbalance, which is shifting the pendulum towards overweight and obese children in Indo-Asian countries, while paying attention to the needs of the ones who are still undernourished.</p>" ]

[]

[ "<title>Background:</title>", "<p>Childhood obesity is an emerging global public health challenge. Evidence for the transition in nutrition in Indo-Asian developing countries is lacking. We conducted these analyses to determine the trends in nutritional status of school-aged children in urban Pakistan.</p>", "<title>Methods:</title>", "<p>Data on the nutritional status of children aged 5 to 14 years from two independent population-based representative surveys, the urban component of the National Health Survey of Pakistan (NHSP; 1990–1994) and the Karachi survey (2004–2005), were analysed. Using normative data from children in the United States as the reference, trends for age- and gender-standardised prevalence (95% CI) of underweight (more than 2 SD below the weight-for-age reference), stunted (more than 2 SD below the height-for-age reference) and overweight and obese (body mass index (BMI) 85^th percentile or greater) children were compared for the two surveys. The association between physical activity and being overweight or obese was analysed in the Karachi survey using logistical regression analysis.</p>", "<title>Results:</title>", "<p>2074 children were included in the urban NHSP and 1675 in the Karachi survey. The prevalence of underweight children was 29.7% versus 27.3% (p = 0.12), stunting was 16.7% versus 14.3% (p = 0.05), and prevalence of overweight and obese children was 3.0 versus 5.7 (p&lt;0.001) in the NHSP and Karachi surveys, respectively. Physical activity was inversely correlated with being overweight or obese (odds ratio, 95% CI, 0.51, 0.32–0.80 for those who engaged in more than 30 minutes of physical activity versus those engaged in less than 30 minutes’ activity).</p>", "<title>Conclusions:</title>", "<p>Our study highlights the challenge faced by Pakistani school-aged children. There has been a rapid rise in the number of overweight and obsese children despite a persistently high burden of undernutrition. Focus on prevention of obesity in children must include strategies for promoting physical activity.</p>" ]

[ "<p>The rising number of overweight and obese children and adolescents has been well documented in many developed countries.##REF##11192651##1## ##REF##15687460##2## Several studies have provided robust evidence that being overweight in childhood increases the risk of atherosclerosis, a risk that continues in to adulthood.##REF##15117859##3## This problem of atherosclerosis might be compounded in Indo-Asian children; muscle-thin, fat-rich babies have been shown to be particularly susceptible to insulin resistance in the presence of accelerated growth during childhood.##REF##12586996##4## ##REF##11255994##5##</p>", "<p>Traditionally, a deficiency in macro- and micronutrients has been the major problem among children in low-income countries.##REF##15024783##6##^–##REF##12035849##10## Nevertheless, owing to progressive urbanisation and the associated changes in lifestyle, the energy balance is shifting.##REF##9771877##11## Childhood obesity is becoming an equally challenging, yet under-recognised, problem in many emerging countries.##REF##12036801##12## Data on nutritional transitioning in children from low-income developing countries including those in Indo-Asia are scarce, however.</p>", "<p>Previously we reported results from the NHSP showing that a quarter of the population aged 15 years or over was overweight or obese using Asian-specific thresholds.##REF##17060656##13## In this paper we report the trends in nutritional status for children aged 5 to 14 years obtained from two surveys in Pakistan, the NHSP (conducted during 1990–1994) and the Karachi Survey (2004–2005). In addition, data on physical activity and healthy dietary habits were also collected in the Karachi survey. Since each of these is an important determinant of weight and obesity, we also describe the relationship between activity and diet in urban Indo-Asian children.##REF##12917717##14## ##REF##16092449##15##</p>" ]

[ "<p>We would like to thank members of the Pakistan Medical Research Council, and the US Department of Health and Human Services for their assistance in acquisition of the NHSP data, and members of the Hypertension Research Group (HRG) for the Karachi Survey. Members of the HRG include: TH Jafar (Chair), J Hatcher, S Badruddin, A Hameed, F Jafary, A Khan, M Karim, A Gilani, S Hashmi, S Jessani, Mr R Bux, Z Qadri, M Saleem, P Cosgrove and Ms A Khan (Aga Khan University, Karachi, Pakistan) and N Chaturvedi and N Poulter (Imperial College, UK).</p>", "<p>THJ was responsible for the study concept and design. ZQ, MI, JH and THJ did the statistical analysis. THJ drafted the manuscript. All authors critically revised the manuscript for important intellectual content.</p>" ]

[ "<fig id=\"ADC-93-05-0373-f01\" position=\"float\"><label>Figure 1</label><caption><title>Trends in nutrition in urban Pakistan.</title></caption></fig>", "<fig id=\"ADC-93-05-0373-f02\" position=\"float\"><label>Figure 2</label><caption><title>Age-related changes in total physical activity and prevalence of overweight and obese girls in Karachi.</title></caption></fig>" ]

[ "<table-wrap id=\"ADC-93-05-0373-t01\" position=\"float\"><label>Table 1</label><caption><title>Age-specific nutritional status of urban school-aged children in the NHSP 1990–1994</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td rowspan=\"2\" align=\"left\" colspan=\"1\">Age (in years)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">All</td><td colspan=\"5\" align=\"left\" rowspan=\"1\">Boys</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">Girls</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Underweight) −2 SD below weight for age % (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age % (n)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">(Overweight or obese) &gt; 85^thpercentile BMI for age % (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Underweight) −2 SD below weight for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Overweight or obese) greater than 85^th percentile BMI for age n (%)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">(Underweight) −2 SD below weight for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age n (%)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">(Overweight or obese) &gt; 85^th perentile BMI for age n (%)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5–6n = 452</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30.3 (137)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.2 (73)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">3.8 (17)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">32.5 (80)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.1 (42)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.3 (08)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">27.7 (57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.0 (31)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">4.4 (09)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">7–8n = 468</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31.2 (146)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">19.2 (90)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">1.5 (07)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">34.1 (79)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.7 (41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.2 (05)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">28.4 (67)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20.8 (49)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.8 (02)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">9–10n = 367</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31.3 (115)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.9 (62)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">2.2 (08)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33.8 (66)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">19.0 (37)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.1 (04)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">28.5 (49)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.5 (25)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">2.3 (04)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">11–12 n = 383</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">34.2 (131)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.9 (61)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">4.2 (16)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">32.2 (65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.3 (33)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.0 (08)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">36.5 (66)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.5 (28)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">4.4 (08)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">13–14 n = 302</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18.2 (56)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.6 (44)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">4.0 (12)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21.6 (32)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12.8 (19)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.4 (05)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">15.6 (24)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.2 (25)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">4.5 (07)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>5–14 n = 1972</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>29.7 (585)</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>16.7 (330)</bold></td><td colspan=\"2\" align=\"left\" rowspan=\"1\"><bold>3.0 (60)</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>31.5 (322)</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>16.8 (172)</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>2.9 (30)</bold></td><td colspan=\"2\" align=\"left\" rowspan=\"1\"><bold>27.7 (263)</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>16.6 (158)</bold></td><td colspan=\"2\" align=\"left\" rowspan=\"1\"><bold>3.2 (30)</bold></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"ADC-93-05-0373-t02\" position=\"float\"><label>Table 2</label><caption><title>Age-specific and age-standardised nutritional status of urban school-aged children in the Karachi survey 2004–2005</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td rowspan=\"2\" align=\"left\" colspan=\"1\">Age (in years)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Overall</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Boys</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Girls</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Underweight) −2 SD below weight for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Overweight or obese) &gt;85^th percentile BMI for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Underweight) −2 SD below weight for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Overweight or obese) &gt;85^th percentile BMI for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Underweight) −2 SD below weight for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Stunted) −2 SD below height for age n (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">(Overweight or obese) &gt;85^th percentile BMI for age n (%)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5–6n = 334</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30.9 (102)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.3 (47)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.4 (15)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30.0 (55)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.5 (26)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.7 (07)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">32.2 (47)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.1 (21)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.4 (08)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">7–8n = 371</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.2 (108)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.8 (65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.8 (13)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31.7 (57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18.2 (32)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.2 (05)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">25.9 (51)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.5 (33)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.4 (08)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">9–10n = 333</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30.5 (101)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.0 (52)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.8 (20)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.9 (48)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20.3 (32)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.1 (08)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31.1 (53)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11.9 (20)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.1 (12)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">11–12n = 343</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28.7 (99)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.4 (50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.0 (21)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.6 (58)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13.7 (27)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.6 (11)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27.4 (41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.2 (23)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.6 (1.0)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">13–14n = 294</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.1 (48)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.9 (26)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.1 (27)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21.4 (28)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.8 (13)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.4 (10)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13.1 (20)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.9 (13)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10.5 (17)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5–14n = 1675</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27.9 (458)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14.6 (240)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.7 (96)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.0 (246)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.5 (130)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.6 (41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26.9 (212)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13.8 (110)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.4 (55)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"ADC-93-05-0373-t03\" position=\"float\"><label>Table 3</label><caption><title>Total physical activity among children aged 5–14 years in Karachi</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Boys % (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Girls % (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Total % (n)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Formal in school</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">394</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">389</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">783</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">None</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">65.0 (256)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">66.6 (259)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">65.8 (515)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1–30 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">13.8 (133)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">33.1 (129)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">33.5 (262)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">⩾ 31 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.3 (05)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.3 (01)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.8 (06)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Informal in school</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">394</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">389</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">783</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">None</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">31.5 (124)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">38.1 (148)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">34.7 (272)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1–30 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">58.9 (232)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">56.8 (221)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">57.9 (453)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">31–60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">6.6 (26)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">4.9 (19)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">5.7 (45)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">3.0 (12)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.3 (01)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.7 (13)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Out of school</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">854</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">815</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1669</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">None</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">21.4 (183)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">36.2 (295)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">28.6 (478)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1–30 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">25.3 (216)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">28.0 (228)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">26.6 (444)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">31–60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">23.1 (197)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">18.9 (154)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">21.0 (351)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">30.2 (258)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">16.9 (138)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">23.7 (396)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Total</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">854</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">815</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1669</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">None</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">16.2 (138)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">26.5 (216)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">21.2 (354)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1–30 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">22.7 (194)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">29.7 (242)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">26.1 (436)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">31–60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">21.4 (183)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">19.4 (158)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">20.4 (341)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;60 minutes</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">39.7 (339)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">24.4 (199)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">32.2 (538)</td></tr></tbody></table></table-wrap>" ]

[]

[ "<boxed-text position=\"float\"><sec id=\"s4a1\"><title>What is already known on this topic</title><list list-type=\"bullet\"><list-item><p>Traditionally, deficiency of macro- and micronutrients has been the major problem among children in low-income countries.</p></list-item></list></sec></boxed-text>", "<boxed-text position=\"float\"><sec id=\"s4b1\"><title>What this study adds</title><list list-type=\"bullet\"><list-item><p>Indo-Asian countries are now experiencing the unique challenge of a rapid rise in childhood obesity despite a persistently high burden of undernutrition.</p></list-item></list></sec></boxed-text>" ]

[]

[]

[]

[]

[ "<fn-group><fn fn-type=\"financial-disclosure\"><p><bold>Funding:</bold> Supported by awards from the NIH-Fogarty International Center (THJ/NC and the Wellcome Trust, UK (THJ/NC/JH).</p></fn><fn fn-type=\"conflict\"><p><bold>Competing interests:</bold> None declared.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"ADC-93-05-0373-f01\"/>", "<graphic xlink:href=\"ADC-93-05-0373-f02\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[]

[ "<title>Results of treatment</title>", "<p>In IPAH, the UK Pulmonary Hypertension Service showed survival figures of 84% at 1 year and 76% at 3 years.##UREF##1##18## In APAH the survival rates were 89% at 1 year and 79% at 3 years. These figures compare favourably with those in international adult and paediatric studies.</p>" ]

[]

[]

[ "<p>Pulmonary hypertension is relatively common in children and has many causes. The management of the condition has changed dramatically in the past 5 years with the introduction of new medicines. However, diagnosis, investigation and choice of therapy remain a challenge. In 2002 the United Kingdom Pulmonary Hypertension Service for Children was established and this has become the mainstay of management in this country. This service, based at Great Ormond Street Hospital for Children, provides advice, expertise and infrastructure support for the most severely affected patients, particularly those with idiopathic pulmonary arterial hypertension for whom chronic intravenous prostacyclin remains the most effective medication. New medicines are being developed which, rather than focussing on dilating a diseased pulmonary vascular bed, aim to structurally remodel the pulmonary vasculature towards normal.</p>" ]

[ "<p>Pulmonary hypertension is more common in children than in adults. A modest elevation in pulmonary arterial pressure (PAP) is tolerable, but a high pressure is associated with obstructive pulmonary vascular disease leading to right heart failure and death. Our perspective on this condition has changed dramatically since I wrote an editorial for this journal in 1998.##REF##10193263##1## Improved diagnostic techniques facilitate assessment, drug discoveries have revolutionised management and the establishment of a UK Service for the Care of Children with Pulmonary Hypertension has facilitated diagnosis and management and provided infrastructure support to improve the quality of life of the most severely affected children. We now have a clinically useful classification of pulmonary hypertension which includes all the types of pulmonary hypertension encountered in childhood (box 1).##REF##15194173##2## We have also established internationally recognised diagnostic and management guidelines.##REF##15589643##3## ##REF##11473937##4## This review is based on the experience gained in establishing and running the UK Service for Children, a service commissioned by the Specialist Commissioning Group. The service is a structured clinical network designed to treat children with pulmonary hypertension rapidly and to provide immediate access to new medicines.</p>", "<p>Pulmonary hypertension is defined as a mean PAP equal to or greater than 25 mm Hg at rest or 30 mm Hg on exercise, a definition which applies to all but the youngest infants. The aetiology is more diverse in paediatric than adult patients (box 1). Pulmonary arterial hypertension is much more common than venous hypertension, particularly in childhood, and the new therapies target arterial rather than venous disease. Pulmonary arterial hypertension is subdivided into idiopathic pulmonary arterial hypertension (IPAH), formerly known as primary pulmonary hypertension, and associated pulmonary arterial hypertension (APAH) when associated with other disorders such as congenital heart disease, connective tissue or lung disease.##REF##15194173##2## There is as yet no evidence of ethnic variability in the different types of pulmonary hypertension seen in British children.</p>", "<p>In 1998 the only drugs available to treat pulmonary hypertension were calcium channel antagonists and intravenous epoprostenol, although epoprostenol was only shown to be efficacious in children with IPAH in 1999.##REF##10069788##5## Now there are effective endothelial receptor antagonists, phosphodiesterase inhibitors and prostacyclin analogues, the first two groups of drugs being effective orally.</p>", "<title>DIAGNOSTIC STRATEGY</title>", "<title>Clinical suspicion of pulmonary hypertension (##FIG##0##fig 1##)</title>", "<p>Pulmonary hypertension should be suspected in any child who is unduly short of breath, tires easily or is syncopal when there is no evidence of heart or lung disease. Children occasionally complain of chest pain. The disorder should also be suspected in those known to suffer from these diseases when increasing shortness of breath cannot be explained by the underlying disease process itself. The physical signs of pulmonary hypertension include a left parasternal, right ventricular lift, an accentuated pulmonary component of the second heart sound and sometimes cool extremities. A diastolic murmur of pulmonary regurgitation may be present, but signs of overt right heart failure are a late event in young children.</p>", "<title>Confirming the clinical suspicion of pulmonary hypertension</title>", "<p>An accurate and complete diagnosis is essential, remembering that dual pathology is not uncommon in children with pulmonary hypertension. A chest <italic>x</italic> ray, ECG and a transthoracic Doppler echocardiogram are mandatory (##FIG##0##fig 1##). The classical findings include a chest <italic>x</italic> ray showing enlarged central pulmonary arteries and diminished peripheral pulmonary vascular markings. ECG findings include evidence of right ventricular dilatation and hypertrophy which can be confirmed by transthoracic echocardiography. Doppler interrogation can estimate pulmonary arterial systolic and diastolic pressures. The right ventricular systolic pressure (RVSP) is estimated from the systolic regurgitant tricuspid flow velocity <italic>v</italic> and the estimated right atrial pressure (RAP) in the Bernouille equation: RVSP = 4<italic>v</italic>##REF##15194173##2##+RAP. A tricuspid regurgitant jet is present in the majority of pulmonary hypertensive patients. Echocardiographic measures of right ventricular function include the Tei index which is the sum of the isovolumetric contraction time and isovolumetric relaxation time divided by the ejection time. It assesses both systolic and diastolic function. The tricuspid annular plane systolic excursion (TAPSE) correlates with the right ventricular ejection fraction.</p>", "<p>Blood tests may show hyperuricaemia, particularly in Eisenmenger syndrome and elevation of brain natriuretic peptide, although less reliably than in adults.##REF##10952954##6##</p>", "<p>Functional capacity is graded according to the NYHA/WHO classification, from the asymptomatic patient in class I to the severely disabled in class IV. Shortness of breath is a common complaint and an objective assessment of exercise capacity is helpful. In a co-operative child aged 6 years or more the results of a 6 min walk test can be compared with those in normal children of the same age and sex.##UREF##0##7## Cardiopulmonary exercise testing to determine maximum VO₂, work rate and anaerobic threshold can also be helpful, but this test should be carried out after the severity of the pulmonary hypertension has been ascertained at cardiac catheterisation, and stressing the child in this way is thought to be safe.</p>", "<title>Classification of pulmonary hypertension: determining causation</title>", "<p>If the chest <italic>x</italic> ray excludes parenchymal lung disease, and echocardiography excludes an intracardiac anomaly, then the child probably has IPAH (##FIG##0##fig 1##). Rarely, pulmonary veno-occlusive disease (PVOD) can masquerade as IPAH. Evaluation must exclude a potentially remedial cause of pulmonary hypertension. The age of the child will obviously determine the ease and success with which certain investigations, such as lung function tests, can be carried out.</p>", "<p>Any child suspected of having IPAH or PVOD/pulmonary capillary haemangiomatosis (PCH) should be referred immediately to the UK Pulmonary Hypertension Service for Children.</p>", "<title>IPAH</title>", "<title>Presentation</title>", "<p>Patients can present throughout childhood, even in infancy. Symptoms vary, are age related and often non-specific. Syncope is relatively common. The commonest misdiagnosis is asthma. Parents report shortness of breath without wheeze, unresponsive to bronchodilator therapy. The familial form of IPAH, which accounts for 6% of all cases, shows genetic anticipation, presentation occurring at a younger age in successive generations.##REF##10973254##8## ##REF##7599869##9## Mutations in the bone morphogenetic receptor-II gene account for the majority of cases of familial IPAH and 26% of sporadic cases.##REF##11015450##10## Pulmonary hypertension also occurs in families with hereditary haemorrhagic telangectasia (HHT) caused by mutations in the activin-like kinase 1 (ALK-1) and endoglin genes.##REF##11484689##11## Taking a careful family history and examining specifically for evidence of HHT is important.</p>", "<title>Investigation</title>", "<p>The systemic arterial oxygen saturation is normal in the absence of an atrial septal defect. Desaturation can occur in the presence of an atrial communication when the PAP, right ventricular and atrial pressures increase and right to left shunting occurs. The ECG findings are characteristic, and include right axis deviation, evidence of right ventricular hypertrophy with or without a strain pattern and right atrial enlargement. In addition to an abnormal chest <italic>x</italic> ray, contrast enhanced spiral CT of the lungs is indicated in older patients to exclude thrombus in the central pulmonary arteries and chronic thrombo-embolic disease. It is also helpful in distinguishing IPAH from PVOD. Ventilation/perfusion scans can be normal in IPAH but may show small peripheral non-segmental perfusion defects. Magnetic resonance imaging can help assess right ventricular function but is not yet part of the routine investigation in children with IPAH. The echocardiogram generally reveals dilated right heart chambers, right ventricular hypertrophy with posterior bowing of the ventricular and, in the absence of an atrial communication, the atrial septum.##REF##12706935##12## The left ventricle may be severely compressed. Right atrial size and left ventricular eccentricity index are predictive of outcome in adults and are routinely assessed in children. Lung function testing can sometimes demonstrate small airways obstruction.</p>", "<p>In addition to routine haematology and biochemistry, thyroid function tests, a thrombophilia screen including antiphospholipid antibodies (lupus anticoagulant, anticardiolpin antibodies) and an auto-immune screen are carried out. Children may seroconvert when they are older. Some children have an immunoglobulin deficiency. They may have a low level of antithrombin III, protein S or protein C, which may be genetic in origin or result from a consumption coagulopathy.</p>", "<p>Screening of other siblings for the familial form of the disease is necessary.</p>", "<title>APAH</title>", "<p>Successful treatment of the pulmonary hypertension depends on the rapidity with which the physician treating the underlying disease recognises that pulmonary hypertension is a major complicating factor in the clinical picture.</p>", "<p>Presentation and the investigation of children with APAH are determined by the underlying disease process. The principle aetiologies are as follows.</p>", "<title>Chronic hypoxia</title>", "<p>Chronic hypoxia leads to pulmonary hypertension. Chronic lung disease of prematurity is a relatively common cause of moderate pulmonary hypertension. Interstitial lung disease, as strictly defined, is uncommon in children, as are the pulmonary complications of connective tissue disease. When pulmonary hypertension does occur in association with connective tissue disease in children, it is usually severe. Of the developmental abnormalities, the commonest association is congenital diaphragmatic hernia. In these patients pulmonary hypertension is relatively common in the neonatal period. It usually abates but can persist indefinitely, be severe and require long term treatment. The extent to which lung disease is causing or contributing to an elevated PAP is revealed by pulmonary function tests, the blood gases, ventilation/perfusion and high resolution CT scans.</p>", "<title>Persistent pulmonary hypertension of the newborn (PPHN)</title>", "<p>This condition is usually self-limiting unless there is a significant irreversible underlying problem such as chronic lung disease of prematurity. Alveolar hypoplasia, usually accompanied by a degree of dysplasia, is signalled by persistent failure to wean off the ventilator and an open lung biopsy may be needed to guide management. PPHN may also be the first indication of IPAH.</p>", "<title>Congenital heart disease</title>", "<p>Sustained pulmonary hypertension is sometimes recognised following a technically successful intra-cardiac repair and can be severe. Typically, the child improves clinically after the repair but then becomes short of breath and tires easily. The more severely affected children are investigated and treated as though they had IPAH. Classical Eisenmenger syndrome in the patient who initially had a large left to right shunt and then slowly developed pulmonary vascular disease with shunt reversal, central cyanosis and clubbing is not usually a problem in childhood. Most patients begin to deteriorate in their teenage years. Any child who appears to have Eisenmenger syndrome should be evaluated carefully to ensure that the cardiac diagnosis is correct and complete and that remedial surgery is not feasible. Sleep studies may be indicated in those with trisomy 21. Paediatric cardiology units are familiar with the small group of children who had a high pulmonary vascular resistance when first seen and were therefore deemed inoperable. In such children the resistance probably remained high from birth. They frequently become symptomatic in childhood and may benefit from medical therapy. Complex surgically naive and post-operative cases for whom curative or palliative surgery is not feasible frequently need reappraisal including cardiac catheterisation with a view to palliation by medical therapy.</p>", "<title>Liver disease</title>", "<p>Pulmonary hypertension is a recognised complication of chronic liver disease. Portal hypertension rather than hepatocellular disease appears to be the main determinant. It is uncommon in childhood but when present can influence the timing of liver transplantation. In adults liver transplantation is contra-indicated if the mean PAP exceeds 35 mm Hg and the pulmonary vascular resistance is greater than 250 dynes/s/cm.##REF##10915166##13##</p>", "<title>PVOD and PCH</title>", "<p>These conditions are uncommon. They can present like IPAH, but recognition is important because their management differs from that of IPAH. PVOD usually presents with shortness of breath, sometimes accompanied by small, frequent haemoptysis. The patient may be desaturated, clubbed and have minimal rales on auscultation. The ECG and echocardiogram can be indistinguishable from IPAH but the lung diffusing capacity is lower and high resolution CT scans can be diagnostic to the experienced radiologist. In addition to the expected features of pulmonary hypertension, contrast CT with vascular imaging shows a patchy centrilobular pattern of ground glass opacities, the lobules having a “pavement appearance” because their margins are demarcated by thickened septal lines caused by oedema. Typically, mediastinal lymphadenopathy is prominent. The contrast scan also confirms the echocardiographic findings of unobstructed venous return in the large pulmonary veins. These children are usually very ill indeed and should be listed for transplantation without delay. Cardiac catheterisation may be indicated to confirm the diagnosis. If the child is relatively well and stable, it can be helpful to do an open lung biopsy in order to distinguish those with PCH who may be amenable to treatment for a short period of time, although such treatment with anti-cancer drugs must be regarded as experimental. Medical treatment of PVOD with pulmonary hypertension specific therapies can be hazardous and is contraindicated.</p>", "<title>Cardiac catheterisation to confirm the diagnosis, assess disease severity and guide therapeutic management and the role of lung biopsy</title>", "<p>The purpose of cardiac catheterisation in children with pulmonary hypertension is to confirm the diagnosis and to ensure that the conclusions drawn from the non-invasive tests were complete and accurate. The catheter also determines disease severity by determining the PAP accurately, is the only reliable means to date of determining pulmonary vascular resistance and tests the vasoreactivity of the pulmonary vasculature. The main determinant of treatment is the response to vasodilator testing with nitric oxide at cardiac catheterisation. Pulmonary vascular resistance can only be determined using the Fick principle if the pulmonary blood flow can be determined accurately by measuring, rather than assuming, the oxygen consumption.</p>", "<p>The risk of both cardiac catheterisation and general anaesthesia are increased in the presence of pulmonary hypertension and therefore the procedure is carefully planned after discussion with the child’s parents. Adequate sedation, optimal ventilation and meticulous attention to acid base status and blood loss is mandatory. The clinical history and the haemodynamic findings may indicate the need for further interventions such as the creation of an atrial septostomy and/or insertion of a Hickman line for continuous infusion of epoprostenol. These procedures are best done under the one anaesthetic, but the family need to be fully informed of their likelihood and significance and consent to these procedures, or not, before the catheterisation study can take place.</p>", "<p>Lung biopsy is rarely justified in pulmonary hypertension. The exceptions are suspicion of PVOD or PCH, of alveolar hypoplasia/dysplasia in PPHN, and very rarely in children with complex congenital heart disease in whom it might still be possible to operate.</p>", "<title>Treatment of pulmonary arterial hypertension</title>", "<p>Immunisation schedules should be maintained, and young children need respiratory syncytial virus prophylaxis with palivizumab. Anaesthesia for any general surgical or dental procedure requires particular care.</p>", "<p>The aim of medical treatment is to dilate the pulmonary vasculature and reverse the abnormal remodelling characteristic of pulmonary vascular disease. The practical difficulties encountered in treating children influence management and include their age, level of understanding, size and in some, the presence of other anomalies. Three signalling pathways are targeted: the prostacyclin, endothelin and nitric oxide pathways.</p>", "<title>Prostacyclin and its analogues</title>", "<p>The most effective therapy is a continuous intravenous infusion of epoprostenol, the sodium salt of prostacyclin. It has a short half-life of 3–5 min, is unstable and the infusion has to be prepared every 24 h. The principle side effects are jaw pain and diarrhoea. The child is dosed according to response. Children need much higher doses than adults. A more stable analogue of prostacyclin, treprostinil, can also be given intravenously but is associated with more prominent side effects, headaches and leg pain. Meticulous care of the Hickman line is essential to prevent local and systemic infections, the latter being extremely uncommon. Treprostinil can also be given by continuous subcutaneous infusion but is painful, the drug stimulating nerve endings and causing induration and sometimes ulceration of the skin.##REF##11897647##14## It is not used in children. Iloprost is a prostacyclin analogue which can be given by inhalation but small, tired children find it difficult to inhale an effective dose every 2 h. The drug is effective for less than 2 h.</p>", "<title>Endothelin receptor antagonists</title>", "<p>The dual endothelin (ET) receptor antagonist bosentan (Tracleer) was the first oral drug shown to be efficacious in IPAH and has been used extensively in this and other types of pulmonary hypertension since its introduction in 2002.##REF##11907289##15## It is efficacious in children.##REF##16216850##16## Its principle side effect is elevation of liver enzymes which necessitates a monthly blood test. Drug interactions can occur. Bosentan decreases effective exposure to warfarin because of induction of CYP3A4 and/or CYP2C9. The newer selective ET-A receptor antagonists, sitaxentan and ambrisentan have not yet been studied in children. Both drugs affect the liver less than bosentan and drug interaction is probably less likely with ambrisentan.</p>", "<title>Phosphodiesterase inhibitors</title>", "<p>Sildenafil was the first drug of this class and is still the most commonly used, particularly in young children with APAH. The principle side effects include erections and systemic hypotension when high doses are used. The dose is 0.5–1 mg/kg/dose, given three to four times a day, rarely more.</p>", "<title>Anticoagulation</title>", "<p>Patients with pulmonary vascular disease are prone to develop thrombosis in situ. Older children are given warfarin and younger ones usually receive aspirin. The INR must be monitored particularly closely in those on endothelin receptor antagonists.</p>", "<title>Oxygen</title>", "<p>Oxygen is a potent pulmonary vasodilator. Nocturnal supplemental oxygen is indicated if there is nocturnal systemic arterial oxygen desaturation and can benefit those with a high PAP.</p>", "<title>Atrial septostomy</title>", "<p>This procedure is indicated in children with IPAH and post-operative pulmonary hypertension suffering from syncope and/or severe right heart failure.##REF##16278272##17## It reduces the effect of a sudden increase in pulmonary arterial and right heart pressures and maintains a left ventricular output.</p>", "<title>Lung and heart–lung transplantation</title>", "<p>The policy of the UK Pulmonary Hypertension Service is to refer children on intravenous epoprostenol for assessment by the transplantation service when they are established on treatment and are still well. They are then reviewed by the transplantation service as indicated.</p>", "<title>WHICH CHILDREN WILL BENEFIT FROM WHICH DRUG?</title>", "<p>It is impossible to generalise about who should and should not be treated. All children with IPAH need urgent treatment, but in those with APAH it is the severity of the pulmonary hypertension and the extent to which even a modest increase in pressure influences their well-being and prognosis which determines the need to treat.</p>", "<title>Treating IPAH</title>", "<p>Without treatment the expected survival is less than 1 year.##REF##10069788##5## The main determinant of treatment is the response to vasodilator testing with nitric oxide at cardiac catheterisation. In those with a positive response the PAP and PVR (pulmonary vascular resistance) must fall to a near normal level with no fall in cardiac output. Only patients with a positive vasodilator response can be treated with a calcium channel antagonist. This applies to less than 10% of those with IPAH. Children who improve and are stable on a calcium channel antagonist need repeat cardiac catheterisation after 1 year or less, because they can become resistant to the drug at any time and need escalation of therapy before they deteriorate. The majority of negative responders present in NYHA/WHO class III–IV and frequently need to be started on intravenous epoprostenol therapy immediately. In a minority it is feasible to initiate therapy with an endothelial receptor antagonist. Most children however, require dual therapy. Sildenafil has not been proven to be efficacious in children. Syncopal children need an urgent atrial septostomy. After discharge from hospital close monitoring, principally by echocardiography, is mandatory since urgent intensification of therapy is frequently necessary.</p>", "<title>Treating APAH</title>", "<title>Congenital heart disease</title>", "<p>Children with severe post-operative pulmonary hypertension are treated like those with IPAH. Symptomatic children with classical Eisenmenger syndrome are treated either with an endothelin receptor antagonist or sildenafil, according to age, sex and maturation. Children with a high PVR who have never been operable are usually more symptomatic at an early age and need similar treatment.</p>", "<title>Chronic lung and connective tissue disease</title>", "<p>These patients are treated with bosentan which is thought to have an anti-fibrotic effect in addition to treating pulmonary vascular disease. Young and less severely affected children receive sildenafil. Those with connective tissue disease may require intravenous epoprostenol.</p>", "<title>PPHN persisting beyond the neonatal period</title>", "<p>Children with a modest increase in PAP are treated with sildenafil unless it is apparent that resolution is not occurring when therapy is intensified.</p>", "<p>In both chronic lung disease and PPHN the aim is to encourage normalisation of the pulmonary vasculature and so be able to stop treatment with relatively new, powerful drugs whose long term effects on children are unknown.</p>", "<title>Bone marrow transplantation</title>", "<p>Pulmonary hypertension can occur as a result of the condition indicating bone marrow transplantation, be a complication of transplantation or be an incidental finding. In any event, treatment with bosentan is contraindicated because it interacts with cyclosporine and tacrolimus. Sildenafil can be given to the less severely affected, but intravenous epoprostenol may be indicated.</p>", "<title>Quality of life</title>", "<p>All children are encouraged to return to school quickly. For those on intravenous therapy, dedicated school carers are given appropriate training by the clinical nurse specialists of the UK Pulmonary Hypertension Service who visit the school regularly. All drugs and equipment for intravenous, inhalational and oral therapy are delivered directly to the child’s home. Psychological support may be necessary, particularly with respect to managing relationships in a family with a chronically sick child. The patients’ organisation, The Pulmonary Hypertension Association UK, is a great source of comfort and support. Hospice care also helps many families. It is the responsibility of the UK Pulmonary Hypertension Service for Children to establish support networks in the community for these families.</p>", "<p>Improving quality of life must be the first priority when treating an incurable disease. In the Quality of Life questionnaires completed by the parents and older children cared for by the UK Pulmonary Hypertension Service the scores for physical performance were low, as expected.##UREF##1##18## The psychosocial scores were significantly higher, almost normal, a result which probably indicates the extent to which expectations change in chronic disease.</p>", "<title>Lung transplantation</title>", "<p>Patients who fail to respond to medical therapy are offered the possibility of lung transplantation. The predicted survival for lung transplantation in children is 4.3 years with a 75% survival at 1 year.##REF##17692783##19##</p>", "<title>New and emerging therapies</title>", "<p>The therapeutic goal is the remodelling of the pulmonary vasculature back to normal, the restoration of endothelial function and the growth of new peripheral pulmonary arteries. New modes of administration, new formulations and new analogues of existing drugs, new endothelin receptor antagonists and new PDE 1/5/6 plus PDE-3 and PDE-1 inhibitors are in development now. Statins, RhoA inhibitors, anti-growth factor drugs, metalloproteinase inhibitors, K channel openers, stem cell and gene therapy and vasoactive intestinal peptide are all under investigation. At present we can stabilise patients for many years, but new, radical medicines used in combination offer the hope of cure and greater promise of tailoring the treatment to the individual child.</p>" ]

[]

[ "<fig id=\"adc-93-07-0620-f01\" position=\"float\"><label>Figure 1</label><caption><title>Investigating pulmonary hypertension: diagnostic strategy. CXR, chest <italic>x</italic> ray; PH, pulmonary hypertension; V/Q, ventilation/perfusion.</title></caption></fig>" ]

[]

[]

[ "<boxed-text position=\"float\"><sec id=\"s1a1\"><title>Box 1 Classification of pulmonary hypertension</title><p>1. Pulmonary arterial hypertension (PAH)</p><list list-type=\"bullet\"><list-item><p>1.1 Idiopathic (IPAH)</p></list-item><list-item><p>1.2 Familial (FIPAH)</p></list-item><list-item><p>1.3 Associated with (APAH)</p></list-item><list-item><list list-type=\"bullet\"><list-item><p>1.3.1 Connective tissue disease</p></list-item><list-item><p>1.3.2 Congenital systemic to pulmonary shunts</p></list-item><list-item><p>1.3.3 Portal hypertension</p></list-item><list-item><p>1.3.4 HIV</p></list-item><list-item><p>1.3.5 <italic>Drugs and toxins</italic></p></list-item><list-item><p>1.3.6 Other</p></list-item></list></list-item><list-item><p>1.4 Associated with significant venous or capillary involvement</p></list-item><list-item><list list-type=\"bullet\"><list-item><p>1.4.1 Pulmonary veno-occlusive disease</p></list-item><list-item><p>1.4.2 Pulmonary capillary haemangiomatosis</p></list-item></list></list-item><list-item><p>1.5 Persistent pulmonary hypertension of the newborn</p></list-item></list><p>2. Pulmonary hypertension associated with left heart diseases</p><list list-type=\"bullet\"><list-item><p>2.1 Left sided atrial or ventricular disease</p></list-item><list-item><p>2.2 Left sided valvular heart disease</p></list-item></list><p>3. Pulmonary hypertension associated with respiratory disease and/or hypoxia</p><list list-type=\"bullet\"><list-item><p>3.1 Chronic obstructive pulmonary disease</p></list-item><list-item><p>3.2 Interstitial lung disease</p></list-item><list-item><p>3.3 Sleep disordered breathing</p></list-item><list-item><p>3.4 Alveolar hypoventilation disorders</p></list-item><list-item><p>3.5 <italic>High altitude</italic></p></list-item><list-item><p>3.6 Developmental abnormalities</p></list-item></list><p>4. <italic>Pulmonary hypertension due to chronic thrombotic/embolic disease</italic></p><p>5. Miscellaneous</p><list list-type=\"bullet\"><list-item><p>Tumour, and others</p></list-item></list><p>Indicated in <italic>italics</italic> are the only conditions NOT to have been encountered in the UK Pulmonary Hypertension Service for Children.</p></sec></boxed-text>" ]

[]

[]

[]

[]

[ "<fn-group><fn fn-type=\"conflict\"><p><bold>Competing interests:</bold> None.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"ADC-93-07-0620-f01\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[ "<title>METHODS</title>", "<p>The two datasets used were from the Gateshead Millennium Baby Study (GMS) and the Children in Focus sub-sample of the Avon Longitudinal Study of Parents and Children (ALSPAC), which between them provide detailed growth data spanning the entire period of the new charts. GMS is a prospective population-based cohort study of feeding and growth in infancy comprising 1029 babies born between June 1999 and May 2000 in Gateshead, an urban borough in the North of England. For this analysis, data from 923 full-term infants were used.##REF##16397011##3## Birth weight was retrieved from the maternity record, and weights at 12 days, 6–8 weeks, 4 months and 12 months were obtained from the Personal Child Health Records as well as height and weight at school entry.##REF##16397011##3## Half were breast fed at birth, but only 10% continued breast feeding beyond 4 months.</p>", "<p>The ALSPAC Children in Focus sub-cohort includes 1335 full-term infants born in Avon, south-west England, between June and December 1992. Weight and length/height measurements were collected at research clinics at birth, 4 months, 8 months, 12 months, 18 months, 24 months and 5 years.##REF##10753147##4## Just less than half (46%) were breast fed at age four months (including up to one formula feed per day).</p>", "<p>For each child, age- and sex-adjusted z-scores for weight, length (height at &gt;2 years old) and body mass index (BMI) were calculated using exact ages at measurement by comparison with both the WHO 2006 and the UK 1990 growth data using software provided respectively by the WHO and the Child Growth Foundation (London, UK). Conditional weight gain was calculated to account for regression to the mean.##REF##16397011##3## Poor infant weight gain was defined as a change in weight SD score &lt;−1.33 SD, which is equivalent to downward crossing through two major centile lines on each growth chart.</p>", "<p>Both studies received appropriate ethics committee approval and obtained informed written consent from each participant.</p>" ]

[ "<title>RESULTS</title>", "<title>Comparisons with UK 1990</title>", "<p>Both cohorts showed a reasonably good fit with the UK 1990 reference during the first year of life, as indicated by mean weight and length z-scores close to zero (##TAB##0##table 1## and ##FIG##0##fig 1##). The only exception was a transient decline in weight z-score in GMS at age 12 days, which may be expected, as the UK 1990 reference makes no allowance for the physiological neonatal weight loss. By age 4–5 years, weight and BMI z-scores in both cohorts were higher than the UK 1990 average.</p>", "<title>Comparisons with WHO 2006</title>", "<p>UK children had relatively high mean z-scores for birth weight and birth length compared with the WHO 2006 standard (##TAB##0##table 1##). After birth, z-scores for weight in the GMS children rapidly declined towards the WHO median by age 2 weeks, and in both cohorts weight showed a good fit up to 4 months (##FIG##0##fig 1##). Length and height in both cohorts showed a good fit at all ages after birth (##TAB##0##table 1##).</p>", "<p>Between 4 months and 1 year, compared with the WHO standard, both cohorts showed a rapid rise in mean weight z-scores. After 1 year, the mean z-scores as assessed by the different growth reference data started to converge (##TAB##0##table 1##, ##FIG##0##fig 1##).</p>", "<p>By the WHO 2006 standard, infants were considerably less likely to be classified as underweight (weight &lt;2nd centile; relative risk at 1 year = 0.15; 95% CI = 0.07 to 0.32) or having poor weight gain (downward-crossing through weight centiles) over the first year, compared with the UK 1990 Reference (##TAB##1##table 2##). Conversely the proportion of children classified as obese (BMI &gt;98th centile) at age 4–5 years was slightly higher according to the WHO 2006 standard (relative risk = 1.35; 95% CI = 1.02 to 1.78; ##TAB##1##table 2##).</p>" ]

[ "<title>DISCUSSION</title>", "<p>In summary, adoption of the new WHO growth charts for UK children up to age 5 years would have a significant impact on the interpretation of their weight gain and growth. However, the effects are complex and appear to differ at various ages. The marked reduction in numbers of infants who would be classified as underweight or growth faltering beyond age 4 months is an expected consequence of the WHO’s decision to have the breastfed child as the normative model. However, UK infants would also be classified as being larger at birth, but not at 2–4 months, and would result in a complex pattern of weight centile changes over the first year for the average UK child (##FIG##0##fig 1##).</p>", "<p>This analysis is based on data from two large representative UK birth cohorts, which between them allow comparison with the WHO charts at a wide range of ages. GMS provides detailed weight data early in infancy, and the ALSPAC provides both weight and height/length from infancy through to the pre-school years. At times of overlap, the two cohorts showed very close similarity in weights and heights, and, at least in infancy, they are also broadly similar to the UK 1990 reference. The gradual increase in weight z-scores by 4–5 years of age compared with the UK 1990 has been previously reported in ALSPAC and probably reflects the secular changes in UK children.##REF##10521196##5## We are therefore confident that our findings in these two cohorts may be extrapolated to contemporary UK children.</p>", "<p>The WHO 2006 Child Growth Standard embodies a number of novel and admirable principles, with the aim of promoting optimal infant and childhood growth. Firstly, the international MGRS source data indicated for the first time that population differences in growth are avoidable, given optimum nutrition and living conditions.##REF##16817679##6## Secondly, the WHO has clearly placed the breastfed child as the norm for growth and development. Conditions of inclusion in the longitudinal component of the MGRS analysis were exclusive or predominant breast feeding up to age 4 months and partial breast feeding to at least 12 months. In consequence, the WHO feels able to publish a standard for optimal growth, rather than simply a description of current prevailing growth norms (a “reference”), which may not reflect ideal growth patterns.</p>", "<p>However, our findings, particularly during the first 2 months, suggest that these standards may not be simply transferable to the UK. On the WHO chart, UK infants would appear larger than average at birth and then cross approximately half a centile space downwards in the first few weeks of life. The explanation for this may be that, although postnatal nutrition in the WHO MGRS cohort was optimal, intrauterine growth appeared to have been constrained, as size at birth was generally smaller than in the UK. In the MGRS constituent datasets, whereas mean birth weights in Norway and USA (3.5–3.6 kg) were similar to that in the UK, the populations from several other countries showed markedly lower mean birth weights (3.1 kg in India, and 3.2 kg in Oman), and this appears to correlate with differences in maternal size.##REF##16817674##7##</p>", "<p>The UK 1990 and other existing national growth charts do not allow for the rapid weight loss and recovery that normally occurs in the first 2 weeks of life.##REF##15102731##8## This is reflected in ##FIG##0##fig 1## by a transient dip in the GMS cohort UK 1990 weight SD scores at age 12 days, which probably corrected itself well before their next measurement at age 6 weeks. In contrast, the WHO standard does allow for normal neonatal weight loss.##REF##16817681##2## Therefore, the apparent downward shift in weight centile of UK children on the WHO chart after birth (##FIG##0##fig 1##) is not simply a transient physiological weight loss, but rather suggests that individual babies with low birth weight in the international MGRS birth cohort showed rapid catch-up growth after birth, even within the first 2 weeks.</p>", "<p>Beyond the first 2–4 months, use of the WHO standard would make it much less likely for UK children to be classified as underweight or growth faltering. Recent work has revealed that mild degrees of weight faltering are unlikely to be associated with major social or medical disorders,##REF##16397011##3## and concerns have been expressed that unnecessary parental anxiety may be caused by over-diagnosis.##REF##17264277##9## A change to a new standard, with a more stringent and thus more specific lower threshold, may therefore be timely.</p>", "<p>In contrast with underweight, adoption of the WHO growth chart would make UK infants and toddlers more likely to be classified as overweight or obese. There is a growing body of evidence that a higher plane of growth during infancy is associated with increased risk of obesity in children and adults.##REF##16227306##10## ##REF##16882560##11## Although it is not at all clear whether intervention in infancy can have a useful impact on later obesity, presenting the model of slower weight gain during later infancy prescribed by the WHO standard may be beneficial to the long-term health of these children.</p>", "<p>The birth weight section of the WHO chart presents other difficulties, as there is no preterm element, which is a well-used feature of UK charts. These two issues taken together suggest that it may not be desirable for the UK to adopt the birth weight section of the WHO chart, beginning its use instead after the first 2 weeks.</p>", "<p>In conclusion, the WHO 2006 Growth Standard places the breastfed child as the norm for growth. Its use would greatly reduce the numbers of UK infants classified as underweight and support efforts to avoid excess weight gain in infancy. However, the WHO 2006 Growth Standard is not representative of size at birth in the UK. In view of the resulting complex weight centile changes in the first few weeks of life, the potential confusion about feeding that this might raise with mothers, and also the absence of a preterm element to the WHO charts, the Department of Health Scientific Advisory Committee on Nutrition and the Royal College of Paediatrics and Child Health have recently jointly recommended that the WHO 2006 Growth Standard is appropriate for use in the UK children, but only from age 2 weeks.##UREF##0##12## For birth weight, the UK 1990 reference would continue. The consequences of these recommendations for monitoring of infant weight gain in the UK are likely to be widespread and will need careful and coordinated consideration.</p>" ]

[]

[ "<title>Background:</title>", "<p>The WHO 2006 Child Growth Standard is based on data from international optimally nourished breastfed infants from birth to age 5 years.</p>", "<title>Objective:</title>", "<p>To assess the potential effect of its use on weight and growth monitoring of UK children.</p>", "<title>Participants:</title>", "<p>Full-term members of two population-based UK birth cohorts: the Children in Focus sub-cohort of the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 1335) and the Gateshead Millennium Baby Study (GMS; n = 923).</p>", "<title>Design:</title>", "<p>Growth data from birth to 5 years were converted into z-scores relative to the WHO 2006 standard.</p>", "<title>Results:</title>", "<p>Compared with the WHO standard, both UK cohorts had higher birth weights (mean z-scores: GMS, 0.17; ALSPAC, 0.34) and ALSPAC had higher birth lengths. After birth, length showed a good fit at all ages. By 2–4 months, both cohorts were similar in weight to the WHO median (mean WHO weight z-score at 4 months: GMS, 0.01; ALSPAC, −0.07), but thereafter the UK cohorts were heavier (mean WHO weight z-score at 12 months: GMS, 0.57; ALSPAC, 0.65). At age 12 months, the risk of being classified as underweight (weight &lt;2nd centile) was considerably lower according to the WHO standard than by the UK 1990 Growth Reference (RR = 0.15, 95% CI = 0.07 to 0.32), and the risk of being classified as obese at 4–5 years (body mass index &gt;98th centile) was slightly increased (RR = 1.35, 95% CI = 1.02 to 1.78).</p>", "<title>Conclusions:</title>", "<p>Adoption of the WHO 2006 Growth Charts would set a markedly lower standard of weight gain beyond the age of 4 months for UK infants and could support efforts to avoid future childhood obesity. However, the WHO standard is not representative of size at birth in the UK.</p>" ]

[ "<p>The World Health Organisation (WHO) Child Growth Standard for infants and children up to the age of 5 years was published in April 2006. It is based on the growth of healthy breastfed children in optimal conditions between 1997 and 2003 from six different countries: Brazil, Ghana, India, Norway, Oman and USA.##REF##15069916##1## ##REF##16817681##2## The WHO Multicentre Growth Reference Study (MGRS) collected data for ∼8500 children who were exclusively breast fed for the first 4 months and were living in a well-supported health environment. In consequence, the WHO aims to provide for the first time a standard on “how children should grow”, rather than a traditional growth reference that describes “how children are growing”.</p>", "<p>There is an understandable enthusiasm for the idea of adopting these charts in the UK, but before doing so it is important to assess how well UK children match, or diverge from, the new charts, in order to understand the implications for growth monitoring and clinical care. We have explored this question using data from two representative UK birth cohorts.</p>" ]

[ "<p>KKO and CMW are members of a Joint Expert Group of the Scientific Advisory Committee on Nutrition and the Royal College of Paediatrics and Child Health tasked with considering the implications of the WHO Growth Standards in the UK. Many of the current data were presented to that Expert Group and have been released for consultation. The views expressed in this article are specific to the authors.</p>", "<p>We are extremely grateful to all the families who took part in the ALSPAC and GMS studies and their research teams.</p>" ]

[ "<fig id=\"adc-93-07-0566-f01\" position=\"float\"><label>Figure 1</label><caption><title>Mean z-scores for weight from birth to 24 months and at 4–5 years, according to WHO 2006 Growth Standard (WHO 2006) or the British 1990 Growth Reference (UK 1990) for the Gateshead Millennium Baby Study (GMS) and the Children in Focus sub-cohort of the Avon Longitudinal Study of Parents and Children (ALSPAC). Dotted lines in each panel indicate the time periods with less density of measurements.</title></caption></fig>" ]

[ "<table-wrap id=\"adc-93-07-0566-t01\" position=\"float\"><label>Table 1</label><caption><title>z-Scores for length/height, weight and body mass index (BMI) from birth according to the WHO 2006 Growth Standard (WHO) or the British 1990 Growth Reference (UK1990) in the ALSPAC and GMS cohorts</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td rowspan=\"3\" align=\"left\" colspan=\"1\">Age</td><td rowspan=\"2\" colspan=\"2\" align=\"left\">Numbers</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">Length/height SDS</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">Weight SDS</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">BMI SDS</td></tr><tr><td colspan=\"2\" align=\"left\" rowspan=\"1\">WHO</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">UK1990</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">WHO</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">UK1990</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">WHO</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">UK1990</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ALSPAC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GMS</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Birth</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1335</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">923</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.65 (1.04)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.04 (1.00)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.34 (1.01)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.17 (1.07)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.03 (1.04)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.20 (1.09)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.00 (0.98)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.17 (1.00)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">12 days</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">806</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.07 (1.00)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.51 (1.03)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">6–8 weeks</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">788</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.17 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.02 (0.99)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 months</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">943</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">796</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.03 (0.91)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.05 (0.90)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.07 (0.90)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.01 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.12 (0.97)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.05 (1.03)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.07 (0.94)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.12 (1.29)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">8 months</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1231</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">601</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.15 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.08 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.46 (0.97)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.49 (0.94)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.10 (1.08)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.22 (1.04)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.50 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.09 (1.06)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 year</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1164</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">774</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.09 (0.95)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.09 (0.94)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.65 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.57 (0.94)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.18 (1.05)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.14 (1.05)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.81 (0.89)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.19 (1.01)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.5 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1088</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.09 (0.97)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.02 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.51 (0.91)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.08 (1.04)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.81 (0.89)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.06 (1.03)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">2 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">977</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.14 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.11 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.40 (0.92)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.15 (1.04)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.66 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.26 (1.03)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4–5 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">963</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">395*</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.11 (0.91)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.16 (0.93)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.08 (0.94)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">−0.01 (0.97)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.35 (0.90)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.49 (0.96)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.31 (1.00)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.45 (1.03)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.63 (0.92)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.87 (0.99)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.42 (0.99)</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.66 (0.99)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"adc-93-07-0566-t02\" position=\"float\"><label>Table 2</label><caption><title>Percentages of children classified as underweight, poor infant weight gain, or obese according to the WHO Growth Standard (WHO) and the British 1990 Growth Reference (UK1990)</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td rowspan=\"2\" align=\"left\" colspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\">ALSPAC</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">GMS</td><td rowspan=\"2\" align=\"left\" colspan=\"1\">Combined:RR (95% CI)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">WHO</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UK1990</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">WHO</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UK1990</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Underweight</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    6–8 weeks</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">3.6</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.9</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.12 (0.87 to 1.43)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    4 months</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.0</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.1</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.86 (0.55 to 1.33)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    8 months</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.7</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.6</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.7</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.8</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.30 (0.17 to 0.56)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    1 year</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.3</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.5</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.15 (0.07 to 0.32)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    1.5 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.6</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.9</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.22 (0.10 to 0.48)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Poor infant weight gain</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    Birth to 1 year</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.7</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">7.1</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.6</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">5.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.24 (0.16 to 0.36)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    6–8 weeks to 1 year</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">5.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">0.08 (0.03 to 0.24)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Obese (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    1 year</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">8.7</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.7</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">3.26 (2.21 to 4.83)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    1.5 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">8.0</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">2.6</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">3.11 (2.06 to 4.71)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    2 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">7.5</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">4.3</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">–</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.74 (1.20 to 2.51)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">    4–5 years</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">7.2</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">5.0</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">10.1</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">8.4</td><td align=\"char\" rowspan=\"1\" colspan=\"1\">1.35 (1.02 to 1.78)</td></tr></tbody></table></table-wrap>" ]

[]

[ "<boxed-text position=\"float\"><sec id=\"s4a1\"><title>What is already known on this topic</title><list list-type=\"bullet\"><list-item><p>The WHO published new growth charts in April 2006 based on infants of non-smoking, breastfeeding mothers living in optimal conditions in six countries.</p></list-item><list-item><p>The WHO proposed that these set a standard for normal growth in infancy applicable throughout the world.</p></list-item></list></sec></boxed-text>", "<boxed-text position=\"float\"><sec id=\"s4b1\"><title>What this study adds</title><list list-type=\"bullet\"><list-item><p>At birth, UK children are longer and heavier than the WHO standard,</p></list-item><list-item><p>After birth, the length of UK children matches the WHO standard closely.</p></list-item><list-item><p>Use of the WHO standard would lead to far fewer UK children being classified as underweight or weight faltering in the first year, but more would be classified as overweight in the pre-school years.</p></list-item><list-item><p>The WHO 2006 Growth Charts would set a lower standard of weight gain for UK infants.</p></list-item></list></sec></boxed-text>" ]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><p>Values are mean (SD).</p></fn><fn id=\"nt102\"><p>*281 GMS children aged &gt;5 years at school entry measurement were excluded as they could not be compared with WHO.</p></fn><fn id=\"nt103\"><p>ALSPAC, Children in Focus sub-cohort of Avon Longitudinal Study of Parents and Children; GMS, Gateshead Millennium Baby Study.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt104\"><p>ALSPAC, Children in Focus sub-cohort of Avon Longitudinal Study of Parents and Children; GMS, Gateshead Millennium Baby Study; RR, relative risk for each outcome using the WHO standard, compared with the UK 1990 reference; Underweight, weight &lt;2nd centile; Poor infant weight gain, conditional weight gain &lt;−1.33 SD, equivalent to downward crossing through two major centile lines on each growth chart; Obese, body mass index &gt;98th centile.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"financial-disclosure\"><p><bold>Funding:</bold> UK Medical Research Council, the Wellcome Trust and the University of Bristol provide core provide support for ALSPAC. The infancy phase of the GMS was funded by the Henry Smith Charity, SPARKS, Northern and Yorkshire NHS R&amp;D and Gateshead NHS R&amp;D.</p></fn><fn fn-type=\"conflict\"><p><bold>Competing interests:</bold> None.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"ADC-93-07-0566-f01\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[ "<title>METHODS</title>", "<p>Children between 5 and 10 years, all Caucasians, were included, if they presented symptoms such as wheezing, prolonged cough or shortness of breath, suggesting asthma for at least 1 month before entry into the study, and significant bronchial reversibility. The latter was defined as at least a 20% diurnal variation in repeatable peak expiratory flow (PEF) measurements, or at least a 15% increase in PEF at least three times within 2 weeks of home recording, or at least a 15% increase in forced expiratory volume in 1 second (FEV₁) 15 min after inhalation of a β₂-agonist, or at least a 15% decline in FEV1 in an outdoor exercise test in the clinic.##REF##9426113##15## According to the symptoms and lung-function tests, the majority of children could be categorised as having mild persistent asthma.##UREF##1##16## Children with acute asthma, an FEV₁&lt;50%##UREF##2##17## and with treatment during the preceding 2 months with ICS, cromones, leukotriene modifiers or long-acting β₂-agonists were excluded. The total cumulative doses of previously used ICS must not have exceeded 36 mg, 12 mg of nasal corticosteroids or oral doses equivalent to 200 mg prednisolone.</p>", "<p>The 18-month study was of a controlled, randomised, double-blind, parallel-group, single-centre design including a 2-week run-in period. Two blinded treatment regimens were initiated with inhaled budesonide via a dry-powder inhaler (Pulmicort Turbuhaler, AstraZeneca, Lund, Sweden), and one open-label treatment regimen was initiated with DSCG via a pressurized metered dose inhaler (pMDI; Lomudal with Fisonair spacer, Aventis Pharma, Holmes Chapel, UK). Patients were randomised as to treatment in balanced blocks as generated by a computer program. During the 2-week run-in period, all enrolled patients received a short-acting β₂-agonist, terbutaline (Bricanyl Turbuhaler, 0.25 mg/dose, AstraZeneca, Lund, Sweden) as needed. After the run-in period, children were assigned to one of three treatment groups: (1) continuous budesonide group, receiving budesonide (400 μg twice daily for the first month, then 200 μg twice daily for 5 months) followed by low-dose budesonide (100 μg twice daily for 12 months); (2) budesonide/placebo group, where patients received identical budesonide treatment as Group 1 for the first 6 months followed by placebo for 12 months; and (3) DSCG control group, where patients received DSCG 10 mg three-times daily for 18 months (##FIG##0##fig 1##).</p>", "<p>All patients were given rescue medication of terbutaline 0.25 mg per dose as needed. For all groups, during exacerbations of asthma, study medication was replaced by budesonide 400 μg twice daily for 2 weeks. Children were withdrawn from the study and given individually tailored therapy if treatment of their exacerbations remained insufficient.</p>", "<p>The study was performed in accordance with the Declaration of Helsinki, and was approved by the local ethics committee. Written, informed consent was obtained from each patient’s parent(s) or legal guardian and from the patient.</p>", "<p>For the budesonide treatment groups, treatment compliance was recorded using a home spirometer (Vitalograph Data Storage spirometer, Vitalograph, Buckingham, UK), which recorded the peak inspiratory flow via Turbuhaler (PIF_TBH) each time a dose of the drug was taken.##REF##9351619##18## In the DSCG group, the returned pMDI drug canisters were counted and weighed every 3 months.</p>", "<p>The primary efficacy variable was morning PEF. Secondary efficacy variables were FEV₁, the number of asthma exacerbations, asthma-free days and rescue medication use. Morning PEF was measured daily at home. FEV1 was measured at the clinic visit every third month. An asthma exacerbation was defined as an increase in symptoms that were not controlled with six doses of rescue terbutaline per 24 h that caused the parent to contact the clinic. All parents were provided with a 24-h emergency telephone number. At the clinic, patients were examined by a paediatrician, who decided whether an exacerbation had occurred and, if so, replaced the regular medication with a 2-week course of budesonide 400 μg twice daily. The treatment of an exacerbation was considered insufficient if the symptoms did not subside during the 2-weeks’ budesonide inhalations that caused the parent to contact the clinic. If an oral or parenteral corticosteroid was needed, the child received individual treatment and was withdrawn from the study.</p>", "<p>All patients recorded their PEF rate daily, as measured by a home spirometer, before taking study medication. They also recorded their asthma symptoms using a visual analogue scale (0–10) and use of rescue medication. An asthma-free day was defined as a 24-h period without use of rescue medication and with a symptom score &lt;2. Standard laboratory spirometry (Spirotrac III, Vitalograph) was performed at all clinic visits.##UREF##3##19##</p>", "<p>The primary indicator of systemic effect was the standing-height velocity, which was measured at each clinic visit using a stadiometer (Holtain, Crymych, UK) following a standardised procedure. Children with Tanner stage I-II at baseline were included. Tanner stage of sexual development is scored from I (pre-adolescence) to V (adult characteristics).##UREF##4##20## Standing height was compared with Finnish reference values.##REF##6464740##21## Other indicator was body mass index (kg/m##REF##8058076##2##).</p>", "<p>The sample size was determined by power calculations for morning PEF. A clinically significant change was assumed to be 40 l/min over an 18-month period. With 60 patients per treatment group, there was a 90% chance of detecting a difference of 24 l/min between treatments. The analysis of growth was performed on the complete study population (excluding pubertal children). All other variables were analysed using intention-to-treat principles, that is, all patients who had taken at least one dose of study medication and had data for the required period(s). Withdrawn patients were handled using last value extended, within period. Comparisons between the combined budesonide groups and the DSCG group were made for months 1–6; from 7–18 months comparisons were made between all three groups.</p>", "<p>For most variables, treatment groups were compared using analysis of variance (ANOVA) with fixed factor treatment and baseline values as covariates. For growth variables, sex was included as an additional factor in the analysis. Time to first asthma exacerbation and time to withdrawal were compared using the log-rank test. The number of exacerbations was compared using a Poisson regression model with fixed factor treatment, time in study as an offset and adjustments made for overdispersion.</p>" ]

[ "<title>RESULTS</title>", "<p>A total of 176 children were enrolled in the study. There were no significant differences between treatment groups in any baseline measures (##TAB##0##table 1##). During the run-in period, the mean use of terbutaline was about one dose every 2 days in all treatment groups. Three patients were withdrawn because of asthma deterioration during continuous budesonide treatment after 6 months of the study. In the budesonide /placebo group, nine children were withdrawn because of asthma deterioration, all after 6 months of treatment. In the DSCG group, eight children were withdrawn during the first 6 months of the study, and four children thereafter (continuous budesonide versus DSCG; p = 0.026). One child on placebo and one child on DSCG were hospitalised, because of deterioration in their asthma. The numbers of patients withdrawn from the treatment groups for reasons not related to asthma were three in the continuous budesonide group, three in the budesonide/placebo group, and four in the DSCG group. The flow of the participants through the trial is presented in the ##FIG##1##fig 2##. The mean treatment compliance for the three treatment groups decreased linearly from an initial level of ∼90% to a mean level of ∼60% towards the end of the study. This was matched by a subsequent reduction in the amount of drug used during the study. Children in the continuous budesonide and budesonide/placebo treatment groups achieved a mean PIF_TBH of 60 l/min during the study period.</p>", "<p>After 6 months, the morning PEF values (l/min) of the budesonide groups improved by 6.6% and by 6.1% in the DSCG group. After 18 months, the increase was 10.3% in the continuous, 10.0% in the budesonide/placebo and 12.5% in the DSCG group. No significant differences were observed between the groups at any time point. After 6 months of treatment, improvement in FEV₁ in litres in the clinic was significantly greater in the budesonide groups than in the DSCG group (9.6 versus 5.9%; p = 0.012). From baseline to 18 months, FEV₁ improved by 18.2%, in the continuous, by 16.9% in the budesonide/placebo and by 17.3% in the DSCG group without any significant differences.</p>", "<p>Over the 18-month study period, 364 exacerbations of asthma were recorded in 133 patients. During the first 6 months of treatment, children receiving budesonide had significantly fewer exacerbations compared with children in the DSCG group (##TAB##1##table 2##). During months 7–18, the continuous budesonide group (ie, children on low-dose budesonide) had significantly fewer exacerbations than either the budesonide/placebo group (ie, children given the placebo) or the DSCG group (##TAB##1##table 2##).</p>", "<p>The median time to the first exacerbation was significantly longer for both the continuous budesonide (344 days) and the budesonide/placebo (268 days) groups compared with the DSCG group (78 days) (p&lt;0.001 for each) (##FIG##2##fig 3##). After 180 days, the median time to the next exacerbation was 233 days for the continuous budesonide group, 138 days for the budesonide/placebo group (ie, during placebo) and 131 days for the DSCG group (continuous budesonide and DSCG; p = 0.03).</p>", "<p>At 6 months, the mean number of asthma-free days increased more in budesonide group than in the DSCG group (##TAB##2##table 3##). During months 7–18, the mean number of symptom-free days increased significantly in the continuous budesonide group compared with the DSCG group.</p>", "<p>During the first 6 months, compared with the run-in period, both budesonide groups used significantly less rescue terbutaline (−0.29 doses/day) than the DSCG group (−0.07 doses/day) (p = 0.012). During months 7–18, the decline was –0.29 doses/day in the continuous budesonide group, −0.22 doses/day in the budesonide/placebo group and −0.18 doses/day in the DSCG group, with no significant differences between the groups.</p>", "<p>From baseline to 6 months, the mean standing–height velocity in the budesonide groups was 2 cm/year slower than in the DSCG group (p&lt;0.001). From 7 to 18 months, height velocity increased in both budesonide groups, with the mean height velocity being greater for the budesonide/placebo group (ie, during placebo) than the continuous budesonide group (6.2 versus 5.6 cm; p = 0.016). After 18 months of treatment, children receiving DSCG had grown, on average, 1.0 cm more than children in the continuous budesonide group (8.8 versus 7.8 cm; p = 0.008) and 0.6 cm more than children in the budesonide/placebo group (ie, during placebo) (8.8 versus 8.2 cm; p = 0.048). Development of standing height is presented as standard deviation scores (SDS) in ##FIG##3##fig 4##. No significant differences in body mass index were observed between treatment groups at any time point.</p>" ]

[ "<title>DISCUSSION</title>", "<p>The artificial nature of the research protocol in our study, as in many other asthma studies with drug interventions, does not pay attention to the evolution of individual disease. Exclusion criteria used in this study affect the selection of children. During the study, the selection was further affected by the withdrawal criteria. Furthermore, a “true” placebo group is impossible to arrange because asthma exacerbations cannot be left untreated, and glucocorticoids used for the treatment of exacerbations might influence the individual evolution of asthma.</p>", "<p>We consider that, clinically, the dominant phenotype of the children examined is mild persistent asthma according to the present guidelines. Some children with moderate persistent asthma were included, as consecutive patients fulfilling the inclusion criteria were allocated to the treatment groups. Within the treatment groups, every patient received fixed doses for a predetermined time despite the individual phenotype of asthma. However, in our study, the treatment regimen could be modified individually by 2-week courses of budesonide given as needed.</p>", "<p>Cessation of inhaled budesonide maintenance treatment has previously been shown to result in a worsening of the disease and a decline in lung function in children with persistent moderate to severe asthma.##REF##8239161##22## In the present study of newly detected mild persistent asthma, a proportion of children had a low number of exacerbations during this intermittent treatment with budesonide. The exacerbation rate during months 7 to 18 in this budesonide/placebo group was similar to that of the DSCG group. In the present study, two weeks’ budesonide given when needed, after the initial regular treatment with budesonide, seems to produce an anti-exacerbation effect comparable with the continuous use of DSCG. However, most withdrawals in the DSCG were early, in contrast to late withdrawals in the regular budesonide and budesonide/placebo groups. This might select more mild phenotypes of asthma to the DSCG group for the last 12 months of treatment and artificially improve the results of DSCG compared with placebo or low-dose budesonide treatments.</p>", "<p>While treatment of patients in the DSCG group was open, exacerbations were diagnosed and treated in the same way as in the other two treatment groups. Treatment in the DSCG group was not associated with measurable systemic effects. However, it was associated with the highest number of asthma exacerbations and withdrawals from the study. The initially high number of exacerbations suggests that DSCG is not suitable to start treatment of newly detected childhood asthma.</p>", "<p>No significant differences between treatment groups were observed in the morning PEF values at any time point during the study. This suggests that morning PEF is not a very sensitive efficacy parameter in long-term studies in children with mild asthma as suggested previously.##REF##11027739##7## During the first 6 months of the study, FEV₁ in litres improved significantly more in the budesonide groups than in the DSCG group. However, at the end of the study the differences in FEV₁ disappeared despite significant differences in the number of exacerbations. This is in agreement with previous observations of changes in FEV₁ in litres between the treatments with budesonide, nedocromil and placebo.##REF##11027739##7## The use of FEV1 values measured in litres has been recommended because predicted values depend on height, which may be affected by ICS.##REF##11027739##7##</p>", "<p>Our results confirm previous observations of a small initial decline in height velocity during treatment with ICS used at comparable doses, followed by normal height velocity.##REF##11027739##7## Decline in height velocity without catch-up growth has been recently observed even during regular low ICS dosage.##REF##12672309##8## However, another study suggests that children treated regularly with budesonide attain their predicted final adult height.##REF##11027740##23## In the present study, height velocity was dose-related; during the low-dose budesonide and placebo treatments, the systemic effect of the initial high-dose budesonide were reduced. In the present 18 months follow-up study, standing height velocity was normalised during low-dose budesonide treatment within 1 year of commencement of treatment. The height velocity increased, however, more rapidly during the placebo treatment than during the low-dose budesonide treatment, suggesting catch-up of the initial loss in standing height.</p>", "<p>While long-term maintenance therapy with low-dose ICS is recommended for mild persistent asthma,##REF##11027739##7## ##REF##12672309##8## ##REF##11739137##24## ##REF##15106238##25## some children do not seem to need continuous inhaled corticosteroid treatment. Advantages of this treatment strategy include a reduced risk of ICS-related growth suppression. Intermittent courses of inhaled or oral corticosteroids have been suggested recently for adults with mild persistent asthma.##REF##15829533##26##</p>", "<p>Regular use of budesonide afforded better exacerbation control but more systemic effect than intermittent use of budesonide given as needed or regular DSCG treatment. No significant differences in the morning PEF and FEV₁ in litres or in asthma-free days were observed between the regular or intermittent budesonide treatments during months 7–18. These findings suggest that the overall anti-asthmatic effect of the intermittent budesonide treatment might be intermediate between the regular low-dose ICS and DSCG treatments. The dose of ICS could be reduced as soon as asthma is controlled. Some children do not seem to need continuous ICS treatment.</p>" ]

[]

[ "<title>Objective:</title>", "<p>To compare the effect of inhaled budesonide given daily or as-needed on mild persistent childhood asthma.</p>", "<title>Patients, design and interventions:</title>", "<p>176 children aged 5–10 years with newly detected asthma were randomly assigned to three treatment groups: (1) continuous budesonide (400 μg twice daily for 1 month, 200 μg twice daily for months 2–6, 100 μg twice daily for months 7–18); (2) budesonide, identical treatment to group 1 during months 1–6, then budesonide for exacerbations as needed for months 7–18; and (3) disodium cromoglycate (DSCG) 10 mg three times daily for months 1–18. Exacerbations were treated with budesonide 400 μg twice daily for 2 weeks.</p>", "<title>Main outcome measures:</title>", "<p>Lung function, the number of exacerbations and growth.</p>", "<title>Results:</title>", "<p>Compared with DSCG the initial regular budesonide treatment resulted in a significantly improved lung function, fewer exacerbations and a small but significant decline in growth velocity. After 18 months, however, the lung function improvements did not differ between the groups. During months 7–18, patients receiving continuous budesonide treatment had significantly fewer exacerbations (mean 0.97), compared with 1.69 in group 2 and 1.58 in group 3. The number of asthma-free days did not differ between regular and intermittent budesonide treatment. Growth velocity was normalised during continuous low-dose budesonide and budesonide therapy given as needed. The latter was associated with catch-up growth.</p>", "<title>Conclusions:</title>", "<p>Regular use of budesonide afforded better asthma control but had a more systemic effect than did use of budesonide as needed. The dose of ICS could be reduced as soon as asthma is controlled. Some children do not seem to need continuous ICS treatment.</p>" ]

[ "<p>Most children with asthma experience their first symptoms before 7 years of age.##REF##2321483##1## Studies of adults and children with asthma have shown that some functional reversibility may be lost if anti-inflammatory treatment is postponed.##REF##8058076##2##^–##REF##10069869##4## The anti-asthmatic effect of inhaled corticosteroids (ICS) has been demonstrated in long-term intervention studies,##REF##1355640##5##^–##REF##16778264##10## and these findings have led to ICS becoming the mainstay of treatment for persistent asthma.##UREF##0##11## ##REF##9802359##12## However, high-dose ICS may have systemic effects such as reduction in height velocity##REF##9385125##6##^–##REF##12672309##8## ##REF##7767512##13## and adrenal insufficiency.##REF##12456538##14##</p>", "<p>In an 18-month intervention, we compared two budesonide therapeutic regimens with a control group treated with a fixed dose of disodium cromoglycate (DSCG). The study was designed to evaluate the anti-asthmatic efficacy and systemic effect of daily versus as-needed budesonide in the treatment of early, mild persistent asthma in children.</p>" ]

[ "<p>This study was conducted by the Department of Allergy, Helsinki University Central Hospital, and in co-operation with the Finnish Association of Allergology and Immunology.</p>", "<p>The authors acknowledge the valuable contribution of the following participants in this study: Tuula Koljonen, Study Nurse¹; Leena Ingelin-Kuortti, Study Nurse¹; Eeva Kiiskilä, Study Monitor²; Eva Holtås, Study Monitor³; Thomas Bengtsson PhD, Biostatistician⁴. ¹Department of Allegy, Helsinki University Hospital, Finland. ²AstraZeneca, Finland; and ³AstraZeneca R&amp;D, Lund, Sweden.</p>" ]

[ "<fig id=\"adc-93-08-0654-f01\" position=\"float\"><label>Figure 1</label><caption><title>Study design. The daily dose of budesonide was divided into two doses, DSCG into three doses.</title></caption></fig>", "<fig id=\"adc-93-08-0654-f02\" position=\"float\"><label>Figure 2</label><caption><title>The flow of the participants through the trial.</title></caption></fig>", "<fig id=\"adc-93-08-0654-f03\" position=\"float\"><label>Figure 3</label><caption><title>Kaplan–Meier plot of the time to first exacerbation for the continuous budesonide (O, n = 57), budesonide/placebo (□, n = 58) and disodium cromoglycate (Δ, n = 60) treatment groups during the 18-month study. The median time to the first exacerbation was significantly longer for both the continuous budesonide (344 days) and the budesonide/placebo (268 days) groups compared with the DSCG group (78 days) (p&lt;0.001 for each). The vertical line indicates the time point (180 days) when budesonide treatment was changed to the low-dose regimen or to placebo. After 180 days, the median time to the next exacerbation was 233 days for the continuous budesonide group, 138 days for the budesonide/placebo group and 131 days for the DSCG group (continuous budesonide and DSCG; p = 0.03).</title></caption></fig>", "<fig id=\"adc-93-08-0654-f04\" position=\"float\"><label>Figure 4</label><caption><title>Mean change in standing height (SDS) over the 18-month study period for the continuous budesonide (◊, n = 50), budesonide/placebo (□, n = 45) and disodium cromoglycate (DSCG) (Δ, n = 43) treatment groups. 1–6 months, both budesonide groups versus DSCG, p&lt;0.001; 7–18 months, continuous budesonide group versus budesonide/placebo group, p = 0.016. Note the fast height velocity during months 7–18 in the budesonide/placebo group.</title></caption></fig>" ]

[ "<table-wrap id=\"adc-93-08-0654-t01\" position=\"float\"><label>Table 1</label><caption><title>Baseline characteristics of treatment groups*</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Treatment group</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Continuous budesonide (n = 58)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Budesonide/placebo (n = 58)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Disodium cromoglycate (n = 60)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Age (years)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.0 (5 to 10)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.7 (5 to 10)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.9 (5 to 10)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Male (%)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">66</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">54</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Tanner pubertal stage I/II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">58/1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">58/1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">61/2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Standing height (cm)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">128.4 (108 to157)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">125.1 (106 to 148)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">125.6 (105 to 148)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Standing height, standard deviation scores (SDS)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.04 (−0.32 to 0.54)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.03 (−0.30 to 0.39)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.04 (−0.43 to 0.32)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Body mass index (kg/m²)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17.5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16.9</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Skin prick test positive (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">36</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Duration of symptoms (months†)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12.8 (1.1 to 70.5)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11.3 (2.0 to 76.4)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11.7 (3.0 to 70.8)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Wheeze ever (n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Asthma symptom score (0–10)‡</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.5 (0.0 to 5.5)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.7 (0.0 to 4.5)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.9 (0.0 to 5.7)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Rescue medication, dose/24 h‡</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.47 (0 to 4.0)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.55 (0 to 3.7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.68 (0 to 2.8)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Morning PEF rate (l/min)‡</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">182 (78 to 301)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">176 (68 to 313)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">184 (94 to 363)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Morning PEF (% predicted value)‡</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">76 (43 to 105)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">77 (42 to 112)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">79 (54 to 107)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEV₁ (L†)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.43(0.89 to 2.15)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.32 (0.72 to 2.36)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.37 (0.63 to 2.45)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEV₁ (%† predicted value)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">87 (57 to 111)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">82 (52 to 107)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">83 (57 to 107)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">FVC (% predicted value)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">90 (64 to 112)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">87 (57 to124)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">89 (56 to 120)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"adc-93-08-0654-t02\" position=\"float\"><label>Table 2</label><caption><title>Number of exacerbation episodes</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"2\" align=\"left\" rowspan=\"1\">Treatment</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">No of patients analysed*</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Exacerbations/patient** (95% CI)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">p Value</td></tr></thead><tbody><tr><td colspan=\"2\" align=\"left\" rowspan=\"1\"><bold>Months 1–6</bold></td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td colspan=\"2\" align=\"left\" rowspan=\"1\">Budesonide</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">115</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.32 (0.22 to 0.46)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td colspan=\"2\" align=\"left\" rowspan=\"1\">DSCG</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.24 (0.95 to 1.63)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">&lt;0.001</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Months 7–18</bold></td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">57</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">0.97 (0.70 to 1.34)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/placebo (Budesonide as needed)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">58</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">1.69 (1.31 to 2.18)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DSCG</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">51</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">1.58 (1.20 to 2.08)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud vs Bud/placebo</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.008</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud vs DSCG</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.023</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/placebo vs DSCG</td><td colspan=\"2\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\">0.728</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"adc-93-08-0654-t03\" position=\"float\"><label>Table 3</label><caption><title>Asthma-free days after the run-in period</title></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Treatment</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">No of patients analysed*</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Mean change in asthma-free days, % ** (95% CI)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">p Value</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Months 1–6</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Budesonide</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">114</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">+20.1 (+14.9 to +25.4)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DSCG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">60</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">+4.1 (−3.2 to +11.3)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">0.001</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Months 7–18</bold></td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+29.2 (+21.2 to +37.2)</td><td colspan=\"4\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/placebo (Budesonide as needed)</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+19.6 (+11.8 to +27.4)</td><td colspan=\"4\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DSCG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">51</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">+11.6 (+3.3 to +19.9)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud vs Bud/placebo</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">0.092</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Bud vs DSCG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">0.003</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bud/Placebo vs DSCG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">0.166</td></tr></tbody></table></table-wrap>" ]

[]

[ "<boxed-text position=\"float\"><sec id=\"s4a1\"><title>What is already known on this topic</title><p>It is still debated whether mild asthma in adults needs regular treatment with inhaled corticosteroids.</p></sec></boxed-text>", "<boxed-text position=\"float\"><sec id=\"s4b1\"><title>What this study adds</title><p>Some children who achieve good initial control of their mild asthma does not seem to need continuous treatment with inhaled corticosteroids.</p></sec></boxed-text>" ]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><p>*Values are means with range in parentheses, unless otherwise stated; †no correlation between duration of the symptoms and FEV₁. ‡Data from the run-in period. FEV₁, forced expiratory volume in 1 s; FVC, forced vital capacity; PEF, peak expiratory flow rate.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt102\"><p>*The total effective number of patients analysed. **The mean number of exacerbations divided by the number of patients in the group. Bud, budesonide.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><p>*The total effective number of patients analysed; **Mean change in asthma-free days compared with the baseline.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"financial-disclosure\"><p><bold>Funding:</bold> The study was sponsored by the Helsinki University Central Hospital (grant TYH 2303) and AstraZeneca, Lund Sweden. This study was done at the Department of Allergy at the Helsinki University Hospital.</p></fn><fn fn-type=\"conflict\"><p><bold>Competing interests:</bold> None.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"ADC-93-08-0654-f01\"/>", "<graphic xlink:href=\"ADC-93-08-0654-f02\"/>", "<graphic xlink:href=\"ADC-93-08-0654-f03\"/>", "<graphic xlink:href=\"ADC-93-08-0654-f04\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>In contemporary medical research, randomised controlled trials are seen as the gold standard for establishing treatment effects where it is ethical and practical to conduct them. In palliative care, randomised controlled trials may be impractical, unethical, or extremely difficult, with multiple methodological problems. The fact and nature of these issues with palliative care trials has been frequently commented upon [##REF##9193371##1##, ####REF##10717728##2##, ##REF##11407200##3####11407200##3##]. Frequently encountered problems include recruitment and attrition, insufficient numbers of patients for any comparison, clinical heterogeneity between patients (condition palliated, comorbidity), heterogeneity in treatments (intervention, dose, duration), different outcomes reported, and use of non-standard scales. A palliative care Outcomes Working Group has recently made recommendations on outcomes they consider to be important in this context and how they might be sought in clinical trials [##REF##17532180##4##].</p>", "<p>Trials that have been done in palliative care are often small, diverse in nature and outcomes, and with high attrition rates, making meta-analysis, and even qualitative systematic review, impractical, unsatisfactory, or both. Moreover, some aspects of palliative care are difficult to capture, given the nature of palliative care as a person-centred approach, in which individual packages of care are often the norm [##REF##10454384##5##].</p>", "<p>With this background, the value of systematic reviews of randomized trials in palliative care might be questioned. One side of the argument would be that without a sufficiency of trials satisfying criteria of quality, validity, and size [##UREF##0##6##] systematic reviews are worthless. Another would see systematic reviews as a necessary first step to obtaining more evidence; despite their limitations, they at least tell us what we don't know, and may indicate how to improve.</p>", "<p>This review set out to examine a subset of Cochrane reviews published under the auspices of the Pain, Palliative, and Supportive Care Review Group, to ascertain the number of successfully completed palliative care systematic reviews from this source over the last nine years, to assess their quality and the strength of the evidence presented to guide clinical practice.</p>" ]

[ "<title>Methods</title>", "<p>A list of published reviews relating to palliative care and registered with the Cochrane Pain, Palliative and Supportive Care Group was obtained from the Review Group Coordinator as of December 2007. Copies of each review were obtained from the Cochrane Database of Systematic Reviews using the most recent upload, issue 1, 2008.</p>", "<p>The following information was extracted from each review:</p>", "<p>• Number of studies included</p>", "<p>• Number of patients included</p>", "<p>• Condition palliated</p>", "<p>• Intervention</p>", "<p>• Trial design (randomized, observational)</p>", "<p>• Measures of quality and/or validity used</p>", "<p>• Whether exclusions due to poor quality were made, or a sensitivity analysis presented</p>", "<p>• Whether a pooled analysis was done</p>", "<p>• Original authors' conclusion on efficacy</p>", "<p>• Original authors' conclusion on strength of evidence</p>", "<p>• Original authors' implications for future research.</p>", "<p>Two reviewers (GH, SD) independently carried out data extraction, using a standard form, and assessed the quality of each review using the Oxman &amp; Guyatt Index of Scientific Quality [##REF##1834807##7##]. To determine the strength of the evidence presented, for each review we assessed the quality of the included studies, based on randomization and blinding since these characteristics are known to affect potential bias [##REF##8721797##8##], and the number of patients available for any analysis, because small numbers are prone to random error [##REF##7819982##9##,##REF##11406908##10##]. Any discrepancies were resolved by consensus.</p>", "<p>There was no prior intention to perform any statistical analyses. What was intended was an evaluation of this set of systematic reviews in palliative care based on the quantity and quality of primary studies available, and the quality of the review process itself, in order to determine their utility for informing clinical practice.</p>" ]

[ "<title>Results</title>", "<p>Details of the 25 published systematic reviews [##REF##15106230##11##, ####REF##14583997##12##, ##REF##17253515##13##, ##REF##17054172##14##, ##REF##16856073##15##, ##REF##16856000##16##, ##REF##16856022##17##, ##REF##16625560##18##, ##REF##16437482##19##, ##REF##15846706##20##, ##REF##15266485##21##, ##REF##15654707##22##, ##REF##15654708##23##, ##REF##14973997##24##, ##REF##15106172##25##, ##REF##15266542##26##, ##REF##15106261##27##, ##REF##14974072##28##, ##REF##14583970##29##, ##REF##12535471##30##, ##REF##12519593##31##, ##REF##12076438##32##, ##REF##11687137##33##, ##REF##10796761##34##, ##REF##10796822##35####10796822##35##] are in Additional file ##SUPPL##0##1##, together with the conclusions of the original authors. The first of these Cochrane reviews was published in 1999, and the most recent in 2007. Sixteen of the reviews concerned drug interventions for pain or other reasons, three involved radiotherapy, three complementary therapy, and one each for a mineral supplement, supportive care, and pleurodesis. Only five of the studies were published before 2003, and the rate of publication was five per year since 2004.</p>", "<title>Primary studies</title>", "<title>Number of trials and patients</title>", "<p>The numbers of included trials ranged from none to 54. Thirteen had fewer than five controlled trials, and 16 had fewer than 10 trials. Three reviews had between 11 and 20 trials, and six more than 20 trials. Six reviews had information on fewer than 100 patients in total in controlled trials, fourteen had fewer than 500, while eight had between 1000 and 5000, and one more than 6,000 patients (see Additional file ##SUPPL##0##1##: Included reviews). Within each review, included trials were frequently heterogeneous, with differing interventions (drug, dose, route, technique) and reported outcomes, so that the number of patients contributing to any single analysis was nearly always much lower than the total number of patients included in the review.</p>", "<p>All the reviews sought randomised controlled trials for inclusion. Five reviews [##REF##15654707##22##,##REF##15106172##25##,##REF##15266542##26##,##REF##12535471##30##,##REF##10796761##34##] sought uncontrolled studies, but only two analysed these in the absence of randomised trials [##REF##15654707##22##,##REF##15266542##26##]. Two reviews [##REF##14974072##28##,##REF##12519593##31##] found no studies that met their inclusion criteria.</p>", "<title>Types of patients</title>", "<p>Eighteen reviews included trials involving only cancer patients. In most cases the type of cancer or site of the primary cancer was not restricted. One review included only AIDS patients [##REF##15106261##27##], two included mixed diagnoses of cancer, lung disease, cardiac failure, cystic fibrosis, and elderly patients [##REF##15846706##20##,##REF##11687137##33##], and one included patients with cancer or unspecified \"terminal illness\" [##REF##17054172##14##].</p>", "<title>Original authors' assessment of quality of included studies</title>", "<p>All reviews with included studies assessed their quality, with the exception of Ballantyne [##REF##15654707##22##] and Quigley [##REF##15266542##26##], who found no randomised trials and included mainly retrospective studies, audits, or case reports, and uncontrolled prospective cohort studies. A number of scales were used. Most (18/23) used the Oxford Quality Score [##REF##8721797##8##], and of these, three [##REF##16856000##16##,##REF##14583970##29##,##REF##12535471##30##] additionally used the Oxford Pain Validity Scale [##REF##10779669##36##], two [##REF##17054172##14##,##REF##15266485##21##] used Rinck [##REF##9193371##1##], one [##REF##16856022##17##] used Detsky [##REF##1569422##37##], and another [##REF##16856073##15##] used both Juni [##UREF##1##38##] and Delphi [##REF##10086815##39##]. Shaw [##REF##14973997##24##] graded trials according to criteria in the Cochrane Handbook [##UREF##2##40##], Feuer [##REF##10796761##34##] according to Mann [##UREF##3##41##], and Ezzo et al [##REF##16625560##18##] used their own set of five questions. Seventeen reviews also assessed allocation concealment using Cochrane criteria [##UREF##4##42##] in at least some of the included trials. Eight of the reviews that assessed trial quality did not use the information to exclude low quality studies, weight analyses, or perform sensitivity analysis for effect of low quality [##REF##15106230##11##, ####REF##14583997##12##, ##REF##17253515##13##, ##REF##17054172##14##, ##REF##16856073##15####16856073##15##,##REF##15654708##23##, ####REF##14973997##24##, ##REF##15106172##25####15106172##25##]. For details of quality scores of included studies see Additional file ##SUPPL##1##2## (Adequacy of included studies), and of the quality scoring tools used see Additional file ##SUPPL##2##3## (Quality and validity tools).</p>", "<p>The original authors themselves indicated that there were frequently major problems with the primary studies, individually or in aggregate. These included low numbers (either in total or available for pooled analysis) in 18 cases, the lack of useful outcomes in 10, methodological heterogeneity in eight, design problems in five, and clinical heterogeneity in two. For example, one review stated that we \" ... need more larger studies with standardised outcomes of clinical relevance and clearer definitions of best supportive care\" [##REF##15266485##21##], while another stated that \"Trials were too ...... short term for results to be meaningful\" and that \"Clinically relevant questions to address include which compounds are most beneficial, optimal dose and administration route, when prophylactic therapy ... should be started ...\" [##REF##14583970##29##].</p>", "<title>Reviewers' assessment of quality of reviews</title>", "<p>The methods used in these 25 reviews appeared to be sound. We attempted to use the Oxman &amp; Guyatt Index of Scientific Quality [##REF##1834807##7##], which asks questions about review methods. All the reviews had effective search strategies, and all looked at methodological quality in some way. However, deficiencies in the primary studies made judgment about assessment of validity and combining data close to impossible, as it was for the original authors. For instance, many reviews made no attempt to combine studies in a pooled analysis because of clinical heterogeneity and diverse interventions and outcomes, a decision that we felt to be correct.</p>", "<p>We also felt that an overall Oxman &amp; Guyatt score for these reviews was inappropriate because it attempts to measure flaws in the reviewing process. Our judgment was that the reviewing process was generally good in these reviews. Limited amounts and quality of data limited conclusions about efficacy or harm, most importantly lack of patient numbers, poor/inconsistent reporting, frequent use of non-standard outcome measures, and excluding outcomes which lack clinical relevance, for example patient satisfaction and long-term morbidity.</p>", "<p>In our assessment of the strength of the evidence presented, we found that of the 25 reviews:</p>", "<p>• 2 had no data – there were no trials found [##REF##14974072##28##,##REF##12519593##31##];</p>", "<p>• 2 included uncontrolled trials [##REF##15654707##22##,##REF##15266542##26##], known to be the subject of significant bias [##REF##8721797##8##];</p>", "<p>• 12 included randomized trials, but with open or non-blinded designs [##REF##14583997##12##,##REF##17054172##14##, ####REF##16856073##15##, ##REF##16856000##16##, ##REF##16856022##17####16856022##17##,##REF##16437482##19##, ####REF##15846706##20##, ##REF##15266485##21####15266485##21##,##REF##15654708##23##, ####REF##14973997##24##, ##REF##15106172##25####15106172##25##,##REF##10796822##35##], again known to be the subject of bias, especially in pain [##REF##9014639##43##];</p>", "<p>• 4 included randomized trials, with a mix of blind and open designs. Of these:</p>", "<p>○ Wong [##REF##12076438##32##] included mostly double blind studies, with 3600 patients, but using different drugs, doses, and routes of administration;</p>", "<p>○ Nicholson [##REF##15106230##11##] had 460 patients and 6/9 trials were double blind, but with different doses, and routes of methadone administration, and different comparators;</p>", "<p>○ Dewey [##REF##17253515##13##] had 60 patients and 4/5 trials were double blind, but they were insufficiently rigorous to be confident of any effect;</p>", "<p>○ Ezzo [##REF##16625560##18##] had 1250 patients in acupuncture trials, with a mix of techniques and controls. The trials and review have been criticized elsewhere [##REF##16956145##44##];</p>", "<p>• 5 included randomised trials with only double blind design. Of these:</p>", "<p>○ Three had fewer than 100 patients [##REF##15106261##27##,##REF##12535471##30##,##REF##10796761##34##];</p>", "<p>○ Roque [##REF##14583970##29##] had only 325 patients in 4 trials using different drugs, and doses, in single or multiple dose schedules, and for different duration;</p>", "<p>○ Jennings [##REF##11687137##33##] had 292 patients in 3 trials, but with different drugs and doses.</p>", "<p>Two reviews [##REF##15846706##20##,##REF##10796822##35##] were considered to have the strongest evidence, although even for these reviews there were limitations with methodological heterogeneity or definition of outcomes. No review provided strong evidence of no effect. Even reviews with relatively large numbers of trials and patients could not provide strong evidence because of inappropriate comparison or trial design [##REF##15654708##23##] or methodological heterogeneity [##REF##16856022##17##].</p>" ]

[ "<title>Discussion</title>", "<p>This systematic review of systematic reviews in palliative care was to question the utility of systematic reviews for informing clinical practice in this area of medicine. It found that 25 reviews were published in the Cochrane Database of Systematic Reviews over nine years, a rate of about 2.7 per year overall, though almost double that rate occurred in the three years to 2007. Despite a respectable level of productivity from this prestigious source, 22/25 reviews could produce only weak evidence of the benefits of any intervention, and even of the two where the evidence was considered to be strong there were caveats.</p>", "<p>The review processes themselves appeared adequate. Deficiencies lay in the primary studies, which were either missing or scant, or were characterized by heterogeneity in the methods, interventions, patients, and outcomes, which made an overall assessment of benefit or harm impossible. These deficiencies are similar to those identified previously [##REF##9193371##1##, ####REF##10717728##2##, ##REF##11407200##3####11407200##3##,##REF##10454384##5##]. The authors of the reviews commonly commented on these deficiencies, and others. The biggest single issue was that of inadequate trials or inadequate patient numbers in high quality trials. In making even this point, the reviews and the reviewers make an important contribution.</p>", "<p>It is likely that these observations are general to systematic reviews in palliative care. We limited our investigation to reviews from the Cochrane Database published through the auspices of the Palliative Care group, but we would expect such reviews to be no worse, and perhaps better, than non-Cochrane reviews [##REF##9676681##45##,##REF##17524137##46##]. The restriction to Cochrane reviews should not limit any generalisability of these findings, especially as this reasonably sized body of reviews consistently makes the same, or very similar, points.</p>", "<p>These findings are not a surprise. The dearth of good quality primary studies in the field of palliative care is widely accepted, and those trials that have been done are often known to have weaknesses [##REF##9193371##1##, ####REF##10717728##2##, ##REF##11407200##3####11407200##3##,##REF##10454384##5##]. Together, these factors underline the limitations of the knowledge base upon which palliative care has to draw. Whether new guidance about outcomes to be measured in palliative care trials would make a difference [##REF##17532180##4##] remains to be seen, but given the difficulties in design and conduct of palliative care trials, rapid change in the corpus of evidence is unlikely.</p>", "<p>The challenge for palliative care is the lack of evidence that is available to support it and the inordinate difficulties in obtaining evidence, for example difficulties with recruitment and attrition in an ill and vulnerable population. This has led to calls for a different framework for examining evidence [##REF##16218158##47##]. Part of the problem is that nearly all randomised controlled trials examine single interventions, while in clinical practice that intervention will often form a small part of a much larger overall package of care [##REF##10454384##5##]. Randomised trials of overall packages of care with small or incremental differences between them are unlikely to be able to measure small improvements, and an evaluation of systematic reviews of palliative care services [##REF##12164104##48##] highlighted similar problems to those of palliative care interventions. High patient losses also make interpretation of randomised trials difficult. It is important that palliative care research moves away from dependence on randomized trials, and explores alternative study designs to identify the most effective treatments and packages of care for its patients.</p>", "<p>There may be alternatives. Nearly all the Cochrane reviews included only randomised trials, and the small number of reviews that did consider non-randomised studies found them to have many of the same problems as randomised trials, with an additional increased risk of bias. We know, from other areas of medicine, that high quality, well-formulated, and impeccably conducted large observational studies, can provide equivalent results to those obtained from randomised controlled trials [##UREF##0##6##,##REF##10861324##49##,##REF##12176803##50##]. To overcome the play of chance these good quality studies need to be large, and to minimise bias they need to be both prospective and inclusive (i.e. a whole population, or all patients attending a clinic in a defined time). Registry studies are studies based on information from registers that systematically record information from all individuals in a defined population. They can be entire populations, as in the death register in the UK, or all patients with a specific characteristic (eg twins) or condition (eg breast cancer) within a defined population. At least one large registry-based programme for continuous quality improvement aimed at cancer pain is ongoing in Italy [##REF##16985391##51##]. An extensive search for observational studies in palliative care has been undertaken, with the aim of identifying good quality observational studies and aspects of their design that make them reliable and useful (Hadley et al., manuscript in preparation). The proven limitation of controlled trials in palliative care may make registry studies a more acceptable option in future.</p>" ]

[ "<title>Conclusion</title>", "<p>Cochrane reviews in palliative care are well performed, but fail to provide good evidence to guide clinical practice because the primary studies are few in number, small, clinically heterogeneous, and of poor quality and external validity. These reviews do, however, tell us how limited the evidence base is, and highlight common deficiencies in primary studies. There are well-documented problems with conducting valid randomised trials in this area, and it may be that for some questions more, and more clinically relevant, information can be obtained from other types of primary study, such as large registry studies.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>In contemporary medical research, randomised controlled trials are seen as the gold standard for establishing treatment effects where it is ethical and practical to conduct them. In palliative care such trials are often impractical, unethical, or extremely difficult, with multiple methodological problems. We review the utility of Cochrane reviews in informing palliative care practice.</p>", "<title>Methods</title>", "<p>Published reviews in palliative care registered with the Cochrane Pain, Palliative and Supportive Care Group as of December 2007 were obtained from the Cochrane Database of Systematic Reviews, issue 1, 2008. We reviewed the quality and quantity of primary studies available for each review, assessed the quality of the review process, and judged the strength of the evidence presented. There was no prior intention to perform any statistical analyses.</p>", "<title>Results</title>", "<p>25 published systematic reviews were identified. Numbers of included trials ranged from none to 54. Within each review, included trials were heterogeneous with respect to patients, interventions, and outcomes, and the number of patients contributing to any single analysis was generally much lower than the total included in the review. A variety of tools were used to assess trial quality; seven reviews did not use this information to exclude low quality studies, weight analyses, or perform sensitivity analysis for effect of low quality. Authors indicated that there were frequently major problems with the primary studies, individually or in aggregate. Our judgment was that the reviewing process was generally good in these reviews, and that conclusions were limited by the number, size, quality and validity of the primary studies.</p>", "<p>We judged the evidence about 23 of the 25 interventions to be weak. Two reviews had stronger evidence, but with limitations due to methodological heterogeneity or definition of outcomes. No review provided strong evidence of no effect.</p>", "<title>Conclusion</title>", "<p>Cochrane reviews in palliative care are well performed, but fail to provide good evidence for clinical practice because the primary studies are few in number, small, clinically heterogeneous, and of poor quality and external validity. They are useful in highlighting the weakness of the evidence base and problems in performing trials in palliative care.</p>" ]

[ "<title>Competing interests</title>", "<p>BW and SD have received research support from charities, government and industry sources at various times, but no such support was received for this work. No author has any direct stock holding in any pharmaceutical company.</p>", "<title>Authors' contributions</title>", "<p>GH and SD were involved with planning the study, data extraction, analysis, and preparation of the manuscript. BW was involved with planning the study and preparation of the manuscript. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1472-684X/7/13/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Andrew Moore and Henry McQuay for the initial concept and for helpful comments on the manuscript.</p>", "<p>No specific funding was obtained for this work. Pain Research is supported in part by the Oxford Pain Research Trust. Authors have an absolute right to publish the results of their research, irrespective of any conclusions reached. No aspect of financial support influenced design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Included reviews. Details of included reviews.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Adequacy of included studies. Details of design, size, and quality of primary studies in each review.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Quality and validity tools. Details of tools used to assess quality and validity in primary studies.</p></caption></supplementary-material>" ]

[]

[]

[ "<media xlink:href=\"1472-684X-7-13-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1472-684X-7-13-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1472-684X-7-13-S3.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>About one third of the population aged 65 or more suffers at least one fall a year, of which 5 to 10% result in severe injuries [##REF##1754661##1##, ####REF##16109159##2##, ##REF##11769786##3##, ##REF##11769784##4####11769784##4##]. More than 90% of hip fractures are the result of a fall [##REF##9801019##5##,##REF##12855529##6##]. Falling and the frequency of falls increases exponentially with age [##REF##1754661##1##,##REF##11769786##3##, ####REF##11769784##4##, ##REF##9801019##5####9801019##5##,##UREF##0##7##]. Injuries resulting from falls incur costs for health providers, social services, patients and their families [##REF##12855529##6##, ####UREF##0##7##, ##REF##12964889##8####12964889##8##].</p>", "<p>An active research agenda exists with a focus on prevention [##REF##16109159##2##]. Cognitive impairment, low body mass index and certain medications such as benzodiazepines have been consistently associated with severe injuries from falls [##REF##9801019##5##,##REF##2017229##9##, ####REF##8177244##10##, ##REF##9494786##11##, ##REF##12921493##12####12921493##12##]. Data on the proportion of fall-related injuries attributable to each of these factors is sparse and it is likely that their relative contribution varies from one setting to another.</p>", "<p>Most studies of risk factors for fractures due to falls have been carried out in developed countries, although the size of the elderly population is increasing fast in middle income countries. In Brazil the proportion of people over 60 doubled from 4.1% in 1940 to 8.6% in the year 2000, and it is expected to reach 14% in 2025 [##UREF##1##13##, ####REF##12806475##14##, ##UREF##2##15####2##15##]. Little is known about the frequency, circumstances, risk factors and consequences of falls in Brazil. Perracini &amp; Ramos [##REF##12488937##16##] examined risk factors for any kind of fall in a cohort of elderly community residents and Rozenfeld et al [##REF##12880517##17##] did a cross-sectional investigation in a recreational facility for the elderly. Coutinho &amp; Silva [##REF##12244369##18##] carried out a case-control study with hospital controls investigating the association between drugs used in the previous 24 hours and the risk of severe fracture after falling.</p>", "<p>We conducted a study to investigate a range of health related factors associated with falls leading to hospitalisation due to fractures among elderly people.</p>" ]

[ "<title>Methods</title>", "<title>Design</title>", "<p>A case-control study was carried out in the city of Rio de Janeiro, Brazil.</p>", "<title>Participants</title>", "<p>Two hundred and fifty cases were selected from patients aged 60 or more, admitted to five state hospitals (two are university hospitals and three are funded by the local government) with a severe fracture following a fall, between 2002–2003. A fall was broadly defined as an episode in which a person came to rest on the ground or floor and severe fracture was the one leading to hospital admittance. These hospitals admitted about 50% of all cases of severe fracture in the people aged 60 or over in Rio de Janeiro and were in different geographic areas of the city. The State Health System in the city covers about 70% of the adult population.</p>", "<p>Two hundred and fifty controls were individually matched for sex, age (± 2 years) and neighborhood (residence of cases and controls in the same block). No elected case refused to participate in the study. Selection of controls was carried out using a systematic procedure starting from the case address, with the direction around the block pre-defined by chance. We did not find more than one eligible control per household. Twenty-one people who filled the criteria for being a control did not want to take part in the study and were replaced.</p>", "<title>Data collection</title>", "<p>The interviewers visited the hospitals everyday to look for new cases. All individuals aged 60 or more admitted to the hospital to treat a fracture were approached and those reporting a fall as the cause of the injury were asked to participate in the study. Interviews took place at hospital (cases) and home (controls) through standard questionnaires applied by trained interviewers of both sexes. All interviewers had a university degree. The questionnaires consisted of a common set of questions and information was obtained from cases, controls and relatives. These included socio-demographic characteristics, circumstances of the fall, self-reported health status before the fall, information on drug use 24 hours and 15 days before the fall (for cases) or before the home visit (for controls), height, weight, current diseases (self reported) and cognitive impairment (evaluated by an adapted translation of the \"Short Care\" [##REF##6699370##19##] which was validated in Brazil by Veras et al [##REF##2094000##20##]); and history of falls and fractures in the previous 12 months. The present study used the information of the drugs taken in the previous 24 hours, categorised in 21 groups [see Additional file ##SUPPL##0##1##].</p>", "<title>Sample size</title>", "<p>Without considering the matching, a sample size of 500 individuals would allow to identify an odds ratio of 2 for an exposure of 13% among controls (confidence level = 0.95 and power = 0.80).</p>", "<title>Statistical analysis</title>", "<p>First, an unadjusted analysis (except for the matching variables) was carried out for all socio-demographic and health related variables using conditional logistic regression. In this level all variables with p-value less than 0.25 were selected for multivariate analysis [##REF##2910056##21##]. Second, a multivariate conditional logistic regression model including those variables was fitted to the data. At this stage, variables with p-value equal or less than 0.05 were maintained in the model. Third, variables with p-value larger than 0.25 in the first stage (univariate analysis) were entered in the model and retained if their p-value were equal or less than 0.05. This last stage was carried out aiming to reduce the chance of excluding important predictors for severe fall related fractures.</p>", "<p>Variations in the magnitude of the odds ratios after removing those variables, and multiplicative interactions between drugs and clinical variables were also investigated. The statistical significance of the interaction terms was investigated comparing the models with and without the interaction term through the likelihood ratio test.</p>", "<p>We used literature-based categories for BMI and cognitive impairment for ease of interpretation.</p>", "<p>Complementary analysis comparing means used Kruskal-Wallis test as data were either asymmetrical or variances were not homogeneous.</p>", "<p>All interviewed people signed an informed consent term. The study was approved by the ethical committee of the National School of Public Health – Oswaldo Cruz Foundation.</p>" ]

[ "<title>Results</title>", "<p>All 250 cases and 250 controls recruited took part in the study. The interval between the fall and the interview did not exceed 48 hours, although some additional information could have been obtained latter. The great majority were women and about half the individuals were aged between 70–79 years old (Table ##TAB##0##1##). Due to matching, cases and controls had a similar distribution for age, with mean age for cases 75.5 years old (sd: 8.2) and 75.3 years old (sd: 7.7) for controls. Widowhood was the most frequent marital status for both groups, but the proportion of divorced was higher among cases than controls. The large majority of those interviewed were not living alone. More than 40% did not complete elementary education. Less than 15% were working before the fall.</p>", "<p>Seventy percent of the falls resulting in severe fracture occurred between 6:00 am and 6:00 pm, with a similar proportion in the morning and in the afternoon. Most falls took place at home (67%), and this proportion increased with age. The most commonly fractured bone was the femur (72%) followed by arm/forearm (19%). Two cases had vertebral fracture (2.7%) and eleven (4.4%) had more than one bone fractured. Ninety nine per cent of the cases had to undergo surgical procedures.</p>", "<p>Health related factors with a level of significance less than 0.25 in their univariate association with fracture (matched analysis) are presented in table ##TAB##1##2##. Increased odds ratios were observed for low BMI, low blood pressure, dizziness, diabetes, cognitive impairment, history of stroke, lack of urine control, poor vision, limit in carrying activities of daily living (ADL), fall in the previous 12 months, use of antidepressants, benzodiazepines, muscle relaxants and cerebral vasodilators while reduced odds ratios were observed for poor health status, regular use of alcohol, calcium supplement and calcium channel blockers. Most benzodiazepines were long acting, and the most frequently prescribed was bromazepan. Almost all prescribed muscle relaxants were carisoprodol.</p>", "<p>Osteoporosis, Parkinson disease, epilepsy, high blood pressure, use of angiotensin converting enzyme (ACE) inhibitors, antihistamines, analgesics, antiacids, alpha and beta-adrenergic blockers, nitrates, non steroidal anti-inflamatory drugs, digoxin, calcium and vitamin D supplements did not reached the pre-defined level of 0.25 significance [see Additional file ##SUPPL##1##2##].</p>", "<p>The average total number of drugs were 2.2 (sd = 1.47) in cases and 2.1 (sd = 1.48) among the controls. The difference was not statistically significant (p = 0.43).</p>", "<p>When variables presented in table ##TAB##1##2## were entered in a multivariate conditional logistic model, diabetes, high blood pressure, rheumatism, poor vision and use of diuretics had significance levels over 0.05 and were dropped from the multivariate model. Table ##TAB##2##3## presents the final model. Body mass index equal or less than 20 kg/m2, cognitive impairment, previous stroke and lack of urine control were associated with increased incidence of severe fall related fractures while use of alcohol at least once a week was associated with reduced incidence. Concerning the use of drugs in the previous 24 hours, benzodiazepines and muscle relaxants were related to an increased risk of severe fractures while calcium channel blockers were associated with a reduced risk. The highest odds ratio (approximately 5 fold) was observed for use of muscle relaxants and history of stroke, although confidence intervals were large. No effect modification was observed for the variables included in the final model.</p>" ]

[ "<title>Discussion</title>", "<p>Most of the cases of severe fracture due to falling in the present study were female. Most fell at home between 6:00 am and 6:00 pm and the great majority of the fractures affected the femur and the arm/forearm. Risk factors identified were low body index mass, cognitive impairment, stroke, lack of urine control, use of benzodiazepine and muscle relaxants.</p>", "<p>Our study in a middle-income country setting agrees with some previously reported associations with fracture due to fall observed in developed countries: low body index mass [##REF##2017229##9##,##REF##7594153##22##,##REF##14718222##23##], cognitive impairment [##REF##9801019##5##,##REF##7594153##22##], stroke [##REF##2017229##9##,##REF##8177244##10##], lack of urine control [##REF##11965823##24##, ####REF##14507600##25##, ##UREF##3##26####3##26##].</p>", "<p>In the present study regular users of alcohol (\"at least once a week\") were at a reduced risk of severe fractures. Findings for alcohol have not been consistent. Peel et al [##UREF##4##27##] found a reduced risk of fall-related fracture for moderate alcohol intake while other authors have found the reverse: higher risk of falls leading to fracture associated with higher use of alcohol [##REF##8177244##10##,##REF##8213744##28##]. \"J\" shape patterns in alcohol use have been observed for outcomes such as cardiovascular disease, with non drinkers or those with very low intakes having higher risks compared to those with mild or moderate drinking patterns. In our study, those who reported using alcohol at least once a week rarely made use of alcohol more than twice a week. It is possible that people drinking at least once a week were healthier than those not drinking. Although we attempted to control for this by the inclusion of other health related variables in the model, we cannot exclude the possibility of residual confounding.</p>", "<p>As in our investigation, previous studies have identified an effect of benzodiazepines on the risk of fall-related fractures [##REF##12921493##12##]. Hartikainen et al [##REF##17921433##29##] carried out a systematic review of 29 studies that reported the association between the use of medicines and the risk of falls or fall-related fractures among people aged 60 or more. Nine of them were case-control studies matched by sex and age like our investigation. The authors concluded that central nervous system drugs, mainly psychotropic drugs, were associated with an increased risk of these accidents,</p>", "<p>Many drugs commonly used by elderly people have not been systematically studied as risk factor for falls [##REF##17921433##29##]. An important and novel result from our study was the association between the use of muscle relaxants in the last 24 hours and severe fracture due to falling. The odds ratio was very high (OR = 4.42) although the 95% confidence interval was wide (1.02–19.21). To the best of our knowledge, there is only one study that reported this empirical association among the elderly. French et al [##REF##17096682##30##] used database information to investigate the relationship between registered primary diagnosis of fracture and previous use of some drugs. The authors found that those registered with fracture were prescribed muscle relaxants 1.4 times more than controls (those with non-specific chest pain). This value is much lower than the one we found, but it is difficult to compare these findings as the study designs were quite different.</p>", "<p>That muscle relaxants can cause falls is biologically plausible: these drugs are recognized to cause weakness, drowsiness, sedation and anticholinergic effects [##REF##14662625##31##]. Data on the use of muscle relaxants by elderly people, especially for extended periods, are limited but such studies that have been done reported usage by: 3% of the 60 and over population in Rio de Janeiro-Brazil [##REF##12700839##32##], 0.77% of the 60 and over population in the USA [##REF##15082991##33##], and 1.2% of the 75 and over age group in Finland [##REF##12153373##34##]. Although muscle relaxants are recommended for short-term treatment of back pain, Dillon et al [##REF##15082991##33##] reported a mean length of use of 2.1 years in the USA; 44.5% of users referred use for more than a year. Although it is generally acknowledged that the use of muscle relaxant may be inappropriate and hazardous in the elderly [##REF##14662625##31##,##REF##9236554##35##], the figures quoted above show that their use and their long term use remains a problem. It is likely that usage figures will be higher in places where there is easy access to medications over the counter, commonly in low and medium income countries such as Brazil. The 2002 criteria for potentially inappropriate medication use in older adults [##REF##14662625##31##] does not mention explicitly the risk of falling and suffering a fracture in its evaluation of miorelaxants; the only group of drugs for which concern with falls is mentioned is long acting benzodiazepines</p>", "<p>In contrast to previous studies we did not find a significant association between visual impairment [##REF##2017229##9##,##REF##12488937##16##,##REF##8684153##36##,##REF##11032158##37##] and diabetes [##REF##8213744##28##,##REF##12242318##38##] with fall related fracture. We did not measure visual acuity but relied on self report and there may have been under-reporting leading to dilution of effect. In the case of diabetes, finding an association with falling may be influenced by the proportion of those with neurological and foot problems. Ottenbacher et al [##REF##12242318##38##] found that the association between diabetes and hip fracture particularly for those taking insulin.</p>", "<p>Our study showed an unexpected inverse association between the use of calcium channel blockers (CCB) and the occurrence of severe fall related fracture. Two systematic reviews [##REF##17921433##29##,##REF##9920228##39##] did not find any association between these variables. We cannot exclude the possibility that this finding was due to residual confounding of self-reported health status. CCB and angiotensin converting enzyme inhibitors (ACEI) were the most reported antihypertensives. Although the proportion of controls taking CCB and ACE was the same (16%), the average total number of drugs referred by the first group was 3.0 while by the second group it was 3.5 (p = 0.02). This suggests that users of CCB could be healthier than those to which ACEI were prescribed.</p>", "<p>The study had some limitations. Most variables were self reported and, in some of the interviews, information was provided or added by relatives that were in the hospital (for cases) or at home (for controls). This could lead to an unknown degree of misclassification of exposures. Moreover, cognitive impairment was evaluated after the fall, and we cannot be sure about the influence of the accident on mental state.</p>", "<p>On the other hand, our study has some strengths. There were no refuses among cases and only few among controls and ascertainment of cases was likely to be high as severe fracture will be hospitalised. Controls were selected from same population as cases. Moreover, the study was done in a low income population from a middle-income country, a setting rarely reported for studies on fall related fractures</p>" ]

[ "<title>Conclusion</title>", "<p>What causes falls and fractures in the elderly is an important question as the size of the elderly population is increasing fast in middle income countries. Our study identifies some similar factors and a few differences, including an important role for miorelaxant drugs which are prescribed over the counter in many countries. We studied fractures leading to hospitalisation and it is possible that muscle relaxants are also associated with less severe falls. Urgent and immediate attention is necessary to confirm and quantify the risks as to inform increased control of these drugs in elderly people.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Fracture after falling has been identified as an important problem in public health. Most studies of risk factors for fractures due to falls have been carried out in developed countries, although the size of the elderly population is increasing fast in middle income countries. The objective of this paper is to identify risk factors for fall related to severe fractures in those aged 60 or more in a middle-income country.</p>", "<title>Methods</title>", "<p>A case-control study was carried out in Rio de Janeiro-Brazil based general hospitals between 2002–2003. Two hundred-fifty hospitalised cases of fracture were matched with 250 community controls by sex, age group and living area. Data were collected for socio-demographic variables, health status and drugs used before the fall. A conditional logistic regression model was fitted to identify variables associated with the risk of fall related severe fracture.</p>", "<title>Results</title>", "<p>Low body mass index, cognitive impairment, stroke and lack of urine control were associated with increased risk of severe fall related fractures. Benzodiazepines and muscle relaxants were also related to an increased risk of severe fractures while moderate use of alcohol was associated with reduced risk.</p>", "<title>Conclusion</title>", "<p>Although the association between benzodiazepines and fractures due to fall has been consistently demonstrated for old people, this has not been the case for muscle relaxant drugs. The decision to prescribe muscle relaxants for elderly people should take into account the risk of severe fracture associated with these drugs.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>ESFC had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: ESFC, LCR and AF. Acquisition of data: ESFC. Analysis and interpretation of data: ESFC, LCR and AF. Drafting the manuscript: ESFC, LCR, AF and KVB. Statistical analysis: ESFC and LCR. Study supervision: ESFC. All authors read and approved the manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2318/8/21/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The Wellcome Trust supported field work (data collection), equipment and travelling costs. The CNPq (Brazilian Research Council) provided scholarship, material and consumables.</p>", "<p>We thank Sidney Dutra da Silva, Luana Silva Garcez de Mendonça, Rosania Silva Garcez de Mendonça, Valdir Alvarenga for collecting data for this study.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Distribution of socio-demographic variables among cases (n = 250) and controls (n = 250).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Variable</td><td align=\"center\">Cases n (%)</td><td align=\"center\">Controls n (%)</td></tr></thead><tbody><tr><td align=\"left\">Sex</td><td/><td/></tr><tr><td align=\"left\"> Female</td><td align=\"center\">55 (78.0)</td><td align=\"center\">55 (78.0)</td></tr><tr><td align=\"left\">Age group (years)</td><td/><td/></tr><tr><td align=\"left\"> 60–69</td><td align=\"center\">59 (23.6)</td><td align=\"center\">56 (22.4)</td></tr><tr><td align=\"left\"> 70–79</td><td align=\"center\">118 (47.2)</td><td align=\"center\">127 (50.8)</td></tr><tr><td align=\"left\"> 80–89</td><td align=\"center\">61 (24.4)</td><td align=\"center\">57 (22.8)</td></tr><tr><td align=\"left\"> 90 and more</td><td align=\"center\">12 (4.8)</td><td align=\"center\">10 (4.0)</td></tr><tr><td align=\"left\">Marital status</td><td/><td/></tr><tr><td align=\"left\"> married</td><td align=\"center\">73 (29.2)</td><td align=\"center\">82 (32.8)</td></tr><tr><td align=\"left\"> widowed</td><td align=\"center\">116 (46.4)</td><td align=\"center\">127 (50.8)</td></tr><tr><td align=\"left\"> divorced</td><td align=\"center\">23 (9.2)</td><td align=\"center\">8 (3.2)</td></tr><tr><td align=\"left\"> never married</td><td align=\"center\">38 (15.2)</td><td align=\"center\">33 (13.2)</td></tr><tr><td align=\"left\">Living alone</td><td/><td/></tr><tr><td align=\"left\"> no</td><td align=\"center\">201 (80.4)</td><td align=\"center\">196 (78.4)</td></tr><tr><td align=\"left\"> yes</td><td align=\"center\">39 (15.6)</td><td align=\"center\">47 (18.8)</td></tr><tr><td align=\"left\"> Institution</td><td align=\"center\">10 (4.0)</td><td align=\"center\">7 (2.8)</td></tr><tr><td align=\"left\">Educational level</td><td/><td/></tr><tr><td align=\"left\"> none + elementary incomplete elementary</td><td align=\"center\">104 (41.6)</td><td align=\"center\">110 (44.0)</td></tr><tr><td align=\"left\">  .level one (about 5 years)</td><td align=\"center\">83 (33.2)</td><td align=\"center\">84 (33.6)</td></tr><tr><td align=\"left\">  .level two (about 4 years)</td><td align=\"center\">37 (14.8)</td><td align=\"center\">30 (12.0)</td></tr><tr><td align=\"left\"> secondary (about 3 years)</td><td align=\"center\">20 (8.0)</td><td align=\"center\">15 (6.0)</td></tr><tr><td align=\"left\"> university</td><td align=\"center\">6 (2.4)</td><td align=\"center\">11 (4.4)</td></tr><tr><td align=\"left\">Working before the fall</td><td/><td/></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">34 (13.6)</td><td align=\"center\">28 (11.2)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Distribution of health related variables¹among cases and controls, odds ratios²(OR), 95% confidence intervals (CI) and p-values (cases = 250, controls = 250).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Variables</td><td align=\"center\">Cases n (%)</td><td align=\"center\">Controls n (%)</td><td align=\"center\">OR (95% CI)</td><td align=\"center\">P value¹</td></tr></thead><tbody><tr><td align=\"left\">BMI – kg/m²</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> 25 or more</td><td align=\"center\">85 (34.1)</td><td align=\"center\">118 (47.2)</td><td align=\"center\">reference</td><td align=\"center\">&lt; 0.01</td></tr><tr><td align=\"left\"> 20–24.9</td><td align=\"center\">107 (43.0)</td><td align=\"center\">104 (41.6)</td><td align=\"center\">1.23 (0.72–2.11)</td><td/></tr><tr><td align=\"left\"> less than 20</td><td align=\"center\">57 (22.9)</td><td align=\"center\">28 (11.2)</td><td align=\"center\">3.31 (1.49–7.37)</td><td/></tr><tr><td align=\"left\">Health status</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> excellent</td><td align=\"center\">27 (10.8)</td><td align=\"center\">43 (17.2)</td><td align=\"center\">reference</td><td align=\"center\">0.01</td></tr><tr><td align=\"left\"> good</td><td align=\"center\">121 (48.4)</td><td align=\"center\">126 (50.4)</td><td align=\"center\">1.79 (0.85–3.76)</td><td/></tr><tr><td align=\"left\"> fair</td><td align=\"center\">90 (36.0)</td><td align=\"center\">61 (24.4)</td><td align=\"center\">1.82 (0.76–4.37)</td><td/></tr><tr><td align=\"left\"> poor</td><td align=\"center\">12 (4.8)</td><td align=\"center\">20 (8.0)</td><td align=\"center\">0.31 (0.08–1.27)</td><td/></tr><tr><td align=\"left\"> Dizziness</td><td align=\"center\">70 (28.0)</td><td align=\"center\">57 (22.8)</td><td align=\"center\">1.33 (0.60–2.21)</td><td align=\"center\">0.17</td></tr><tr><td align=\"left\"> Low blood pressure</td><td align=\"center\">15 (6.0)</td><td align=\"center\">3 (1.2)</td><td align=\"center\">5.00 (1.45–17.27)</td><td align=\"center\">0.01</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Diabetes</td><td align=\"center\">52(20.8)</td><td align=\"center\">39 (15.6)</td><td align=\"center\">1.42 (0.90–2.25)</td><td align=\"center\">0.14</td></tr><tr><td align=\"left\"> Cognitive impairment³</td><td align=\"center\">64 (28.7)</td><td align=\"center\">27 (10.8)</td><td align=\"center\">3.64(2.02–6.58)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\"> Stroke</td><td align=\"center\">28 (11.2)</td><td align=\"center\">8 (3.2)</td><td align=\"center\">4.33 (1.78–10.53)</td><td align=\"center\">&lt;0.01</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Lack of urine control</td><td align=\"center\">69 (27.6)</td><td align=\"center\">30 (12.0)</td><td align=\"center\">3.05 (1.82–5.12)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\"> Poor vision⁴</td><td align=\"center\">21 (8.8)</td><td align=\"center\">9 (3.6)</td><td align=\"center\">2.63 (1.16–5.88)</td><td align=\"center\">0.02</td></tr><tr><td align=\"left\"> Limited in carrying ADL⁵</td><td align=\"center\">146 (58.4)</td><td align=\"center\">113 (45.2)</td><td align=\"center\">1.85 (1.24–2.70)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\">Current use of alcohol</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> not used</td><td align=\"center\">198 (79.2)</td><td align=\"center\">161 (64.4)</td><td align=\"center\">reference</td><td align=\"center\">&lt; 0.01</td></tr><tr><td align=\"left\"> less than once a week</td><td align=\"center\">35 (14.0)</td><td align=\"center\">44 (17.6)</td><td align=\"center\">0.79 (0.40–1.55)</td><td/></tr><tr><td align=\"left\"> at least once a week</td><td align=\"center\">17 (6.8)</td><td align=\"center\">45 (18.0)</td><td align=\"center\">0.42 (0.17–1.02)</td><td/></tr><tr><td align=\"left\"> Fall in the previous 12 months</td><td align=\"center\">94 (37.8)</td><td align=\"center\">79 (31.6)</td><td align=\"center\">1.34 (0.91–1.98)</td><td align=\"center\">0.14</td></tr><tr><td align=\"left\"> Antidepressant⁶</td><td align=\"center\">8 (3.2)</td><td align=\"center\">3 (1.2)</td><td align=\"center\">2.67 (0.71–10.05)</td><td align=\"center\">0.15</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Benzodiazepine⁶</td><td align=\"center\">44 (17.6)</td><td align=\"center\">19 (7.6)</td><td align=\"center\">2.56 (1.44–4.57)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\"> Ca channel blocker⁵</td><td align=\"center\">22 (8.8)</td><td align=\"center\">41 (16.4)</td><td align=\"center\">0.47 (0.27–0.84)</td><td align=\"center\">0.01</td></tr><tr><td align=\"left\"> Ca supplement</td><td align=\"center\">5 (2.0%)</td><td align=\"center\">12 (4.8)</td><td align=\"center\">0.42 (0.15–1.18)</td><td align=\"center\">0.10</td></tr><tr><td align=\"left\"> Diuretics⁶</td><td align=\"center\">35 (14.0)</td><td align=\"center\">48 (19.2)</td><td align=\"center\">0.68 (0.42–1.10)</td><td align=\"center\">0.12</td></tr><tr><td align=\"left\"> Muscle relaxant⁶</td><td align=\"center\">21 (8.4)</td><td align=\"center\">8 (3.2)</td><td align=\"center\">5.33 (1.55–18.30)</td><td align=\"center\">&lt;0.01</td></tr><tr><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Cerebral Vasodilators⁶</td><td align=\"center\">27 (10.8)</td><td align=\"center\">14 (5.6)</td><td align=\"center\">2.08 (1.05–4.15)</td><td align=\"center\">0.04</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Association of health related variables and severe fall related fractures. Adjusted¹odds ratios (OR), 95% confidence intervals (CI) and p-values (cases = 250, controls = 250)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Variables</td><td align=\"center\">OR (95% CI)</td><td align=\"center\">P value²</td></tr></thead><tbody><tr><td align=\"left\">BMI</td><td/><td/></tr><tr><td align=\"left\"> 25 or more</td><td align=\"center\">reference</td><td/></tr><tr><td align=\"left\"> 20–24.9</td><td align=\"center\">1.18 (0.71–1.96)</td><td align=\"center\">0.63</td></tr><tr><td align=\"left\"> less than 20</td><td align=\"center\">3.43 (1.64–7.17)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\"> Cognitive impairment</td><td align=\"center\">2.19 (1.09–4.41)</td><td align=\"center\">0.03</td></tr><tr><td align=\"left\"> Stroke</td><td align=\"center\">5.27 (1.31–21.20)</td><td align=\"center\">0.02</td></tr><tr><td align=\"left\"> Lack of urine control</td><td align=\"center\">3.16 (1.42–7.03)</td><td align=\"center\">&lt;0.01</td></tr><tr><td align=\"left\">Current use of alcohol</td><td/><td/></tr><tr><td align=\"left\"> not used</td><td align=\"center\">reference</td><td/></tr><tr><td align=\"left\"> less than once a week</td><td align=\"center\">0.71 (0.38–1.33)</td><td align=\"center\">0.29</td></tr><tr><td align=\"left\"> at least once a week</td><td align=\"center\">0.40 (0.18–0.89)</td><td align=\"center\">0.02</td></tr><tr><td align=\"left\"> Benzodiazepine</td><td align=\"center\">2.22 (1.07–4.58)</td><td align=\"center\">0.03</td></tr><tr><td align=\"left\"> Ca channel blocker</td><td align=\"center\">0.40 (0.19–0.86)</td><td align=\"center\">0.02</td></tr><tr><td align=\"left\"> Muscle relaxant</td><td align=\"center\">4.42 (1.02–19.21)</td><td align=\"center\">0.04</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Categories and ATC codes for the drugs used in the last 24 hours. The table provided presents the Anatomical Therapeutic Chemical Code for the drugs investigated.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Variables with p-value greater than 0.25 (univariate analysis). The table provided presents the odds ratios and 95% confidence intervals for the variables that did not reach statistical criteria in the preliminary analysis for inclusion in the multivariate analysis.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>1. Selection criteria for this table was univariate p-value &lt; 0.25. P-values for the 2 × n comparisons</p><p>2. matched by sex, age group and neighbourhood. OR estimated using conditional logistic regression</p><p>3. adapted translation of the \"Short Care\"</p><p>4. unable to identify someone at the opposite side of the room</p><p>5. unable to perform at least one of the following activities on his(her) own: use of public transport, drive, walk short distances, eat own meals, dress up, take medication, comb, go up and downstairs, take shower, cut nails, control urine.</p><p>6. in the previous 24 hours</p></table-wrap-foot>", "<table-wrap-foot><p>1. Each variable is controlled for the other ones in the table plus self-reported health status and activities in daily living using conditional logistic regression.</p><p>2. P-values for each variable category compared to the reference level.</p><p>Model fit statistics: McFadden's R²= 0.297, McFadden's Adj R²= 0.206, Count R²= 0.777, Likelihood-ratio χ²_{(14 df)}= 91.485, p &lt; 0.001</p></table-wrap-foot>" ]

[]

[ "<media xlink:href=\"1471-2318-8-21-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2318-8-21-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Postural control is the foundation of our ability to stand, move independently or prevent fall during loss of balance when fall is initiated. Thus, deterioration of the postural control system due to aging can lead to balance impairment, inability to react properly (e.g., speed and amplitude), limitations of mobility and eventual disability. Consequently, there is a clinical need for developing cost-effective interventions for improving balance and reducing balance impairments that may lead to falls. In the elderly population, about one out of three individuals fall [##REF##3205267##1##]. Falls may result in acute injuries, including traumatic brain injuries [##REF##17122685##2##] and spinal cord injuries [##REF##16454771##3##] or hip fractures [##UREF##0##4##]. Hip fractures occurring as a result of falls are a common source of impairment, disability and even death [##REF##11769786##5##]. Overall, fall related injuries constitute a serious public health problem and are associated with high health care costs [##UREF##1##6##].</p>", "<p>There are well-documented studies that show that exercise is beneficial to people with heart disease [##REF##15729214##7##] and that it reduces the risk of diabetes [##REF##15633340##8##], stroke [##REF##14579487##9##], hypertension [##REF##15712736##10##], and osteoporosis [##REF##15456348##11##], increases muscle power [##REF##12720593##12##], reduces frailty [##REF##15699531##13##], and improves balance control [##REF##16400783##14##, ####REF##15636460##15##, ##REF##14963375##16####14963375##16##] in the elderly. Research studies investigating exercise as a means of falls prevention in older adults has shown controversial results. Several studies show that exercise prevents falls [##REF##11686957##17##, ####REF##8617895##18##, ##REF##14687345##19##, ##REF##15785256##20##, ##REF##15814861##21##, ##REF##12851185##22####12851185##22##] and other studies have shown no effect [##REF##1427246##23##, ####REF##10671804##24##, ##REF##14687346##25####14687346##25##]. Even well-respected studies on balance training in the elderly population appear to have either ignored or misunderstood the importance of basic principles of physical training and exercise physiology (e.g., awareness, continuity, motivation, overload, periodicity, progression and specificity) [##REF##7016357##26##, ####UREF##2##27##, ##REF##9554029##28##, ##UREF##3##29##, ##UREF##4##30####4##30##], especially with respect to the concept of specificity in balance training in the elderly population. Thus, an exercise intervention targeting a certain function <underline>must</underline> provide a challenge/overload to the system and be progressive as well as specific for this function, otherwise a training effect should not be expected. A common misunderstanding appears to be that strength or even cardiovascular training per se should improve balance function [##REF##1466871##31##, ####REF##9224433##32##, ##REF##8440855##33##, ##REF##8150304##34##, ##UREF##5##35##, ##REF##8375679##36##, ##REF##9440412##37####9440412##37##]. There is a documented relationship between falls and muscle strength in the elderly [##REF##9224433##32##]; however, results are controversial and other studies show minimal or even no differences in strength between fallers and non-fallers [##REF##10630286##38##,##REF##15501837##39##]. Studies that have demonstrated improvements in balance function after strength training have usually related balance to a task where muscle strength, or joint torque production, is a dominant and obvious component of the task (e.g., sit-to stand [##REF##9422460##40##,##REF##9520919##41##], rapid backward walking [##REF##8150304##34##]). In fact, balance improvement related to strength training appears to occur primarily in individuals with severely compromised strength and muscle function [##REF##9440412##37##,##REF##8440860##42##,##REF##10469937##43##]. This view is supported in a Cochrane Review by Latham et al. [##REF##12804434##44##] of 62 randomized control trials including a total of 3674 subjects showing no statistically significant effects of progressive strength training in elderly subjects on objective clinical measures of balance function or on physical disability measures. According to the principles of training, some of which were introduced above, training of balance as a skill must incorporate exercises that closely mimic and provide a challenge to the successful performance of functional tasks. This is supported in the literature; in fact, it has been reported that exercises functionally related to balance, mobility, postural alignment and coordination [##REF##8996463##45##] that challenge the postural control system [##REF##8996463##45##,##UREF##6##46##] can improve the ability of fallers to maintain their balance. Furthermore, it has been suggested that a routine of Tai Chi exercise can help improve [##REF##9105340##47##] or maintain [##REF##8617896##48##] balance control. Using a balance-specific intervention that included perturbation exercises, Wolfson et al. [##REF##8617896##48##], in an elegant study, were able to demonstrate improvements in balance function in healthy 75–90-year-old individuals that appeared to counteract normal age-related balance deterioration. Recently, Mansfield et al. [##UREF##7##49##] suggested the use of a perturbation platform that moves suddenly and unpredictably in one of four directions: forward, backward, left or right as a part of a training program. Oddsson et al. [##UREF##8##50##] proposed a specific training program that involves use of unpredictable, multi-directional perturbations to evoke stepping responses in elderly persons. A randomized controlled trial of the two above-mentioned studies has been conducted to investigate effects of the proposed training programs on gait and balance function in healthy elderly individuals (not yet published). In an interesting training approach for adults, Rogers et al. [##REF##12560410##51##] showed that a three-week period of either voluntary or waist-pull-induced step training reduced step initiation time. During the three-week training regimen, the subjects performed either twice weekly induced step training (destabilizing large waist pulls) or voluntary step practice to a somatosensory reaction stimulus cue (nondestabilizing small waist pulls). However, three of the above-mentioned studies [##REF##8617896##48##,##UREF##7##49##,##REF##12560410##51##] utilized expensive equipment (e.g., moving-platform and waist pulls) that would not be available to most elderly individuals or even in rehabilitation clinics. The currently proposed water-based intervention is based on Oddsson et al.'s [##UREF##7##49##] method and will incorporate similar principles in a group setting with the use of inexpensive equipment that can be acquired by anyone in the pool in a group setting.</p>", "<p>A rapid step is the most important protective postural strategy since it can prevent a fall from occurring. It can arise from large perturbations (e.g., slips, trips and collisions), but is also frequently recruited at lower magnitudes of perturbation or as a consequence of volitional movement (e.g., self-induced perturbation such as turning, bending, reaching) [##REF##9149760##52##]. It is important for fall-prevention programs to include specific stepping exercises on balance-recovery reactions, whether they are compensatory or voluntary in nature. A recent study Melzer et al. [##REF##17545207##53##] found that voluntary step execution was statistically significantly different between non-fallers and fallers during dual task condition (adding a cognitive load). The risk of falling by participants with dual task voluntary step execution times ≥ 1100 ms was 5 times that of participants with execution times &lt;1100 ms. Thus, improving the ability to step quickly, especially under dual task conditions, in response to a loss of balance determines whether a fall occurs in elderly persons. Compared to young adults, older people showed reduced step length [##REF##8176145##54##] an increased frequency of collisions between the swing foot and stance leg during lateral perturbations [##REF##10819317##55##] and an increased frequency of multiple-step responses [##REF##8176145##54##, ####REF##10819317##55##, ##REF##8914501##56####8914501##56##], with a lateral second step following the forward or backward step [##REF##8914501##56##]. All the above results suggest that specific and progressive training to improve the speed and length of the stepping response may reduce the risk of falls in older subjects.</p>", "<p>Volitional or compensatory stepping can be divided into three phases: 1) the step initiation phase, 2) the anticipatory postural adjustments phase (APA), and 3) the swing phase. The duration of the step initiation phase is mainly dependent on peripheral sensory detection and afferent nerve conduction time followed by central neural processing and efferent nerve conduction time.</p>", "<p>Step training (volitional or compensatory) may increase the speed of central neural processing capabilities during the specific function. During the APA phase, neural control of volitional stepping differs from stepping evoked by postural perturbation [##REF##9149760##52##,##REF##16026675##57##], whereas these APAs are typically absent or significantly reduced during large perturbations [##REF##9149760##52##,##REF##8152600##58##,##REF##10575080##59##]. Thus it was suggested that training volitional stepping might lead to improved control of the APAs, but would probably not improve compensatory stepping, especially due to lack of training specificity. Finally, the swing phase incorporates the actual motor execution of the task when the leg is lifted and moved to the target location. Hence, specific and progressive training using water resistance to improve the swing phase speed may provide a benefit in the ability to execute not only effective compensatory stepping reactions but also volitional stepping response.</p>", "<p>The present study aims to test a novel water-based training program that includes perturbation of balance during water-based exercises, specifically targeting stepping responses. To date, only a few studies have examined the effects of water-based training on balance control in the elderly. These studies demonstrated increased Berg Balance score [##UREF##9##60##], improved leaning balance [##UREF##10##61##,##UREF##11##62##] and Functional Reach [##REF##8808995##63##], and improvement in the step test (step 7.5 cm high and return to the floor as many times as possible over a period of 15 seconds), quality of life, but not fear of falling [##REF##15924512##64##], following training. To our knowledge, no studies have directly addressed the potential of using perturbation-based training to counter specific impairments in compensatory and voluntary stepping responses. By training in a water environment, the fear of falling as a result of perturbation exercises may be reduced in elderly persons. Fear of falling may reduce the feasibility of land-based perturbation training (i.e., outside the water). We hypothesize that subjects who undergo a water-based training program that includes perturbation exercises will show greater improvements in the ability to step rapidly, compared to control subjects who undergo no training. In this paper, we describe the development of a water-based training program that includes perturbation exercises and lay out the protocol for a randomized controlled cross-over trial to evaluate the efficacy of this program.</p>", "<title>Development of the water-based training program</title>", "<title>Water-based perturbation exercises</title>", "<p>While subjects try to stand in the water and maintain a stable upright stance over the base of support (BOS) – defined by the feet – water movement and turbulence play an important role by overloading the postural control systems during standing and reaching movement (while feet are fixed on the pool floor) and during change of support movement (e.g., stepping). For stance (exercise levels 1 and 2 in the proposed water-based training program), this relative motion of water causing displacement of either the body's Center of Mass (COM) (via water motion and turbulence) or the BOS (standing on unstable balls or a \"noodle\" placed underneath the subject's feet on the pool floor), these exercises in water might cause perturbed balance (e.g., during leaning, turning, reaching) thus challenging the balance control system. During gait exercises (exercise levels 3 and 4 in the proposed water-based training program), the water motion and turbulence can also be induced and create disturbance due to unexpected turbulence and water resistance perturbation of the COM (e.g., simulate tripping) and BOS perturbations (e.g., simulate slipping due to a slip on the pool floor on a low-friction pool surface, tripping on an obstacle placed on the pool floor). Additional exercises (level 5) will use perturbation exercises provided by the instructors or classmates to evoke balance-recovery stepping reactions against the water resistance. The perturbation methods may fulfill the fundamental biomechanical requirement (disruption of the COM-BOS relationship) and elicit postural and stepping reactions that are similar in many respects to land-based training. Hence, it is possible that the training benefits derived using water-based training that includes perturbation exercises may generalize to the reactions evoked outside the water. This, however, remains to be established since postural reaction within the water may be different from postural reaction on land.</p>", "<p>For this study, the motion of the water inside the swimming pool and the water turbulence were made specifically to deliver the postural perturbations needed to improve postural control mechanism in up-right stance. To evoke stepping and grasping reactions during training, additional pushes will be made by the instructors and by the training associates. Subjects will be instructed to respond to the pushes by stepping as quickly as possible, if required. One important feature of the perturbation approach is that the direction of perturbation (pushes) will be unpredictable.</p>", "<title>The water-based perturbation training program</title>", "<p>The water-based training program is based on the Functional and Specific Balance Training Program (Five Level Program) published by Oddsson et al. [##UREF##7##49##]. The training program adheres to the principles of exercise prescription – specificity, progressive overload, individualization. The program is performed on five levels, where each level reflects different demands on the postural control system. Levels 1–4 include exercises that are focused on the skill to maintain balance (voluntary control), whereas level 5 also includes perturbation exercises that focus on the skill to recover balance (automatic postural responses). We have adapted the program to water-based training.</p>", "<p><bold>Level 1</bold>: Standing exercises with external support (e.g., pool wall) (Figure ##FIG##0##1##).</p>", "<p>Exercises on this level may present little challenge to the postural control system. The goal of the training at this level is mainly directed towards a cognitive understanding of the exercises, and an improvement in self-confidence for the water-based exercises on higher levels. At this level the participants also adjust to the water, become aware of unique characteristics such as the floating force and turbulence, the warmth and feel of the water. Participants begin with simple exercises such as diving, breathing and holding their breath under the water, and gaining confidence in this relatively new medium. These exercises can also be used as safe \"rest\" after more difficult bouts of exercise. Some general effects on strength, coordination, and conditioning are expected. Everyone should progress through this level as soon as possible. However, elements from exercises at this level will also be included on the other levels.</p>", "<p>Examples:</p>", "<p>1. Standing and holding the pool wall, wide stance, with support of one hand on the wall or a fixed object. Repeat with narrow stance and support.</p>", "<p>2. Standing and holding the pool wall, wide stance, with support, and shift weight left and right, forward and backward as far as possible.</p>", "<p>3. Standing and holding the pool wall and rotating trunk left and right as far as possible, with support.</p>", "<p>4. Standing and holding the pool wall, wide stance, with support, lift one foot at a time. Repeat in narrow stance.</p>", "<p>5. Standing and holding the pool wall, wide stance, with support, and inserting their head into the water.</p>", "<p>6. Changing the base of support or closing eyes will increase the level of the exercises.</p>", "<p><bold>Level 2</bold>: Standing exercises including double leg stance with no external support (Figure ##FIG##1##2##).</p>", "<p>The training on this level will challenge postural control in a predictable and controlled manner through voluntary movements. Exercises are similar to level 1 but without external support. For the purpose of activating relevant associated postural adjustments, which are the target of the training at this level, it is more beneficial to execute an exercise slowly with small amplitude rather than using external support, because this will completely change the set of muscles that are recruited for balance control during the task. Thus, it is expected that water motion (small unexpected perturbations) will challenge postural control, increase lower limb muscle activity and might be very challenging for elderly persons. Depending on the skill of the subject, these exercises can also be used as safe \"rest\" after more challenging bouts of exercise.</p>", "<p>Examples: the same as in level 1 but without external support (holding the pool wall).</p>", "<p><bold>Level 3</bold>: Standing exercises including single leg stance with no external support.</p>", "<p>To increase the challenge of exercises at this level, instructors will add dual task exercises and external resistance exercises (e.g., weights).</p>", "<p>Examples:</p>", "<p>1. Standing on one leg while the other leg pushes and pulls a \"noodle\" (long float).</p>", "<p>2. The same as the first, while playing with a ball or adding cognitive task.</p>", "<p>3. Standing on wide/narrow base of support, holding a \"noodle\" with both hands and trying to push it in the water while maintaining balance.</p>", "<p>4. Riding on a \"noodle\" and maintaining balance.</p>", "<p>5. Standing with one leg on a balance ball or \"noodle\".</p>", "<p>6. Standing with both legs on the \"noodle\" and maintaining balance, with or without an additional task</p>", "<p>7. Standing with both legs on a \"noodle\", holding a \"noodle\" with both hands and trying to push it in the water while maintaining balance.</p>", "<p><bold>Level 4</bold>: Gait exercises, dynamic base of support with no external support. Exercises on this level incorporate specific gait training against water resistance.</p>", "<p>Examples:</p>", "<p>1. Walking in all directions (e.g., forward, backward and sideways), at different speeds and in different water depths.</p>", "<p>2. Changing direction as fast as the subject can.</p>", "<p>3. Walking on a \"noodle\" or flat balls with and without additional cognitive tasks.</p>", "<p>4. Adding head movements to challenge the vestibular system.</p>", "<p><bold>Level 5</bold>: Perturbation exercises, for improving reactive and proactive responses. Exercises on this level include different forms of external perturbations, expected as well as unexpected ones that require a proactive or reactive response by the subject. Perturbations requiring a proactive response by the subject may be applied during different forms: water turbulence, the partner or group exercises (Figure ##FIG##2##3##).</p>", "<p>Examples:</p>", "<p>1. The same as levels 3 and 4 but against massive water turbulence and in deeper water.</p>", "<p>2. Standing with wide stance while his or her partner pushes the classmate in different directions, with and without warning.</p>", "<p>3. The same as before but while standing on noodle, changing base of support, in eyes open/closed condition, adding cognitive tasks.</p>", "<p>4. Walking and being pushed by instructor or classmates with and without additional cognitive tasks.</p>", "<p>Participants will also be exposed to exercises where they will be encouraged to either resist a balance perturbation or avoid stepping or executing one or several steps as quickly as possible, including forward and immediately lateral.</p>", "<title>Specificity</title>", "<p>The need to target specific goals is considered an important concept, well established and accepted in the exercise physiology literature for decades [##REF##7016357##26##, ####UREF##2##27##, ##REF##9554029##28##, ##UREF##3##29##, ##UREF##4##30####4##30##]; any successful athlete must live by these rules to maintain or improve function and performance. These fundamental principles of successful exercise prescription apply to anyone regardless of age, sex, or level of fitness [##REF##8772277##65##], even patients.</p>", "<p>The water-based program that includes perturbation exercises targets specific age-related impairments in compensatory and voluntary stepping responses, and water motion and turbulence during standing and walking exercises targeting balance control system to allow keeping balance as follows:</p>", "<p>1. <bold>Speed and length of stepping: </bold>Due to the reduction in speed [##REF##17545207##53##,##REF##15271111##66##] and length [##REF##8176145##54##] of voluntary stepping, older adults take more steps to recover balance [##REF##10819317##55##] and tend to respond to perturbations with a multiple-step response more frequently than younger adults [##REF##8176145##54##, ####REF##10819317##55##, ##REF##8914501##56####8914501##56##]. Although use of multiple steps can be a pre-planned strategy in some situations [##REF##8176145##54##], it appears that the multiple steps emerge as a consequence of lack of lower limb muscle power and its relation to reduced functional abilities, which is well documented [##REF##17508098##67##], and inability to take a rapid and long first step. To increase the ability to take a rapid and long step, subjects will be instructed to respond to the perturbation (level 5 exercises) as quickly with as long a step as they possibly can.</p>", "<p>2. <bold>Medio-Lateral instability during standing and stepping</bold>: Medio-lateral instability in elderly individuals compared with young and elderly fallers compared with nonfallers [##REF##15501837##39##,##REF##14999032##68##] is well documented. To increase the ability to control Medio-lateral balance during stance, subjects will be instructed not to take a step and remain standing during standing exercises (level 2 and 3 exercises) against water turbulence, and will be challenged by narrow base and tandem stance or even more difficult standing on flat ball or a \"Noodle\". This specific training will improve the balance control mechanism.</p>", "<p>3. <bold>Medio-Lateral instability during stepping: </bold>Medio-lateral instability in elderly individuals compared with young [##REF##9149760##52##,##REF##10575080##59##] and the tendency of elders to fall laterally toward the swinging leg during compensatory step execution appears to be a problem related to increased risk of lateral fall and hip fracture [##REF##10819317##55##]. To increase ability to take an additional long lateral step rapidly, subjects will be instructed to respond to the perturbation (level 5 exercises) as quickly as possible by stepping forward (or backward) and adding an extra lateral step as quickly as they can. This exercise resembles plyometric exercises which improve muscle power and speed.</p>", "<p>4. <bold>Improved cross-over stepping: </bold>Maki et al. [##REF##10819317##55##] suggested that collisions between the swing foot and stance leg during lateral perturbation can delay speed of stepping and increase risk of fall. Water-based stepping exercises against water resistance is a tool to train and increase the speed of stepping rapidly with no fear that such collisions will cause a fall during exercise. Also during walking exercises (level 4 exercises) lateral cross-over steps will be made (also over an obstacle that will be placed on pool floor, under the water and against water resistance).</p>", "<p>5. <bold>Reduced ability to take a rapid step during attention demanding tasks (dual task): </bold>Balance-recovery reactions require attentional resources and cognitive processing during compensatory [##REF##10219006##69##, ####REF##12127181##70##, ##REF##11733716##71####11733716##71##] and voluntary stepping [##REF##17545207##53##,##REF##15271111##66##,##UREF##12##72##]. To improve the ability to rapidly switch attention, cognitive tasks will be included during training.</p>", "<p>6. <bold>Increased visual dependency during control of posture: </bold>During some of the exercises in each of the training levels (levels 1–5), subjects will be instructed to close their eyes and control balance in stance and during water turbulence (i.e., water perturbations) subjects will be instructed to keep their body rigid.</p>", "<title>Overload and Progression</title>", "<p>The main factor that modifies the demand of the task is water resistance. Aquatic physical therapy is based on several important bioengineering properties. The basic forces acting upon the patient while in the water consist of buoyancy, drag, and inertial forces. According to key hydrodynamic principles, a moving limb under water is acted on by drag and lift forces. Total drag can be defined as a resistant force opposite to the direction of movement of an object. The viscous properties of the water behind an object are referred to as form drag. The turbulence is generated by the mass of water that is sucked along behind an object in the form of retarding eddies and is proportional to the size and shape of the frontal area that is being pushed against the water. The relationship between the drag force and the velocity of the movement is nonlinear, so that the drag increases as a function of velocity squared (v²). Once the speed doubles, the consequent drag force quadruples. If the participant is in a head-out immersion, the buoyancy decreases his weight-bearing on the ground and by that his sensory input is reduced; this may increase the challenge on the balance control system, thus increasing overload. Furthermore, when the water is turbulent, it causes a continuous perturbation of posture during fix of support exercises and especially during exercise involving change of support (e.g., stepping, walking). Progressions will also be made by including open and closed eyes, stance width, single (level 3) and double leg support (level 2), standing on unstable support surface (such as a flat ball and noodles) during standing. Increased step speed will dramatically increase water resistance and a rapid extra step after the first step is challenging for power production (at all levels of training). Increasing the magnitude of the applied perturbations (e.g., pushes by the instructor and classmates) and applying it unexpectedly, and increasing the speed of forward and backward walking increases the load during gait and balancing.</p>", "<title>Individualization</title>", "<p>The balance training intervention is performed on five levels where each level reflects different increasing demands on the postural control system Training programs should be tailored to the individual needs and abilities of the participant [##UREF##13##73##]. This process requires interaction with an experienced therapist, instructor, or coach and should not be based on a \"cookbook\" approach to training. As in any type of training, for improvement to occur it is crucial to maintain a progressive and specific training load for each of the participants. Progressions should be made when the individuals have reached adaptation. On each level the instructor can instantly modify an exercise to be more or less challenging for each participant. For example, the instructor can increase the difficulty of a certain exercise by instructing a participant to use less external support, close the eyes, decrease the support area (stand on one leg, narrow the stance or on noodle, not use the arms to balance, move the head during the exercises, etc.) while another participant will not find this equally challenging. These \"tools\" allow the instructor to implement exercises on a group level that are still challenging for each individual, even if the skill level in the group varies. In addition, variability is important to keep subjects motivated and excited to pursue the training.</p>", "<title>Generalizability</title>", "<p>The goal of each session in the current program is to constantly challenge the postural control system with exercises that incorporate elements related to the demands of normal activities of daily living [##UREF##14##74##]. To promote generalizability, during the water-based and perturbation exercises the subjects perform a variety of real life dual tasks (cognitive and movement tasks).</p>", "<title>Instructors</title>", "<p>The program should be implemented by two instructors or physical therapists (and a life saver outside the pool) who, based on each individual subject's background and current skill/fitness level, can assess at what level a subject should begin the training program to maximize compliance and outcome and maintain safety. Any form of physical training, either learning and perfecting a sport skill or rehabilitating after an injury or disease, is a process that incorporates both physiological and psychological factors. These factors must harmonize on an individual level for the training process to be successful. A very important role of the instructor is to monitor the training process on an individual level and adapt the training program to optimize outcome and maximize performance. When needed, the instructor should be able to modify the execution of an exercise \"on-the-fly\" to customize the difficulty on an individual level. The instructor and the lifeguard are near by and fully alert to the security of each participant.</p>", "<p>The instructors should be able to direct the subject's attention toward important aspects of the skill being learned to increase awareness. To enhance learning, subjects in this study are provided with instructions regarding the task goals. For example, subjects will be told to take steps as quickly and for as long as possible during balance perturbations or to avoid limb movements during upright stance counteracting water turbulence. These instructions will be gradually reduced as training progresses to avoid dependency [##REF##10413263##75##]. During the training period there is little risk that a participant will fall. Although the participants will be pushed during the perturbation exercises, the water will keep the participant from falling on the pool floor and injuring him/herself in the most demanding levels of exercise. The risk should be minimal. At the beginning, exercises in level 5 will incorporate mild/gentle external balance perturbation exercises applied by the instructor. <bold>It is important to note that these exercises will be customized to each subject's ability. They will be designed to be challenging but never dangerous</bold>. The participants will be repeatedly instructed to ask for help if they feel uncomfortable about performing a certain exercise. Initially, the training will progress slowly to help everyone find their level of ability and not take any unnecessary risks. In fact, an important part of the training is to make each individual learn what their ability is. Overall, the training should be less dangerous than land-based exercises or other activities of daily living.</p>", "<title>Improving gait and balance in Stroke survivors – Pilot Data</title>", "<p>The following section describes findings from a pilot study conducted in collaboration between Ben-Gurion University and the hydrotherapy center in Shaa'r Ha-Negev using the training program presented here. A group of 8 participants (3 female, 5 male) between 71 and 85 years participated in the program two-times a week for 12 weeks. Compliance with the exercise program was excellent (88% average attendance over the 12-week program). Overall, functional status variables improved for all of the participants. Stroke survivors showed the largest improvement in Timed Up and Go (from 14.3 sec to 12.2 sec), and in Berg Balance Test (from 47.3 to 50.2).</p>" ]

[ "<title>Methods/design</title>", "<title>Experimental protocol to assess the efficacy of the training program</title>", "<p>A randomized controlled cross-over trial will be performed to assess the efficacy of the water-based training program that uses perturbation of balance to trigger automatic reflex-like postural responses as well as volitional stepping reactions. Ethical approval for this study was obtained from the Research Ethics Board of Soroka Medical Center and Ben-Gurion University Helsinki Committee (Trial registration number #NCT00708136).</p>", "<title>Recruitment of subjects</title>", "<p>Community-dwelling older adults will be recruited from the community of the Sha'ar Hanegev council via advertisements in local newspapers, the internal brochure of the \"Yahdav\" elderly center and by personal contacts. The subjects who ambulate independently will be randomly allocated to either the water-based exercise group or the control group without intervention. A short interview examined whether the subjects met the inclusion-exclusion criteria. Participants were excluded if they had received physiotherapy or hydrotherapy, or attended community exercise classes in the past six months, had orthopedic surgery within the prior year; showed an indication of cognitive impairment (Mini-Mental Score &lt;24 [##REF##1202204##76##]), had severe focal muscle weakness or paralysis, serious visual impairment, severe peripheral or compression/entrapment neuropathies, any neurological disorders causing balance or motor problems, or cancer (metastases or under active treatment). Prior to their inclusion all subjects received medical clearance from their primary care physician to participate in the study.</p>", "<title>Randomization and blinding</title>", "<p>Subjects will be randomly assigned, using a table of random numbers, to either the balance training intervention group or the control group, who received no intervention. Random sequence generation will be performed by an individual who will not interact with subjects during the balance-testing sessions (IM). Subjects will be informed that they will be randomly assigned to one of the two groups, and the control subjects will be offered the opportunity to participate in a separate 3-month water-based training program after the training period. The individual who administers the training programs (OE) will be the only member of the research team aware of the subjects' group allocation. A blinded research assistant will administer the balance tests and will perform any data processing that involves subjective judgments. Scripts will be used during testing to ensure that all subjects receive the same instructions.</p>", "<title>Intervention</title>", "<p>The intervention program will last 12 weeks, with two 30-minute sessions per week (24 training sessions). This duration and intensity is similar to that used previous perturbation-based training studies [##UREF##8##50##,##REF##12560410##51##,##UREF##15##77##,##REF##16340099##78##]. All subjects will be asked to refrain from initiating any other new exercise programs, or otherwise consciously change their activity levels, during their participation in the study. For the perturbation-based training program, each session will consist of 2–5 minutes of warm up exercises, 15–20 minutes of water-based exercises including voluntary step training (see levels 1–4 exercises), about 5 minutes of perturbation training, and 2–5 minutes of cool-down exercises.</p>", "<title>Types of data to be obtained and measurement techniques</title>", "<p>The following tests will be performed, for research purposes only, on all participants in the study. All outcome measures will be assessed before and after the training period.</p>", "<title>Functional and objective balance tests</title>", "<p>The following standardized functional tests will be administered.</p>", "<p>1. <underline>Voluntary Step Execution Test</underline>[##REF##17545207##53##,##REF##15271111##66##,##UREF##12##72##]: This test will be performed on the portable Kistler 9287 force plate (Kistler Instrument Corp, Winterthur, Switzerland). Participants will be instructed to stand relaxed, view a target placed on a wall 3 m in front of them and to take a step as quickly as possible following a random somatosensory cue. Following a brief learning period, assessments will be made in three directions in random order (forward, backward, and sideways). The time from lifting of the foot (step start) to placing it on the ground will be measured using a portable force plate. The average of these measurements will represent the step execution time. Step execution will also be measured during performance of a secondary attention-demanding task, as described in details by Melzer and Oddsson [##REF##17545207##53##,##REF##15271111##66##,##UREF##12##72##] (Figure ##FIG##3##4##). Inter- and intra-rater reliability was good to excellent for the pooled population of young and elderly and for elderly only ((ICC(2,1) = 0.74–0.92 and 0.62–0.88, respectively) [##UREF##12##72##].</p>", "<p>The five primary outcome measures correspond to the specific aspects of voluntary step execution that were targeted in the water-based training program that include perturbation exercises. The following events were extracted from the ground reaction force data (cf. Figure): (1) The step initiation phase was detected from the tap cue (a spike in the shear ground reaction forces in the anterior-posterior direction (C in Figure) to the first medio-lateral deviation of the center of pressure (COP) towards the swing leg (COP excursion greater than 4 mm from baseline sway following the tap (A in Figure); (2) Foot-off (FO in Figure ##FIG##3##4## was defined at the sudden change in the slope of COP towards the stance leg in the medio-lateral direction; (3) Foot-contact (FC in Figure ##FIG##3##4##) was defined as the onset of unloading the stance leg seen in the vertical ground reaction force; (4) Preparatory phase duration was calculated as the time from step initiation to foot-off; (5) The swing phase duration was calculated as the time from foot-off to foot-contact. The analysis of step execution data extracted specific temporal events using a program written in MatLab (Math Works Inc, Cambridge, MA, USA).</p>", "<p>We have chosen the voluntary step execution test during single and dual task conditions to be measured since in a review published recently, Piirtola and Era [##REF##16439819##79##] found that measures related to dynamic posturography (moving platforms) were not predictive of falls [##REF##16439819##79##]. However Melzer et al. [##REF##17545207##53##] found that application of the voluntary step execution test similar to the test in the proposed study identified elderly fallers.</p>", "<p>2. <underline>Stabilogram-Diffusion Analysis:</underline> An automated algorithm will be used to extract standardized stabilogram-diffusion parameters from each of the COP data sets collected during quiet standing. These parameters include diffusion coefficients, critical displacement, critical time and scaling exponents for both lateral and anterior-posterior sway directions [##REF##8224055##80##,##REF##7589299##81##]. For each of the conditions (eyes open and eyes closed), participants will be required to stand on the platform 10 times with the eyes open and 10 times with the eyes closed for 30 s each. For each trial, they will be instructed to sway as little as possible.</p>", "<p>A computerized automated procedure will be used to analyze the center of pressure recordings. Eighteen parameters (see below) will be extracted from the stabilogram-diffusion analysis to describe different aspects of the postural control process. These include two sets of the following parameters; one for medio-lateral and one for the anterior posterior direction and one resultant (refer to Figure ##FIG##4##5## for a graphical illustration of the stabilogram-diffusion plot):</p>", "<p>C_TCritical Time, separates short-term and long-term regions. Indicates where the balance control system switches from an open-loop to a closed loop behavior.</p>", "<p>C_DCritical Displacement, indicates mean square displacement of the COP at the Critical Time. Indicator of short-term body sway that the subject is able to control.</p>", "<p>D_SShort-term diffusion coefficient, indicates the stochastic activity (frequency and amplitude) of the COP, the random walker, in the short-term region. Assessed from the slope of the stabilogram-diffusion plot in the short-term region.</p>", "<p>D_LLong-term diffusion coefficient, as D_Sfor the long-term region.</p>", "<p>H_SShort-term scaling exponent, indicates the degree of correlation between past and future values of the COP. A value of 0.5 indicates a classical random walk (50% chance of COP displacement in one direction or the other); &lt;0.5 indicates anti-persistence, i.e., the COP tends to come back to a certain equilibrium point (suggests closed-loop control); &gt;0.5 indicates persistence, i.e., the COP tends to drift away (suggests open-loop control). Values can be between 0 and 1.</p>", "<p>H_LLong-term scaling exponent, as H_Sfor the long-term region.</p>", "<p>Stabilogram-diffusion parameters will be extracted for both eyes-open and eyes-closed conditions. The difference in critical displacement between eyes-open and eyes-closed will be used as an indicator of how much an individual relies on vision to control body sway. A large increase in sway with eyes closed would indicate visual reliance.</p>", "<p>3. <underline>Berg Balance Scale</underline>[##REF##1444775##82##]: The participant is scored on 14 tasks graded on a 0–4 scale to evaluate balance function under different conditions (maximum score 56). Wang et al. [##REF##17185241##83##] found good internal consistency reliability (Cronbach's alpha = 0.77), good inter-rater reliability (ICC(2,1) = 0.87), and moderate correlation with the TUG and usual gait speed (Spearman's rho = -0.53 and 0.46, respectively).</p>", "<p>4. <underline>Get-Up-and-Go Test</underline>[##REF##1991946##84##]: The participant is seated in a chair that is placed 3 meters from a wall. The participant is instructed to rise from the chair, walk at a normal pace to the wall, turn around, return to the chair, and sit down. This task is timed by the researcher using a stopwatch. A practice trial is allowed prior to the actual test. The tester remains near the participant throughout the test to prevent a fall or injury. The TUG [##REF##1991946##84##] was found to be correlated with other measurements, such as gait speed (<italic>r </italic>= -0.61) and the Barthel Index (<italic>r </italic>= -0.78). The TUG was shown to have a sensitivity and specificity of 87% for identifying older adults who are prone to falls. The measures showed significant inter-correlation (r = 0.93). Intra-tester and inter-tester reliability have been reported as high in elderly populations, ICC = 0.92–0.96 [##REF##10960937##85##].</p>", "<title>Questionnaires</title>", "<p>The following questionnaires will be administered to all participants enrolled in the study. Other secondary outcome measures will be analyzed to evaluate whether the training had any benefits extending beyond effects on balance reactions</p>", "<p>1. Fear of falling (Fall Efficacy Scale, FES).</p>", "<p>2. Memory and cognition (Folstein Mini-Mental State Examination).</p>", "<p>3. Late Life Function and Disability Index (LL-FDI). The LL-FDI is a scale developed by Jette and Haley at Boston University. This scale is specifically designed to be sensitive to changes in physical function, something previous measures did not do as well [##REF##11909886##86##,##REF##11909885##87##]. The LL-FDI was recently translated to Hebrew. The function component of LL-FDI found to be a reliable (ICC(2,1) = 0.77–0.90) and valid measure of balance function (Berg Balance Scale, <italic>r </italic>= 0.48, <italic>P </italic>&lt; 0.001) and gait speed (Get-Up-and-Go Test, <italic>r </italic>= -0.52, <italic>P </italic>&lt; 0.001) [##REF##17943680##88##].</p>", "<title>Randomized Cross-Over Clinical Trial</title>", "<p>We have decided to conduct a Randomized Cross-Over Clinical Trial, a prospective, analytical, experimental study. Individuals will be randomly allocated to one of two groups (water-based balance training program and controls) and, after a 3-month training period with a 1-month washout period, participants will be switched to the other group for the same period. The control group will not receive any instructions and will not be encouraged to change their physical activity, activities of daily living or social habits during the study. The participants will be examined during the baseline and post-test in a single blind fashion to determine whether a water-based training program that includes external perturbation exercises is an effective treatment to improve speed of stepping and balance control measures in upright stance.</p>", "<title>Statistical analysis</title>", "<p>Normality will be ascertained by the Shapiro-Wilk statistic (non-significant) and normal Q-Q plots, indicating that parametric statistics are able to be used. A repeated measures analysis of variance for intervention * time will performed to determine if there are any differences in effect between the two exercise training circuits. The repeated measures of time are baseline, 3 months (post-intervention of the first group – 1^stcircuit) and (6 months post-intervention of the second group – 2^ndcircuit). The effects of training on the mean step reaction times (step initiation, time to foot-off, time to foot-contact, preparatory phase, and swing phase), postural stability measure (C_T, C_D, D_S, D_L, H_S, H_L), BBS, TUG, and LL-FDI scores will be calculated using SPSS (version 10.1, SPSS Corp., Chicago, IL). Order of intervention will be also analyzed as a covariate in order to detect any carryover effect from the previous intervention. If a difference between the two training circuits will be found for any variable, <italic>post hoc </italic>comparisons with Bonferroni adjustment will be made. Wilcoxon signed rank test and Mann-Whitney U-tests will be used in case the variable was not normally distributed. Results will be presented as mean values ± SD, the level considered to be statistically significant was <italic>p </italic>&lt; 0.05.</p>", "<title>Sample size estimate</title>", "<p>A sample size requirement of 36 was estimated to detect an effect size of 0.8, powered at 80% and alpha of 5% was chosen for a clinically meaningful estimate. The estimation was performed two-sided. Based on a paper by Melzer et al. [##REF##17545207##53##] the investigators found that step execution (average foot-contact times) during the execution of cognitive tasks were 1414 ms ± 417 for elderly fallers and 1165 ± 352 in elderly non-fallers. It was estimated that 32 subjects are required to detect a clinical change in this parameter. For the current study we have used an attrition rate of 10% (32 × 1.10 = 36).</p>" ]

[]

[ "<title>Discussion</title>", "<p>This study is the first to use water-based training that includes perturbation exercises and water turbulence in a group setting as an intervention to reverse age-related impairments in the ability to step quickly and recover from loss of balance. It differs from previous studies done in the water in this area in a number of significant ways. To date, no study has proposed using a water-based training program that includes perturbations to train stepping reactions and investigate the potential of water turbulence to improve stability. Only four exercise regimens have proposed the use of perturbations to improve stepping in elderly persons; all were land-based exercises regimens [##UREF##7##49##, ####UREF##8##50##, ##REF##12560410##51####12560410##51##,##REF##15213472##89##].</p>", "<p>The water-based training program that includes perturbation exercises as outlined is targeted specifically to: 1) step execution-recovery reactions that are known to be impaired in older adults and associated with increased falling risk [##REF##17545207##53##]; 2) the water-turbulence during voluntary exercises challenges balance control in multiple directions; 3) the perturbations are applied by instructors and classmates in predictable and unpredictable manners that allow subjects to exercise safely and progress when needed. Based on our previous findings [##REF##17545207##53##,##REF##15271111##66##], ongoing cognitive exercises are included to increase the load and specificity of training.</p>", "<p>We hypothesize that the novel water-based balance training that includes perturbation exercises will improve balance control and increase speed of stepping, and this should help to reduce the incidence of falls. Due to the limitation of randomized controlled cross-over trials, the investigation of effects on falling is beyond the abilities of the present study. The results of the present study will add evidence regarding the effectiveness of perturbation-based balance training programs, and will be novel in conducting the perturbation exercises in water against water resistance and in a group setting that provides cost-effective exercise programs for long-term improvement followed by maintenance of the training benefits.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Gait and balance impairments may increase the risk of falls, the leading cause of accidental death in the elderly population. Fall-related injuries constitute a serious public health problem associated with high costs for society as well as human suffering. A rapid step is the most important protective postural strategy, acting to recover equilibrium and prevent a fall from initiating. It can arise from large perturbations, but also frequently as a consequence of volitional movements. We propose to use a novel water-based training program which includes specific perturbation exercises that will target the stepping responses that could potentially have a profound effect in reducing risk of falling. We describe the water-based balance training program and a study protocol to evaluate its efficacy (Trial registration number #NCT00708136).</p>", "<title>Methods/Design</title>", "<p>The proposed water-based training program involves use of unpredictable, multi-directional perturbations in a group setting to evoke compensatory and volitional stepping responses. Perturbations are made by pushing slightly the subjects and by water turbulence, in 24 training sessions conducted over 12 weeks. Concurrent cognitive tasks during movement tasks are included. Principles of physical training and exercise including awareness, continuity, motivation, overload, periodicity, progression and specificity were used in the development of this novel program. Specific goals are to increase the speed of stepping responses and improve the postural control mechanism and physical functioning. A prospective, randomized, cross-over trial with concealed allocation, assessor blinding and intention-to-treat analysis will be performed to evaluate the efficacy of the water-based training program. A total of 36 community-dwelling adults (age 65–88) with no recent history of instability or falling will be assigned to either the perturbation-based training or a control group (no training). Voluntary step reaction times and postural stability using stabiliogram diffusion analysis will be tested before and after the 12 weeks of training.</p>", "<title>Discussion</title>", "<p>This study will determine whether a water-based balance training program that includes perturbation exercises, in a group setting, can improve speed of voluntary stepping responses and improve balance control. Results will help guide the development of more cost-effective interventions that can prevent the occurrence of falls in the elderly.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>LO designed initially the land based perturbation training program. All authors contributed to design of the study and the development of the water based balance training program that include perturbation exercises. IM and LO and OE wrote the paper, OE will administer the training program. IT collects the data and subject recruitment and IM process the data and perform the statistical analyses. All authors contributed significantly to the preparation of the paper, and read and approved the final version.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2318/8/19/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors wish to acknowledge management of the hydrotherapy center in Shaa'r Ha-Negev, Israel, who aided in the recruitment of subjects.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Level 1 exercise – standing on a noodle, maintaining balance with external support (see the red arrow).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Level 2 exercise – standing on a flat ball with narrow base stance, maintaining balance without external support (e.g., paying attention to how challenging the task is).</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Level 5 exercise – standing on a noodle and maintaining balance while the participant is being pushed.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>An example of forward step execution data for a 90-year-old subject during single (bottom) and dual (top) task conditions. Note that the tap cue is detectable in all of the signals. Note the differences in step reaction times between the two task conditions (distance between C and A). COPx = Mediolateral center of pressure, Fy = Ground reaction forces (shear forces) in antero-posterior direction. Fz = Vertical ground reaction forces, mm = millimeter, N = Newton. The following events are marked with vertical lines: Tap cue (C), Initial deviation of COPx (A), Foot-off (FO), Foot contact (FC).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p>A schematic Stabilogram-Diffusion plot indicating the parameters that can be extracted to describe properties of the postural control process.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1471-2318-8-19-1\"/>", "<graphic xlink:href=\"1471-2318-8-19-2\"/>", "<graphic xlink:href=\"1471-2318-8-19-3\"/>", "<graphic xlink:href=\"1471-2318-8-19-4\"/>", "<graphic xlink:href=\"1471-2318-8-19-5\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The congenitally tortuous internal carotid artery (ICA) is an uncommon but important anomaly for the otolaryngologist, to recognize. Numerous descriptions of the anomalies of the greatest vessels of the head and neck, as well as of the ICA have been presented in the literature. The deformities of the ICA have been reported with a large variability of pattern and degree. Some of them determine a dislocation of the ICA that can be found at the level of the pharyngeal wall in some cases. Because of this dislocation, the ICA may cause a widening of the retropharyngeal and lateropharyngeal soft tissues. The ectopic ICA poses a risk during both major oropharyngeal tumor resection and less extensive procedures, such as tonsillectomy, adenoidectomy, and uvulopalatopharyngoplasty. We report a case of a 56 year-old male patient suffering from dysphagia associated with aberrant ICA manifesting itself as a pulsative protruding of the left lateral wall of the oropharynx.</p>" ]

[]

[]

[]

[ "<title>Conclusion</title>", "<p>Ectopic internal artery is a very rare variation. The venous anomalies are relatively more frequent than arterials [##REF##7356771##1##]. The ICA originates from the third aortic arch, and it remains controversial whether the common and external carotids have the same third aortic arch origin or they originate from the aortic sac [##UREF##0##2##, ####UREF##1##3##, ##REF##8760481##4##, ##REF##1732967##5####1732967##5##]. The ICA irrigates most of the cerebral hemispheres and the orbits, and contributes with ramifications to the frontonasal area.</p>", "<p>The ICA ascends within the carotid sheath towards the scull base. It is first crossed laterally by the hypoglossal nerve as this nerve passes forward from its position behind the internal carotid. ICA then crosses the occipital artery, as this artery passes posteriorly from its origination of the external carotid artery. Near the skull base the ICA crosses laterally towards the posterior belly of the digastric muscle and the muscle attached to the styloid process. Laterally to the carotid canal is the deep lobe of the parotid gland. Medially to the carotid are the retropharyngeal space and the superior constrictor muscle.</p>", "<p>Other vital structures located close to the ICA, are the internal jugular vein, the cranial nerves IX to XII, and the external carotid artery. Inferiorly the internal jugular vein lies laterally to the ICA. The glossopharyngeal nerve passes forward between the internal and external carotid artery at the bifurcation. The hypoglossal nerve passes forward laterally to the internal carotid artery just above the bifurcation. The external carotid artery travels anterior to the ICA throughout its entire course.</p>", "<p>The major congenital abnormalities of the ICA can be classified as agenesis, aplasia and hypoplasia, and they can be unilateral or bilateral. Absence of the ICA is referred to as agenesis or aplasia [##UREF##2##6##].</p>", "<p>Anomalies of ICA in the neck may be vascular neoplasms or ectopic position. Vascular neoplasms are more common in children, but two relatively rare neoplasms that occur in the adults are the angiosarcoma and hemangiopericytoma.</p>", "<p>The ectopic carotid artery usually occurs in the temporal bone [##REF##7356771##1##]. Angulations of the ICA is a rare condition, while the variations in the course of the carotid artery are divided into two distinct categories: tortuosity and kinking [##REF##3515599##7##]. Elongation, redundancy, undulation, and a S-shaped curve are classified as tortuosity, while any sharp bend in the vessel is classified as kinking. The causes of this malformation are atherosclerosis as observed in our patient, and congenital deformity. The mean age at diagnosis is 58 years, and the patients are usually asymptomatic.</p>", "<p>While the reports of fatal posttonsillectomy hemorrhage and the dissections of Kelly clearly describe the unusual laterally placed of the ICA, midline carotid arteries are even less commonly reported [##UREF##3##8##]. Kelly noted that only four of his 150 patients had posterior pharyngeal wall pulsation. In addition, there are two reports of cases of profuse postadenoidectomy hemorrhage due to laceration of a midline ICA. Mc Kenzie et al described two fatal cases coarsening ICA injuries during adenoidectomy, one of which resulted in complete arterial ablation [##UREF##4##9##]. Bergqvist described a visible ICA in the nasopharynx that had not been detected preoperatively but was seen intraoperatively after an adenoidectomy had been performed [##UREF##5##10##].</p>", "<p>Ectopic ICAs should be differentiated from other vascular lesions, such as angiosarcoma and hemangiopericytoma. Peritonsillar abscess, masses as lymphomas, and other tumors must be take under consideration, when a panicula in the oropharynx is detected.</p>", "<p>We prefer the use of CT or MRI since they are less invasive than angiogram and provide spatial information about the adjacent pharyngeal anatomy. In MRA the resolution of details is not as precise as in angiograms and imaging artifacts due to turbulent flow or patient movement may be a major limitation. Another one examination for the evaluation of carotid vessels is the EcoColorDoppler (ECD), which is easy to perform, and gives quick and important information that MRI and CT do not provide (velocimetry, haemodynamics) [##REF##17147084##11##].</p>", "<p>Transposition of the ICA bulging the posterior pharyngeal wall constitutes a risk factor for impressive intraoperative and postoperative hemorrhage in surgical procedure such as adenoidectomy, tonsillectomy, uvulopalatopharyngoplasty and incision of peritonsillar abscess, which are often performed by young and inexperienced ENT doctors. The surgeon should be careful in performing routine surgical procedures in the area of the upper pharynx, which generally represent the most frequent interventions carried out by inexperienced surgeons as the first steps of their surgical training. The hidden presence of an asymptomatic anomaly of the internal carotid artery may cause impressive and life-threatening hemorrhage. In the literature is reported a massive blood loss during tonsillectomy in a child with congenital vascular malformation of the lips and the oropharynx [##REF##9189972##12##].</p>", "<p>In our case the referring physician thought that panicula in the lateral wall of oropharynx was edema. The otolaryngologists surgeons must use caution in evaluating patients with masses in the pharynx and augment a careful and complete head and neck examination with appropriate imaging studies before operating. A thorough ocular and digital exploration of the pharynx for arterial pulsations should never be omitted.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Ectopic internal carotid artery (ICA) is a very rare variation. The major congenital abnormalities of the ICA can be classified as agenesis, aplasia and hypoplasia, and they can be unilateral or bilateral. Anomalies of the neck artery may be vascular neoplasms or ectopic position. Carotid angiograms provide absolute confirmation of an aberrant carotid artery, while EcoColorDoppler (ECD) gives also important information about the evaluation of carotid vassels. Nevertheless Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) of the neck provide spatial information about the adjacent pharyngeal anatomy and are less invasive than angiogram. Injuries to the ICA during simple pharyngeal surgical procedures can be catastrophic due to the risk of massive bleeding. We report a case of a 56 year-old male patient suffering from dysphagia associated with aberrant ICA manifesting itself as a pulsative protruding of the left lateral wall of the oropharynx.</p>" ]

[ "<title>Case presentation</title>", "<p>A 56 year-old male patient was admitted to our service with dysphagia, and malaise that had progressed over the last week. Oral examination revealed an edema at the gingival and the soft palate area, as well as a redness and pulsative protruding of the left lateral wall of the oropharynx. The rest clinical evaluations, as well as the blood tests were normal. Because of the palatal edema, he was administered methylprednisolone per os. No other medication was given.</p>", "<p>A Computed Tomography (CT) of the neck was then performed, which revealed the helicoids, ectopic course of the right internal carotid artery (ICA) at the level of the oropharynx (figure ##FIG##0##1a##). Multiplanar reconstruction at the coronal plane demonstrates an angiographic appearance of the vessels of the neck, showing the ectopic portion of the right ICA (figure ##FIG##0##1b##).</p>", "<p>The abnormal extension of the ICA subsequently was confirmed by Magnetic Resolution Angiography (MRA) of the neck (figure ##FIG##1##2##). This abnormal course of the ICA was responsible for the gross appearance at the posterior wall of the oropharynx.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Publication of the manuscript was consented by the patient.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>a. CT scan of the neck, following contrast administration.</bold> Axial section of the level of the oropharynx, demonstrates the horizontal extension of the right ICA towards the midline and behind the oropharynx. b. Multiplanar reconstruction at the coronal plane demonstrates an angiographic appearance of the vessels of the neck, showing the ectopic portion of the right ICA.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Magnetic Resolution Angiography after gadolinium administration shows the helicoids-ectopic course of the right ICA, immediately after the carotid bulb.</bold> Notice also, the significant stenosis of the controlateral left ICA.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1746-160X-4-20-1\"/>", "<graphic xlink:href=\"1746-160X-4-20-2\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>E-Health is described as a revolutionary new paradigm for health care that has evolved as a result of advances in information, telecommunication, network technologies and information management. These technologies have transformed the way that health care is delivered [##UREF##0##1##,##REF##15615295##2##]. Today's technology has the capability to support people in managing almost all aspects of their health care, from seeking general health information to clinical consults without ever having to leave their homes; yet even the most basic personal health information, like specific results of tests, contained in medical charts is not currently readily available through existing technologies (like the Internet) to most consumers of health care [##REF##17626550##3##,##REF##15684128##4##]. This inaccessibility makes it difficult for consumers of health care to be active participants in their own health and wellness. There is consensus that in order for patients to be true partners in the health care encounter, they must have access to their own personal clinical health information (Wiljer et al., Patient Accessible EHRs: Building consensus for successful implementation strategies, <italic>submitted</italic>) that is commonly stored in institutional electronic health records (EHRs). An Electronic Health Record (EHR) is a computerized version of an individual's health record that may contain a person's full health and medical record or can be used for certain records, such as lab results, in conjunction with a more traditional paper-based patient chart. The EHR may be accessible online from many separate, interoperable automated systems within an electronic network and it can facilitate the electronic integration of health care providers by enabling the retrieval of information about patients when and where it is most needed [##REF##16357345##5##]. The ability to provide patients with access to their personal health information can be facilitated through the use of emerging technologies, most commonly through the Internet [##REF##14728493##6##, ####REF##12595402##7##, ##REF##16011818##8##, ##REF##15249261##9####15249261##9##]. This type of access to one's own health information can help prepare individuals to better manage and cope with their health status. In turn, this type of access may have a positive impact on the health care system that can be recognized through more efficient use of resources resulting in health care savings [##REF##17626550##3##]. Access to personal health information is a fundamental right supported by the law [##REF##11660676##10##] and the emergence of new technologies alters how that right can be fulfilled. It has been demonstrated that access to one's health information using these technologies is desired by many health care consumers [##REF##12595402##7##,##REF##11369478##11##, ####REF##10864552##12##, ##REF##14965405##13##, ##REF##15507869##14##, ##REF##17523576##15####17523576##15##].</p>", "<p>Early adopters of new technologies in health care, primarily in the United States and the United Kingdom, are reporting the potential benefits of providing people with access to their electronic health record [##REF##14728493##6##,##REF##15249261##9##,##REF##14965405##13##,##REF##15507869##14##,##REF##17712090##16##, ####REF##12217158##17##, ##REF##15142919##18####15142919##18##], with little to no disruption in clinical operations [##UREF##1##19##]. Access to one's medical record in either traditional paper format or electronically can potentially: 1) enhance patients' understanding of their condition [##REF##12467796##20##]; 2) empower individuals to become active participants in their own care [##REF##10981541##21##, ####UREF##2##22##, ##REF##12680044##23####12680044##23##]; 3) result in better medical management [##UREF##3##24##,##REF##15187074##25##]; 4) lead to more effective provider-patient communication [##REF##12467796##20##,##REF##15187074##25##, ####REF##3304403##26##, ##REF##10099751##27####10099751##27##] and; 5) may improve satisfaction and outcomes [##REF##15187074##25##,##REF##15829480##28##], possibly through improved adherence to health promotion recommendations [##REF##3772566##29##]. A recent randomized trial (ClinicalTrials.gov: NCT00142077) demonstrated a modest impact of a Personal Health Record-based employee health program with tailored, targeted health messages on influenza prevention and control [##REF##18343794##30##]. Providing patient access to their personal health information is also cited as a way of achieving a model of patient-centred care [##UREF##4##31##].</p>", "<p>Although technology exists to support patient access to their medical record, and the law supports individuals' rights to access their health record the health care community has been slow to adopt the use of patient accessible electronic health records. Although several reasons could be cited for this slow uptake process, the absence of a key technology, the EHR, is a significant obstacle to making progress in providing patient accessible electronic records. A 2003 white paper from the American Association of Medical Informatics identifies \"the lack of ubiquitous EHR usage\" as the main environmental barrier to patient accessible health records [##REF##14728253##32##].</p>", "<p>There has recently been a noticeable increase in institutional interest in and adoption of EHRs and Canada Health Infoway has set the target of 50% of Canadians having their electronic health records available to their healthcare providers by 2010 [##UREF##5##33##]. The adoption of systems that provide patient access to these EHRs, such as patient portals or personal health records (PHRs) has been slower to follow. Systems such as these capture either elements of data or all the data stored in the EHR [##REF##16357345##5##] and can be easily provided to the consumer. A PHR system can also incorporate data entered by patients themselves. Slower growth in this area may result from physicians' reluctance to embrace the use of information and communication technology (ICT) solutions [##REF##15318579##34##, ####REF##15492027##35##, ##REF##16717265##36####16717265##36##].</p>", "<p>To assess the readiness for the implementation and adoption of EHRs and PHRs in Canada, a national scan of Canadian general and acute care hospitals was conducted to determine organizational readiness for patient accessible records, to understand organization and staff values related to patient access to their records, and organizational perceptions of patients desires and needs. The scan was conducted under the auspices of the Canadian Committee for Patient Accessible Electronic Health Records (CCPAEHR). The CCPAEHR is a group of Canadian researchers, clinicians, information specialists and educators working together to assess and promote patient access to and involvement with EHRs. This paper will report on the results of this scan and will draw conclusions in an attempt to elucidate the trends in the adoption of EHRs in Canadian hospitals, and the movement towards adoption of PHRs and patient accessible EHRs.</p>" ]

[ "<title>Methods</title>", "<title>Study population</title>", "<p>The frame sample was generated from Scott's Canadian Medical Directory. Eligibility required a designation of either public or acute care hospital, and an active email address for the institutions' Chief Executive Officer (CEO).</p>", "<title>Research design</title>", "<p>Based on a review of the literature and input from members of CCPAEHR and staff at Canada Health Infoway, a questionnaire was created to measure national readiness for the adoption and implementation of the EHR and perceptions regarding the use of EHR and PHR [See Additional file ##SUPPL##0##1##]. The survey instrument included questions pertaining to current record keeping practices using a paper based record and an EHR, the information technology infrastructure to support the EHR, and perceptions about providing patient access to the EHR. Access was defined broadly and could include a number of solutions. For the purpose of this study, we were interested in any configuration of electronic patient information that could be called an EHR, including a computerized record of a person's health and/or medical history that may contain a person's full health and medical record, or just certain records, such as laboratory or diagnostic testing results. Having access to these results provides people, particularly those with chronic illness, access to important information that can help in disease self-management. The questionnaire was reviewed, and tested for face validity by members of the CCPAEHR.</p>", "<p>Data collection took place over an eight-week period and CEOs of eligible institutions were emailed a letter of introduction and a link to the electronic questionnaire in English and French. The CEO was asked to complete the questionnaire and submit it within two weeks of receipt. In addition, the CEO was asked to forward the link for the questionnaire to the chiefs of medicine, nursing and informatics, or the individual who was regarded as the most appropriate to respond. A reminder email message was sent two weeks after initial contact was made, and again, three weeks prior to the close of study date.</p>", "<title>Analytic approach</title>", "<p>Data were analyzed using both Questionpro [##UREF##6##37##] and the SPSS statistical analysis package. Descriptive statistics were used to summarize the basic features of the data, and cross tabulations were used to show the relationship between variables.</p>", "<title>Ethics</title>", "<p>This study was approved by the Research Ethics Board (06-0318-CE) of the University Health Network.</p>" ]

[ "<title>Results</title>", "<p>Two hundred thirteen emails were sent to CEOs of Canadian general and acute care hospitals with a 39% (83/213) response rate.</p>", "<title>Demographics</title>", "<p>As shown in Table ##TAB##0##1##, while the majority of respondents were from Ontario 58.8% (n = 30), there was representation from across the country. Most of the respondents (67.9%) selected \"other\" to describe their role. These individuals most commonly self identified as either Managers of Health Records or Health Information Services or Privacy Officers. Just under half of the responses came from institutions with fewer than 100 beds, but there were responses from a number of medium-sized and larger hospitals as well. One respondent answered on behalf of a health care system (which included 13 hospitals in total), but over half (58.5%) indicated that their hospital was part of a larger health care system.</p>", "<title>The electronic record</title>", "<p>Just over half (54.2%) of hospitals surveyed reported having some sort of EHR; however, 97.6% indicated that the EHR was not the sole method for recording patient information. There were very few institutions that had predominately an electronic record; most commonly (39%) hospitals had records that were between 11–50% electronic (Table ##TAB##1##2##).</p>", "<p>Almost half (44.6%) of the respondents thought that their institution was \"on track\" with the rest of the country in terms of adoption and use of an EHR; 35.4% indicated that their institution was lagging behind on adoption and implementation. For hospitals that have an electronic record, adoption of the EHR was most commonly a recent phenomenon. Just over half (67.5%) of respondents reported adoption of the EHR within the last 5 years (Table ##TAB##2##3##).</p>", "<title>Perceptions about providing access to the EHR</title>", "<p>Survey respondents identified hospital financial resources as the most important barrier (86.7%) to effectively providing patients access to their EHR. Patient computer literacy and clinician buy-in were also thought to be very important barriers to patient access (Table ##TAB##3##4##).</p>", "<p>Only 3% of respondents had conducted any formal survey of staff perceptions about providing patients with access to their EHR and there were no respondents who had conducted a survey of patient perceptions regarding access to their EHR. Very few (3.6%) respondents thought that staff would be willing and eager to provide patient access to their EHR. Just over one-quarter (28.6%) thought that staff would be hesitant but willing to provide such access and 17.9% thought that staff would support partial access for patients to their EHR. There were an additional 50% who responded that staff perceptions were unknown to them, or that no survey had been conducted. Respondents were also asked to give their opinions on what they thought patients' perceptions were regarding access to their EHR. Less than one half of respondents thought that patients would be eager (17%) or hesitant (17%) to access their electronic health record.</p>", "<p>When asked about which elements of the EHR people should have access to, the respondents indicated that staff would be most willing to provide patients with access to their test results (25%) and diagnosis (20.2%), but a quarter thought that patients would desire access to their full record (Table ##TAB##4##5##).</p>" ]

[ "<title>Discussion</title>", "<p>The Canadian health care system is characterized by two trends: the emergence of e-health [##UREF##0##1##,##REF##11720962##38##] and a shift from paternalistic-type medicine to a consumer-based approach [##REF##11369478##11##,##REF##11193991##39##]. Today's patients can be well versed in their disease, seek information from numerous and varying sources including the Internet and have the desire to be active participants in making health care decisions [##UREF##7##40##]. Patients are now more commonly regarded as partners in their care [##REF##11005395##41##, ####REF##8055402##42##, ##REF##8803747##43##, ##REF##8678709##44####8678709##44##]. They are often eager to retrieve quality health related information on the Internet. There is a growing interest in developing innovative ways of providing access to one's personal health and medical record [##REF##14728493##6##,##REF##15249261##9##,##REF##14965405##13##,##REF##17712090##16##,##UREF##1##19##,##REF##11079863##45##,##REF##15299001##46##].</p>", "<p>The results of this research suggest that Canadian acute care and public hospitals are moving in the direction of adopting EHRs as is indicated in Tables ##TAB##1##2## and ##TAB##2##3##. The results suggest this is especially true in the province of Ontario from which a majority of respondents came. The high percentage of respondents from Ontario reflects a system of less centralization in Ontario than in others provinces across the country. Over half of the respondents to this study had some sort of EHR in place for between 1 – 5 years, but the EHR was not the only mechanism for recording patient data, as shown in Table ##TAB##1##2##.</p>", "<p>A significant number of our respondents thought that their institution was on track with the rest of the country in terms of adoption of EHR. This finding supports the general trend towards adoption of this technology; however, with the national agenda of having a fully interoperable pan-Canada EHR by 2010 [##UREF##8##47##], it is somewhat discouraging that over 30% of institutions self-identified as being behind on adoption and implementation of EHRs. Respondents identified financial barriers as the major obstacle to implementation of EHRs. This result reflects the perception of respondents; not necessarily the percentage of the institutional budget spent on information technologies (IT); information that was not solicited in this survey.</p>", "<p>Organizations seem to be responding even more slowly to the consumerist trend in health care, and people's desire for access to their health information. Less than 25% of participants responded that patients would like access to their full electronic health record and only 16% thought that patients would like access to their lab results. This perception is in contrast to other Canadian studies that suggest that the majority of patients and the public would like access to components of their health record [##REF##17523576##15##]. Although less than 10% of respondents thought that health care professionals would want patients accessing their full EHR, 25% did indicate that they thought patients should have access to some records such as laboratory test results</p>", "<p>For successful wide scale adoption of new technologies like EHR, this survey highlights the need for a culture shift in the health care environment to one that better supports embracing new technologies. There were a small number of respondents who self-identified as leaders in Canada in the field of EHR. These early adopters play an important role in influencing and encouraging others in the change process. Early adopters of PHR technologies in the United States and United Kingdom, for example, have reported that the majority of participants found that accessing their health record was easy and that their medical record was complete and accurate [##REF##14965405##13##,##REF##15507869##14##]. The majority of participants in that study found the information in their PHR to be understandable. Only a few respondents were concerned about confidentiality or about the possibility of learning of negative test results [##REF##15299001##46##]. These results suggest that providing people with access to their EHR is potentially less of a problem than is feared by many health care providers. It also suggests that our respondents' perceptions about patient attitudes regarding access to their PHR may not reflect what patients really want.</p>", "<p>Our results suggest that administrators of Canadian Healthcare institutions and health care providers are still anxious about providing access to their EHR. When asked about providers' willingness to provide patient access to the EHR only very few respondents thought that providers would be eager and willing to open the record. On the other hand, when asked about patient desire to access the EHR many more respondents thought that patients would be willing and eager. Similarly, in the opinion of the health care administrators and providers, clinicians were less likely to be willing to open up the full EHR, despite the belief that patients would want access to the full record. These results are representative of the disconnect that exists between consumer desire and provider willingness. These results most likely reflect unwillingness on the part of the providers to give up \"ownership\" (a legal concept) of the medical record. Providers traditionally have seen the record as existing in their domain and have not fully embraced the role of custodian of the record (Wiljer D, Urowitz S, Carter A, Leonard K, Catton P. Guardians and Gatekeepers: Whose Record is it Anyways? <italic>Submitted</italic>). Recognizing this, systems can be implemented that would reduce provider/intuitional hesitation for providing patient access to the EHR. Firstly, having a mechanism in place to deal with patient anxieties that may result from viewing their record is necessary, and secondly there needs to be a refocusing of attitudes related to the understanding of EHR ownership. Traditionally, the perception has been that ownership of the record has resided with the provider or the institution [##REF##18326386##48##], when in fact certain jurisdictions have described the provider/institution more as the custodian of information (PHIPA 54.1). A landmark ruling from the Supreme Court of Canada in 1992 (McInerney vs MacDonald) specified that patients have a right to access their personal health information. Embracing these types of changes would advance the system towards wider adoption of a ubiquitous EHR, which would in turn support readily accessible PHRs.</p>", "<title>Limitations</title>", "<p>Due to the complex methodology for distributing the questionnaire to the broadest pool of respondents, the reported response rate may not be completely accurate. Two hundred thirteen emails were sent to CEOs of Canadian general and acute care hospitals who were asked to forward the questionnaire to others in their institutions. CEOs who were responsible for more than one hospital within a health care system only received one link to the questionnaire. There was no method for tracking the number of questionnaires that were forwarded to multiple recipients within each institution, and therefore it was not possible to calculate the actual number of surveys distributed. There were at least 3 hospitals that had multiple respondents and one respondent who completed a single questionnaire for 13 separate hospitals. Although it is possible that more than the original 213 questionnaires were distributed, we can only report an approximate response rate of 39% (83/213) calculated based on the number of surveys originally distributed and the number of unique responses returned.</p>", "<p>As a result of the low response rate, the results from this cross sectional survey may not be representative of all Canadian acute care and general hospitals. The low number of respondents to the survey limited the authors to a descriptive analysis without making statistical inferences on the reliability of the comparisons.</p>" ]

[ "<title>Conclusion</title>", "<p>A necessary pre-request for PHR adoption is the availability of EHR solutions. This study was undertaken to determine the readiness of Canadian hospitals to support patient access to the EHR. Readiness was determined not only based on the availability of an EHR but on institutional and provider perceptions of patients' desires, ability and willingness to access their health record.</p>", "<p>Results of this study suggests that Canadian hospitals are slowly moving in the direction of patient accessible EHRs. Although 54% of Canadian hospitals have adopted the use of EHRs, this adoption process is still in its infancy. Most institutions are in a state of transition and still have a significant percentage of their records in paper-based format. A full scale adoption of these technologies poses several potential challenges and a significant proportion of Canadian hospitals are not fully prepared or engaged for the implementation of patient accessible EHRs.</p>", "<p>The best way to achieve a balance between patients' desire for access to their records and providers' hesitations about providing that access is still being debated. Before widespread use of PHR can become a reality, it is paramount that change occurs in organizational culture around such issues as ownership and rights to personal health information. This requirement for change presents numerous future opportunities for a number of organizational and research projects aimed at addressing these needs. The challenges should not arrest the movement towards the implementation of PHRs, but should fuel research to create the best possible service to meet all of the stakeholders' needs.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Access to personal health information through the electronic health record (EHR) is an innovative means to enable people to be active participants in their own health care. Currently this is not an available option for consumers of health. The absence of a key technology, the EHR, is a significant obstacle to providing patient accessible electronic records. To assess the readiness for the implementation and adoption of EHRs in Canada, a national scan was conducted to determine organizational readiness and willingness for patient accessible electronic records.</p>", "<title>Methods</title>", "<p>A survey was conducted of Chief Executive Officers (CEOs) of Canadian public and acute care hospitals.</p>", "<title>Results</title>", "<p>Two hundred thirteen emails were sent to CEOs of Canadian general and acute care hospitals, with a 39% response rate. Over half (54.2%) of hospitals had some sort of EHR, but few had a record that was predominately electronic. Financial resources were identified as the most important barrier to providing patients access to their EHR and there was a divergence in perceptions from healthcare providers and what they thought patients would want in terms of access to the EHR, with providers being less willing to provide access and patients desire for greater access to the full record.</p>", "<title>Conclusion</title>", "<p>As the use of EHRs becomes more commonplace, organizations should explore the possibility of responding to patient needs for clinical information by providing access to their EHR. The best way to achieve this is still being debated.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>SU participated in the design of the study, the development of the questionnaire, the analysis of data and drafted the final manuscript. DW participated in the design of the study, the development of the questionnaire and contributed to the final manuscript. EA was responsible for data management and contributed to the analysis. GE contributed to the creation of the questionnaire and to the final manuscript. CDL contributed to the creation of the questionnaire and to the final manuscript. TH contributed to the creation of the questionnaire and to the final manuscript. HP contributed to the creation of the questionnaire and to the final manuscript. KJL contributed to the creation of the questionnaire and to the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1472-6947/8/33/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge the members of the Canadian Committee for Patient Accessible Electronic Health Records (CCPAEHR) for their support of projects related to patient accessible electronic health records and for their contributions to this manuscript. They would also like to acknowledge Naa Kwarley Quartey for her assistance in compiling the manuscript. The authors thank the Canadian Institute for Health Research (CIHR) and Canada Health Infoway (CHI) for their financial support for this project and Cancer Care Ontario for their ongoing financial support of CCPAEHR and its activities. In addition, the authors would like to thank research assistant David Neligan, and summer student Julia Catton for managing logistics of the survey.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Demographics of Responders to Survey</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\" colspan=\"2\"><bold>Demographic</bold></td><td align=\"center\"><bold>Respondents %</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Location</bold></td><td align=\"left\">Ontario</td><td align=\"center\">58</td></tr><tr><td align=\"left\"><bold>N = 50</bold></td><td align=\"left\">British Columbia</td><td align=\"center\">16</td></tr><tr><td/><td align=\"left\">Manitoba</td><td align=\"center\">10</td></tr><tr><td/><td align=\"left\">Alberta</td><td align=\"center\">8</td></tr><tr><td/><td align=\"left\">North West Territories</td><td align=\"center\">4</td></tr><tr><td/><td align=\"left\">New Brunswick</td><td align=\"center\">2</td></tr><tr><td/><td align=\"left\">Nunavut</td><td align=\"center\">2</td></tr><tr><td colspan=\"3\"/></tr><tr><td align=\"left\"><bold>Role</bold></td><td align=\"left\">Chief Executive Officer</td><td align=\"center\">9.4</td></tr><tr><td align=\"left\"><bold>N = 54</bold></td><td align=\"left\">Chief of Medicine</td><td align=\"center\">3.8</td></tr><tr><td/><td align=\"left\">Chief of Nursing</td><td align=\"center\">11.3</td></tr><tr><td/><td align=\"left\">Chief Information Officer</td><td align=\"center\">7.6</td></tr><tr><td/><td align=\"left\">Other</td><td align=\"center\">67.9*</td></tr><tr><td colspan=\"3\"/></tr><tr><td align=\"left\"><bold>Hospital size</bold></td><td align=\"left\">Less than 100</td><td align=\"center\">49.0</td></tr><tr><td align=\"left\"><bold>N = 51</bold></td><td align=\"left\">100 to 400</td><td align=\"center\">33.3</td></tr><tr><td/><td align=\"left\">More than 400</td><td align=\"center\">17.7</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Percent of Patient Record that is Electronic N = 41</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>% Electronic</bold></td><td align=\"center\"><bold>Respondents %</bold></td></tr></thead><tbody><tr><td align=\"left\">0–10%</td><td align=\"center\">29.3</td></tr><tr><td align=\"left\">11–50%</td><td align=\"center\">39</td></tr><tr><td align=\"left\">51–90%</td><td align=\"center\">29.3</td></tr><tr><td align=\"left\">91–100%</td><td align=\"center\">2.4</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Time from Commencement of Adoption of EHR N = 43</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Years</bold></td><td align=\"center\"><bold>Respondents %</bold></td></tr></thead><tbody><tr><td align=\"left\">&lt;1 yr</td><td align=\"center\">16.3</td></tr><tr><td align=\"left\">&gt;1 yr</td><td align=\"center\">51.2</td></tr><tr><td align=\"left\">&gt;5 yrs</td><td align=\"center\">27.9</td></tr><tr><td align=\"left\">&gt;10 yrs</td><td align=\"center\">4.7</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Importance of Barriers to PAEHRs N = 54</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Barriers</bold></td><td align=\"center\"><bold>Very Important %</bold></td><td align=\"center\"><bold>Important %</bold></td><td align=\"center\"><bold>Moderately %</bold></td><td align=\"center\"><bold>Not Important %</bold></td><td align=\"center\"><bold>Not Very Important %</bold></td></tr></thead><tbody><tr><td align=\"left\">Finances</td><td align=\"center\">66.7</td><td align=\"center\">9.2</td><td align=\"center\">16.7</td><td align=\"center\">3.7</td><td align=\"center\">3.7</td></tr><tr><td align=\"left\">Clinician buy-in</td><td align=\"center\">50</td><td align=\"center\">27.8</td><td align=\"center\">14.8</td><td align=\"center\">7.4</td><td align=\"center\">0</td></tr><tr><td align=\"left\">Patient Access to Computers</td><td align=\"center\">27.8</td><td align=\"center\">22.2</td><td align=\"center\">33.3</td><td align=\"center\">11.1</td><td align=\"center\">5.6</td></tr><tr><td align=\"left\">Patient Computer Literacy</td><td align=\"center\">48.1</td><td align=\"center\">13</td><td align=\"center\">22.2</td><td align=\"center\">9.3</td><td align=\"center\">7.4</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Respondents' Perceptions of Provider and Patient Attitudes Regarding Accessible Elements of the EHR</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Elements of the EHR</bold></td><td align=\"center\"><bold>Provider % </bold><break/><bold>N = 84</bold></td><td align=\"center\"><bold>Patient % </bold><break/><bold>N = 68</bold></td></tr></thead><tbody><tr><td align=\"left\">Full Record</td><td align=\"center\">10.7</td><td align=\"center\">25</td></tr><tr><td align=\"left\">Tests Results</td><td align=\"center\">25</td><td align=\"center\">16.2</td></tr><tr><td align=\"left\">Diagnosis</td><td align=\"center\">20.2</td><td align=\"center\">13.2</td></tr><tr><td align=\"left\">Pathology Reports</td><td align=\"center\">10.7</td><td align=\"center\">5.9</td></tr><tr><td align=\"left\">Clinician Notes</td><td align=\"center\">2.4</td><td align=\"center\">2.9</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Appendix A. CCPAEHR Survey (English).</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>*Other roles most commonly included Managers of Health Records, Health Information Services or Privacy Officers.</p></table-wrap-foot>" ]

[]

[ "<media xlink:href=\"1472-6947-8-33-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Phytochemicals induce an array of biological responses in animal cells, including enzyme inhibition, protection against oxidation and regulation of cellular signaling pathways. Among phytochemicals with xenobiotic activities, the stilbenes are of great interest for their potential medical impact. Stilbene compounds, particularly pterostilbene and resveratrol, have been associated with antidiabetic, anticarcinogenic and antilipogenic activities <italic>in vitro </italic>and <italic>in vivo </italic>[##REF##17220336##1##, ####REF##15853379##2##, ##REF##17684136##3##, ##REF##15203173##4####15203173##4##]. Specific enzymatic targets are known for some of these xenobiotic activities. Pterostilbene and related compounds inhibit the cytochrome P450 enzymes, CYP1A1 and CYP1B1, which induce carcinogenicity of environmental teratogens [##REF##17440990##5##]. Pterostilbene also inhibits cyclooxygenases COX-1 and COX-2, interfering with endocrine functions and supporting analgesic activity [##REF##17726731##6##]. Significant increase in activity of hexokinase, while significant decrease in activity of glucose-6-phosphatase and fructose-1,6-bisphosphatase, were observed after oral administration of pterostilbene in diabetic rats [##REF##16616938##7##]. The related compound, resveratrol, stimulates sirtuin enzymes to promote longevity in response to dietary restriction [##REF##15328413##8##,##REF##15254550##9##]. Resveratrol has also been demonstrated to protect against obesity- and diet-related disease in rodents [##REF##17112576##10##]. Additional interactions with new targets may be found to underlie other activities of these compounds.</p>", "<p>While dietary stilbenes and flavonoids are of particular interest for their potential health benefits, <italic>in vivo </italic>activity is limited by low bioavailability due to rapid metabolism and excretion. Studies have found that methoxylation can protect flavonoids from derivatization, thereby improving biostability [##REF##16854778##11##,##REF##16868069##12##]. However, there is also evidence that methoxylation can alter bioactivity. For example, methoxylated flavones induced different cell-cycle arrest points in cultured human cells than hydroxylated flavones [##REF##17250812##13##]. Thus, methoxylation may alter interactions with target proteins, as well as increase bioavailability. These reports on altered bioactivity in methoxylated flavonoids triggered our interest to investigate the effects of methoxylation on stilbene bioactivity, particularly in a whole organism, to assess effects on postmitotic cells in adult tissues as well as on actively dividing cells.</p>", "<p>Use of invertebrates provides one approach to address these questions rapidly and economically in a whole organism. In particular, the roundworm, <italic>Caenorhabditis elegans</italic>, offers many advantages for such analyses. <italic>C. elegans </italic>has a short generation time of 1 week and are easily maintained in large numbers with ordinary laboratory equipment. The adult body is approximately 1 mm in length, and contains most of the tissues present in higher vertebrates, such as a complete nervous system, striated muscles and an intestine with digestive, detoxification and innate immune functions. It is of note that the adult somatic tissues are post-mitotic and therefore lack cell-replacement capacity. <italic>C. elegans </italic>are hermaphrodites and able to self-fertilize, which has greatly facilitated the genetic analysis of developmental and cell biological processes in this organism. Previous uses of <italic>C. elegans </italic>for pharmacological studies have taken advantage of mutant strains for mechanistic studies, in addition to basic studies of compound-induced gene expression or phenotypic changes [##REF##17499272##14##, ####REF##16441844##15##, ##REF##17167099##16####17167099##16##].</p>", "<p>In our study, we used <italic>C. elegans </italic>to compare the bioactivities of methoxylated and hydroxylated stilbenes, based on the parent compound resveratrol. Seven stilbenes differing in hydroxylation and methoxylation patterns were examined for effects on survival of <italic>fem-1(hc17) </italic>sterile adults and growth of germline tumors in <italic>gld-1(q485) </italic>mutants. Methoxylated stilbenes exhibited greater bioactivity in both assays, as compared with hydroxylated stilbenes. Steady-state levels for three of these compounds (one mono-, one di-, and one tri-methoxylated) were measured in treated worms and were not found to correlate with relative bioactivity. This suggests that the greater bioactivity of methoxylated stilbenes does not reflect differential uptake of the compounds. These findings demonstrate that methoxylation substitution enhances stilbene bioactivity in this whole-organism model. Methyl group-specific target site interactions may be one factor accounting for the differential bioactivities of these compounds. Alternatively, methoxylation may protect stilbenes from metabolic modification and excretion, leading to higher potency <italic>in vivo </italic>in <italic>C. elegans </italic>than hydroxylated stilbenes.</p>" ]

[ "<title>Methods</title>", "<title><italic>C. elegans </italic>strains and culture conditions</title>", "<p><italic>C. elegans </italic>strains were maintained at 15°C on NGM agar medium with a live, slow-growing OP50 bacterial lawn for a food source following standard protocols [##REF##4366476##36##]. The following mutant strains were used in this study: BA17, <italic>fem-1(hc17)</italic>, and JK1466, <italic>gld-1(q485)/dpy-5(e61) unc-13(e51)</italic>. Strains were obtained from the <italic>Canorhabditis </italic>Genetics Center at the University of Minnesota.</p>", "<title>Chemical sources and methoxylated stilbene preparation</title>", "<p>Resveratrol and picetannol were obtained from commercial sources (Sigma-Aldrich, Inc. and Calbiochem-Novobiochem Corp., respectively). The methoxylated stilbenes pinostilbene, desoxyrhapontigenin, 3-hydroxy-5,4'-dimethoxystilbene and pterostilbene (Figure ##FIG##0##1##) were synthesized by partial methylation of <italic>trans</italic>-resveratrol as previously reported [##REF##12033810##34##]. The methoxylated stilbenes were purified by preparative layer chromatography (Merck Silica gel 60 F254; EMD Chemicals Inc., Gibbstown, NJ) using the developing solvent chloroform:methanol (96:4) with 1% formic acid. The Rf values for pterostilbene, 3-hydroxy-5,4'-dimethoxystilbene, pinostilbene and desoxyrhapontigenin are 0.61, 0.57, 0.28, and 0.20, respectively. These stilbenes were identified from their ¹H-NMR spectra (Bruker 400 MHz; Bruker, Billerica, MA). All stilbenes were dissolved in ethanol to 25 mg/mL before use. 5-Fluoro-deoxyuracil (Sigma Chemical Co.) was dissolved to 1 mg/mL in sterile water and stored frozen at -20°C until use. For treating <italic>C. elegans </italic>adults, each compound was added in a 200 μL volume to the top of a 1-day old bacterial lawn grown on NGM medium to final concentrations as indicated. Compounds were allowed 2 hours to diffuse through the agar medium before animals were added.</p>", "<title>Survival assays</title>", "<p>For survival analyses, synchronized populations of sterile <italic>fem-1(hc17) </italic>hermaphrodites were obtained by first transferring several fertile hermaphrodites to a fresh plate at 25°C and allowing them to lay eggs for several hours. The parent hermaphrodites were removed and embryos were allowed to develop into sterile adults at 25°C, which takes approximately 48 hours [##REF##6541600##17##]. On the first day of adulthood, referred to as day 0, sterile adults were transferred onto fresh media supplemented with stilbenes at indicated concentrations, and maintained at 25°C. Adult survival was scored every 2–3 days by the animal's ability to move in response to a gentle mechanical stimulus. Statistical analysis of survival was performed using the JMP software package.</p>", "<title>Germline tumor growth assays</title>", "<p>The <italic>gld-1(q485) </italic>mutation causes a defect in oocyte development that results in growth of germline tumors that fill the somatic gonad, eventually leading to the animal's death [##REF##7713419##20##,##REF##7713420##21##]. To examine the effects of the stilbenes on <italic>gld-1(q485) </italic>germline tumors, day 0 adults were placed on stilbene-containing medium in the presence of OP50 bacteria as food source. After 4 days at 20°C, animals were fixed in methanol and germcell nuclei were visualized by staining with DAPI. Images were collected with the entire animal in view using the 4× objective on a Nikon E800 microscope equipped with a Hamamatsu Orca ER CCD camera using OpenLab imaging software. NIH Image J software was used to measure germline tumor growth in treated and untreated animals. Tumor area was measured by outlining the entire DAPI-stained tumor.</p>", "<title>Determination of stilbene uptake</title>", "<p>Uptake was determined for three stilbenes (desoxyrhapontigenin, pterostilbene and resveratrol-trimethylether) by measuring the steady-state levels of each stilbene in adult <italic>fem-1(hc17) </italic>hermaphrodites treated under the same conditions as those used for survival assays. After a 2-day treatment on stilbene-supplemented medium, animals were collected into eppendorf tubes, washed with sterile M9 and allowed to settle under a minimal volume of liquid. The samples were frozen at -80°C for storage. For the analysis of stilbenes, samples were thawed in ice and homogenized in 300 μL of 0.2 M phosphate buffer then centrifuged (4°C, 4000 rpm, 15 min). The supernatant was collected and the pellet was homogenized further with fresh 300 μL of 0.2 M phosphate buffer then centrifuged. The supernatants were combined and loaded on an Oasis^®HLB solid phase extraction cartridge (Waters Corporation, Milford, MA) that has been preconditioned with 0.2 M phosphate buffer. The stilbenes were eluted with 2 mL of methanol and collected in a vial. The eluate was dried under a stream of nitrogen, redissolved in 1 mL of ethyl acetate, filtered (0.2 μm nylon filter) then dried again under a stream of nitrogen. The dried sample was treated with 30 μL of N,O-<italic>bis </italic>[trimethylsilyl]trifluoroacetamide:dimethylformamide (BSTFA: DMF, 1:1; Pierce Biotechnology, Inc., Rockford, IL) and heated at 70°C for 45 min. Derivatized sample was analyzed for stilbenes by gas chromatography-mass spectrometry (GC-MS). GC-MS was performed on a JEOL GCMate II spectrometer (JEOL USA Inc., Peabody, MA) in tandem with an Agilent 6890N gas chromatograph (Agilent Technologies, Santa Clara, CA) using a J&amp;W DB-5 capillary column (0.25 mm internal diameter, 0.25 μm film thickness, 30 m length; Agilent Technologies). The GC temperature program was: initial 190°C, increased to 240°C at 25°C/min rate and held at this temp for 14 min, then finally increased to 300°C at the rate of 25°C/min and held at this temperature for 1 min. The carrier gas was ultrahigh purity helium, at 1 mL/min flow rate. The injection port, GC-MS interface and ionization chamber were at 250, 230 and 230°C, respectively. The volume of injection was 1 μL, splitless injection. Mass spectrum was acquired in positive, electron impact (70 eV), selected ion monitoring mode. Resveratrol-trimethylether (retention time 10.6 min) was monitored at <italic>m/z </italic>270, 239 and 196; desoxyrhapontigenin (retention time 13.1 min) was monitored at <italic>m/z </italic>328, 313 and 206; pterostilbene (retention time 13.6 min) was monitored at <italic>m/z </italic>386, 371 and 297. Quantitation was performed from calibration curve of authentic stilbene samples. GC-MS analyses were in duplicates. For conversion from pg/worm to molarity concentration <italic>in vivo</italic>, the volume of a wildtype hermaphrodite on day 4 of adulthood was taken to be 4.5 μL, as previously determined [##REF##12571101##37##].</p>" ]

[ "<title>Results and discussion</title>", "<p>Seven methoxylated or hydroxylated stilbenes were compared for effects on <italic>C. elegans </italic>survival and tumor growth. This collection included two hydroxylated structures (resveratrol and piceatannol), two monomethoxylated structures (pinostilbene and desoxyrhapontigenin), two dimethoxylated structures (3-hydroxy-5,4'-dimethoxystilbene and pterostilbene) and one trimethoxylated structure (resveratrol-trimethylether) (Figure ##FIG##0##1##). Bioactivity in <italic>C. elegans </italic>has been reported only for resveratrol, which extended adult lifespan [##REF##15254550##9##]. It was of interest, therefore, to compare adult survival in animals treated with resveratrol and the related compounds.</p>", "<p>For survival assays, young adult (day 0) animals were transferred onto fresh medium supplemented with the test compound at a range of concentrations. The compounds were tested at indicated concentrations in the growth medium (below). <italic>C. elegans </italic>nematodes are surrounded by a thick collagenous cuticle and are therefore relatively impermeable to environmental compounds. Consistent with this, our measurements demonstrated that internal concentrations of these compounds were significantly lower than their concentrations in the medium. Survival was scored every 2–3 days as the ability to move in response to a gentle mechanical stimulus. During the first week of adulthood, <italic>C. elegans </italic>hermaphrodites are reproductively competent and normally produce 200–300 progeny. Since progeny production would complicate survival analysis, these experiments were performed using <italic>fem-1(hc17) </italic>animals that are sterile due to a spermatogenesis defect [##REF##6541600##17##,##REF##700253##18##]. Our prior analyses have confirmed that <italic>fem-1(hc17) </italic>and wildtype animals have similar lifespan characteristics [##REF##16441844##15##].</p>", "<p>Under our experimental conditions, both hydroxylated and one monomethoxylated stilbene, pinostilbene, had negligible or modestly beneficial effects on adult survival (Figure ##FIG##1##2##). Consistent with previous reports, we observed that resveratrol had a modestly beneficial effect on adult lifespan (0–15% at 100 μM dose) (Table ##TAB##0##1##). However, the effect was variable and did not attain statistical significance in our experiments. In addition, piceatannol and pinostilbene had beneficial effects on lifetime survival. The effects of these compounds were also modest (5–15%) and were not statistically significant.</p>", "<p>The methoxylated stilbenes, desoxyrhapontigenin, 3-hydroxy-5,4'-dimethoxystilbene, pterostilbene and resveratrol-trimethylether, each exhibited significant detrimental effects on adult survival (Figure ##FIG##2##3##). At a 100 μM dose initiated on the first day of adulthood, survival was reduced 11–26% by desoxyrhapontigenin, 48–57% by 3-hydroxy-5,4'-dimethoxystilbene, 21–28% by pterostilbene and 18–51% by resveratrol-trimethylether (Table ##TAB##0##1##). The toxicity of resveratrol-trimethyether increased steeply within a relatively limited dose range, between 5–20 μM. In contrast, the toxicity of desoxyrhapontigenin, 3-hydroxy-5,4'-dimethoxystilbene and pterostilbene gradually increased between the 20–100 μM doses. The observed difference in activity between the monomethoxylated stilbenes, desoxyrhapontigenin being toxic while pinostilbene not, may be due to differences in steric hinderance introduced by the bulky methoxy groups at different positions in the stilbene ring. Without knowing the target site(s) in <italic>C. elegans </italic>for these stilbenes, it can be speculated that the position of the methoxy group at ring A in pinostilbene causes unfavourable fit for target site inhibition. Differences in activity of these monomethoxylated stilbenes have been demonstrated in other studies; <italic>e.g</italic>., pinostilbene moderately inhibited the catalytic activity of cytochrome P450 2E1, while desoxyrhapontigenin was not inhibitory [##REF##16684708##19##]. We noted that animals treated with either methoxylated or hydroxylated stilbenes did not display any other noticeable phenotypes, such as altered feeding or movement rates.</p>", "<p>The somatic tissues of <italic>C. elegans </italic>adults are comprised solely of post-mitotic cells and lack the ability to renew by stem cell replacement. To more closely examine the effects of methoxylated stilbenes on mitotically-active cells in this organism, we examined their effects on growth of germline tumors produced in <italic>gld-1(q485) </italic>animals. The <italic>C. elegans </italic>hermaphrodite gonad is a U-shaped structure that is bisymmetric and contains the germ cell pool (Figure ##FIG##3##4A##, <italic>gld-1(+)</italic>). Within each gonad arm, germ cells in the distal region undergo mitotic proliferation in response to <italic>Notch</italic>-like signals produced by cells at the distal tips of the gonad arms. As germ cells migrate along the gonad arm, they exit from mitosis, undergo meiosis and subsequently differentiate into mature oocytes. In <italic>gld-1(q485) </italic>mutants, the germ cells fail to exit from mitosis and continue to proliferate throughout the gonad forming a germline tumor that is lethal to the animal (Figure ##FIG##3##4A##, <italic>gld-1(q485)</italic>) [##REF##7713419##20##,##REF##7713420##21##].</p>", "<p>Several stilbenes have demonstrated antiproliferative effects on mammalian cancer cells <italic>in vitro </italic>[##REF##17542483##22##, ####UREF##0##23##, ##REF##9499448##24##, ##REF##17764700##25####17764700##25##]. To assess the effects of methoxylation on antitumor activity <italic>in vivo</italic>, tumor area was measured in <italic>gld-1(q485) </italic>adults treated for four days with either resveratrol trimethylether, desoxyrhapontigenin or pterostilbene, which are methoxylated and toxic to adults, or resveratrol, which is hydroxylated and nontoxic. As controls, germline tumor area was also measured in animals treated with carrier only (ethanol) or with 5-fluoro-2'-deoxyuradine (FUDR), a thymidylate synthetase inhibitor that blocks cell proliferation [##REF##13418758##26##,##REF##4505665##27##]. FUDR was chosen as a positive control for its known antiproliferative effects in <italic>C. elegans</italic>, which have been demonstrated by inhibition of embryonic and larval development [##REF##153845##28##]. After four days of treatment, animals were collected and germline tumors were visualized by DAPI staining to visualize germcell nuclei. Because the level of DAPI staining was not quantitative between animals, we DAPI signal intensity was not used as a measure of tumor size. Rather, tumor size was directly measured as the area of the DAPI-stained gonad.</p>", "<p>For the initial tests of tumor growth suppression, each compound was tested at a 100 μM dose in the growth medium (Figure ##FIG##3##4B##). At this concentration, FUDR exhibited a modest inhibitory effect on <italic>glp-1(q485) </italic>germline tumor growth in two of three experiments (-4%, -7%, -19%; <italic>p </italic>≤ 0.05 for trials 2, 3, t-test vs untreated). At 100 μM dose, the methoxylated stilbenes resveratrol trimethylether and desoxyrhapontigenin were also associated with consistent reductions in tumor size. Pterostilbene also modestly reduced tumor size, and this effect was statistically significant in 2 of 3 trials (<italic>p </italic>≤ 0.05, t-test vs untreated). In contrast, resveratrol had a negligible effect on <italic>gld-1(q485) </italic>germline tumor size which was not statistically significant (-4%, <italic>p </italic>= 0.35). As expected from its known antiproliferative effect, FUDR treatment also appeared to decrease tumor size, although the effect was statistically significant in only 2 of 3 trials.</p>", "<p>To better quantify the effects of stilbenes and FUDR on <italic>gld-1(q485) </italic>tumor growth, two stilbenes, resveratrol and pterostilbene, and FUDR were examined at a series of additional doses between 50–400 μM. Over this range of concentrations, both FUDR and pterostilbene were associated with 10–20% reduction in tumor area (Figure ##FIG##4##5A, B##). The effects of pterostilbene were somewhat variable between trials, and were statistically significant for 3 of 4 experiments at both the 200 and 400 μM dose. The 200 and 400 μM doses of FUDR were consistently associated with smaller tumor area and these effects were significant in all 4 trials. Resveratrol at the 200 and 400 μM dose was not associated with statistically significant reductions in tumor area for any of the three trials conducted. These data demonstrate that the enhanced bioactivity of methoxylated stilbenes <italic>in vivo </italic>in <italic>C. elegans </italic>can be detected as a reduction in <italic>glp-1(q485) </italic>tumor area as well as by adult toxicity.</p>", "<p>The differential bioactivities of methoxylated and hydroxylated stilbenes in <italic>C. elegans </italic>adults might reflect differences in uptake or bioavailability. In general, intact <italic>C. elegans </italic>adults take up compounds relatively poorly due to their thick, impermeable cuticle. This impermeability has impeded pharmacodynamic analysis in this organism. However, steady-state levels of compounds can be measured in treated animals to provide one measure of pharmacodynamics. To assess whether differential uptake correlated with bioactivity in <italic>C. elegans</italic>, steady-state levels for pterostilbene, resveratrol-trimethylether and desoxyrhapontigenin were determined in animals treated for 2 days with 100 μM of each compound in the culture medium. The levels of these stilbenes in <italic>C. elegans </italic>nematodes ranged from 20–80 μM, indicating relatively efficient uptake (Figure ##FIG##5##6##). These concentrations were within the range of serum stilbene levels detected after dietary stilbene supplementation with human volunteers (approx. 2 μM) and rabbits (42.8 μM) [##REF##15779070##29##]. It is also within the dose range where resveratrol was observed to induce dilation of isolated retinal arterioles (50 μM) [##REF##17724212##30##]. These three compounds, while all methoxylated, exhibited different levels of toxicity in adult <italic>C. elegans</italic>. In treated worms, levels of pterostilbene were slightly elevated compared with resveratrol-trimethylether and desoxyrhapontigenin (Figure ##FIG##5##6##). However, the most toxic compound in this group, resveratrol-trimethylether, was present at less than one-third the level of pterostilbene. These data suggest that relative bioactivity did not solely reflect steady-state levels in intact animals, although, this experiment does not directly compare the pharmacokinetic profile of each compound in <italic>C. elegans</italic>.</p>", "<p>This study compared the effects of methoxylated and hydroxylated stilbenes on adult lifespan and tumor growth in <italic>C. elegans </italic>nematodes. In this organism, stilbene methoxylation was associated with toxicity under chronic treatment conditions and reduced tumor size <italic>in vivo</italic>. Overall, this study corroborated other findings of enhanced bioactivities in methoxylated versus hydroxylated stilbenes in other experimental systems [##REF##16919455##31##]. However, ours is the first study to systematically evaluate the effects of stilbene methoxylation on bioactivity in a whole organism, using <italic>C. elegans</italic>.</p>", "<p>The mechanisms for enhanced bioactivity of methoxylated stilbenes may reflect increased biostability <italic>in vivo </italic>due to reduced efficiency of metabolic modification leading to excretion. In the case of another group of compounds, the flavonoids, substituting the hydroxyl groups with methoxy groups was shown to improve flavonoid stability in cultured cells and liver microsomes by blocking metabolic modification and excretion [##REF##16868069##12##,##REF##16854778##11##]. In mammals, hydroxylated flavonoids were shown to undergo glucuronidation by hepatic enzymes to promote excretion [##REF##16854778##11##]. Thus, methoxylation may block this modification and may also promote biostability. Indeed, one naturally methoxylated stilbene, pterostilbene, is cytotoxic in several cellular systems [##REF##7525878##32##]. In contrast, the hydroxylated stilbene, resveratrol, has also been shown to be cytotoxic, but is poorly retained in plasma compared with pterostilbene [##UREF##1##33##]. Thus, methoxylation differences between pterostilbene and resveratrol may improve bioactivity by increasing <italic>in vivo </italic>stability.</p>", "<p>The basis for the toxicity and antiproliferative activities of methyoxylated stilbenes in <italic>C. elegans </italic>adults is not known. The somatic cells of <italic>C. elegans </italic>adults are entirely postmitotic, ruling out antiproliferative effects as the basis for methoxylated stilbene toxicity. However, the toxicity and antitumor activities of methoxylated stilbenes in <italic>C. elegans </italic>adults may reflect interactions with common biological targets. Studies in other experimental systems show that stilbenes are potent antioxidants [##REF##12033810##34##,##REF##11316812##35##]. However, resveratrol and pterostilbene, which have strikingly different activity <italic>in vivo </italic>in adult <italic>C. elegans</italic>, demonstrated similar antioxidant activity <italic>in vitro</italic>, suggesting that antioxidant activity is not the underlying reason for the difference in stilbene bioactivities in <italic>C. elegans</italic>. Stilbenes are also known to inhibit specific cellular enzymes, such as cytochrome P450 and COX enzymes. One study has compared the relative inhibition of mammalian CYP1 cytochrome P450 enzymes by pterostilbene, pinostilbene and desoxyrhapontigenin [##REF##17440990##5##]. In this study, these three methoxylated stilbenes demonstrated increased CYP1 inhibition relative to resveratrol, in partial agreement with our results. However, pinostilbene demonstrated slightly stronger CYP1 inhibition than pterostilbene and desoxyrhapontigenin, a finding not consistent with our <italic>C. elegans </italic>toxicity data. Stilbenes also inhibit COX-1 and -2 monooxygenases. <italic>C. elegans </italic>nematodes do not have any obvious COX-1 or -2 homologs, although the <italic>C. elegans </italic>genome sequence does contain numerous monooxygenases that might have similar mechanisms of action to mammalian COX-1 and -2 enzymes. Further characterization of the <italic>in vivo </italic>targets for methyoxylated stilbenes in <italic>C. elegans </italic>may provide insight into other bioactivities of these compounds in human cells.</p>" ]

[ "<title>Results and discussion</title>", "<p>Seven methoxylated or hydroxylated stilbenes were compared for effects on <italic>C. elegans </italic>survival and tumor growth. This collection included two hydroxylated structures (resveratrol and piceatannol), two monomethoxylated structures (pinostilbene and desoxyrhapontigenin), two dimethoxylated structures (3-hydroxy-5,4'-dimethoxystilbene and pterostilbene) and one trimethoxylated structure (resveratrol-trimethylether) (Figure ##FIG##0##1##). Bioactivity in <italic>C. elegans </italic>has been reported only for resveratrol, which extended adult lifespan [##REF##15254550##9##]. It was of interest, therefore, to compare adult survival in animals treated with resveratrol and the related compounds.</p>", "<p>For survival assays, young adult (day 0) animals were transferred onto fresh medium supplemented with the test compound at a range of concentrations. The compounds were tested at indicated concentrations in the growth medium (below). <italic>C. elegans </italic>nematodes are surrounded by a thick collagenous cuticle and are therefore relatively impermeable to environmental compounds. Consistent with this, our measurements demonstrated that internal concentrations of these compounds were significantly lower than their concentrations in the medium. Survival was scored every 2–3 days as the ability to move in response to a gentle mechanical stimulus. During the first week of adulthood, <italic>C. elegans </italic>hermaphrodites are reproductively competent and normally produce 200–300 progeny. Since progeny production would complicate survival analysis, these experiments were performed using <italic>fem-1(hc17) </italic>animals that are sterile due to a spermatogenesis defect [##REF##6541600##17##,##REF##700253##18##]. Our prior analyses have confirmed that <italic>fem-1(hc17) </italic>and wildtype animals have similar lifespan characteristics [##REF##16441844##15##].</p>", "<p>Under our experimental conditions, both hydroxylated and one monomethoxylated stilbene, pinostilbene, had negligible or modestly beneficial effects on adult survival (Figure ##FIG##1##2##). Consistent with previous reports, we observed that resveratrol had a modestly beneficial effect on adult lifespan (0–15% at 100 μM dose) (Table ##TAB##0##1##). However, the effect was variable and did not attain statistical significance in our experiments. In addition, piceatannol and pinostilbene had beneficial effects on lifetime survival. The effects of these compounds were also modest (5–15%) and were not statistically significant.</p>", "<p>The methoxylated stilbenes, desoxyrhapontigenin, 3-hydroxy-5,4'-dimethoxystilbene, pterostilbene and resveratrol-trimethylether, each exhibited significant detrimental effects on adult survival (Figure ##FIG##2##3##). At a 100 μM dose initiated on the first day of adulthood, survival was reduced 11–26% by desoxyrhapontigenin, 48–57% by 3-hydroxy-5,4'-dimethoxystilbene, 21–28% by pterostilbene and 18–51% by resveratrol-trimethylether (Table ##TAB##0##1##). The toxicity of resveratrol-trimethyether increased steeply within a relatively limited dose range, between 5–20 μM. In contrast, the toxicity of desoxyrhapontigenin, 3-hydroxy-5,4'-dimethoxystilbene and pterostilbene gradually increased between the 20–100 μM doses. The observed difference in activity between the monomethoxylated stilbenes, desoxyrhapontigenin being toxic while pinostilbene not, may be due to differences in steric hinderance introduced by the bulky methoxy groups at different positions in the stilbene ring. Without knowing the target site(s) in <italic>C. elegans </italic>for these stilbenes, it can be speculated that the position of the methoxy group at ring A in pinostilbene causes unfavourable fit for target site inhibition. Differences in activity of these monomethoxylated stilbenes have been demonstrated in other studies; <italic>e.g</italic>., pinostilbene moderately inhibited the catalytic activity of cytochrome P450 2E1, while desoxyrhapontigenin was not inhibitory [##REF##16684708##19##]. We noted that animals treated with either methoxylated or hydroxylated stilbenes did not display any other noticeable phenotypes, such as altered feeding or movement rates.</p>", "<p>The somatic tissues of <italic>C. elegans </italic>adults are comprised solely of post-mitotic cells and lack the ability to renew by stem cell replacement. To more closely examine the effects of methoxylated stilbenes on mitotically-active cells in this organism, we examined their effects on growth of germline tumors produced in <italic>gld-1(q485) </italic>animals. The <italic>C. elegans </italic>hermaphrodite gonad is a U-shaped structure that is bisymmetric and contains the germ cell pool (Figure ##FIG##3##4A##, <italic>gld-1(+)</italic>). Within each gonad arm, germ cells in the distal region undergo mitotic proliferation in response to <italic>Notch</italic>-like signals produced by cells at the distal tips of the gonad arms. As germ cells migrate along the gonad arm, they exit from mitosis, undergo meiosis and subsequently differentiate into mature oocytes. In <italic>gld-1(q485) </italic>mutants, the germ cells fail to exit from mitosis and continue to proliferate throughout the gonad forming a germline tumor that is lethal to the animal (Figure ##FIG##3##4A##, <italic>gld-1(q485)</italic>) [##REF##7713419##20##,##REF##7713420##21##].</p>", "<p>Several stilbenes have demonstrated antiproliferative effects on mammalian cancer cells <italic>in vitro </italic>[##REF##17542483##22##, ####UREF##0##23##, ##REF##9499448##24##, ##REF##17764700##25####17764700##25##]. To assess the effects of methoxylation on antitumor activity <italic>in vivo</italic>, tumor area was measured in <italic>gld-1(q485) </italic>adults treated for four days with either resveratrol trimethylether, desoxyrhapontigenin or pterostilbene, which are methoxylated and toxic to adults, or resveratrol, which is hydroxylated and nontoxic. As controls, germline tumor area was also measured in animals treated with carrier only (ethanol) or with 5-fluoro-2'-deoxyuradine (FUDR), a thymidylate synthetase inhibitor that blocks cell proliferation [##REF##13418758##26##,##REF##4505665##27##]. FUDR was chosen as a positive control for its known antiproliferative effects in <italic>C. elegans</italic>, which have been demonstrated by inhibition of embryonic and larval development [##REF##153845##28##]. After four days of treatment, animals were collected and germline tumors were visualized by DAPI staining to visualize germcell nuclei. Because the level of DAPI staining was not quantitative between animals, we DAPI signal intensity was not used as a measure of tumor size. Rather, tumor size was directly measured as the area of the DAPI-stained gonad.</p>", "<p>For the initial tests of tumor growth suppression, each compound was tested at a 100 μM dose in the growth medium (Figure ##FIG##3##4B##). At this concentration, FUDR exhibited a modest inhibitory effect on <italic>glp-1(q485) </italic>germline tumor growth in two of three experiments (-4%, -7%, -19%; <italic>p </italic>≤ 0.05 for trials 2, 3, t-test vs untreated). At 100 μM dose, the methoxylated stilbenes resveratrol trimethylether and desoxyrhapontigenin were also associated with consistent reductions in tumor size. Pterostilbene also modestly reduced tumor size, and this effect was statistically significant in 2 of 3 trials (<italic>p </italic>≤ 0.05, t-test vs untreated). In contrast, resveratrol had a negligible effect on <italic>gld-1(q485) </italic>germline tumor size which was not statistically significant (-4%, <italic>p </italic>= 0.35). As expected from its known antiproliferative effect, FUDR treatment also appeared to decrease tumor size, although the effect was statistically significant in only 2 of 3 trials.</p>", "<p>To better quantify the effects of stilbenes and FUDR on <italic>gld-1(q485) </italic>tumor growth, two stilbenes, resveratrol and pterostilbene, and FUDR were examined at a series of additional doses between 50–400 μM. Over this range of concentrations, both FUDR and pterostilbene were associated with 10–20% reduction in tumor area (Figure ##FIG##4##5A, B##). The effects of pterostilbene were somewhat variable between trials, and were statistically significant for 3 of 4 experiments at both the 200 and 400 μM dose. The 200 and 400 μM doses of FUDR were consistently associated with smaller tumor area and these effects were significant in all 4 trials. Resveratrol at the 200 and 400 μM dose was not associated with statistically significant reductions in tumor area for any of the three trials conducted. These data demonstrate that the enhanced bioactivity of methoxylated stilbenes <italic>in vivo </italic>in <italic>C. elegans </italic>can be detected as a reduction in <italic>glp-1(q485) </italic>tumor area as well as by adult toxicity.</p>", "<p>The differential bioactivities of methoxylated and hydroxylated stilbenes in <italic>C. elegans </italic>adults might reflect differences in uptake or bioavailability. In general, intact <italic>C. elegans </italic>adults take up compounds relatively poorly due to their thick, impermeable cuticle. This impermeability has impeded pharmacodynamic analysis in this organism. However, steady-state levels of compounds can be measured in treated animals to provide one measure of pharmacodynamics. To assess whether differential uptake correlated with bioactivity in <italic>C. elegans</italic>, steady-state levels for pterostilbene, resveratrol-trimethylether and desoxyrhapontigenin were determined in animals treated for 2 days with 100 μM of each compound in the culture medium. The levels of these stilbenes in <italic>C. elegans </italic>nematodes ranged from 20–80 μM, indicating relatively efficient uptake (Figure ##FIG##5##6##). These concentrations were within the range of serum stilbene levels detected after dietary stilbene supplementation with human volunteers (approx. 2 μM) and rabbits (42.8 μM) [##REF##15779070##29##]. It is also within the dose range where resveratrol was observed to induce dilation of isolated retinal arterioles (50 μM) [##REF##17724212##30##]. These three compounds, while all methoxylated, exhibited different levels of toxicity in adult <italic>C. elegans</italic>. In treated worms, levels of pterostilbene were slightly elevated compared with resveratrol-trimethylether and desoxyrhapontigenin (Figure ##FIG##5##6##). However, the most toxic compound in this group, resveratrol-trimethylether, was present at less than one-third the level of pterostilbene. These data suggest that relative bioactivity did not solely reflect steady-state levels in intact animals, although, this experiment does not directly compare the pharmacokinetic profile of each compound in <italic>C. elegans</italic>.</p>", "<p>This study compared the effects of methoxylated and hydroxylated stilbenes on adult lifespan and tumor growth in <italic>C. elegans </italic>nematodes. In this organism, stilbene methoxylation was associated with toxicity under chronic treatment conditions and reduced tumor size <italic>in vivo</italic>. Overall, this study corroborated other findings of enhanced bioactivities in methoxylated versus hydroxylated stilbenes in other experimental systems [##REF##16919455##31##]. However, ours is the first study to systematically evaluate the effects of stilbene methoxylation on bioactivity in a whole organism, using <italic>C. elegans</italic>.</p>", "<p>The mechanisms for enhanced bioactivity of methoxylated stilbenes may reflect increased biostability <italic>in vivo </italic>due to reduced efficiency of metabolic modification leading to excretion. In the case of another group of compounds, the flavonoids, substituting the hydroxyl groups with methoxy groups was shown to improve flavonoid stability in cultured cells and liver microsomes by blocking metabolic modification and excretion [##REF##16868069##12##,##REF##16854778##11##]. In mammals, hydroxylated flavonoids were shown to undergo glucuronidation by hepatic enzymes to promote excretion [##REF##16854778##11##]. Thus, methoxylation may block this modification and may also promote biostability. Indeed, one naturally methoxylated stilbene, pterostilbene, is cytotoxic in several cellular systems [##REF##7525878##32##]. In contrast, the hydroxylated stilbene, resveratrol, has also been shown to be cytotoxic, but is poorly retained in plasma compared with pterostilbene [##UREF##1##33##]. Thus, methoxylation differences between pterostilbene and resveratrol may improve bioactivity by increasing <italic>in vivo </italic>stability.</p>", "<p>The basis for the toxicity and antiproliferative activities of methyoxylated stilbenes in <italic>C. elegans </italic>adults is not known. The somatic cells of <italic>C. elegans </italic>adults are entirely postmitotic, ruling out antiproliferative effects as the basis for methoxylated stilbene toxicity. However, the toxicity and antitumor activities of methoxylated stilbenes in <italic>C. elegans </italic>adults may reflect interactions with common biological targets. Studies in other experimental systems show that stilbenes are potent antioxidants [##REF##12033810##34##,##REF##11316812##35##]. However, resveratrol and pterostilbene, which have strikingly different activity <italic>in vivo </italic>in adult <italic>C. elegans</italic>, demonstrated similar antioxidant activity <italic>in vitro</italic>, suggesting that antioxidant activity is not the underlying reason for the difference in stilbene bioactivities in <italic>C. elegans</italic>. Stilbenes are also known to inhibit specific cellular enzymes, such as cytochrome P450 and COX enzymes. One study has compared the relative inhibition of mammalian CYP1 cytochrome P450 enzymes by pterostilbene, pinostilbene and desoxyrhapontigenin [##REF##17440990##5##]. In this study, these three methoxylated stilbenes demonstrated increased CYP1 inhibition relative to resveratrol, in partial agreement with our results. However, pinostilbene demonstrated slightly stronger CYP1 inhibition than pterostilbene and desoxyrhapontigenin, a finding not consistent with our <italic>C. elegans </italic>toxicity data. Stilbenes also inhibit COX-1 and -2 monooxygenases. <italic>C. elegans </italic>nematodes do not have any obvious COX-1 or -2 homologs, although the <italic>C. elegans </italic>genome sequence does contain numerous monooxygenases that might have similar mechanisms of action to mammalian COX-1 and -2 enzymes. Further characterization of the <italic>in vivo </italic>targets for methyoxylated stilbenes in <italic>C. elegans </italic>may provide insight into other bioactivities of these compounds in human cells.</p>" ]

[ "<title>Conclusion</title>", "<p>Stilbene methoxylation was associated with increased <italic>in vivo </italic>bioactivity as tested by toxicity and tumor growth in <italic>C. elegans</italic>. In general, increasing degree of methoxylation was correlated with increasing bioactivity, with the exception of pinostilbene. However, methoxylation and toxicity were not correlated with steady-state levels of these compounds in treated animals. These findings suggest that methoxylation enhances bioactivity possibly through increased interactions with <italic>in vivo </italic>targets. A working hypothesis to account for these results is that stilbene methoxylation protects the compound from conjugation and subsequent excretion, thereby increasing biostability and bioavailability in <italic>C. elegans</italic>.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Stilbenes are 1,2-diphenylethylene congeners produced by plants in response to stress. Many stilbenes also exhibit xenobiotic activities in animal cells, such as inhibition of cancer cell growth, neuroprotection, and immune modulation. <italic>In vivo</italic>, hydroxylated stilbenes are metabolized by glucuronidation to facilitate excretion. Methoxylated stilbenes are metabolized more slowly, which may have a positive effect on <italic>in vivo </italic>bioactivity. Here, we have directly compared <italic>in vivo </italic>bioactivities of methoxylated and hydroxylated stilbenes in a whole organism using the roundworm <italic>Caenorhabditis elegans</italic>, an advantageous experimental system for such studies due to its rapid lifecycle, genetic amenability and relatively low-cost.</p>", "<title>Results</title>", "<p>Toxicity towards <italic>C. elegans </italic>adults was observed for trimethoxylated and dimethoxylated stilbenes, as well as the monomethoxylated stilbene desoxyrhapontigenin. Toxicity was not observed for the monomethoxylated stilbene, pinostilbene, nor for hydroxylated stilbenes. The methoxylated stilbenes that exhibited toxicity also showed stronger inhibitory effects than the hydroxylated stilbenes on germline tumor growth in <italic>gld-1(q485) </italic>adults. However, steady-state levels of three inhibitory methoxylated stilbenes did not directly correlate to their relative bioactivities.</p>", "<title>Conclusion</title>", "<p>These findings demonstrate that, for the group of stilbenes investigated, methoxylation generally increased bioactivity <italic>in vivo </italic>in a whole organism, with the exception of pinostilbene. Differences in bioactivity in <italic>C. elegans </italic>adults did not appear to correlate with differential uptake. Rather, we speculate that methoxylated stilbenes may have increased interactions with biological targets <italic>in vivo </italic>or may interact with specific targets unaffected by hydroxylated stilbenes. The potent activities of methoxylated stilbenes provide a basis for further investigations to identify <italic>in vivo </italic>targets for these compounds.</p>" ]

[ "<title>Authors' contributions</title>", "<p>MAW and CAW conceived of and designed the <italic>C. elegans </italic>experiments, which were performed entirely by MAW. AMR prepared the stilbene derivatives and performed the uptake determinations. CAW, MAW and AMR prepared the manuscript. All authors have read and approved the manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Strains were obtained from the <italic>Caenorhabditis </italic>Genetics Center, housed by the University of Minnesota and funded by the National Center for Research Resources of the National Institutes of Health. We thank J. Joseph, N. Greig and D. Longo for helpful discussions. This work was funded in part by the Intramural Research Program of the National Institute on Aging, NIH (Z01 AG000320-06 LN [2007] Genetic and environmental factors that regulate aging and longevity).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Structures of methoxylated and hydroxylated stilbenes tested in this study.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Hydroxylated and one monomethoxylated stilbene had modest beneficial effects on adult <italic>C. elegans </italic>survival</bold>. (A, C, E) Representative survival curves of adult sterile <italic>fem-1(hc17) </italic>animals treated with indicated doses of each compound or vehicle in the medium. Experiments for each compound were conducted concurrently for all doses shown. (B, D, F) Summary data from n = 1–3 independent experiments per concentration tested, showing dose-response for each compound. Complete survival statistics are presented in Table 1.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Methoxylated stilbenes were toxic to <italic>C. elegans </italic>adults</bold>. (A, C, E, G) Representative survival curves of <italic>fem-1(hc17) </italic>sterile adults treated with compounds as indicated from the first day of adulthood. (B, D, F, H) Summary data for independent experiments at indicated concentrations. Complete survival statistics presented in Table 1.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Methoxylated stilbenes, desoxyrhapontigenin and resveratrol-trimethyether, demonstrated modest anti-tumor activity <italic>in vivo</italic></bold>. (A) Upper right, cartoon of normal germ cell proliferation and differentiation in <italic>gld-1(+) </italic>animals. Below, cartoon of aberrant germline tumors formed in <italic>gld-1(q485) </italic>animals. In tumor-containing <italic>glp-1(q485) </italic>adults, DAPI staining allows visualization and quantification of germline tumors as the fluorescent area filling the body. (B) Mean germline tumor size (area ± SEM) relative to control in <italic>glp-1(q485) </italic>adults treated with 100 μM doses of indicated stilbenes or FUDR. Results are average from at least 3 independent experiments. In each experiment, tumor area was determined for 12–47 individuals per compound (average ± SD = 23.1 ± 10.12 animals). Significance was judged in paired t-test (2-tailed); * <italic>p </italic>&lt; 0.05 versus untreated.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Titration of germline tumor growth suppression by FUDR, resveratrol and pterostilbene</bold>. (A) Representative images of DAPI-stained <italic>glp-1(q485) </italic>animals treated for four days with 100 μM or 400 μM doses of FUDR, resveratrol and pterostilbene. The inhibitory effect of FUDR and pterostilbene on tumor size is particularly evident near the central region of the animal where the reflexed arms of the distal gonad meet (arrow in (a), (c) and (e)). (a, h) vehicle-treated controls. (h) is from the same experimental series as (c); (a) is from the same experimental series as other images; (b, c), FUDR at 100 μM (b) and 400 μM (c); (d, e), pterostilbene at 100 μM (d) and 400 μM (e); (f, g) resveratrol at 100 μM (f) and 400 μM (g). Scale bar = 250 μM. (B) Summary of results from three independent experiments for each compound at indicated doses. Each concentration was tested in at least 3 independent trials and a total of 36–100 animals were measured per compound dose in all experiments. Significance was judged by a paired t-test (2-tailed); *, #, ^ <italic>p </italic>&lt; 0.05 versus untreated for FUDR-, pterostilbene- or resveratrol-treated animals, respectively.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Steady-state levels of three stilbene compounds in treated <italic>C. elegans </italic>adults did not correlate with toxicity</bold>. Animals were treated for two days with a toxic dose (100 μM) of indicated compound in the medium. After collection, stilbene levels determined as described in methods. Compounds were measured in two independent samples for each treatment with paired negative control. Averages and SDs between both measurements are shown; statistical significance was determined by t-test.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Adult survival statistics for all trials.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Trial</bold></td><td align=\"center\"><bold>Concentration (μM)</bold></td><td align=\"center\" colspan=\"2\"><bold>Mean lifespan (days)</bold></td><td align=\"center\"><bold>Relative survival (%)</bold></td><td align=\"center\"><bold><italic>p </italic>(Logrank)</bold></td><td align=\"center\"><bold>n (failed, censor)</bold></td></tr><tr><td/><td/><td colspan=\"2\"><hr/></td><td/><td/><td/></tr><tr><td/><td/><td align=\"center\"><bold>Treated</bold></td><td align=\"center\"><bold>Control</bold></td><td/><td/><td/></tr></thead><tbody><tr><td align=\"left\" colspan=\"7\"><bold><italic>Resveratrol-trimethylether</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">9.7</td><td align=\"center\">12.16</td><td align=\"center\">80%</td><td align=\"center\">0.004</td><td align=\"center\">61,0</td></tr><tr><td align=\"center\">4</td><td align=\"center\">20</td><td align=\"center\">7.72</td><td align=\"center\">11.26</td><td align=\"center\">69%</td><td align=\"center\">&lt; 0.001</td><td align=\"center\">61,0</td></tr><tr><td align=\"center\">4</td><td align=\"center\">40</td><td align=\"center\">7.72</td><td align=\"center\">11.26</td><td align=\"center\">69%</td><td align=\"center\">&lt; 0.001</td><td align=\"center\">74,0</td></tr><tr><td align=\"center\">4</td><td align=\"center\">100</td><td align=\"center\">7.18</td><td align=\"center\">11.26</td><td align=\"center\">64%</td><td align=\"center\">&lt; 0.001</td><td align=\"center\">70,2</td></tr><tr><td align=\"center\">5</td><td align=\"center\">5</td><td align=\"center\">18.83</td><td align=\"center\">18.49</td><td align=\"center\">102%</td><td align=\"center\">0.91</td><td align=\"center\">46,3</td></tr><tr><td align=\"center\">5</td><td align=\"center\">20</td><td align=\"center\">16.41</td><td align=\"center\">18.49</td><td align=\"center\">89%</td><td align=\"center\">0.055</td><td align=\"center\">42,3</td></tr><tr><td align=\"center\">5</td><td align=\"center\">100</td><td align=\"center\">15.18</td><td align=\"center\">18.49</td><td align=\"center\">82%</td><td align=\"center\">0.005</td><td align=\"center\">37,6</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">9.02</td><td align=\"center\">15.32</td><td align=\"center\">59%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">49,5</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">7.98</td><td align=\"center\">15.32</td><td align=\"center\">52%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">51,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">7.54</td><td align=\"center\">15.32</td><td align=\"center\">49%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">52,0</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>3-OH-5,4'- dimethoxystilbene</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">6.34</td><td align=\"center\">12.16</td><td align=\"center\">52%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">53,0</td></tr><tr><td align=\"center\">2</td><td align=\"center\">20</td><td align=\"center\">11.05</td><td align=\"center\">11.05</td><td align=\"center\">100%</td><td align=\"center\">0.986</td><td align=\"center\">47,2</td></tr><tr><td align=\"center\">2</td><td align=\"center\">40</td><td align=\"center\">10.52</td><td align=\"center\">11.05</td><td align=\"center\">95%</td><td align=\"center\">0.234</td><td align=\"center\">40,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">10.38</td><td align=\"center\">15.32</td><td align=\"center\">68%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">56,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">7.68</td><td align=\"center\">15.32</td><td align=\"center\">50%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">54,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">6.56</td><td align=\"center\">15.32</td><td align=\"center\">43%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">55,3</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>Pterostilbene</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">9.55</td><td align=\"center\">12.16</td><td align=\"center\">79%</td><td align=\"center\">0.005</td><td align=\"center\">69,9</td></tr><tr><td align=\"center\">4</td><td align=\"center\">20</td><td align=\"center\">10.43</td><td align=\"center\">11.26</td><td align=\"center\">93%</td><td align=\"center\">0.336</td><td align=\"center\">54,0</td></tr><tr><td align=\"center\">4</td><td align=\"center\">40</td><td align=\"center\">10</td><td align=\"center\">11.26</td><td align=\"center\">89%</td><td align=\"center\">0.035</td><td align=\"center\">65,1</td></tr><tr><td align=\"center\">4</td><td align=\"center\">100</td><td align=\"center\">8.07</td><td align=\"center\">11.26</td><td align=\"center\">72%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">51,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">13.72</td><td align=\"center\">15.32</td><td align=\"center\">90%</td><td align=\"center\">0.058</td><td align=\"center\">55,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">14.41</td><td align=\"center\">15.32</td><td align=\"center\">94%</td><td align=\"center\">0.142</td><td align=\"center\">51,4</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">10.98</td><td align=\"center\">15.32</td><td align=\"center\">72%</td><td align=\"center\">&lt; 0.001</td><td align=\"center\">51,0</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>Desoxyrhapontigenin</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">10.64</td><td align=\"center\">12.16</td><td align=\"center\">88%</td><td align=\"center\">0.12</td><td align=\"center\">61,1</td></tr><tr><td align=\"center\">3</td><td align=\"center\">100</td><td align=\"center\">11.31</td><td align=\"center\">15.37</td><td align=\"center\">74%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">36,0</td></tr><tr><td align=\"center\">3</td><td align=\"center\">200</td><td align=\"center\">11.61</td><td align=\"center\">15.37</td><td align=\"center\">76%</td><td align=\"center\">&lt; 0.0001</td><td align=\"center\">44,1</td></tr><tr><td align=\"center\">4</td><td align=\"center\">20</td><td align=\"center\">10.2</td><td align=\"center\">11.26</td><td align=\"center\">91%</td><td align=\"center\">0.12</td><td align=\"center\">74,0</td></tr><tr><td align=\"center\">4</td><td align=\"center\">40</td><td align=\"center\">10.38</td><td align=\"center\">11.26</td><td align=\"center\">92%</td><td align=\"center\">0.11</td><td align=\"center\">71,2</td></tr><tr><td align=\"center\">4</td><td align=\"center\">100</td><td align=\"center\">9.44</td><td align=\"center\">11.26</td><td align=\"center\">84%</td><td align=\"center\">0.003</td><td align=\"center\">50,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">14.18</td><td align=\"center\">15.32</td><td align=\"center\">93%</td><td align=\"center\">0.494</td><td align=\"center\">54,3</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">15.31</td><td align=\"center\">15.32</td><td align=\"center\">100%</td><td align=\"center\">0.48</td><td align=\"center\">59,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">13.63</td><td align=\"center\">15.32</td><td align=\"center\">89%</td><td align=\"center\">0.027</td><td align=\"center\">46,9</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>Pinostilbene</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">13.6</td><td align=\"center\">12.16</td><td align=\"center\">112%</td><td align=\"center\">0.062</td><td align=\"center\">68,1</td></tr><tr><td align=\"center\">2</td><td align=\"center\">20</td><td align=\"center\">10.04</td><td align=\"center\">11.05</td><td align=\"center\">91%</td><td align=\"center\">0.266</td><td align=\"center\">55,0</td></tr><tr><td align=\"center\">2</td><td align=\"center\">40</td><td align=\"center\">11.53</td><td align=\"center\">11.05</td><td align=\"center\">104%</td><td align=\"center\">0.319</td><td align=\"center\">42,5</td></tr><tr><td align=\"center\">3</td><td align=\"center\">100</td><td align=\"center\">16.9</td><td align=\"center\">15.37</td><td align=\"center\">110%</td><td align=\"center\">0.448</td><td align=\"center\">41,0</td></tr><tr><td align=\"center\">3</td><td align=\"center\">200</td><td align=\"center\">15.23</td><td align=\"center\">15.37</td><td align=\"center\">99%</td><td align=\"center\">0.411</td><td align=\"center\">42,5</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">14.24</td><td align=\"center\">15.32</td><td align=\"center\">93%</td><td align=\"center\">0.319</td><td align=\"center\">56,3</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">17.33</td><td align=\"center\">15.32</td><td align=\"center\">113%</td><td align=\"center\">0.085</td><td align=\"center\">60,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">16.24</td><td align=\"center\">15.32</td><td align=\"center\">106%</td><td align=\"center\">0.724</td><td align=\"center\">51,2</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>Resveratrol</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">1</td><td align=\"center\">100</td><td align=\"center\">12.18</td><td align=\"center\">12.16</td><td align=\"center\">100%</td><td align=\"center\">0.867</td><td align=\"center\">70,3</td></tr><tr><td align=\"center\">2</td><td align=\"center\">20</td><td align=\"center\">11.85</td><td align=\"center\">11.05</td><td align=\"center\">107%</td><td align=\"center\">0.182</td><td align=\"center\">48,4</td></tr><tr><td align=\"center\">2</td><td align=\"center\">40</td><td align=\"center\">10.53</td><td align=\"center\">11.05</td><td align=\"center\">95%</td><td align=\"center\">0.924</td><td align=\"center\">55,0</td></tr><tr><td align=\"center\">3</td><td align=\"center\">100</td><td align=\"center\">16.64</td><td align=\"center\">15.37</td><td align=\"center\">108%</td><td align=\"center\">0.435</td><td align=\"center\">30,4</td></tr><tr><td align=\"center\">3</td><td align=\"center\">200</td><td align=\"center\">17</td><td align=\"center\">15.37</td><td align=\"center\">111%</td><td align=\"center\">0.337</td><td align=\"center\">38,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">14.65</td><td align=\"center\">15.32</td><td align=\"center\">96%</td><td align=\"center\">0.804</td><td align=\"center\">54,5</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">16.17</td><td align=\"center\">15.32</td><td align=\"center\">106%</td><td align=\"center\">0.501</td><td align=\"center\">59,0</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">17.55</td><td align=\"center\">15.32</td><td align=\"center\">115%</td><td align=\"center\">0.055</td><td align=\"center\">58,0</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold><italic>Piceatannol</italic></bold></td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">2</td><td align=\"center\">20</td><td align=\"center\">11.72</td><td align=\"center\">11.05</td><td align=\"center\">106%</td><td align=\"center\">0.362</td><td align=\"center\">44,0</td></tr><tr><td align=\"center\">2</td><td align=\"center\">40</td><td align=\"center\">11.58</td><td align=\"center\">11.05</td><td align=\"center\">105%</td><td align=\"center\">0.5</td><td align=\"center\">37,9</td></tr><tr><td align=\"center\">3</td><td align=\"center\">100</td><td align=\"center\">17.78</td><td align=\"center\">15.37</td><td align=\"center\">116%</td><td align=\"center\">0.094</td><td align=\"center\">55,1</td></tr><tr><td align=\"center\">3</td><td align=\"center\">200</td><td align=\"center\">17.5</td><td align=\"center\">15.37</td><td align=\"center\">114%</td><td align=\"center\">0.166</td><td align=\"center\">55,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">20</td><td align=\"center\">13.71</td><td align=\"center\">15.32</td><td align=\"center\">89%</td><td align=\"center\">0.231</td><td align=\"center\">50,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">40</td><td align=\"center\">15.63</td><td align=\"center\">15.32</td><td align=\"center\">102%</td><td align=\"center\">0.75</td><td align=\"center\">50,1</td></tr><tr><td align=\"center\">6</td><td align=\"center\">100</td><td align=\"center\">16.6</td><td align=\"center\">15.32</td><td align=\"center\">108%</td><td align=\"center\">0.146</td><td align=\"center\">50,1</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1471-2210-8-15-1\"/>", "<graphic xlink:href=\"1471-2210-8-15-2\"/>", "<graphic xlink:href=\"1471-2210-8-15-3\"/>", "<graphic xlink:href=\"1471-2210-8-15-4\"/>", "<graphic xlink:href=\"1471-2210-8-15-5\"/>", "<graphic xlink:href=\"1471-2210-8-15-6\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>With the prevalence of allergic rhinitis estimated at 21% – 23% for the European population and 20% – 40% for the western population, appropriate diagnosis and treatment of allergic rhinitis is of global importance [##REF##9003207##1##,##REF##15516669##2##]. Family physicians are usually first approached by patients experiencing symptoms; however, little information exists regarding the rationale to perform specific IgE blood testing, which parameters are most important, and the value of such testing. Given the need to determine if symptoms are truly attributed to allergic mechanisms, it is important that family physicians consider diagnostic testing in conjunction with a careful examination of patient history, clinical evidence, and environmental exposure factors to optimize patient care. The consequences of untreated symptoms can lead to multiple future complications while the consequences of misdiagnosis can lead to inappropriate treatments [##REF##17581263##3##].</p>", "<p>Chronic rhinitis has detrimental effects on quality of life and work productivity [##REF##11029350##4##,##REF##17404676##5##]. Although medications may control symptoms in some patients, it is difficult to distinguish between allergic rhinitis and non-allergic rhinitis using clinical evaluation and medication trials. Two commonly applied methods are used to uncover an allergic etiology and identify possible causes. These include skin prick tests (SPT), and specific IgE tests that are thought to produce concordant measures on a dichotomous basis for specificity and sensitivity, as well as a propensity toward appropriate diagnoses in relation to the presence of specific IgE antibody levels [##REF##10388467##6##,##REF##12877445##7##]. Decisions to utilize these tests are influenced by experience, patient history, diagnostic accuracy and efficacy of the test, and how well test results relate to symptoms [##REF##14970151##8##,##REF##11122298##9##].</p>", "<p>When presented with patient complaints and bothersome symptoms that may or may not be related to allergic rhinitis, physicians rely on numerous strategies to make an appropriate diagnosis. How family physicians weigh the importance of these patient-related parameters when recommending specific IgE testing is largely unknown, yet instrumental to determine appropriate treatment and follow-up therapy. To address this research question, we used a trade off approach (conjoint analysis) to evaluate family physicians' preference to recommend specific IgE blood testing with respect to patient symptoms, family history, and medication use. A second approach using visual analog scaling (VAS) was added to validate and compare findings obtained from the conjoint analysis. Visual analog scales have been used extensively in clinical assessment to quantify patient perceptions of disease severity and the impact of symptoms on health [##UREF##0##10##,##REF##17925497##11##]. Further evaluation was performed to determine if family physicians perceive that testing, as part of the care process was valuable to patient care. As healthcare gatekeepers, family physicians have the best opportunity to construct a baseline assessment of these patients to determine if current treatment strategies are effective, or if patients would benefit from a referral to an allergist or other specialist.</p>" ]

[ "<title>Methods</title>", "<title>Study sample</title>", "<p>Primary care (family) physicians in a southeastern state in the United States were identified through already established medical societies and physician mailing lists that were complied at the Recruitment and Retention Shared Facility at the University of Alabama, Birmingham. Mailing addresses, telephone numbers, fax numbers, specialty area, and practice affiliation was verified for 424 physicians in Alabama. From the list of 424 physicians, a sample of 150 physicians was randomly selected to participate in the study. Three separate mailings containing 50 questionnaires were sent by priority mail, one week apart to these physicians at their respective practice sites. The questionnaire package contained a letter of invitation to participate in the study, along with a self-addressed stamped envelope for the returned questionnaire. Thirty-two questionnaires were completed and returned during the first month, follow-up reminder calls were conducted three weeks after the initial mailing (77 calls were answered), and 14 surveys were faxed per request by providers. A total of fifty completed surveys were returned within two months. The estimated sample size of 50 was determined for this study following examples for studies with repeated-measures designs [##UREF##1##12##]. As an incentive, a gift certificate for a local department store was mailed to physicians who completed the questionnaire.</p>", "<title>Instrument Development</title>", "<p>Techniques to evaluate preference include standard gamble, alternate rating (e.g., visual analog) scale, and time trade-off [##UREF##2##13##]. Besides these techniques, conjoint analysis (a trade off approach among attributes) is another technique that is used to evaluate the importance of preference measurements [##REF##15185386##14##]. Choices are usually presented in the form of profiles that are ranked or rated (e.g., recommend specific IgE testing – yes or no). The part-worth values (coefficients) for each attribute are obtained from the random effects logistic regression model analysis with repeated measures (50 responses × 9 profiles = 450 observations), which follows stated choice experiments based on choice theory [##UREF##3##15##,##UREF##4##16##]. Although developed in marketing research, the use of conjoint analysis in health care is becoming a valuable tool [##REF##12112494##17##, ####REF##15006950##18##, ##UREF##5##19##, ##REF##16707175##20####16707175##20##].</p>", "<p>In an attempt to simplify the conjoint exercise for this study, each attribute was assigned three levels (see Additional file ##SUPPL##0##1##). For example, symptom severity was assigned \"high,\" \"medium,\" or \"low,\" and symptom length appeared as symptoms for \"less than 5 years,\" \"symptoms for 10 years,\" and \"symptoms for more than 20 years.\" Family history included \"neither parent has allergic rhinitis,\" \"mother has allergic rhinitis,\" and \"both parents have allergic rhinitis.\" Medication use included the use of \"over-the-counter medications to control allergy symptoms,\" \"prescribed antihistamines,\" and the \"prescribed nasal spray to control allergy symptoms.\" Effects coding was used to construct the numerical values of the profile attributes. The \"low\" level was the reference value and was denoted as -1. The \"high\" level was denoted as +1.</p>", "<p>A one-third fractional factorial design using repeated measures was chosen to minimize the number of profiles to 9 thereby attempting to avoid respondent fatigue. Two additional profiles were produced manually as holdout profiles for use in validation [##UREF##6##21##]. Each profile portrayed an individual with a pre-determined set of allergic symptoms and clinical indicators. For the dependent variable, family physicians were asked to provide a \"yes\" or \"no\" response to whether they would recommend specific IgE blood testing for this patient. For the purposes of this study, which specific IgE blood test was used by family physicians was not important, or what type of test (food or inhalant) was performed.</p>", "<p>The hypothesis for this study was that the estimated part-worth values or coefficients, exponentiated to odds ratios in this study, for each of the four profile attributes were simultaneously equal to zero. In the next section, family physicians were asked to indicate if recommendations to test were influenced by managed care guidelines, value of testing, referral activities, familiarity with specific IgE testing, relation of test results to symptoms, and value of test to practice, the likelihood to use specific IgE testing using a ten-point scale \"less likely to test\" to \"more likely to test.\" Specific IgE blood testing was rated using a scale ('1' = not valuable to '6' highly valuable) for overall value, value compared to skin testing, and value compared to not testing at all. Demographic characteristics of participating family physicians, such as age, gender, years in practice, and practice site information, were elicited in the last section of the questionnaire. To assess questionnaire validity, participants provided an estimate of a patient's overall health status given the impact of various symptoms and clinical indicators with 0 being the \"Worst Possible State\" and 100 being the \"Best Possible State.\" The means for these items were compared to those rankings obtained from the conjoint exercise to offer additional information regarding testing.</p>", "<title>Data analysis</title>", "<p>Descriptive statistics were provided for demographic variables. The conjoint exercise data were analyzed using a random effects logistic regression model. This type of model was chosen since it produces standard errors that account for the intra-individual correlation. Assumptions of normality, linearity, and equal variances among the items were evaluated to ensure appropriate interpretation of statistical analyses. All statistical analyses were performed using Stata/SE version 9 (College Station, Texas, USA). An Institutional Review Board from the University of Alabama, Birmingham, granted approval for the study.</p>" ]

[ "<title>Results</title>", "<title>Demographics</title>", "<p>Participating physicians (33% response rate) were more likely to be male, between 40 and 60 years of age and with about 20 years of clinical experience in a private practice setting (Table ##TAB##0##1##). Independent <italic>t</italic>-test revealed that among older physicians (&gt; 50 years), those with 10 or more years in practice placed a greater value on specific IgE testing than not testing (n = 32; mean = 4.6) compared to those with less than 10 years in practice (<italic>n </italic>= 18; mean = 3.8; <italic>t </italic>= 2.2; <italic>P </italic>= 0.03).</p>", "<title>Conjoint model</title>", "<p>Results from the random effects logistic regression model are presented in Table ##TAB##1##2##. The interaction between study attributes and demographic characteristics was not significant. Attributes, that are more likely to influence decision to request specific IgE blood testing, were symptom severity, length of time having symptoms, and history for allergic rhinitis reported for both parents. Results reveal the log likelihood = -196.983, Wald χ²= 94.03, <italic>P </italic>&lt; 0.0001, with 448 observations for 50 physicians each physician evaluating 9 profiles, thus supporting the hypothesis that the impact of parameters on specific IgE blood testing are not perceived equally. Symptom severity had the greatest impact on physician decisions to test patients for allergic rhinitis (OR, 12.11; 95%CI, 7.1–20.7). Thus, one would expect that physicians would be 12 times more likely to consider the specific IgE blood test for patients with high symptom severity compared to patients with low symptom severity. Although not significant, other attributes such as length of symptoms and both parents having a history of allergic rhinitis influenced physician decisions to test (OR, 1.46; 95%CI, 0.96–2.2: OR, 1.44; CI, 0.95–2.2, respectively). However, some physicians may not be willing to trade among the alternatives when the decision involved a potentially dominant attribute, where symptom severity may be the only reason to recommend specific IgE blood testing. To assess the potentially dominant effect of symptom severity [##REF##17257725##22##], two versions of the model were run – one containing profiles where symptom severity was present and one containing only those where symptom severity was absent (results not shown). In both situations, other parameter estimates were significant indicating the hypothesis that coefficients were simultaneously equal to zero was rejected regardless of the presence of the symptom severity.</p>", "<title>Validation</title>", "<p>Two methods were used to validate the results of the conjoint exercise – the use of a holdout profile and an alternate rating method. First, was to estimate predictive validity for the holdout profile using the regression model developed from the 9 orthogonal profiles. The relation between the observed response for the holdout profiles and the predicted responses was then examined. The predicted values for the holdout profiles were quite similar to the observed value. The predicted mean probabilities were 82.7% and 78.4% compared to the observed values 70% and 78%, respectively. The differences were not significantly different (<italic>t</italic>-test; <italic>p </italic>= 0.162, <italic>p </italic>= 0.996, respectively) suggesting that the conjoint model exhibits acceptable internal predictive validity. Second, was the use of a VAS where participants responded to each item from the conjoint study presented separately. Lower mean scores obtained for each domain indicated that the particular domain represented choices that were less desirable to the respondent. Symptom severity (mean = 36.7; SD = 16.4) and symptom length (mean – 36.0; SD = 16.6) were ranked the worst followed by medication use (52.6; SD = 21.5), and family history (mean = 61.0; SD = 24.0), revealing consistent response patterns between the conjoint study and the VAS.</p>", "<title>Impact of testing issues on value</title>", "<p>Kaiser-Meyer-Olkin measure of sampling adequacy for the final principal components analysis was 0.82 and the significant (<italic>p </italic>≤ 0.001) Bartlett test of sphericity supported the use of factor analysis for the items used to assess testing issues [##UREF##7##23##]. One factor was retained for testing issues accounting for 54.6% of the variance. Two items, difficulty in interpreting test results and insurance coverage were dropped from the analysis. The factor structure was further verified by reanalyzing the reliability of the dimension. Descriptive statistics (item's mean and standard deviation) and Cronbach's alpha for study items are presented in Table ##TAB##2##3##. Most noteworthy, was that physicians perceived that \"how well the test correlated with symptoms\" was given the highest score (mean = 7.6; SD = 1.9) with respect to \"more likely to use specific IgE testing.\" In addition, physicians perceived that specific IgE testing had significant (<italic>p </italic>≤ 0.007) value overall, perceived value compared to not testing, and perceived value was comparable to skin testing. Cronbach's alpha for the remaining nine items for testing issues was 0.90 and 0.86 for the three items consisting of testing value, indicating a high degree of internal consistency or a high signal-to-noise ratio (i.e., error variance minimized) across individuals [##UREF##8##24##].</p>", "<p>Linear regression analysis was used to assess the relationship between testing issues and testing value. As hypothesized, results using composite scores for testing issues and testing value revealed a moderately positive association between these two dimensions (β = 0.624, <italic>t </italic>= 5.296, <italic>p </italic>≤ 0.001) with (R²= 0.39) 39% of the variance explained by the model.</p>" ]

[ "<title>Discussion</title>", "<p>According to our results, family physicians consider symptom severity to be the significant determinant, followed by symptom length and family history when recommending the use of specific IgE blood testing for patients suspected of having allergic rhinitis. Physicians in practice for 10 years or more placed greater value on specific IgE testing compared to those in practice for less than ten years. Moreover, results from VAS were consistent with findings from the conjoint study. Our findings were also corroborated in another recent study where VAS for symptom severity compared favorably with standard quality of life measures [##REF##17362246##25##].</p>", "<p>Professional organizations such as the American Academy of Allergy, Asthma, and Immunology and the European Academy of Allergology and Clinical Immunology recognize that allergic disease is a major health concern often requiring specific allergen avoidance and treatment strategies that are based on positive findings from history and diagnostic testing [##UREF##9##26##,##UREF##10##27##]. Results from this study support the positions elicited from the Joint Task Force on Practice Parameters for Rhinitis and Allergic Rhinitis and its Impact on Asthma (ARIA) in that family physicians are capable of recommending specific IgE testing, using the test to confirm allergic disease and identifying possible allergens [##REF##16267324##28##, ####REF##11707753##29##, ##REF##9860027##30####9860027##30##]. Also consistent with recommendations from the Joint Task Force, results from the VAS closely approximated the findings of the conjoint study, thus revealing the usefulness of VAS in clinical practice to assess symptom severity for patients suspected of having allergic rhinitis.</p>", "<p>Values for each item relating to patient perceptions of the test, patient demand to have testing performed, other clinical indicators, and the type of allergic rhinitis were summated to create a composite score. This composite score for testing issues yielded a moderately positive correlation with testing value, thus providing initial evidence that issues associated with testing and the process of care were linked to outcomes such as testing value. Moreover, positively framing the information describing the benefits of testing and the value of testing to patients is also known to influence their expectations of benefits [##REF##8892495##31##].</p>", "<p>Limitations include a low response rate and a cross-sectional study representing one geographical region. In addition, family physicians may consider attributes that were not evaluated in this study when deciding to request specific IgE blood testing for patients suspected of having allergic rhinitis. Hypothetical profiles were developed for this study and may not include all aspects of information provided by patients to family physicians, reflect what happens in actual clinical practice, and represent the opinions of physicians in other geographical areas.</p>", "<p>Given the economic burden of allergic rhinitis on society and the research evidence that supports an inverse relationship between health status and specific IgE antibody levels [##REF##17390749##32##, ####REF##15842227##33##, ##REF##16210045##34####16210045##34##], current guidelines should be repositioned and possibly modified to allow family physicians to have a more active role in specific IgE blood testing. Although ARIA suggests the SPT as a first line choice when further evaluation of patients is needed, interpretation of test results requires extensive training and experience. Thus, specific IgE testing was examined in this study as a practical choice for primary care physicians. As suggested from this study and supported in the literature, with proper training family physicians would become more adept at quantifying the results from specific IgE blood testing and recognizing when to refer patients (e.g., continued treatment failure, complications, and beyond scope of expertise) to allergists or other specialists [##REF##12952100##35##, ####REF##17416408##36##, ##REF##17300530##37##, ##REF##11978231##38####11978231##38##]. Another important aspect of training is the need to consider specific IgE blood test and SPT results in the context of patient history, especially when discrepancy exists between test results and symptoms. Diagnostic testing, <italic>per se</italic>, is no substitute for a thorough examination of patient symptoms, health status, and medical history. In summary, allergists and family physicians understand that test results coupled with the findings of a careful clinical examination serve as the foundation to establish a strategy for treatment, from which future health outcomes can be evaluated to determine the success of treatment.</p>" ]

[ "<title>Conclusion</title>", "<p>Family physicians rely on symptom severity, and to some extent on length of time that symptoms are present and family history to determine whether patients should be tested to determine the presence of allergic disease. Physicians with more practice experience placed greater value on specific IgE testing. Findings also revealed a moderately positive association between the issues influencing the use of specific IgE blood testing and test value. Overall, family physicians valued specific IgE blood testing, especially compared to not testing.</p>", "<p>From the study findings, family physicians can use symptom severity as a gauge in clinical practice to determine if patients should undergo detection and testing for allergic rhinitis or related conditions perhaps much earlier during the process of clinical evaluation, especially in the presence of severe symptoms and a positive family history. Baseline evaluation will also increase the likelihood of determining the correct diagnosis and appropriate treatment, and to ascertain the need for referral. Future research is needed to address the impact of patient expectations and treatment experience on value and other outcome measures.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Test results for allergic disease are especially valuable to allergists and family physicians for clinical evaluation, decisions to treat, and to determine needs for referral.</p>", "<title>Methods</title>", "<p>This study used a repeated measures design (conjoint analysis) to examine trade offs among clinical parameters that influence the decision of family physicians to use specific IgE blood testing as a diagnostic aid for patients suspected of having allergic rhinitis. Data were extracted from a random sample of 50 family physicians in the Southeastern United States. Physicians evaluated 11 patient profiles containing four clinical parameters: symptom severity (low, medium, high), symptom length (5, 10, 20 years), family history (both parents, mother, neither), and medication use (prescribed antihistamines, nasal spray, over-the-counter medications). Decision to recommend specific IgE testing was elicited as a \"yes\" or \"no\" response. Perceived value of specific IgE blood testing was evaluated according to usefulness as a diagnostic tool compared to skin testing, and not testing.</p>", "<title>Results</title>", "<p>The highest odds ratios (OR) associated with decisions to test for allergic rhinitis were obtained for symptom severity (OR, 12.11; 95%CI, 7.1–20.7) and length of symptoms (OR, 1.46; 95%CI, 0.96–2.2) with family history having significant influence in the decision. A moderately positive association between testing issues and testing value was revealed (β = 0.624, <italic>t </italic>= 5.296, <italic>p </italic>≤ 0.001) with 39% of the variance explained by the regression model.</p>", "<title>Conclusion</title>", "<p>The most important parameters considered when testing for allergic rhinitis relate to symptom severity, length of symptoms, and family history. Family physicians recognize that specific IgE blood testing is valuable to their practice.</p>" ]

[ "<title>Competing interests</title>", "<p>This study was supported by an unrestricted research grant from Phadia US Inc., Portage, Michigan.</p>", "<title>Authors' contributions</title>", "<p>SLS conceptualized the study, examined the study design, performed the statistical analysis, and drafted the manuscript. SEH setup the study design, performed the statistical analysis, and drafted the manuscript. PBW conceptualized the study, examined the study design, and provided a critical assessment of the manuscript. HE coordinated and managed the collection of data for the study and reviewed the manuscript. All authors approved the manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2296/9/47/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>No acknowledgements</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Demographic Characteristics of Family Physicians</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Characteristic</td><td align=\"center\">Value (n = 50)</td></tr></thead><tbody><tr><td align=\"left\">Age, y</td><td/></tr><tr><td align=\"left\"> Mean (SD)</td><td align=\"center\">49 (12.0)</td></tr><tr><td align=\"left\"> Range</td><td align=\"center\">29 – 79</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Years in Practice</td><td/></tr><tr><td align=\"left\"> Mean (SD)</td><td align=\"center\">18.6 (12.4)</td></tr><tr><td align=\"left\"> Range</td><td align=\"center\">2 – 52</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Gender, no. (%)</td><td/></tr><tr><td align=\"left\"> Male</td><td align=\"center\">35 (71.4)</td></tr><tr><td align=\"left\"> Female</td><td align=\"center\">14 (28.6)</td></tr><tr><td/><td/></tr><tr><td align=\"left\">Practice type, no. (%)</td><td/></tr><tr><td align=\"left\"> Private/Independent</td><td align=\"center\">43 (87.8)</td></tr><tr><td align=\"left\"> Managed care setting</td><td align=\"center\">6 (12.2)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Results from the random effects logistic regression model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Attribute</td><td align=\"left\">Level</td><td align=\"left\">Odds Ratio</td><td align=\"left\">P-value</td><td align=\"left\">95% CI</td></tr></thead><tbody><tr><td align=\"left\">Symptom severity</td><td align=\"left\">High</td><td align=\"left\">12.11</td><td align=\"left\">&lt;0.001^a</td><td align=\"left\">[7.1, 20.7]</td></tr><tr><td/><td align=\"left\">Medium</td><td align=\"left\">1.46</td><td align=\"left\">0.281</td><td align=\"left\">[0.84, 1.9]</td></tr><tr><td/><td align=\"left\">Low*</td><td align=\"left\">0.06</td><td/><td/></tr><tr><td align=\"left\">Length of symptoms</td><td align=\"left\">&gt;20 years</td><td align=\"left\">1.46</td><td align=\"left\">0.073^b</td><td align=\"left\">[0.96, 2.2]</td></tr><tr><td/><td align=\"left\">5 years to 20 years</td><td align=\"left\">1.39</td><td align=\"left\">0.074^b</td><td align=\"left\">[0.96, 2.2]</td></tr><tr><td/><td align=\"left\">&lt;5 years*</td><td align=\"left\">0.47</td><td/><td/></tr><tr><td align=\"left\">History of allergic rhinitis</td><td align=\"left\">Both parents</td><td align=\"left\">1.44</td><td align=\"left\">0.089^b</td><td align=\"left\">[0.95, 2.2]</td></tr><tr><td/><td align=\"left\">Mother only</td><td align=\"left\">1.20</td><td align=\"left\">0.37</td><td align=\"left\">[0.80, 1.8]</td></tr><tr><td/><td align=\"left\">Neither parent*</td><td align=\"left\">0.58</td><td/><td/></tr><tr><td align=\"left\">Medication use</td><td align=\"left\">Intranasal corticosteroids</td><td align=\"left\">1.12</td><td align=\"left\">0.586</td><td align=\"left\">[0.75, 1.7]</td></tr><tr><td/><td align=\"left\">Prescribed antihistamines</td><td align=\"left\">1.33</td><td align=\"left\">0.171</td><td align=\"left\">[0.89, 2.0]</td></tr><tr><td/><td align=\"left\">OTC allergy medications*</td><td align=\"left\">0.67</td><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Descriptive Statistics and Scale Evaluation for Issues and Test Value</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">Mean (SD)</td></tr></thead><tbody><tr><td align=\"left\">Testing issues *</td><td/></tr><tr><td align=\"left\"> Managed care practice guidelines</td><td align=\"center\">5.4 (2.3)</td></tr><tr><td align=\"left\"> Patient's perceived value of the test</td><td align=\"center\">6.5 (1.9)</td></tr><tr><td align=\"left\"> Reduced need to refer patients to allergists</td><td align=\"center\">6.8 (2.0)</td></tr><tr><td align=\"left\"> Difficulty in interpreting test results</td><td align=\"center\">4.4 (2.6)</td></tr><tr><td align=\"left\"> Familiarity with test use</td><td align=\"center\">6.9 (2.3)</td></tr><tr><td align=\"left\"> Patient demand to have the test done</td><td align=\"center\">7.0 (1.9)</td></tr><tr><td align=\"left\"> Type of allergic rhinitis (intermittent vs. persistent)</td><td align=\"center\">6.6 (1.9)</td></tr><tr><td align=\"left\"> How well test results relate to symptoms</td><td align=\"center\">7.6 (1.9)</td></tr><tr><td align=\"left\"> Value of testing to my practice</td><td align=\"center\">6.9 (2.3)</td></tr><tr><td align=\"left\">Testing value **</td><td/></tr><tr><td align=\"left\"> Overall value of specific IgE as a diagnostic tool</td><td align=\"center\">3.9 (1.1)</td></tr><tr><td align=\"left\"> Compared to skin testing, usefulness of specific IgE blood testing</td><td align=\"center\">3.9 (1.4)</td></tr><tr><td align=\"left\"> Compared to not testing at all, usefulness of specific IgE blood testing</td><td align=\"center\">4.3 (1.2)</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Testing for allergic disease: Parameters considered and test value. Sample profile used for data collection in the conjoint exercise</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>*Baseline attribute level</p><p>^ap &lt; 0.05; ^bp &lt; 0.10</p><p>Log likelihood = -196.983; Wald Chi square = 94.03; p &lt; 0.0001</p><p>448 observations for 50 individuals</p></table-wrap-foot>", "<table-wrap-foot><p>* Issues – scale = 1 less likely to test, 10 = more likely to test; (measure of internal consistency of items – α = 0.90)</p><p>** Value – scale = 1 not valuable; 6 = highly valuable; (measure of internal consistency of items – α = 0.86)</p></table-wrap-foot>" ]

[]

[ "<media xlink:href=\"1471-2296-9-47-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Trauma is the most common cause of death in people younger than 50 years of age and accounts for more years of life lost than cancer, heart disease, and stroke combined. Injuries cause 5 million deaths every year worldwide (9% of global mortality).[##UREF##0##1##] In Europe alone injuries account for approximately 800,000 deaths (10% of all deaths) and 14% of all disability-adjusted life years (DALY).[##UREF##1##2##] Injuries are an important source of medical costs, economic losses, and immaterial losses. Trauma can therefore be regarded as a neglected epidemic.</p>", "<p>For improving the trauma care specialized trauma centers are designated and specialized trauma care protocols, like the worldwide used ATLS^®guidelines, were developed.[##UREF##2##3##] Because there is a narrow window of opportunity between the moment that a patient deteriorates and actually dies, the ATLS guidelines prioritize care and focus on (potentially) life-threatening injuries rather than distracting but less important injuries. As a consequence a systematic approach of clinical examination and diagnostics is developed to recognize the most life-threatening injuries first. These should be treated immediately and preferably within 'the golden hour'.[##UREF##2##3##]</p>", "<p>The imaging studies most frequently used in trauma patients include conventional X-rays, ultrasonography (FAST), and computed tomography scanning (CT). Although conventional X-rays and ultrasonography are widely used and easily accessible for many institutions, they have a limited sensitivity for injuries such as spine fractures,[##REF##15920400##4##] pulmonary contusion, rib fractures, pneumothoraces or vascular injuries to the mediastinum, [##REF##9790205##5##, ####REF##11740271##6##, ##REF##11450784##7##, ##REF##9333958##8####9333958##8##] and intra-abdominal, pelvic and retroperitoneal injuries.[##REF##16411014##9##,##REF##18203940##10##] Also, the amount of time necessary to obtain an overview of all the injuries is limited.</p>", "<p>Recent improvements in CT technology with respect to image quality and speed have led to an increasingly important role of CT scanning in management of severely injured patients. However, the biggest problem with CT scanning is that this technique is frequently time-consuming due to logistical (location of CT scanner in other departments of the hospital) and technical issues. This implies that CT can only be used in hemodynamically stable patients where time to OR for surgical stabilization is a less critical factor. Furthermore, the fact that the same CT scanner is scheduled for elective patients as well as trauma patients means that an unplanned, prioritized trauma patient will disrupt the scheduled patient care and logistics and will lead to increased waiting times.</p>", "<p>In order to improve patient care and workflow in acute trauma patients, the Academic Medical Center (AMC) in Amsterdam, the Netherlands, has initiated a project together with Siemens Inc. A new and revolutionary concept was developed in which the CT scanner is transported to the patient instead of the patient to the CT scanner. Main feature is a radiolucent trauma resuscitation table and a CT scanner that slides over the patient in the trauma resuscitating room. In addition there are also possibilities for conventional X-ray imaging and ultrasonography. With this concept the most important diagnostic modalities for trauma evaluation are available in the shockroom and CT scanning is possible at any moment during initial trauma evaluation. Furthermore, no further transport and patient transfers are required which can endanger the patient itself during the diagnostic phase (potentially leading to dislodgement of tubes, lines, cables, etc). Overall this concept will likely result in a faster and improved workflow and diagnostic imaging of trauma patients.</p>" ]

[ "<title>Methods/design</title>", "<title>Study objectives</title>", "<p>The primary objective is to prove the beneficial effects of early shockroom CT scanning on trauma patients by comparing the effects of a strategy involving early shockroom CT scanning with a standard diagnostic imaging strategy on patient outcome. In the latter strategy the CT scan is not located in the shockroom, but elsewhere in the hospital. The secondary objectives are to document the impact of introducing shockroom CT-scanning on logistics, capacity utilization, waiting times, economies of scale, substitution patterns, and investments.</p>", "<title>Study design</title>", "<p>The REACT-trial is a prospective, patient-randomized study that will compare the clinical work-up of trauma patients in a setting where the CT scanner is located in the shockroom (AMC) with the standard situation where CT scanning takes place at the Radiology Department (VUmc).</p>", "<title>Setting/Participating centers</title>", "<p>The Trauma Center North-West Netherlands is one of 10 designated Level-I trauma centers in the Netherlands. It is constituted by the 'Vrije Universiteit' medical center (VUmc) and the Academic Medical Center (AMC), which are both located approximately 8 kilometers apart from each other in Amsterdam. Each of these two hospitals, together with the surrounding affiliated hospitals, is responsible for the care of trauma victims in its region (2.7 million inhabitants in total) that are distributed over these hospitals. In both hospitals, patients are evaluated by a multidisciplinary team in the trauma resuscitation room ('shockroom'), which is fully equipped for initial management of trauma patients, including conventional X-rays and ultrasonography.</p>", "<p>The initial evaluation of trauma patients after arrival is according to ATLS guidelines and the same in both hospitals. After the primary survey, standard X-rays (i.e. thorax, pelvis and cervical spine) and sonography will be done according to the ATLS guidelines.</p>", "<p>In the VUmc the CT scanner (64-slice) is located in the Radiology Department on the second floor. This requires transportation of the patient with at least 4 patient transfers from trolley to the CT table and vice versa.</p>", "<p>In the AMC a concept was developed in which the CT scanner is transported to the patient instead of the patient to the CT scanner. Main feature is a radiolucent trauma resuscitation table and a 4-slice CT scanner (SOMATOTOM Sensation 4, Siemens) placed on a rail which enables the scanner to slide over the patient. Because of a mirrored design of a second shockroom that is separated by radiation shielded sliding doors the CT scanner can be transferred over the rails into the second room after the imaging is finished. The first advantage of this design is that no interference is experienced from the CT scanner during trauma resuscitation. Secondly, the design allows simultaneous use of the mirrored trauma rooms, with the sliding CT scanner accessible to both rooms.</p>", "<p>Both trauma resuscitating settings are equipped with a conventional X-ray installation and ultrasound. As a result of the AMC concept no further patient transport or transfers are necessary for obtaining a CT scan and all radiography can be performed in the trauma room. In addition, at any time during trauma resuscitation CT imaging can be performed.</p>", "<title>Endpoints</title>", "<p>The primary outcome criterion used is the number of days spent outside the hospital in the first year following the trauma. This outcome is responsive to differences in mortality (no additional days outside hospital), to differences in hospital stay for the initial admission and to differences in readmission rate.</p>", "<p>The secondary outcome parameters include general health outcome at 6 and 12 months after the shockroom admission (using the EuroQol and HUI-3 questionnaires), morbidity and mortality during the first year following the trauma and various time intervals and process of care parameters of the initial admission (time to intervention, time to active bleed management, ICU and total hospital stay, etc.). Furthermore the radiation dosage is calculated in both strategies based on the actual number and type of radiological examinations related to the initial trauma performed in each patient during the first year.</p>", "<title>Study group</title>", "<p>All acute trauma patients are eligible for inclusion for the REACT trial when transported by the ambulance or helicopter to the AMC or VUmc shockroom according to the current pre-hospital triage system based on: Injury mechanism, Revised Trauma Score (RTS) and presence of traumatic brain injury. These factors determine the level of care that has to be present in the facility to which patients are transported.</p>", "<p>The exclusion criteria for subsequent follow-up and analysis are patients younger than 16 years of age and patients who die during transport to the hospital.</p>", "<p>The start of the study was scheduled for 1-11-2005.</p>", "<title>Randomization</title>", "<p>Randomization will be performed at the \"Meldkamer Ambulancezorg Amsterdam\" (MKA), the organization in charge of the coordination and distribution of ambulances and patients. Randomization will be performed using a computer program on a 1:1 basis with varying block sizes of 8, 12, and 16. Ambulance personnel will receive instructions according to the outcome of the randomization. Each eligible patient involved in a specific accident will be randomized. After each randomization, there is a pre-specified time interval of 1 hour in which eligible patients will be automatically transported to the other trauma center in order to minimize peak pressure in the study centers and guarantee optimal utilization of the two trauma centers. These patients are included in the trial, but are not formally randomized. In extreme cases, prehospital ambulance personnel can decide to waive the outcome of randomization, if they deem that the status of the patient requires the immediate attention of the closest hospital and death is imminent.</p>", "<p>Because the distance between the two hospitals is relatively short (8 km) no significant delay in treatment by patient transport is encountered regardless of the outcome of the randomization.</p>", "<title>Sample size</title>", "<p>Based on the primary outcome criterion for both strategies, it is estimated that the common standard deviation is a total of 12 days. To detect an overall difference of 2 days in the number of days spent outside the hospital within the first year between the two strategies, 562 patients per group are needed for a two-sided significance level of 0.05 with a power of 0.80.</p>", "<p>Based on historical data, we expect around 500 shockroom patients to be admitted on a yearly basis at each of the two participating centers. Therefore, the total number of eligible patients per year would be 1000 patients. We expect that a quarter of these patients will be excluded for various reasons (age &lt; 16 yrs, lost to follow up, etc.) leading to a total of 750 inclusions per year. Consequently, a 1 1/2-year period should be sufficient to include the necessary total number of 1124 (2 × 562) patients.</p>", "<title>Ethics and informed consent</title>", "<p>The research protocol was primarily submitted to both the local Medical Ethics Committee (MEC) of the AMC and the VUmc to be reviewed. Both committees have been accredited to judge studies for the Central Committee on Research Involving Human Subjects and determined that the proposed study is not subject to the Medical Research Involving Human Subjects Act (WMO) and that therefore no further judgment is required for the study. Informed consents are not required from patients.</p>", "<title>Data analysis</title>", "<p>The main analyses of primary and secondary outcomes will be conducted for all randomized patients according to the result of the randomization (intention-to-treat). Additional analyses include:</p>", "<p>(1) Per-protocol analysis excluding patients that are transported to a different hospital rather than the result of the assignment procedure.</p>", "<p>(2) Analysis of included patients treated either in the AMC or the VUmc independent of the randomization through the assignment procedure.</p>", "<p>We will conduct both unadjusted and adjusted analyses. We will use gender, mechanism of trauma (sharp/blunt), initial Glasgow Coma Scale (GCS), RTS score and the presence of intubation to adjust for possible differences in severity of trauma between the AMC and VUmc patients.</p>", "<p>For subgroup analysis the following analyses will be performed:</p>", "<p>Hemodynamically unstable patients (non-responders (SBP &lt; 90) vs. transient responders (SBP &gt; 90 with continuous fluid requirement)); Sharp vs. blunt trauma patients; Patients prehospitally treated by Mobile Medical Teams; Neurotrauma patients; Presence or absence of a seatbelt sign; Torso trauma vs. isolated extremity trauma; Intubated vs. spontaneously breathing.</p>", "<p>For final analysis standard statistical techniques will be used to compare the different outcomes between the two hospitals.</p>" ]

[]

[ "<title>Discussion</title>", "<p>The REACT trial is a multicentered, prospective randomized trial that evaluates the effect of the newly introduced Amsterdam Trauma Workflow concept on trauma care. The main goal of the Amsterdam Trauma Workflow concept is to minimize the total diagnostic work-up time of the initial trauma evaluation by integrating all diagnostic modalities in the trauma resuscitating room. This concept makes it possible to perform CT imaging earlier during the trauma evaluation without the need to transport the patient to the radiology department. This adjustment will likely result in a faster and improved workflow of trauma patients, that leads to a more complete diagnostic workup in the early phases of trauma resuscitation. This could potentially change therapeutic management options and eventually lead to a better outcome in severely injured trauma patients. The direct availability of CT scanning during the entire trauma resuscitation phase could mean that this could become available for even hemodynamically unstable patients</p>", "<p>A second advantage of this concept is the reduction in the number of patient manipulations, patient transfers and transports. Generally, these actions can have the aforementioned, adverse effects, which could expose the already critically ill patients to extra dangers. However, the introduction of the multifunctional radiolucent patient treatment table, that is suitable for resuscitation, conventional diagnostic imaging and CT scanning, minimize these actions and their additional risks.</p>", "<p>While the REACT study design enables us to describe the diagnostic and therapeutic procedures following initial CT scanning on an individual patient level, the REACT trial also gives us the opportunity to evaluate its effect on an institutional level.</p>", "<p>Because of the additional CT scanning capacity that was created by adding the sliding CT scanner that services the two mirrored trauma rooms, logistics for the radiology department will be influenced for both acute (trauma) patients and elective CT scanning. By potentially eliminating the need to reckon with unplanned acute CT imaging, the regular elective CT scans can be planned better and more efficient, possibly leading to a reduction of waiting times and waiting lists. Critically ill patient groups (i.e. trauma patients and patients with intracranial bleedings, acute aneurysms or abdomens, ICU patients, etc.) who need CT scanning can have their total diagnostic work-up completed in the shockroom before transport to their destination of treatment. In some cases the diagnostic work-up can even be completed simultaneously for two patients because of the mirrored shockroom design.</p>", "<p>Furthermore, the REACT study design enables us to describe in detail the diagnostic and therapeutic procedures following initial CT scanning of trauma patients in the shockroom or at the Radiology Department. We may be able to demonstrate a trade-off in the volume and cost of health care use between early detection of injuries and timely therapeutic management on one hand and late detection by additional diagnostic testing and subsequent therapies on the other.</p>", "<p>Another possible institutional effect might be that a shockroom CT scan may be used as an attractive alternative to other imaging procedures or to sequential diagnostic testing strategies in other patient groups (for instance stroke patients, patients with acute abdominal pain, etc), since it remains an all-inclusive multifocal diagnostic modality. As a consequence substitution of diagnostic modalities or changes in patient groups presenting for CT scanning may occur as a result of joint production.</p>", "<p>Finally, the total costs of realizing this concept are of substantial amount and therefore this shockroom design has to be assessed during the study period in a cost-effectiveness analysis.</p>" ]

[ "<title>Conclusion</title>", "<p>The REACT trial is a prospective randomized multicenter trial that compares the effects of a new and revolutionary concept with a sliding CT scanner located in the trauma resuscitating room with a conventional setting, respectively a CT scanner located in the Radiology department. Results are expected early in 2009.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Trauma is a major source of morbidity and mortality, especially in people below the age of 50 years. For the evaluation of trauma patients CT scanning has gained wide acceptance in and provides detailed information on location and severity of injuries. However, CT scanning is frequently time consuming due to logistical (location of CT scanner elsewhere in the hospital) and technical issues. An innovative and unique infrastructural change has been made in the AMC in which the CT scanner is transported to the patient instead of the patient to the CT scanner. As a consequence, early shockroom CT scanning provides an all-inclusive multifocal diagnostic modality that can detect (potentially life-threatening) injuries in an earlier stage, so that therapy can be directed based on these findings.</p>", "<title>Methods/design</title>", "<p>The REACT-trial is a prospective, randomized trial, comparing two Dutch level-1 trauma centers, respectively the VUmc and AMC, with the only difference being the location of the CT scanner (respectively in the Radiology Department and in the shockroom). All trauma patients that are transported to the AMC or VUmc shockroom according to the current prehospital triage system are included. Patients younger than 16 years of age and patients who die during transport are excluded. Randomization will be performed prehospitally.</p>", "<p>Study parameters are the number of days outside the hospital during the first year following the trauma (primary outcome), general health at 6 and 12 months post trauma, mortality and morbidity, and various time intervals during initial evaluation. In addition a cost-effectiveness analysis of this shockroom concept will be performed.</p>", "<p>Regarding primary outcome it is estimated that the common standard deviation of days spent outside of the hospital during the first year following trauma is a total of 12 days. To detect an overall difference of 2 days within the first year between the two strategies, 562 patients per group are needed. (alpha 0.95 and beta 0.80).</p>", "<title>Discussion</title>", "<p>The REACT-trial will provide evidence on the effects of a strategy involving early shockroom CT scanning compared with a standard diagnostic imaging strategy in trauma patients on both patient outcome and operations research.</p>", "<title>Trial registration</title>", "<p>ISRCTN55332315</p>" ]

[ "<title>Abbreviations</title>", "<p>REACT: Randomized study of Early Assessment by CT scanning in Trauma patients, AMC: Academic Medical Center, VUmc: 'Vrije Universiteit' medical center. CT: Computed Tomography, FAST: Focused Assessment with Sonography in Trauma, SBP: systolic blood pressure, HUI-3: Health Utility Index 3, MKA: Meldkamer Ambulancezorg Amsterdam</p>", "<title>Competing interests</title>", "<p>T.P. Saltzherr is a research fellow at the Trauma Unit Department of Surgery, employed by the AMC Medical Research B.V. and supported by a grant from Siemens Medical Solutions, Den Haag, the Netherlands.</p>", "<title>Authors' contributions</title>", "<p>TPS drafted the manuscript. PHPFKJ and JCG co-authored the writing of the manuscript. All other authors participated in the design of the study and are local investigators at the participating centers.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-227X/8/10/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>ZONMW, grant number 3920.0005</p>", "<p>We would like to thank our Advisory board for their input and efforts during the design, preparation and implementation of the trial.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Stuve-Wiedemann syndrome (SWS) is an autosomal recessive disorder characterized by bowing of the long bones and other skeletal anomalies, episodic hyperthermia, and respiratory and feeding distress usually resulting in early death [##UREF##0##1##,##REF##8723080##2##]. Stüve-Wiedemann syndrome belongs to the group of congenital bowing disorders of bone, but corresponds to a specific condition different from camptomelic and kyphomelic dysplasias on the basis of distinctive radiographic manifestations, which include stubby long bones with internal cortical thickening and large metaphyses [##REF##12514358##3##, ####REF##9674906##4##, ##REF##9674905##5##, ##REF##15324311##6####15324311##6##]. In 1998, SWS was merged with another rare skeletal dysplasia, Schwartz-Jample syndrome, type 2. Schwartz-Jampel syndrome (SJS) is a term applied to 2 different autosomal recessive inherited conditions, sometimes termed SJS type I and SJS type II. SJS type I has recognized subtypes, IA and IB, which are similar except that type IB manifests earlier and with greater severity. The most commonly recognized and described type is IA, which exhibits muscle stiffness, mild and largely nonpregressive muscle weakness, and a number of minor morphological abnormalities. In affected patients, problems with motor development frequently become evident during the first year of life. Usually, the characteristic dysmorphic features lead to an early diagnosis, no later than the age of 3 years. Types IB and type II now known to be a separate disease more commonly referred to as Stüve-Wiedmann syndrome [##REF##12514358##3##, ####REF##9674906##4##, ##REF##9674905##5##, ##REF##15324311##6####15324311##6##]. SWS is phenotypically similar to SJS type IA and IB, but in practice we believe that SWS do manifests the abnormal features earlier and the prognosis is unpleasant. Furthermore, in Schwartz-Jampel syndrome type 1, it is true that it is phenotypically similar but genetically it is a distinct disorder caused by mutation in the HSPG2 gene on chromosome 1p36.1-p34. Parental consanguinity in our present patient is highly suggestive of autosomal recessive inheritance. We report what might be the first clinical report of SWS from a consanguineous family in Austria.</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>The clinical phenotype in our current patient plus the detailed radiographic documentation with absence of any biochemical marker in favor of a metabolic disorder was the baseline to establish the diagnosis of SWS. The cardinal features of Stüve-Wiedemann syndrome are joint contractures, bone dysplasia, and small stature. Severe respiratory difficulties and feeding problems are additional problems. Hypotonia rather than stiffness is prominent. Frequent bouts of hyperthermia have been described. A high infant mortality rate is a common association. Chen et al., [##REF##11424139##7##] a case of a child surviving to age 9 years, stated that only 2 patients with long survival had been reported. In addition to problems with bone dysplasia, these children also manifest dysautonomic and neuropathic features, including reduced patellar reflex, lack of corneal reflex, and paradoxical perspiration at low temperatures [##UREF##0##1##, ####REF##8723080##2##, ##REF##12514358##3####12514358##3##].</p>", "<p>Al-Gazali et al. [##REF##12514358##3##] reported 3 children from 2 inbred Arab families with Stüve-Wiedemann syndrome who had survived the first year of life; their ages were 6, 2.8, and 2 years. All exhibited a characteristic phenotype resembling that described by Chen et al. [##REF##11424139##7##] In all 3 children, the skeletal abnormalities progressed to severe bowing of the long bones with prominent joints and severe spinal deformity. All exhibited neurologic symptoms including temperature instability with excessive sweating, reduced pain sensation with repeated injury to the tongue and limbs, absent corneal reflexes, and a smooth tongue. There were also multiple fractures and progressive scoliosis. All 3 children had normal intelligence. Chabrol et al., [##REF##9382147##8##] reported three cases from two consanguineous gypsy families. One case was noted to have hyperaminoaciduria and hepatic failure. Decreased activities of mitochondrial complex I and IV were found in two cases. There are also recurrent episodes of unexplained hyperthermia. Raas-Rothschild et al., [##UREF##1##9##] reported two sibs who died from severe pulmonary hypertension with pulmonary artery wall abnormality.</p>", "<p>The cases of Stüve and Wiedemann [##UREF##0##1##,##REF##8723080##2##] died in the neonatal period. Kozlowski and Tenconi's case [##REF##8723081##10##] was aged three-and-a-half years and was said to have slight developmental delay. The differential diagnosis is camptomelic or kyphomelic dysplasia [##UREF##2##11##]. Siguady et al., [##REF##9823491##12##] reported two fetuses with overlapping features between Stüve-Wiedemann syndrome and the neonatal form of Schwartz-Jampel syndrome. Cormier-Daire et al., [##REF##9674905##5##] report six cases and provides a good review of the condition. Di Rocco et al., [##UREF##3##13##] reported a 13-year-old survivor (and a 3 year old case). They encountered the accumulations of lipid droplets in the muscles of their patients. Although what this means remains unclear and further research might elucidate the correlation. The gene has been mapped to 5p13 at locus D5S418 and mutations have been encountered in the leukemia inhibitory factor receptor (LIFR). Dagoneau et al [##REF##14740318##14##] studied the genetic material of 19 patients who had been diagnosed with either SWS or SJS type II, they found that all patients had null mutations in their LIFR gene at the above-mentioned locus.</p>", "<p>In summary, our current patient presented with congenital contractures, associated with temperature instability and excessive sweating. The latter seems to indicate a form of dysautonomia. Neither the pathophysiological mechanism nor the pathological course in our current patient seems similar to children with metabolic disorders. It is noteworthy to mention that cases of syndromic malformation complex are not uncommon for pediatricians/health care professionals; therefore, they should be appropriately informed on the subject. Their early identification/diagnosis requires adequate medical attention, since they will often be responsible for initial guidance that families receive.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Expressionless face associated with multiple contractures has been encountered in an infant. There is a wide range of misconception regarding the categorization of children with multiple contractures among different pediatric disciplines. The fundamental element in categorizing children with multiple contractures is \"the etiological understanding\". In the absence of concomitant neuromuscular disease, however, the search for other reasons is mandatory. Our present paper signifies the necessity of proper interpretations of unusual clinical and radiographic features.</p>", "<title>Case presentation</title>", "<p>We describe a 3-months-old-infant presented with the phenotypic and the radiographic features consistent with the diagnosis of Stüve-Wiedemann syndrome. We report what might be the first clinical report of Stüve-Wiedemann syndrome from a consanguineous family in Austria.</p>", "<title>Conclusion</title>", "<p>Congenital limitations of the hips in a newborn infant raise the possibility of \" Congenital Hip Dislocation\". As congenital hip dislocation is a dysplastic process. Here further knowledge by the pediatrician and the orthopaedic surgeon is needed. Our present patient appears to constitute a distinct pathological entity consistent with Stüve-Wiedemann syndrome (SWS). Superti-Furga et al, and Cormier-Daire et al, also suggest that Stüve-Wiedemann syndrome and Schwartz-Jampel syndrome type 2 are allelic conditions. We wish to stress that, given the rarity of syndromic malformation complex, our impression is that it is more common than it is reported.</p>" ]

[ "<title>Case presentation</title>", "<p>The child was referred to the orthopaedic department by the pediatrician because of a suspicion of congenital hip dislocation! Referral was done at the age of 7 weeks. He was a product of normal gestation, at birth his growth parameters were around the 10^thpercentile. The mother was a 25-years-old gravida 1 abortus 0 married to a 31-year-old related man (first cousin). At birth respiratory distress syndrome was the major concern.</p>", "<p>Examination showed growth around the 10 Th percentile. Expressionless face associated with typical pursed appearance of the mouth, blepharophimosis, multiple contractures and umbilical hernia (fig ##FIG##0##1##). The child had normal genetalia. Hearing, and vision were normal. All other investigations including an abdominal ultrasound, karyotyping, and metabolic tests, which aimed to test calcium, phosphorus, and vitamin D metabolism, were normal. Plasma carnitine and fatty acids, lactate/pyruvate ratios, and urinary organic acid excretions were assayed and found to be normal. Additional laboratory tests showed normal TSH/T4, a negative Guthrie test and normal karyotype. Search for specific mutations in the LIFR gene on chromosome 5p13 showed negative results as well.</p>", "<p>Skeletal abnormalities include multiple joint contractures, thoracic kyphosis, mild bowing of the long bones, and a valgus deformity of the ankles. On the bases of skeletal survey, skull radiogram showed squared jaw with hypoplastic rami. Chest radiogram showed a narrow upper thoracic cage but with normal heart borders (fig ##FIG##1##2##). Spine radiograph showed platyspondyly and coronal clefts of the vertebral bodies. Lower limb radiograph showed epiphyseal dysplasia of the capital femoral epiphyses, hypoplastic ileae, horizontally dysplastic acetabulae, coxa vara, shortening of the femoral necks, broad femora and tibiae with bilateral but asymmetrical degrees of mild bowing. In addition the angulation of the femora was associated with internal thickening of the cortex. (fig ##FIG##2##3##). Upper limb radiograph showed joint contractures, associated with vertical lucencies in the metaphyseal region, mild bowing and thick cortices, and epiphyseal dysplasia with metaphyseal widening.</p>", "<title>Abbreviations</title>", "<p>SWS: Stüve-Wiedemann syndrome; SJS: Schwartz-Jampel syndrome; HSPG2 gene: heparan sulfate proteoglycan 2; LIFR: Leukemia inhibitory factor receptor alpha.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All of the authors were involved in the clinico-radiographic assessment and finalising the paper. All authors have red and approved the final version of the paper.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the parents for the purpose of publication of the manuscript and figures of their child. A copy of the written consent is available for review by the editor-in-Chief of this journal.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank the parents for their remarkable cooperation.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Proband's photo showed expressionless face associated with typical pursed appearance of the mouth, blepharophimosis, multiple contractures and umbilical hernia.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Anteroposterior chest radiograph Chest radiogram showed a narrow upper thoracic cage (Bell-like) but with normal heart borders</bold>.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Anteroposterior lower limb radiograph showed epiphyseal dysplasia of the capital femoral epiphyses, hypoplastic ileae, horizontally dysplastic acetabulae, coxa vara, shortening of the femoral necks, broad femora and tibiae with bilateral but asymmetrical degrees of mild bowing.</bold> In addition the angulation of the femora was associated with internal thickening of the cortex.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1757-1626-1-121-1\"/>", "<graphic xlink:href=\"1757-1626-1-121-2\"/>", "<graphic xlink:href=\"1757-1626-1-121-3\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Acute aortic dissection results from a tear in the intima and media of the aortic wall, with the subsequent creation of a false lumen in the outer half of the media and elongation of this channel by pulsatile blood flow. Dissection of the aorta is associated with a high degree of morbidity and mortality despite continuing improvements in diagnostic and surgical techniques [##REF##9081132##1##], and hypertension is present as the most common cause in 70–90% of patients with aortic dissection [##UREF##0##2##]. A number of normal daily and athletic activities require isometric or static exercise. Sports such as weightlifting and other high-resistance activities are used by power athletes to gain strength and skeletal muscle bulk. These exercises significantly increase blood pressure, heart rate, myocardial contractility, and cardiac output. Hypertension has long been recognized as an important risk factor for the development of aortic aneurysms and dissections [##REF##9081132##1##,##REF##10696543##3##]. Also, it has been speculated that the very high blood pressure generated during the lifting of weights, particularly with staining accompanied by a Valsalva maneuver, may be the cause of an aortic intimal tear [##REF##10696543##3##]. Pre-participation cardiovascular evaluation of young competitive athletes is warranted on the basis of the available evidence [##REF##15689345##4##]. Patients with predisposing conditions to aortic dissection, including hypertension, should be sturdily encouraged to refrain from weightlifting. We present a case of aortic dissection in a young athlete with a history of hypertension.</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>The cardiovascular system adapts to exercise. Top-level training is often associated with morphological changes in the heart including increases in the left ventricular chamber size, wall thickness, and mass. The increase in the left ventricular mass as a result of training is called\" athletes' heart\" [##REF##10645932##5##]. Morganroth and his colleagues [##REF##1119766##6##] distinguished two different morphological forms of athletes' heart: a strength-trained heart and an endurance-trained heart. According to their theory, athletes involved in endurance training, sports with a high dynamic component like running, are presumed to demonstrate eccentric left ventricular hypertrophy, characterized an unchanged relationship between left ventricular wall thickness and left ventricular radius (i.e. ratio of wall thickness to radius), which means an increased left ventricular chamber size with a proportional increase in wall thickness. On the other hand, strength-trained athletes involved in mainly static or isometric exercise like weightlifting, bodybuilding, and wrestling, are presumed to demonstrate concentric left ventricular hypertrophy, which is characterized by an increased ratio of wall thickness to radius, which means an increased left ventricular wall thickness with an unchanged left ventricular chamber size. In addition to the aforementioned changes, in weightlifters as strength-trained athletes, cardiac output, heart rate, and blood pressure tend to increase. A rapid increase in the systemic arterial blood without a decrease in the peripheral vascular resistance, in combination with aortic medial degeneration, may contribute to the development of the aortic dissection [##REF##2322060##7##]; this is an event that may occur in non-trained weightlifters or those with predisposing factors for aortic dissection, like hypertension, congenital cardiovascular disease (e.g. coarctation of aorta, congenital stenotic aortic valve, and unicuspid and bicuspid aortic valve), supravalvular aortic stenosis, connective tissue disorders (e.g. the Marfan syndrome and familial cystic medial degeneration syndromes), and fibromuscular dysplasia. Also in athletes who have mild-to-moderate aortic enlargement, an increased blood pressure due to heavy weightlifting, raises aortic wall stress to a level that begets aortic dissection [##REF##16847387##8##]. Aortic dissection is a very tragic event because of its high mortality rate of about 32%, and the most common causes of death after aortic dissection involving the ascending aorta include the rupture into the pericardial cavity with resultant tamponade, occlusion of the coronary arteries, and free rupture into the chest or abdomen [##UREF##0##2##]. All athletes must be assessed for predisposing factors for aortic dissection, and all patients should be encouraged to undergo appropriate diagnostic studies like echocardiography and blood pressure monitoring while weightlifting to recognize possible predisposing factors for aortic dissection. Athletes who do have a problem should be encouraged to avoid or limit their exercise or activity by their cardiologist. It is vital that this disastrous event be prevented in young people.</p>" ]

[ "<title>Conclusion</title>", "<p>We strongly advise that athletes with one of the predisposing factors for aortic dissection eschew intense physical exertion. Unfortunately, survival after such dissections is extremely unanticipated because of the lengthy extension of the intimal tear, massive hemorrhage, and organ dysfunction.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Acute aortic dissection can occur at the time of intense physical exertion in strength-trained athletes like weightlifters, bodybuilders, throwers, and wrestlers.</p>", "<p>Rapid rise in blood pressure and history of hypertension are the most common causes of aortic dissection in athletes. It is a very tragic event because of its high mortality rate of about 32% in young patients. We report a case of aortic dissection in a young weightlifter with an extensive intimal tear of the aorta, from the sinus of Valsalva to the abdominal aorta.</p>" ]

[ "<title>Case presentation</title>", "<p>A 37-year-old Iranian man with a history of hypertension and long history of weightlifting was admitted to our hospital complaining of knifelike retrosternal chest pain, which was abrupt while lifting weight, accompanied by severe sweating and palpitation. Distal pulses were weakly palpable. Electrocardiography showed non-sinus arrhythmia, Wolf-Parkinson-White (WPW) syndrome, and Q in lead III and avf. Echocardiography findings were normal left ventricular size with concentric left ventricular hypertrophy (LVH), left ventricular ejection fraction (LVEF) of about 55%, dilated ascending aorta of about 56 mm, and mild mitral regurgitation. In addition, the intimal flap in the ascending aorta was seen collapsed. The diagnosis was obtained by computed tomography (CT) angiography, which showed a typical aspect of type A of Stanford classification of aortic dissection (ascending aorta, transverse arch, and descending thoracic aorta were involved) [fig ##FIG##0##1##]. The intimal tear was located just above the Valsalva sinus running to the abdominal aorta with hemopericardium [fig ##FIG##1##2##, ##FIG##2##3##]. Subsequently, the patient developed cardiac arrest and cardiopulmonary resuscitation (CPR) was performed. He was taken emergently for the surgical replacement of the aortic valve and repair of type I aortic dissection. Femoral artery cannulation, median sternotomy, and right atrial cannulation for total cardiopulmonary bypass (CPB) were carried out. At the opening of the pericardium, there was a typical ascending aneurysm which was extended to the origin of the innominate artery [fig ##FIG##3##4##]. After aortotomy, the entry site of the aortic dissection was identified anteriorly. The dissection was extended into the aortic arch and then into the aortic root. On the other hand, the ascending aorta was fully dissected with an extension of the proximal dissection toward the abdominal aorta. Because of the destruction of the sinus of Valsalva by the dissection, the Bental procedure was performed. The segment of the aorta containing the intimal tear was subsequently resected and replaced with a Dacron graft. Teflon felt was used and attached to the aortic wall with continuous sutures on the outer bound of it. Also, glue was applied to fill the entire space between the dissected fragile layers. CPB and aortic cross-clamp times were 300 and 240 minutes, respectively. After long-run anesthesia and cardiopulmonary bypass, the patient was weaned from CPB and admitted to intensive care unit (ICU) with inotropic support. Twenty-four hours after ICU admission, the patient developed a deep coma with pupils reactive to light, fully dilated left pupil, and no response to painful stimuli. Brain CT scan demonstrated acute infarction in the left cerebral hemisphere, right frontal lobe, brain swelling with midline shift, and subtentorial hernia. The blood pressure was dependent on inotropic support, and the cardiac rhythm was junctional. Cardiac arrest occurred after a few minutes. Unfortunately, CPR was not successful and the patient expired on the first day of operation.</p>", "<title>Abbreviations</title>", "<p> WPW: Wolf-Parkinson-White; CT: Computed tomography; LVH: Left ventricular hypertrophy; LVEF: Left ventricular ejection fraction; ICU: Intensive care unit; CPR: Cardiopulmonary resuscitation; CPB: Cardiopulmonary bypass.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>AK carried out the surgery and was directly involved in the conception, design and drafting of the manuscript. SS participated in the diagnosis and treatment; also gave critical comments on the results. PY collaborated in the design of the study and was directly involved in drafting and revising the manuscript. All the authors read and approved the final manuscript.</p>", "<title>Consent section</title>", "<p>Written informed consent was obtained from the patient's family for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Semicoronal reconstructed CT angiography reveals flap in the ascending aorta and arch (arrow).</bold> The false and true lumens are patent. Hemopericardium is also seen (astrix).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Axial source image of CT angiography reveals the flap in the ascending aorta compatible with type A of Stanford dissection: Arrows are showing the flap in ascending aorta and astrixes are showing hemopericardium.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Axial source image of CT angiography reveals the flap in the descending aorta compatible with type A of Stanford dissection: Arrows are showing the flap in descending aorta.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Axial source image of CT angiography show aneurysmal dilation of ascending aorta along with type A aortic dissection.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1757-1626-1-99-1\"/>", "<graphic xlink:href=\"1757-1626-1-99-2\"/>", "<graphic xlink:href=\"1757-1626-1-99-3\"/>", "<graphic xlink:href=\"1757-1626-1-99-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Extraperitoneal endometriosis, i.e. the presence of ectopic, functional endometrium outside the peritoneal cavity is exceedingly rare. Cutaneous endometriosis is a form of extraperitoneal endometriosis, sometimes associated with previous laparoscopic or open abdominal operative procedures [##REF##16176520##1##]. Diagnostic imaging may be used for accurate preoperative diagnosis and evaluation of the extent of cutaneous endometriosis lesions, but publication of such images in the medical literature has been scarce, due to the rarity of this condition. We present herein two cases of cutaneous endometriosis following cesarean section, both systematically evaluated preoperatively with 2-D ultrasound, power Doppler, and MRI.</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>Cutaneous endometriosis developing on scars of previous operations is a rare condition. Scar or incisional endometriosis is usually confined in superficial layers of the abdominal wall, but it may sometimes infiltrate deeper layers and present in exceptional cases even as a uterocateneous fistula [##REF##14671417##2##]. Various theories have been proposed concerning the etiopathogenesis of endometriosis in general, including retrograde menstruation, metaplasia, and venous or lymphatic dissemination [##REF##10451771##3##,##REF##18288381##4##]. Many patients with scar endometriosis do not have any signs or prior history of peritoneal endometriosis, suggesting that this condition might be probably caused by endometrial cell dissemination into the wound at the time of surgery. Since the proliferative capacity of end-differentiated cells is limited, transfer of endometrial stem cells to incisions of the abdominal wall at the time of uterine surgery, followed by proliferation at the new site, seems to be the most plausible explanation for development of scar endometriosis.</p>", "<p>Incisional endometriosis presents typically as a firm, palpable lump at the site of a surgical scar, usually accompanied by cyclic pain and swelling during menses. Cyclic bleeding may also occur. Cyclic symptoms and signs should alert to clinical diagnosis of endometriosis. Macroscopically, the mass is usually non-discrete, rubbery and often multiloculated, containing chocolate cysts. Differential diagnosis includes hernias, lipomas, hematomas, abscesses, cheloids, suture granulomas, sebaceous cysts, as well as malignant tumors, including desmoid tumors, sarcomas, lymphomas or primary malignancies of the skin and metastatic tumors [##REF##8619458##5##].</p>", "<p>Due to the rarity of incisional endometriosis, there is no data available concerning cost-effectiveness of different diagnostic methods. At a first glance, the simplest and less costly approach would be excisional biopsy followed by histological examination of the lesion, without prior imaging evaluation. However, this may lead to inadequate excision, and subsequently disease recurrence, necessitating re-excision. On the other hand, preoperative evaluation with imaging techniques can facilitate total surgical excision. On 2-D sonography, scar endometriosis lesions may appear as cystic or multicystic, mixed or solid masses, with internal vascularity on power Doppler. Though these findings are not specific [##REF##12528172##6##], 2-D sonography allows preoperative evaluation of the extent of such lesions. If 2D- and Doppler-ultrasound studies seem inadequate, the extent and biologic behaviour can be further evaluated by MR-imaging. T1-weighted MRI shows lesions isodense to muscle, while T2-weighted images show high signal intensity with marked enhancement [##REF##16498086##7##]. Thus, operative resection can be planned accurately and safely, particularly in recurrent and extensive lesions infiltrating deeper layers of the abdominal wall.</p>", "<p>Combined oral contraceptives, progestogen-only therapy and GnRH-analogues have been used in the therapeutic management of cutaneous endometriosis, but recurrence is common after discontinuation of treatment. On the other hand, wide excision of the whole lesion, even if this necessitates fascial excision, leads to permanent cure. Recurrence is rare following surgical treatment, and is usually attributed to inadequate excision [##REF##12781893##8##].</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, use of diagnostic imaging, including 2-D ultrasound, power Doppler sonography and MRI, in the preoperative assessment of suspected scar endometriosis lesions is very helpful for accurate determination of the extent of disease. This approach enhances total surgical excision, which is crucial for definitive diagnosis and avoidance of disease recurrence.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Scar or incisional endometriosis is a rare, often misdiagnosed, pathologic condition of the abdominal wall. Two cases of incisional endometriosis are presented. Both patients presented with atypical cyclic pain and palpable nodules on scars of previous cesarean sections. In both cases, the mass was totally excised, after accurate preoperative evaluation with 2-D ultrasound, power Doppler and MRI. Microscopic examination confirmed the preoperatively presumed diagnosis of cutaneous endometriosis. In cases of suspected scar endometriosis, preoperative diagnostic imaging is valuable in determining the extent of disease, thus enhancing accurate and total excision.</p>" ]

[ "<title>Case presentation</title>", "<title>Case 1</title>", "<p>A 28 year-old white woman, G2P1, presented with atypical cyclic pain on a small, firm lump at the outer margins of the scar of a previous cesarean section, performed five years earlier. Patient history details were as follows: Occupation: housewife; Ethnicity: Greek; Weight 75 Kg; Height: 165 cm; Medical history: one previous cesarean section, otherwise unremarkable; Family history: unremarkable; Patient habits and medications: non-smoker, no alcohol consumption, no current medications. Sonographic examination of the abdominal scar showed a hypoechoic mass, with internal echoes, infiltrating the subcutaneous fat, extending up to the sheath of the rectus abdominis muscle (Figure ##FIG##0##1A##). Power Doppler showed internal vascularity within the lesion (Figure ##FIG##0##1B##). MRI showed that the lesion was isodense to muscle and confirmed its localization in subcutaneous fat tissue (Figure ##FIG##1##2A##). The lesion was removed surgically and diagnosis of endometriosis was confirmed histologically.</p>", "<title>Case 2</title>", "<p>A 29 year-old white woman, G2P1, presented complaining of atypical cyclic pain on the scar of a previous cesarean section, performed six months earlier. Patient history details were as follows: Occupation: Secretary; Ethnicity: Greek; Weight: 65 Kg; Height: 167 cm; Medical history: one previous cesarean section, otherwise unremarkable; Family history: unremarkable; Patient habits and medications: non-smoker, no alcohol consumption, no current medications. On clinical examination, a firm lump was found on the abdominal scar. Ultrasound scan showed a large hypoechoic mass with internal echoes, measuring approximately 10 mm, located at the lateral margin of the scar (Figure ##FIG##0##1C##). Power Doppler sonography showed increased vascularity within the mass (Figure ##FIG##0##1D##). On static MRI the mass appeared isodense to muscle (Figure ##FIG##1##2B## and ##FIG##1##2C##), while T2-weighted imaging showed increased signal-intensity within the lesion. After total surgical excision, histological examination showed that the mass consisted of endometrial tissue and stroma, suggesting cutaneous endometriosis.</p>", "<title>Abbreviations used</title>", "<p>2-D: Two-dimensional; MR(I): Magnetic Resonance (Imaging); G: Gravida; P: para; GnRH: Gonadotropin Releasing Hormone.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>GP conceived the study and participated in patient management acquisition of data, interpretation of data, and was a major contributor in writing the manuscript. JT participated in patient management, acquisition of data, and drafting of the manuscript. MZ revised critically the manuscript adding substantial intellectual content. DA participated in patient management, acquisition of data, and drafting of the manuscript. JB coordinated the study and patient management and revised critically the manuscript. All authors have read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from both patients – in their native language – for publication of this case report and accompanying images. Copies of the written consent are available for review by the Editor-in-Chief of this journal</p>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>2-D and power Doppler sonographic views of scar endometriosis nodules</bold>. Using 7.5 MHz transducers, scar endometriotic lesions appeared hypoechoic, with internal echoes on 2-D ultrasound (A, C), and with internal vascularity on power Doppler (B, D). A and B: Case 1; C and D: Case 2.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>MRI of scar endometriosis nodules</bold>. Endometriotic lesions (arrows) appear isodense to muscle on transverse (A, B) and axial (C) T1-weighted spin-echo MRI. A: Case 1; B and C: Case 2.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1757-1626-1-97-1\"/>", "<graphic xlink:href=\"1757-1626-1-97-2\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[]

[]

[ "<title>Discussion</title>", "<p>Carbon monoxide (CO) is a tasteless, odourless gas resulting from incomplete combustion. While almost certainly under-diagnosed, there are nearly 200 documented serious poisonings every year in the UK, occurring most commonly from house fires, faulty gas heaters and car exhausts [##REF##9924447##1##]. CO has approximately 240 times the affinity of oxygen for binding to haemoglobin, and forms the COHb complex which impairs tissue oxygen delivery, inhibits mitochondrial oxidative phosphorylation, and inactivates cytochrome oxidase [##REF##7966524##2##].</p>", "<p>There is a spectrum of clinical features from headache, nausea, and flu-like symptoms through to coma with hyperventilation, convulsions, pulmonary oedema, myocardial ischaemia and cherry-red skin colouring. Levels of COHb correlate poorly with clinical features, but it is generally accepted that an initial level of greater than 15% suggests significant toxicity.</p>", "<p>Management depends on the severity of the poisoning. The initial aims are removal from the source, and administration of high-flow oxygen. CO elimination has a dependent relationship with the FiO₂: in room air the half-life of COHb is up to 5 hours; with high-flow oxygen and a reservoir mask this reduces to approximately 70 minutes; and hyperbaric oxygen reduces this further to about 25 minutes [##REF##10713010##3##,##REF##4061987##4##].</p>", "<p>Our difficulty in the above case was that the patient almost certainly had undiagnosed COPD, and hence when high-flow oxygen was given – the preferred initial management strategy – the patient retained CO₂and became increasingly obtunded, necessitating a reduction in the FiO₂, and hence prolonging the clearance of carbon monoxide.</p>", "<p>The gold standard treatment for severe CO poisoning is hyperbaric oxygen therapy. This markedly raises the arterial oxygen level, and in COPD patients prone to CO₂retention would clearly cause significant elevation of pCO₂. Furthermore emphysematous bullae may rupture under an elevated pressure, hence COPD is a relative contra-indication to hyperbaric oxygen therapy.</p>", "<p>A search of Pubmed found nothing published on the management of carbon monoxide poisoning in patients with chronic obstructive lung disease, and clearly a careful balance needs to be found between the level of administered oxygen, the patient's pCO₂, and the required rate of clearance of CO.</p>", "<p>We suggest that patients with carbon monoxide poisoning and a significant smoking history – even if not formally diagnosed with COPD – have regular ABG analysis during treatment to ensure that they are not developing a dangerous respiratory acidosis. Carbon dioxide retention in such patients limits the use of uncontrolled high-flow oxygen, and thus in certain circumstances early intubation may need to be considered. The use of hyperbaric oxygen therapy in such patients should be considered only with extreme caution.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>We present the case of a 70 year-old man with carbon monoxide poisoning following a house fire. A significant smoking history and likely underlying chronic lung pathology complicated treatment, as due to symptomatic retention of carbon dioxide we were unable to use high-flow oxygen to facilitate the elimination of carbon monoxide. We suggest that patients with risk factors for obstructive lung disease be monitored extremely carefully during treatment for carbon monoxide toxicity.</p>" ]

[ "<title>Case report</title>", "<p>A 70 year-old retired man presented to the Emergency Department following a house fire. The flat below his had caught fire during the night, awakening the patient and his family. Smoke rose through the floors and windows, and the patient and his wife were exposed to significant smoke inhalation. Following rescue by the fire brigade and initial high-flow oxygen therapy by the ambulance service, the man arrived at hospital drowsy and less responsive than he had been at the scene.</p>", "<p>Past medical history included hypertension, type 2 diabetes, L4/5 disc prolapse. Medications were bendrofluazide, amlodipine, metformin, atorvastatin, and a multivitamin. He denied any allergies. There was no family history of note, and the patient was a non-drinker but had a significant smoking history of at least 20 cigarettes per day for over 50 years, and was a current smoker.</p>", "<p>Examination revealed no evidence of external burns, facial burns, singed nostril hair, hoarseness, stridor, or overt evidence of airway obstruction. However the patient was expectorating carbonaceous sputum. Initial blood pressure was 139/84, pulse 74 beats per minute, and pulse oximeter saturations of 100% on high-flow oxygen. The patient was oriented but drowsy with a GCS of 14/15, losing a point for eye-opening.</p>", "<p>Oxygen was removed, and a subsequent arterial blood gas analysis showed pH 7.4 (NR 7.35–7.45), pO₂10.1 kPa (NR &gt; 10.6), and pCO₂of 5.46 kPa (NR 4.6–6.0). High-flow oxygen at 15 litres/minute with a reservoir bag was recommenced as the patient's pulse oximeter saturations fell to 92% on air. Over the next hour the patient became increasingly difficult to rouse and a repeat arterial blood gas analysis showed a pH of 7.32 and a raised pCO₂of 7.80 kPa. With the substitution of controlled flow oxygen at 0.24 FiO₂the patient rapidly became more alert, and despite persistent oxygen saturations of 94%, suffered no subjective or objective dyspnoea. A later arterial blood gas analysis showed normalisation of the pCO₂level.</p>", "<p>Blood results were unremarkable apart from a COHb level of 9% (NR &lt; 2%), compared with his wife who had no symptomatology or clinical signs, but an initial COHb level of 11%.</p>", "<p>Repeat measurements four hours later showed that the patient's COHb level had dropped to 5%, while his non-smoking wife had a level of only 1%. Both patients were observed overnight and were discharged the following morning with no short-term ill effects of their exposure.</p>", "<title>Abbreviations</title>", "<p>ABG: Arterial blood gas; CO: Carbon monoxide; CO_2: Carbon dioxide; COHb: Carboxy-haemoglobin; COPD: Chronic obstructive pulmonary disease; FiO_2: Fraction of inspired oxygen; GCS: Glasgow coma score; NR: Normal range.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>Case report and discussion written jointly by JMB, WJW and TRAL. All authors have read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Posttraumatic stress disorder (PTSD) was defined as a psychiatric disease in 1980 and included in the third edition of the DSM by the American Psychiatric Association (APA) [##UREF##0##2##]. Considerable advances have been made in the research to understand PTSD physiopathologic and psychopathological mechanisms and to develop possible treatments. At a time when contradictions and questions arise in PTSD research [##REF##17085011##3##, ####REF##17141468##4##, ##REF##17084064##5##, ##REF##17055216##6####17055216##6##], researchers in the area acknowledge the possible conceptual frailty of this diagnosis and search for a more consistent theoretical classification.</p>", "<p>The plethora of terms used in PTSD literature, such as aggression, violence, disaster, catastrophe, barbarism, stressful event and trauma, do not point to a corresponding understanding of the meanings, applications and limits of these constructs. These terms are often vaguely used, meanings change in different studies, and there is a lack of conceptual references to guide their use in scientific literature. Some of the most common expressions define events according to consequences, such as in the case of the word \"stressor\", and not according to the characteristics of that single event [##UREF##1##7##,##UREF##2##8##].</p>", "<p>An initial attempt to undo such terminological confusion is to refer to etymology and to retrace the path of the concept into clinical practice. Rather than to establish definitive positions about this topic, the purpose of this study is to promote a discussion of conceptual questions about PTSD terms. Therefore, this study presents definitions of catastrophe, disaster, trauma, violence and barbarism from a clinical perspective to clarify their scope and limitations.</p>" ]

[]

[]

[ "<title>Discussion</title>", "<title>About the event</title>", "<p>The word disaster has its origin in the Italian word <italic>disastro </italic>(dis + astro, \"bad star\") [##UREF##3##9##], and refers to an event marked by destruction, death, physical injury and human suffering that causes permanent changes to human societies, ecosystems and the environment [##UREF##1##7##]. \"Disasters generate an array of individually and collectively experienced stressors of varying degrees of intensity that interact with multiple characteristics of the person and environment to produce diverse outcomes that evolve over time\" [##REF##16612819##10##].</p>", "<p>Disasters tend to expose unselected populations to trauma, randomly. Within a given community, individuals can be directly, indirectly or remotely exposed to the event. The medical model focuses on specific intervention for each of these groups, aiming to prevention, healing and recovery of PTSD and other psychiatric disorders. On the other hand, the wellness models comprehend disasters from the distress challenge, focusing on restoring homeostasis [##REF##16242154##11##]. Therefore, should disasters survivors be viewed as \"psychologically damaged by the experiences that befell them or was it more appropriate to validate the experience of trauma from a humanistic and existential perspective by viewing their responses as an adaptation to frightening environmental events?\" [##REF##8526234##12##]. These points of view on disaster need not to be in conflict. Taken together, these models constitute a broader perspective, addressing the negative (distress symptoms, disease) and positive effects (resilience and post-traumatic growth) of disaster [##REF##16242154##11##].</p>", "<p>Ecological disasters may also be called catastrophes, events of great proportions usually associated with natural phenomena that cause death and destruction. The origin of <italic>catastrophe </italic>is Greek (<italic>kata + strophein</italic>) and its literal meaning was \"overturn\". According to its definition, it is an event that causes trauma [##UREF##4##13##] due to its capacity to destroy most of a community. Catastrophes are extreme events that cause PTSD in a large number of victims in the affected community, and are easily identified as events that cause physical suffering. Individual traumatic events, however, are only accessed by the healthcare professionals through the patient's narrative. Personal history, trauma impact on psyche, educational level, and other factors that compose the patient's subjective life determine the choice and use of different terms to describe the situation experienced.</p>", "<p>A careful examination of the words used by patients is fundamental to understand the psychological impact of events that may trigger traumatic responses. Situations described as \"catastrophic\" may not necessarily indicate that the situation that the patients experienced was a \"catastrophe\", although it may have an equally devastating psychological representation.</p>", "<p>The event alone has importance to the mental healthcare professional only when it is a situation that can produce psychopathological responses from the patient. The idea of a \"disaster taxonomy\" is based on the principle that there are variable emotional responses that depend on the type of disaster, the degree of personal impact, the size of the group affected, and the geographical and temporal range of the event [##UREF##1##7##].</p>", "<p>The \"disaster taxonomy\" stresses the importance of avoiding overlapping or confusing terms to define events because their different aspects may trigger different psychological responses. The use of an adequate terminology requires the understanding of how a traumatic situation causes and becomes part of a stressful process, which may be divided intro three major stages: 1) environmental input in the form of an event; 2) immediate apprehension of the event; and 3) psychological responses after the event [##UREF##2##8##].</p>", "<p>The first stage is restricted to the event itself, and may be objectively measured in number of victims, degrees in the Richter scale, or square kilometers of affected area. \"Pure\" words, without qualifiers, such as \"event\", \"stimulus\", \"loss\", \"disaster\" or \"catastrophe\" are used for such description. The second stage goes beyond the isolated event and incorporates the initial perceptions of the victim. Words such as \"danger\", \"shock\", \"risk of death\", \"threat\" or \"stressor\" illustrate the interaction between the stimulus and the person that experiences it. The third stage corresponds to the psychological response to the event, and words such as \"mourning\", \"response to stress\" or \"trauma\" are used [##UREF##2##8##]. Intense psychological responses are not always associated with concrete situations; for example, the imminence of a possible terror attack may produce an important effect on psyche and trigger a typical PTSD response.</p>", "<title>Trauma</title>", "<p>The word <italic>trauma</italic>, originally used in medicine, has an Indo-European root with a double meaning: a) to rub, grind, perforate; and b) overcome, to go through [##UREF##4##13##,##UREF##5##14##]. <italic>Trauma </italic>is a violent shock that is capable of producing an impact that the individual cannot resist. Therefore, <italic>trauma </italic>that \"perforates\" is the same that makes \"go through\", which describe the two possible psychic developments seen in a traumatic situation: the development of PTSD or of resilience – the ability to go through trauma and to introject meaning into one's own life.</p>", "<p>The formal recognition of PTSD in 1980 changed the conceptual understanding of <italic>trauma</italic>. In the 19^thCentury, except in the psychoanalytic literature, the word <italic>trauma </italic>referred primarily to wounds or violent tissue rupture and had no psychological connotations. The hypothesis that a terrible event might cause effects other than those merely physical was developed in the 1860's, with the description of the \"Railroad Spinal Syndrome\" by John Eric Erichsen [##REF##8731540##15##]. Since then, a proliferation of descriptive terminologies related to traumatic experiences emerged, many of which pointed to railway accidents or combat experiences, like \"spinal concussion\", \"soldier's heart\", \"traumatic shock\", \"shell shock\", \"battle fatigue\", \"war psychoneurosis\" etc. [##REF##10721399##16##]</p>", "<p>In 1882, Jean-Martin Charcot studied patients whose psychic symptoms appeared after severe trauma, such as train crashes or wars, and served as traumatic triggers in individuals that had a certain inherited predisposition or \"<italic>diáthese</italic>\". Therefore, he described the \"<italic>névrose traumatique\" </italic>or <italic>\"hystérie traumatique\" </italic>to classify these cases. Charcot concluded that a physical trauma could produce emotional disorders [##REF##17064877##17##].</p>", "<p>In <italic>On the psychical mechanism of hysterical phenomena </italic>(1893), Freud expanded on the concept of <italic>traumatic neurosis</italic>. The conceptual fluctuations of the word <italic>trauma </italic>in Freudian works suggest that the relative difficulties to establish this definition are much older than the conceptual confusion observed in PTSD. In his early papers, Freud used <italic>trauma </italic>as a key to explain the etiology of neurosis. From 1897 on, the concept loses importance as the concept of fantasy develops and takes the place previously held by traumatic events. However, the infamy of the First World War brought back the problems of \"traumatic neurosis\" to Freudian works, particularly in <italic>Introduction to psychoanalysis and the war neurosis </italic>(1919) [##UREF##6##18##] and in <italic>Beyond the pleasure principle </italic>(1920) [##UREF##7##19##].</p>", "<p><italic>Trauma </italic>was understood by psychoanalysis as an unspeakable experience, not elaborated, not signified, that was <italic>incorporated </italic>but could not be <italic>introjected</italic>, according to Nicolas Abraham (1919–1975) and Maria Torok (1925–1998) [##UREF##8##20##]. The barrier to symbolic elaboration is what assigns the traumatic quality to experiences. This approach reveals the point of view of psychoanalytical clinical practice: the expansion of the psychic creative and integrative dimensions may be the result of an elaborated, <italic>introjected </italic>trauma. In contrast, the paralyzing expansion of the <italic>incorporated </italic>trauma perpetuates the symptomatic reliving of suffering disconnected from language and, thus, far from the attribution of meaning to experience. Therefore, the way the event is treated or elaborated may become the traumatic element itself [##UREF##9##21##].</p>", "<title>Violence</title>", "<p><italic>Violence </italic>may be understood as the action of force or the act of violation. From Latin, <italic>violentia </italic>carries the broad meaning of behaviors with an origin in <italic>vis </italic>(force, vigor) and refers to \"vehemence; passionate and uncontrolled force.\" Acts of excessive violence may result in the violation of rules, rights and norms, in which cases violence is understood as <italic>violare </italic>(violation, infraction) [##UREF##10##22##]. The definitions that combine the ideas of force and violation may increase the terminological confusion, because some acts of force do not result in the violation of norms, such as boxing fights, and some acts of violation do not require the use of force, such as the violation of human rights.</p>", "<p>Violence may be initially understood according to a minimalist concept (violence as <italic>violentia</italic>), which is restricted to an act that should meet three conditions: deliberate attitude of the perpetrator, physical force, and destructive intent. <italic>Episodic violence </italic>corresponds to this concept and is characterized by the fact that it is direct and perpetrated fast and intermittently as an acute insult to a person's well being by means of a dramatic form of violence.</p>", "<p>On the other side, the comprehensive concept (violence as <italic>violentia</italic>) includes psychic and subjective elements and stresses the victim's perspective. Its standard form is <italic>structural violence</italic>, an indirect form of violence whose norms are established socially and that is defined as a chronic insult to well being that kills or harms people slowly by continuous deprivation of basic human needs [##UREF##10##22##,##UREF##11##23##].</p>", "<p>An example of a comprehensive concept of violence is found in the definition by the World Health Organization (WHO): \"Violence is the intentional use of physical force or power, threatened or real, against oneself, another person, or against a group or community, that either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation\" [##UREF##12##24##]. According to the WHO topology, violence may be self-directed, interpersonal or collective, and perpetrated by means of physical, sexual or psychological attacks, deprivation or neglect.</p>", "<p>The WHO definition validates the concept of violence as an international, and not only local, problem, and prescribes the protection of vulnerable populations. However, the incorporation of the notion of <italic>intention </italic>adds complexity to this concept because intention is not always identifiable in a violent act [##UREF##13##25##]. The restriction of this concept to its intentional-actional aspect reduces the chances of considering the merely psychological dimension of some acts of violence, and invalidates the understanding that there are aggressive attitudes that lack a fully violent character [##REF##12833806##26##].</p>", "<p>The depth and breadth of the WHO definition are adequate to that organization's purposes, which require an ecological model of violence centered on multiple levels. However, when the breadth of what is denoted in a term expands, its descriptive power is retracted [##UREF##14##27##]. A comprehensive definition expands the use of the term \"violence\" to situations that result from economic poverty, social alienation, or political repression.</p>", "<p>The application of this comprehensive concept of violence to PTSD would result in very permissive boundaries for the definition of a phenomenon as violent. Traumatic situations that have social, political or economic origins are beyond the reach of psychiatric and psychological treatments. Moreover, evil-minded individuals could distort the use of this broader sense of the word to claim medical benefits and secondary gains based on this \"happy combination of a vague descriptive content and a negative emotional connotation\" [##UREF##14##27##].</p>", "<p>The concept of violence as force (minimalist conception) was refuted by Hannah Arendt, who established the distinction between power, potency (vigor), force, authority and violence. In the common sense, these terms are usually misunderstood or mistaken because are comprehended as a whole from the aspects of the domination of someone or something over others [##UREF##15##28##, ####UREF##16##29##, ##UREF##17##30####17##30##]. Arendt defines violence based on its merely instrumental property (depersonalization of violence), on the refusal of organicistic metaphors of violence (denaturalization of violence), and through the loss of the magical or demoniac characteristic that are commonly attributed to it (demythification of violence).</p>", "<p>Arendt's theory of violence, although developed in the field of political science, also enriches the clinical care to victims of violence. The idea of denaturalization of violence destroys positivist references and inspires practices that go farther then a merely organicistic or psychologizing understanding of traumatic phenomena.</p>", "<p>The notion of depersonalization of violence adds new meanings to the psychotherapy of domestic violence victims, who usually have ambiguous feelings for the perpetrators, which complicates their psychotherapeutic implication in the process of elaborating trauma. To understand violence by means of its instrumental character and not by personification of evil allows the victims to elaborate on their suffering based on the functions that violence operates in that relationship, and not based on a moral judgment of the aggressor.</p>", "<p>Finally, demythification of violence indicates the \"banalization of evil\" and has clear implications on psychotherapeutic care because a barbarian type of violence is a barrier to the process of understanding the traumatic experience, as will be seen next.</p>", "<title>Barbarism</title>", "<p>The first appearance of the word \"barbarism\", associated with rude, brutal and unintelligible speech, is found in Homer's <italic>Iliad</italic>. This term was used by ancient Greeks to refer to foreign peoples. The term, originally not disqualifying, referred to those that did not understand Greek and pronounced inarticulate and incomprehensible sounds, such as onomatopoeias: \"bar-bar-bar\". Barbarians only became dangerous and culturally inferior enemies after the Greco-Persian Wars (5th Century B.C.). The notion of barbarism as a clear opposition to civilization is assigned to Romans, who borrowed the term \"barbarism\" from the Greek and for the first time raised an insurmountable barrier between <italic>Romans </italic>and <italic>Barbarians </italic>[##UREF##18##31##].</p>", "<p>Romans started using the term not only to describe peoples beyond their borders, but also for those in their own world who did not belong to the Greek-Roman cultural world [##UREF##18##31##]. Therefore, the meanings of barbarism were built in opposition to different understandings of civilization, in the sense of (a) civility; (b) historical and cultural background; or (c) humanity in a moral sense. Therefore, Barbarians were those who lived, respectively, in ancient, lower stages of (a) <italic>socialization; </italic>(b) <italic>culture</italic>; or, more importantly, (c) in a <italic>pre-human </italic>(savage) stage in relation to those that called them barbarians [##UREF##19##32##].</p>", "<p>It is no longer startling that a highly refined and educated civilization may reach the worst of barbarism, such as in Nazi Germany, which used the advancement of their techniques and knowledge to exterminate human beings rationally and in an industrial scale. Therefore, the simple and single definitions of barbarism and civilization as opposites do not exist [##UREF##19##32##]. The term barbarism expresses agreement with the idea of civilization and, therefore, of superior and inferior cultures. Conversely, to accept a relativist position and to deny the concept of barbarism also poses difficulties. This point of view renders individuals enclosed in the specificity of their culture, and, therefore, the existence of universal values is denied. Therefore, those who spouse a relativist position would not be able to fight \"barbarian\" practices because they understand that cultures are equal in their right to express their habits and customs [##UREF##19##32##].</p>", "<p>This dialectical trap may be avoided by defining a culture as barbarian if it lacks structures to recognize the alterity of things, by defining customs as barbarian if their effects deny a specific form of human existence, and by describing individuals as barbarian if they are incapable of tolerating diversity. The meaning of barbarism is more clearly defined when a culture is analyzed in relation to itself, not by classifying as barbarian those who were left out of any civilization process, but by recognizing barbarism when people fall behind, in a peculiarly hideous way, their own civilization even though this civilization has achieved the highest levels of development [##UREF##20##33##].</p>", "<p>In general, terrorist attacks can be considered as one specific form of barbarism, once \"attackers tend to use horrific violence to cause massive destruction and death and to use other tactics (e.g., biological weapons) to terrify the public\" [##REF##18245572##1##], and mostly innocent civilians in nonwar zones. Recent surveys on the impact of international terrorism on mental health points to the important aspect that different forms of violence tend to induce different impacts on mental health [##REF##18245572##1##].</p>", "<p>The terrorism and other barbarian aspects of violence imply a lack of meaning rather than some symbolic construction that \"justifies\" the traumatic event that affected the victims or their relatives. Finding a \"justification\" for violence outlines a symbolic shield against terror, the initial mechanism of assigning meaning to traumatic experiences. Conversely, lack of meaning is the trademark of barbarian violence and an obstacle to the elaboration of trauma and its consequent symbolic integration in the victim's life. This significant gap is filled by the abundance of symptoms that result from the persistence of the traumatic memory.</p>", "<title>Conceptual developments</title>", "<p>The tenth edition of the International Classification of Diseases (ICD-10) and the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) describe similar criteria to diagnose PTSD. According to criterion A of DSM-IV, a diagnosis of PTSD should be made when \"the person has experienced, witnessed, or been confronted with an event or events that involve actual or threatened death or serious injury, or a threat to the physical integrity of oneself or others\" (criterion A1), and whose response to the event \"involved intense fear, helplessness or horror\" (criterion A2) [##UREF##21##34##]. According to the ICD-10 guidelines, \"the patient has been exposed to a stressful event or situation (either short- or long-lasting) of an exceptionally threatening or catastrophic nature, which is likely to cause pervasive distress in almost anyone\" [##UREF##22##35##].</p>", "<p>The historical trajectory of the concept of PTSD, from DSM-III to the revised edition of DSM-IV, attests to \"the centrality of the stressor criterion in the definition of this disorder\" [##REF##11704077##36##]. In the DSM-IV, there is an attempt to objectively define the \"traumatic event\", as it clearly establishes that the stressor is limited to experienced or witnessed situations that necessarily involve <italic>death</italic>, serious <italic>injury </italic>or a threat to <italic>physical integrity</italic>. In regard to the first stage of the process of stress – the isolated environmental input – the criterion A1 indicates a return to the older meaning of the word \"trauma\", which refers exclusively to a <italic>bodily wound</italic>, as originally used in medicine.</p>", "<p>The second stage in the process of stress can be found in criterion A2 of the DSM-IV, and reflects the psychological dimension of trauma through the immediate apprehension of the event by the victim in the form a response of \"intense fear, helplessness or horror.\" Some authors question the restriction of criterion A2 to only these trauma-related emotions, \"when there is recent evidence that both anger with others and shame\" are also \"strong predictors of PTSD symptoms longitudinally\" [##REF##10948489##37##].</p>", "<p>The criterion A1 excludes the situations that do not involve direct physical violence or \"threat to physical integrity\", but that are capable of producing psychopathological responses of reliving, avoidance, and hyperarousal. The point here is not to artificially expand the criterion to include the more questionable dimensions of a broader concept of violence. The purpose is to rectify, from a nosographic perspective, the conclusion that, if an event can be simply characterized as a \"threat\", such threat may be defined not only as physical threat, but also as moral coercion, psychic intimidation, or symbolic coercion. A good example of such is the development of PTSD by some victims of bullying, a type of violence that is perpetrated not necessarily and only by means of threat to physical integrity, but that may occur by means of systematic psychological attacks that take the form of verbal offense, acts with the intent to ridicule in front of others, and social isolation from youth groups with certain physical or psychic characteristics.</p>", "<p>Furthermore, in the context of ongoing terrorist threats, especially after the 9/11 attacks, the presence of widespread posttraumatic stress disorder symptoms among individuals not directly exposed to the attacks was documented and replicated in independent cross-sectional and longitudinal studies [##REF##17516775##38##]. This <italic>indirect exposure</italic>, largely through the media, questions the \"perhaps outdated stimulus-response model\" based on the \"conventional assumptions that a disaster should be defined as local and must be directed experienced to cause psychopathology\" [##REF##17516775##38##].</p>", "<p>The fragility of the ICD-10 approach to the event itself is shown, initially, in the circularity of its definition, once it is based on the response elicited, which leads to a tautology: to develop posttraumatic <italic>stress </italic>disorder, the patient should have \"been exposed to a <italic>stressful </italic>event or situation.\" Besides, the description of the nature of this <italic>stressor </italic>as \"something <italic>exceptionally </italic>threatening or catastrophic\" evokes the conceptual weakness of this criterion rather than is an attempt to outline or characterize the type of event. After all, if the notion of <italic>exceptionality </italic>refers to something that is \"out of the ordinary\" and that \"occurs <italic>beyond the limits of what is usual</italic>, normal, frequent or ordinary\" [##UREF##3##9##], what would these limits be, and by whom would they be established?</p>", "<p>Moreover, this construct becomes even more complex when analyzed according to an individual perspective. A person with PTSD symptoms may have perceived as <italic>exceptionally threatening </italic>a situation that might not cause pervasive distress \"in almost anyone.\" The perspective adopted in the ICD-10 is in disagreement with a decisive factor in clinical practice: for patients that present typical PTSD symptoms, the traumatic factor is not necessarily identified in the reality that they can share, but maybe only in their personal and subjective experiences.</p>", "<p>The conceptual inaccuracy of criterion A of the ICD-10 may also be found in the specification of the nature of the event as \"catastrophic\" or \"threatening\". How to discuss, then, the barbarian forms of violence that are not a catastrophe or do not constitute a direct threat, but that are capable of triggering PTSD? Barbarism may be described as a type of violence that, in some cases, prescinds from the association with \"exceptional threat\" for its perpetration. Barbarism may simply be a paroxysmal form of violence, an act without warning, without threat, whose only objective is destruction and death of another human being.</p>", "<p>Not infrequent are cases of people that get together to perpetrate acts of violence against homeless, black or native people, gays or members of other minorities by ambushing the victims, sometimes when asleep, without any type of previous threat. Because of the barbarian death of one of their members, these minorities may develop chronic hyperarousal, avoidance and intrusive thoughts of situations associated with that barbarism, and, therefore, meet all the criteria for a PTSD diagnosis although they have not concretely experienced a direct threat. In such situations, something that should be perceived as normal by most anyone, such as belonging to a minority group (blacks, natives, gays), is experienced as an \"exceptionally threatening\" situation.</p>", "<p>In the same manner, \"there are now replicated findings that PTSD symptoms related to the September 11, 2001, attacks occurred in large numbers of persons who did not fit the traditional definition of exposure to a traumatic event\" [##REF##17516775##38##]. It is like if individuals were all the time perceiving this \"exceptionally threatening\" overall. Therefore, in face of such considerations, how can a limit be established between what would or would not cause this \"exceptionally threatening\" or this \"pervasive distress in almost anyone\"?</p>", "<p>A careful analysis of the criteria currently used by the APA and WHO psychiatric guidelines shows inaccurate definitions of violence, disaster, catastrophe, trauma and barbarism. Such critical appraisal should inspire new studies to improve diagnostic and therapeutic parameters used in clinical practice.</p>", "<p>In the analysis of the DSM-IV criteria, such improvement should focus on the fact that this classification limits the real event or threat to the <italic>physical aspect </italic>of trauma. According to the considerations above, violence prescinds from force and physical damage, and the psychological dimension of a threat may be the most devastating face of violence. The restriction of this criterion to the minimalist concept of violence may exclude diagnoses and treatment of a significant number of patients with PTSD. At the same time, a broad understanding of violence exceeds the limits of clinical practice, as demonstrated in the discussion of the concept established by the WHO. Between these two concepts, there is an alternative: to include the aspect of psychological violence as one more possible trigger of PTSD without expanding the concept to the point of introducing aspects that are too broad for clinical practice.</p>", "<p>The ICD-10 also shows misconceptions in its criterion A, such as the generalizing definitions discussed above. New definitions of this diagnostic category should necessarily include the \"impossibility of symbolic elaboration\" as a condition for the development of this disorder. This is a dimension that includes the senses of \"trauma\", \"barbarism\" and, many times, \"catastrophe\", and replaces vague expressions such as \"exceptionally threatening.\"</p>", "<p>The difficulty in understanding and elaborating an event adds an important diagnostic value to this criterion because it assigns priority to a person's individual psychic response rather than to the effects found in \"almost anyone.\" This latter expression is not only imprecise, but may also exclude PTSD cases that, although originated in individual situations, may result in psychic sequelae of traumatic characteristics.</p>", "<p>In summary, the aspects discussed may be organized as a blueprint for the changes in criterion A of the diagnostic classifications as follows:</p>", "<p>A) Delayed psychic response to a situation or event (either short- or long-lasting) whose understanding or symbolic elaboration is not possible for the person because of the magnitude of physical or psychological threat or the actual presence of death, injury or severe psychological distress, with an immediate response of intense fear, helplessness, dissociation or horror.</p>", "<title>Final considerations</title>", "<p>The examination of PTSD terminology defined two completely different tasks: the understanding of the meaning of the expressions used by the patient; and the search for terms that translate such expressions into medical language. The \"disaster\" described by the patient may be only an unexpected experience that requires an intense existential implication for which this person does not feel prepared. A situation referred to as \"traumatic\" raises the examiner's interest in obtaining details of the circumstances of the event described because the extension and intensity of the stimulus may reflect differently in psyche. A more severe psychopathological presentation is marked by silence and difficulty in elaboration, which may indicate experiences of severe contact with a form of violence, such as barbarism.</p>", "<p>The purpose of clarifying the terms used in the field of PTSD is to provide a resource for conceptual clarity, terminological precision, and understanding of meaningful nuances of the words used in clinical practice. Patients seen after an experience of imminent death do not need therapists that operate according to a good-versus-evil system, or who assign all evil to the perpetrator and reinforce the patient's role as a victim. These patients have already \"faced death\" and, therefore, therapy should not be conducted through the personalization of violence; it is not the positivist naturalization of violence that provides the theoretical basis for the clinical treatment of PTSD; and, finally, it is not the mythification of violence that will enable society to overcome this phenomenon.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Several terms in the scientific literature about posttraumatic stress disorder are used with different meanings in studies conducted by different authors. Words such as <italic>trauma, violence, catastrophe, disaster </italic>and <italic>barbarism </italic>are often used vaguely or confusingly, and their meanings change in different articles. The lack of conceptual references for these expressions complicates the organization of literature. Furthermore, the absence of clear concepts may be an obstacle to clinical treatment because the use of these words by the patients does not necessarily point to a diagnosis of posttraumatic stress disorder.</p>", "<title>Discussion</title>", "<p>A critical review of scientific literature showed that stress can be divided in stages to facilitate specific terminological adjustments to the event itself, to the subject-event interaction and to psychological responses. Moreover, it demonstrated that the varying concept of trauma expands into fundamental psychotherapeutic definitions and that the meanings of violence associated with barbarism are an obstacle to resilience. Therefore, this study updates the etymological origins and applications of these words, connects them to the expansions of meanings that can be operated in the clinical care of patients with posttraumatic stress disorder, and analyzes them critically according to the criterion A of DSM-IV and ICD-10.</p>", "<title>Summary</title>", "<p>The terminology in the literature about posttraumatic stress disorder includes a plethora of terms whose meanings are not fully understood, and that, therefore, limit this terminology. The analysis of these terms suggested that the transformation of the concept of <italic>trauma </italic>led to a broader understanding of this phenomenon in its psychic dimensions, that a barbarian type of violence constitutes an obstacle to resilience, and that the criterion A of the DSM-IV and ICD-10 shows imprecision and conceptual fragilities.</p>", "<title>Methods</title>", "<p>To develop this debate article, a current specialized literature review was achieved by searching and retrieving the key terms from two major databases: PubMed and PsycINFO. The key terms included \"disaster\", \"catastrophe\", \"barbarism\", \"terrorism\", \"trauma\", \"psychic trauma\" and \"violence\", also in combination with the terms \"PTSD\", \"concept\" and \"conceptual aspects\". The data were captured specially from review articles. The included studies were those mostly identified by the authors as relevant by the presence of a <italic>conceptual approach </italic>in any part of the paper. Researches that relied solely on empirical indicators, like psychopathological, neurobiological or pharmacological aspects, were excluded. The focus here was in conceptual aspects, even when some few empirical studies were included.</p>", "<p>As it was noted a paucity of medical references related to conceptual aspects of these terms, a wider literature needed to be included, including chapters, books and articles proceeded from the Humanities areas. \"Interdisciplinary research is needed in this area to include perspectives from a range of different disciplines\" once that \"to promote public health (...) new dimensions of such interactions and the implications thereof should be pursued in collaboration with researchers from broader areas\" [##REF##18245572##1##].</p>" ]

[ "<title>Summary</title>", "<p>1. The plethora of terms used in PTSD literature does not reflect the understanding of meanings, applications and limits of these concepts.</p>", "<p>2. The \"disaster taxonomy\" indicates event characteristics that may generate different psychic responses and, therefore, requires precise terms to describe the three stages of the process of stress.</p>", "<p>3. Because of changes in the concept of trauma along time, it can now be understood in its integrative or paralyzing psychic dimensions depending on how the traumatic experience is elaborated.</p>", "<p>4. The use of a broad concept of violence in PTSD leads to questions out of the range of psychotherapy, and the barbarian type of violence functions as a barrier to resilience.</p>", "<p>5. The criterion A of the ICD-10 and DSM-IV show conceptual imprecision and fragilities that may have effects on the diagnosis and treatment of victims of violence.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>LLB conceived of the study, performed the literature search, participated in the interpretation and discussion of data, drafted and wrote the manuscript. JPF performed the literature search, participated in the interpretation and discussion of data, coordinated the multiple revisions of the manuscript. MFM conceived of the study, participated in the interpretation of data and coordinated the multiple revisions of the manuscript. JJM participated in the interpretation of data and critically revised the first versions of the manuscript. All authors read and approved the final version of the manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-244X/8/68/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>This study was funded by a grant from the State of São Paulo Research Council, Fapesp (Proc. 04/15039-0), and the Millennium Institute, the National Research Council, CNPq (Proc. 42.122/2005-2). Dr. Jair Mari is a Level I CNPq Researcher.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The ingestion of caustic substances induces a wide range of injuries to the gastrointestinal tract, which can be mild or fatal, or lead to chronic disease [##UREF##0##1##]. Caustic ingestion in children is usually accidental ingestion [##REF##15538587##2##], while ingestion by adults is often due to suicidal intent, and injuries tend to be more severe [##REF##15266217##3##].</p>", "<p>Caustic agents with a pH level &lt;2 or &gt;12 rapidly penetrate layers of the esophagus resulting in necrosis-induced eschar formation in the mucosa that limits deep tissue penetration [##UREF##1##4##]. The extent of tissue destruction depends on the physical form, type, and concentration of corrosive agent, premorbid state of the tissue, contact duration, and amount of substance ingested. Esophageal mucosa is thought to be more resistant to acidic than alkaline substances, as alkaline liquids are often highly viscous and thus persist for a longer duration in the esophageal mucosa [##REF##1728104##5##]. Liquefaction necrosis occurs and serious esophageal injury becomes inevitable once alkaline liquids penetrate deep muscle layers [##UREF##2##6##].</p>", "<p>The gold standard of safely assessing depth, extent of caustic ingestion injury, and appropriate therapeutic regimen is esophagogastroduodenoscopy (EGD). Indications, mucosal injury classification, optimal timing, and the degree of esophageal injuries that necessitate EGD in relation to treatment regimens, however, are matters of debate [##UREF##1##4##, ####REF##1728104##5##, ##UREF##2##6##, ##REF##12869880##7##, ##REF##15557970##8##, ##REF##12172355##9##, ##REF##11175619##10####11175619##10##]. The objective of this study was to report our clinical experience and to evaluate the role of a 6-point EGD classification system of injury in predicting outcomes and guiding therapy in adult patients diagnosed with caustic agent ingestion.</p>" ]

[ "<title>Methods</title>", "<p>A retrospective chart review of 288 adult patients (&gt;18 years of age) who were admitted to Chang Gung Memorial Hospital, Tao-Yuan, Taiwan, for caustic ingestion between June 1999 and July 2006 was conducted. Parameters analysed were age, gender, intent of ingestion, substance ingested and amount, time to expiration, ICU admittance, length of hospital stay, complications, and the severity of mucosal injury as assessed by EGD.</p>", "<p>EGD with a standard upper GI endoscope was performed by experienced physicians within 24 hours of ingestion. Endoscopes used were Olympus GIF XQ-230, GIF Q-240X, and GIF Q-260, with diameters of 9.2 mm, 9.4 mm, and 9.2 mm, respectively (Olympus, Tokyo, Japan). Oral cavity xylocaine spray was used for anaesthesia except in 15 cases, which received ventilation support under general anaesthesia because of respiratory difficulty (n = 11) or unclear consciousness (n = 4). Gentle insufflations and retrovisual methods were performed carefully or avoided in the presence of severe stomach injury. Mucosal damage was graded using a modified endoscopic classification described by Zagar et al [##REF##2032601##11##] (Table ##TAB##0##1##).</p>", "<p>Patients were treated with a proton pump inhibitor or H2 antagonist and were maintained without oral intake until their condition was considered stable. Patients received parenteral nutrition during this period. If infection was suspected, antibiotics (a 1^stgeneration cepholasporin and gentamicin) were administered after blood cultures were obtained. If a patient's condition destablized or respiratory difficulty was encountered, they were transferred to the intensive care unit for further evaluation. After discharge, patients were followed in the outpatient clinic for at least 6 months. Any complications observed during follow-up were recorded. Upper GI complications included bleeding, perforation, and stricture formation. Bleeding was defined as melena, hematemasis, and/or coffee-ground vomitus. Perforation was diagnosed by the presence of free air on a plain chest radiograph. Stricture was defined as dysphagia, symptoms of regurgitation, or difficulty in swallowing with confirmation by endoscopy, esophagogram, and/or upper GI radiography. Systemic complications included renal insufficiency, liver damage, diffuse intravascular coagulation, and hemolysis. Liver damage was defined as an elevation in the serum level of alanine aminotransferase or asparatate aminotransferase greater than 3 times the upper normal limit. Renal insufficiency was defined as a plasma creatinine level of &gt;1.4 mg/dL in the absence of other renal diseases. Criteria for disseminated intravascular coagulation and/or hemolysis were prolonged plasma coagulation time, decreased fibrinogen or antithrombin levels, and decreased platelet count.</p>", "<p>Demographic data were described by mean and standard deviations for normally distributed continuous variables, median and interquartile range for non-normally distributed continuous variables, and frequencies and percentages for categorical variables. Wald's Chi-Square tests adjusted for age obtained by generalized estimation equations were used to evaluate for overall survival and complications over grade of mucosal injury. Data subset was subsequently analyzed using logistic regression. Data were analyzed using SAS 9.0 (SAS Institute Inc, Cary, NC, US), and <italic>P </italic>&lt; 0.05 was considered significant.</p>" ]

[ "<title>Results</title>", "<p>A total of 273 patients consisting of 127 (47%) males and 146 females (53%) with a mean age of 43.77 ± 18.46 were included in our analysis (Table ##TAB##1##2##). One patient attempted suicide twice with different corrosive substance in a 3-month period. Fifteen patients were excluded from analysis as a result of missing data (n = 14) or endoscopy failure due to severe laryngeal edema (n = 1). Ingestion intent was primarily attributed to suicide (n = 194, 71.06%) while 28.94% (n = 79) of the cases were accidental. The amount of ingested substance ranged from 2 ml to 3000 ml and was estimated based on the history given by the patient or family member. Industrial cleaning agents containing lye or other alkaline chemical (ie, caustic soda, drain cleaners, machine cleaners, and deacidification products containing sodium hydroxide or sodium-potassium hydroxide, dishwater detergents) or caustic acids were considered caustic substances. Ingestion of industrial cleaning agents (n = 131, 47.99%) and strong acids (n = 95, 34.80%) comprised the majority of cases. Other caustic substances such as pesticides, caustic food, drugs, and other substances comprised the rest of the cases. Of these, 35.16%, 34.43%, and 30.40% were alkaline, hydrochloric acid, or unidentified acid-based substances, respectively.</p>", "<p>The results of EGD in this study showed that grade 3b injuries were the most common caustic injury (n = 82, 30.04%), followed by grade 2b injuries (n = 62, 22.71%) (Table ##TAB##1##2##). Of the 82 grade 3b patients, the esophagus was inspected in 100% of patients, the stomach was inspected in 98% (80/82), and duodenum was inspected in 84% (69/82). Severe injuries were observed in the stomach (n = 116, 42.50%), the duodenum (n = 120, 43.1%), and the esophagus (n = 71, 26.00%). Age distribution among grades of mucosal injury was significantly different (<italic>P </italic>= 0.0107, Table ##TAB##1##2##) and was subsequently used as an adjusting factor.</p>", "<p>Table ##TAB##2##3## illustrates select variables that influenced caustic injury survival and associated complications compared with the grades of mucosal injury. Overall, the mean hospital stay was 8 days (range 0–90); hospital mortality was 6.59% (18/273); and 29 patients were admitted to the ICU. Deaths occurred from 3 days to 2 months after ingestion of the substance as a result of esophageal perforation (n = 1), tracheal perforation with active bleeding (n = 1), hematemesis with sudden apnea (n = 4), lung cancer (n = 1), or multiple organ failure (n = 11). Seventy-six patients (27.8%) developed GI complications and 20.5% (56/273) of patients developed systematic complications. Stricture formation was the most common complication observed in all patients (n = 66, 24.18%) and patients with grade 3b mucosal injury (n = 44, 53.66%), followed by aspiration pneumonia (n = 31, 11.36% vs. n = 20, 24.39%) and respiratory failure (n = 21, 7.69% vs. n = 16, 19.51%).</p>", "<p>Stricture formation typically occurred 2 weeks after caustic ingestion. Management of the 66 patients with a stricture included gastrojejunostomy (n = 24), dilation with endoscope (n = 21), medical treatment (n = 10), esophagectomy (n = 5), jejunostomy (n = 4), esophago-colonic bypass (n = 1), and nasogastric feeding due to old CVA (n = 1). Of the 21 patients dilated endoscopically, 11 patients required subsequent surgery due to perforation (n = 3, one in the esophagus, two in the pyloric area) and failure of dilation (n = 8). Gastrojejunostomy were performed due to gastric outlet obstruction or EC junction stricture. The time of operation was determined by the patient's symptoms and signs. Fifty-one patients received surgery due to perforation (n = 6) and stricture (n = 34), and 11 patients required surgery after endoscopic dilation. Four deaths (in 51 patients who required surgery) were due to multiple organ failure, sepsis, or hematemesis.</p>", "<p>The majority of complications were observed in patients with grade 3b burns, and these were more likely to result in prolonged hospital stay (n = 13), death (n = 14), and ICU admission (n = 19). Statistical significance was observed in duration of hospital stay, ICU admittance, systematic complications, aspiratory pneumonia, respiratory failure, GI complications, and GI stricture among patients with different grades of mucosal injury (all <italic>P </italic>&lt; 0.05; Table ##TAB##2##3##).</p>", "<p>Table ##TAB##3##4## shows the odds ratio of endoscopic grades 2a versus 2b, and 3a versus 3b among selected variables. Grade 2b mucosal injuries were 2.5 times more likely to result in longer hospital stay (95% CI: 1.32–4.87, <italic>P </italic>&lt; 0.05) than 2a. Other variables analysed did not show a statistically significant difference. Grade 3b mucosal injuries were 2.4 times more likely to result in longer hospital stay (95% CI: 1.25–4.80, <italic>P </italic>&lt; 0.05), and 10.8 times more likely to be admitted to the ICU (95% CI: 2.05–200.39, <italic>P </italic>&lt; 0.05), than grade 3a injuries. Additionally, patients with grade 3b burn injuries were 4.1 times more likely to develop systematic complications (95% CI: 1.55–13.29, <italic>P </italic>&lt; 0.05), 4.07 times more likely to develop GI complications (95% CI: 1.81–9.69, <italic>P </italic>&lt; 0.05) and 3.34 times more likely to develop stricture (95% CI: 1.47–8.09, <italic>P </italic>&lt; 0.05) than those with grade 3a burns.</p>", "<p>Table ##TAB##4##5## shows select variables compared with acid and alkali ingestion. Statistical significance was observed in duration of hospital stay only (<italic>P </italic>= 0.0419).</p>" ]

[ "<title>Discussion</title>", "<p>The results of this study confirm Zargar's endoscopic classification of mucosal injuries post caustic ingestion in relation to clinical outcome. Grade 3b mucosal injury assessed by EGD was a predictor of prolonged duration of hospital stay, ICU admittance, and GI and systematic complications. Over 80% of patients with grade 3 burns develop stricture formation, while one-third of those with grade 2 develop pyloric stenosis, acid regurgitation, and perforation [##REF##2032601##11##, ####REF##2753330##12##, ##REF##1539568##13####1539568##13##]. In our data, only 50% of patients with grade 3 burns developed stricture formation, while 10% of those with grade 2 developed GI complication. Our lower results may be because of the development and use of more effective anti-acid medications (proton pump inhibitors, H2 antagonists) and more aggressive use of nasogastric irrigation to reduced effect of the substance ingested [##UREF##2##6##]. The primary reason for ingestion in our patient population was suicidal intent (71%); thus, the injury produced was generally greater and more extensive than that in individuals who ingest caustic substances out of curiosity or by accident [##REF##4046703##14##].</p>", "<p>Caustic ingestion typically refers to the ingestion of strongly alkaline or acidic household or industrial cleaning products. Alkalis can be found in drain openers, bleaches, toilet bowl cleaners, and detergents containing hydrogen peroxide or sodium hydroxide at concentrations from 4% to 54% [##REF##1728104##5##]. Solid alkaline variants such as crystals or particles adhere to the mucous membrane and increase esophageal injury as a result of prolonged contact with the mucosa [##REF##1728104##5##]. Acid ingestion, which tends to occur less frequently in Western countries (&lt;5%), is more common in countries like Taiwan where hydrochloric acid and sulphuric acid (found in toilet bowl cleaners, antirust compounds, battery fluids, and commercial pesticides) are readily accessible [##REF##12869880##7##].</p>", "<p>Earlier studies have questioned the recommendation of routine endoscopic evaluation of all patients after presumed caustic ingestion [##REF##1586425##15##,##REF##7841737##16##] on the basis that in the absence of symptoms following unintentional ingestion severe injury is unlikely. The tensile strength of healing tissues in the first 3 weeks is low due to an absence of collagen. New collagen formation does not begin until the second week after injury. Thus, it is advocated that endoscopy should be avoided from 5 to 15 days after caustic ingestion [##REF##2032601##11##]. Currently, EGD evaluation within 12 hours and no later than 24 hours after caustic ingestion is considered safe, and may be beneficial up to 96 hours after ingestion [##REF##14618516##17##,##UREF##3##18##]. EGD is not recommended from 2 to 3 days up to 2 weeks after caustic ingestion as a result of wound softening.</p>", "<p>Early classification of caustic substance induced injuries may be beneficial in predicting outcomes [##REF##11932786##19##,##REF##15332026##20##]. Though there are no strict guidelines regarding when endoscopy is indicated, ingestion of larger amounts of corrosives, persistent symptoms, as well as suicidal intention are considered indications for endoscopy in the absence of a third degree burn of the hypopharynx [##REF##10488978##21##,##REF##9001276##22##]. Flexible endoscopy and concurrent endoscopic ultrasound using a high-frequency catheter probe have decreased the rate of perforation that occurs with rigid instruments [##REF##15557970##8##]. This study suggests that patients with mucosal damage exceeding grade 2a are at a higher risk of developing serious complications, while patients with mild mucosal damage have a significantly reduced mortality and morbidity. Death in our patients with grade 2a injury (n = 1) was due to tracheoesophageal fistula, sepsis and acute bleeding; with 2b injuries (n = 2) was lung cancer and sudden apnea, and with 3a injury (n = 1) was hematemesis with sudden apnea. In the patients with grade 2b and 3a injuries, ICU observation and nutritional support may be mandatory if there are any signs of bleeding and the patient experiences abdominal pain, and antibiotics are cautiously recommended in those with lung involvement. Patients with grade 3a lesions may not require immediate surgery [##REF##2032601##11##,##REF##12444992##23##,##REF##16937538##24##].</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, the results of this study indicate that patients with findings of grade 3b burns on endoscopy have high the risk of perforation and complications. Endoscopy done within 12 hours and no later than 24 hours following caustic ingestion to classify mucosal injury subsequent to caustic ingestion is useful to determine the severity of injury, particularly in suicidal cases, and thus helpful in predicting outcomes. A 6-point grading system of mucosal injury, rather than a 4- or 5-point system is useful for predicting immediate and long-term complications, and guiding appropriate therapy.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The ingestion of caustic substances induces an extensive spectrum of injuries to the aerodigestive tract which include extensive necrosis and perforation of the esophagus and stomach. The gold standard of safely assessing depth, extent of injury, and appropriate therapeutic regimen is esophagogastroduodenoscopy (EGD). The objective of this study was to report our clinical experience and to evaluate the role of a 6-point EGD classification system of injury in predicting outcomes in adult patients diagnosed with caustic agent ingestion.</p>", "<title>Methods</title>", "<p>The study was a retrospective medical chart review from 273 patients admitted to the Chang Gung Memorial Hospital in Tao-Yuan, Taiwan between June 1999 and July 2006 for treatment of caustic ingestion. The patients underwent EGD within 24 hours of admission and mucosal damage was graded using Zagar's modified endoscopic classification scheme. After treatment, patients were followed in the outpatient clinic for a minimum of 6 months.</p>", "<title>Results</title>", "<p>A total of 273 patients were included for analysis. Grade 3b injury was the most common caustic injury (n = 82, 30.03%), followed by grade 2b injuries (n = 62, 22.71%). Stricture was the most common complication (n = 66, 24.18%), followed by aspiration pneumonia (n = 31, 11.36%), and respiratory failure (n = 21, 7.69%). Compared to grade 3a mucosal injury, grade 3b mucosal injuries were at greater risk of prolonged hospital stay (odds ratio [OR]: 2.44; 95% confidence interval [CI]: 1.25–4.80), ICU admission (OR: 10.82; 95% CI: 2.05–200.39), and gastrointestinal (OR: 4.15; 95% CI: 1.55–13.29) and systemic complications (OR: 4.07; 95% CI: 1.81–14.07).</p>", "<title>Conclusion</title>", "<p>In patients with caustic ingestion, EGD should be performed within 12 to 24 hours and categorized according to a 6-point scale. Patients with grade 3b burns identified on endoscopy have high rates of morbidity. The 6-point scale is useful for predicting immediate and long-term complications, and guiding appropriate therapy.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>C-LC and C-HL carried out the molecular genetic studies, participated in the sequence alignment and drafted the manuscript. J-HT`and Y-YC carried out the immunoassays. P-CC participated in the sequence alignment. N-JL participated in the design of the study and performed the statistical analysis. H-TC conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-230X/8/31/prepub\"/></p>" ]

[]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Zargar's grading classification of mucosal injury caused by ingestion of caustic substances</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">Grade 0</td><td align=\"left\">Normal examination</td></tr><tr><td align=\"left\">Grade 1</td><td align=\"left\">edema and hypermia of the mucosa</td></tr><tr><td align=\"left\">Grade 2a</td><td align=\"left\">Superficial ulceration, erosions, friability, blisters, exudates, hemorrhages, whitish membranes</td></tr><tr><td align=\"left\">Grade 2b</td><td align=\"left\">Grade 2a plus deep discrete or circumferential ulcerations</td></tr><tr><td align=\"left\">Grade 3a</td><td align=\"left\">Small scattered areas of multiple ulceration and areas of necrosis with brown-black or greyish discoloration</td></tr><tr><td align=\"left\">Grade 3b</td><td align=\"left\">Extensive necrosis</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Patient demographic features and caustic ingestion characteristics by endoscopic grade of mucosal injury</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Variables</bold></td><td align=\"left\"><bold>Overall</bold></td><td align=\"center\" colspan=\"7\"><bold>Endoscopic Grade</bold></td></tr><tr><td/><td align=\"left\"><bold>(n = 273)</bold></td><td colspan=\"7\"/></tr><tr><td/><td/><td colspan=\"7\"><hr/></td></tr><tr><td/><td/><td align=\"left\"><bold>0</bold></td><td align=\"left\"><bold>1</bold></td><td align=\"left\"><bold>2a</bold></td><td align=\"left\"><bold>2b</bold></td><td align=\"left\"><bold>3a</bold></td><td align=\"left\"><bold>3b</bold></td><td align=\"left\"><bold><italic>P</italic></bold></td></tr><tr><td/><td/><td align=\"left\"><bold>(n = 3)</bold></td><td align=\"left\"><bold>(n = 31)</bold></td><td align=\"left\"><bold>(n = 56)</bold></td><td align=\"left\"><bold>(n = 62)</bold></td><td align=\"left\"><bold>(n = 39)</bold></td><td align=\"left\"><bold>(n = 82)</bold></td><td/></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">43.77 ± 18.46</td><td align=\"left\">37.00 ± 27.78</td><td align=\"left\">40.45 ± 15.54</td><td align=\"left\">42.21 ± 18.96</td><td align=\"left\">40.92 ± 16.72</td><td align=\"left\">44.10 ± 17.78</td><td align=\"left\">48.32 ± 19.94</td><td align=\"left\">0.0107*</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">127 (46.52)</td><td align=\"left\">3 (100)</td><td align=\"left\">16 (5.93)</td><td align=\"left\">31 (11.48)</td><td align=\"left\">26 (9.63)</td><td align=\"left\">16 (5.93)</td><td align=\"left\">35 (12.96)</td><td align=\"left\">0.1534</td></tr><tr><td align=\"left\">Accidental Ingestion</td><td align=\"left\">79 (28.94)</td><td align=\"left\">1 (33.33)</td><td align=\"left\">10 (32.26)</td><td align=\"left\">19 (33.93)</td><td align=\"left\">14 (22.58)</td><td align=\"left\">15 (38.46)</td><td align=\"left\">20 (24.39)</td><td align=\"left\">0.3820</td></tr><tr><td align=\"left\">Class of Substance</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Alkaline</td><td align=\"left\">96 (35.16)</td><td align=\"left\">3 (100)</td><td align=\"left\">9 (29.03)</td><td align=\"left\">22 (39.29)</td><td align=\"left\">24 (38.71)</td><td align=\"left\">13 (33.33)</td><td align=\"left\">25 (30.49)</td><td align=\"left\">0.5302</td></tr><tr><td align=\"left\"> Acid</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> HCL</td><td align=\"left\">94 (34.43)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">12 (38.71)</td><td align=\"left\">13 (23.21)</td><td align=\"left\">23 (37.10)</td><td align=\"left\">11 (28.21)</td><td align=\"left\">35 (42.68)</td><td align=\"left\">0.1498</td></tr><tr><td align=\"left\"> Other Acid</td><td align=\"left\">83 (30.40)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">10 (32.26)</td><td align=\"left\">21 (37.50)</td><td align=\"left\">15 (24.19)</td><td align=\"left\">15 (38.46)</td><td align=\"left\">22 (26.83)</td><td align=\"left\">0.4086</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Type of Substance</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Industrial cleaning</td><td align=\"left\">131 (47.99)</td><td align=\"left\">2 (66.67)</td><td align=\"left\">15 (48.39)</td><td align=\"left\">26 (46.43)</td><td align=\"left\">28 (45.16)</td><td align=\"left\">18 (46.15)</td><td align=\"left\">42 (51.22)</td><td align=\"left\">0.9574</td></tr><tr><td align=\"left\"> Drug</td><td align=\"left\">3 (1.10)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">2 (3.57)</td><td align=\"left\">1 (1.61)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">0.2862</td></tr><tr><td align=\"left\"> Pesticide</td><td align=\"left\">13 (4.76)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">1 (3.23)</td><td align=\"left\">5 (8.93)</td><td align=\"left\">3 (4.84)</td><td align=\"left\">4 (10.26)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">0.0194*</td></tr><tr><td align=\"left\"> Strong acid</td><td align=\"left\">95 (34.80)</td><td align=\"left\">1 (33.33)</td><td align=\"left\">11 (35.48)</td><td align=\"left\">15 (26.79)</td><td align=\"left\">24 (38.71)</td><td align=\"left\">14 (35.90)</td><td align=\"left\">30 (36.59)</td><td align=\"left\">0.7028</td></tr><tr><td align=\"left\"> Food</td><td align=\"left\">12 (4.40)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">2 (6.45)</td><td align=\"left\">2 (3.57)</td><td align=\"left\">2 (3.23)</td><td align=\"left\">2 (5.13)</td><td align=\"left\">4 (4.88)</td><td align=\"left\">0.9265</td></tr><tr><td align=\"left\"> Others</td><td align=\"left\">19 (6.96)</td><td align=\"left\">0 (0.00)</td><td align=\"left\">2 (6.45)</td><td align=\"left\">6 (10.71)</td><td align=\"left\">4 (6.45)</td><td align=\"left\">1 (2.56)</td><td align=\"left\">6(7.32)</td><td align=\"left\">0.7013</td></tr><tr><td align=\"left\">Package Volume (ml)</td><td align=\"left\">100 (2–3000)</td><td align=\"left\">20 (10–100)</td><td align=\"left\">50 (30–100)</td><td align=\"left\">100 (35–150)</td><td align=\"left\">100 (50–150)</td><td align=\"left\">100 (50–120)</td><td align=\"left\">100 (50–200)</td><td align=\"left\">0.4423</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Select parameters compared with endoscopic grade of mucosal injury</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Variables</bold></td><td align=\"center\"><bold>Overall</bold><break/><bold> (n = 273)</bold></td><td align=\"center\" colspan=\"7\"><bold>Endoscopic Grade</bold></td></tr><tr><td/><td/><td colspan=\"7\"><hr/></td></tr><tr><td/><td/><td align=\"center\"><bold>0</bold><break/><bold> (n = 3)</bold></td><td align=\"center\"><bold>1 </bold><break/><bold>(n = 31)</bold></td><td align=\"center\"><bold>2a </bold><break/><bold>(n = 56)</bold></td><td align=\"center\"><bold>2b </bold><break/><bold>(n = 62)</bold></td><td align=\"center\"><bold>3a </bold><break/><bold>(n = 39)</bold></td><td align=\"center\"><bold>3b </bold><break/><bold>(n = 82)</bold></td><td align=\"center\"><bold><italic>P</italic></bold>^†</td></tr></thead><tbody><tr><td align=\"left\">Hospital Stay (days)</td><td align=\"center\">8 (0, 90)</td><td align=\"center\">4 (3, 10)</td><td align=\"center\">2 (1, 51)</td><td align=\"center\">4.5 (0, 87)</td><td align=\"center\">7 (2, 44)</td><td align=\"center\">9 (0, 33)</td><td align=\"center\">13 (0, 90)</td><td align=\"center\">0.0147<bold>*</bold></td></tr><tr><td align=\"left\">Expired</td><td align=\"center\">18 (6.59)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">2 (3.23)</td><td align=\"center\">1 (2.56)</td><td align=\"center\">14 (17.07)</td><td align=\"center\">0.0648</td></tr><tr><td align=\"left\">Time to Expired (days)</td><td align=\"center\">15.5 (3, 56)</td><td align=\"center\">NA</td><td align=\"center\">NA</td><td align=\"center\">11 (11, 11)</td><td align=\"center\">16 (15, 32)</td><td align=\"center\">16 (16, 16)</td><td align=\"center\">15 (3, 56)</td><td align=\"center\">--</td></tr><tr><td align=\"left\">ICU Admission</td><td align=\"center\">29 (10.62)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">2 (6.45)</td><td align=\"center\">2 (3.57)</td><td align=\"center\">5 (8.06)</td><td align=\"center\">1 (2.56)</td><td align=\"center\">19 (23.17)</td><td align=\"center\">0.0244<bold>*</bold></td></tr><tr><td align=\"left\">Systemic Complication</td><td align=\"center\">56 (20.51)</td><td align=\"center\">1 (33.33)</td><td align=\"center\">3 (9.68)</td><td align=\"center\">4 (7.14)</td><td align=\"center\">11 (17.74)</td><td align=\"center\">5 (12.82)</td><td align=\"center\">32 (39.02)</td><td align=\"center\">0.0111<bold>*</bold></td></tr><tr><td align=\"left\"> Aspiration Pneumonia</td><td align=\"center\">31 (11.36)</td><td align=\"center\">1 (33.33)</td><td align=\"center\">2 (6.45)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">4 (6.45)</td><td align=\"center\">3 (7.69)</td><td align=\"center\">20 (24.39)</td><td align=\"center\">0.0068<bold>*</bold></td></tr><tr><td align=\"left\"> Respiratory Failure</td><td align=\"center\">21 (7.69)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">2 (6.45)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">2 (3.23)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">16 (19.51)</td><td align=\"center\">0.0023<bold>*</bold></td></tr><tr><td align=\"left\"> DIC</td><td align=\"center\">10 (3.67)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">1 (1.61)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">8 (9.76)</td><td align=\"center\">0.1524</td></tr><tr><td align=\"left\"> Hepatic</td><td align=\"center\">10 (3.67)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">4 (6.45)</td><td align=\"center\">2 (5.13)</td><td align=\"center\">3 (3.66)</td><td align=\"center\">0.6841</td></tr><tr><td align=\"left\"> Renal</td><td align=\"center\">7 (2.56)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">1 (1.61)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">5 (6.10)</td><td align=\"center\">0.4300</td></tr><tr><td align=\"left\">Gastrointestinal Complication</td><td align=\"center\">76 (27.84)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">4 (7.14)</td><td align=\"center\">9 (14.52)</td><td align=\"center\">12 (30.77)</td><td align=\"center\">51 (62.20)</td><td align=\"center\">&lt;0.0001<bold>*</bold></td></tr><tr><td align=\"left\"> Stricture</td><td align=\"center\">66 (24.18)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">2 (3.57)</td><td align=\"center\">9 (14.52)</td><td align=\"center\">11 (28.21)</td><td align=\"center\">44 (53.66)</td><td align=\"center\">&lt;0.0001<bold>*</bold></td></tr><tr><td align=\"left\"> Bleeding</td><td align=\"center\">13 (4.76)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">2 (3.57)</td><td align=\"center\">1 (1.61)</td><td align=\"center\">2 (5.13)</td><td align=\"center\">8 (9.76)</td><td align=\"center\">0.3656</td></tr><tr><td align=\"left\"> Perforation</td><td align=\"center\">6 (2.20)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">5 (6.10)</td><td align=\"center\">0.2306</td></tr><tr><td align=\"left\"> Fistula</td><td align=\"center\">2 (0.73)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.79)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">0 (0.0)</td><td align=\"center\">1 (1.22)</td><td align=\"center\">0.6302</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Select parameters and odds ratio of endoscopic grade 2a versus 2b, 3a versus 3b</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Variables</bold></td><td align=\"center\"><bold>Endoscopic Grading </bold><break/><bold>2a vs. 2b </bold><break/><bold>OR (95% CI)</bold></td><td align=\"center\"><bold><italic>P</italic></bold></td><td align=\"center\"><bold>Endoscopic Grading </bold><break/><bold>3a vs.3b </bold><break/><bold>OR (95% CI)</bold></td><td align=\"center\"><bold><italic>P</italic></bold></td></tr></thead><tbody><tr><td align=\"left\">Median Hospital Stay (days)</td><td align=\"center\">2.52 (1.32, 4.87)</td><td align=\"center\">0.0052*</td><td align=\"center\">2.44 (1.25, 4.80)</td><td align=\"center\">0.0102*</td></tr><tr><td align=\"left\">Expired (days)</td><td align=\"center\">1.88 (0.17, 41.13)</td><td align=\"center\">0.6124</td><td align=\"center\">7.17 (1.32, 133.49)</td><td align=\"center\">0.0640</td></tr><tr><td align=\"left\">ICU Admission</td><td align=\"center\">2.37 (0.49, 17.02)</td><td align=\"center\">0.3159</td><td align=\"center\">10.82 (2.05, 200.39)</td><td align=\"center\">0.0241*</td></tr><tr><td align=\"left\">Systemic Complication</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Overall</td><td align=\"center\">2.89 (0.92, 11.03)</td><td align=\"center\">0.0871</td><td align=\"center\">4.15 (1.55, 13.29)</td><td align=\"center\">0.0083*</td></tr><tr><td align=\"left\"> Aspiratory Pneumonia</td><td align=\"center\">4.12 (0.57, 83.15)</td><td align=\"center\">0.2163</td><td align=\"center\">3.58 (1.10, 16.22)</td><td align=\"center\">0.0553</td></tr><tr><td align=\"left\"> Respiratory Failure</td><td align=\"center\">1.77 (0.16, 38.89)</td><td align=\"center\">0.6453</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"left\"> DIC</td><td align=\"center\">0.91 (0.04, 23.27)</td><td align=\"center\">0.9443</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"left\"> Hepatic</td><td align=\"center\">3.74 (0.53, 74.44)</td><td align=\"center\">0.2448</td><td align=\"center\">0.82 (0.13, 6.48)</td><td align=\"center\">0.8280</td></tr><tr><td align=\"left\"> Renal</td><td align=\"center\">0.95 (0.04, 24.54)</td><td align=\"center\">0.9710</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"left\">Gastrointestinal Complication</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Overall</td><td align=\"center\">2.10 (0.66, 8.47)</td><td align=\"center\">0.2183</td><td align=\"center\">4.07 (1.81, 9.69)</td><td align=\"center\">0.0010*</td></tr><tr><td align=\"left\"> Stricture</td><td align=\"center\">4.56 (1.11, 30.86)</td><td align=\"center\">0.0596</td><td align=\"center\">3.34 (1.47, 8.09)</td><td align=\"center\">0.0053*</td></tr><tr><td align=\"left\"> Bleeding</td><td align=\"center\">0.41 (0.02, 4.50)</td><td align=\"center\">0.4794</td><td align=\"center\">2.05 (0.48, 14.07)</td><td align=\"center\">0.3818</td></tr><tr><td align=\"left\"> Perforation</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"left\"> Fistula</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Select parameters compared with alkali and acid ingestion groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Variables</bold></td><td align=\"center\"><bold>Alkali</bold><break/><bold> (n = 96)</bold></td><td align=\"center\" colspan=\"2\"><bold>Acid</bold></td><td align=\"center\"><bold><italic>P</italic></bold>^†</td></tr><tr><td/><td/><td colspan=\"2\"><hr/></td><td/></tr><tr><td/><td/><td align=\"center\"><bold>HCL </bold><break/><bold>(n = 94)</bold></td><td align=\"center\"><bold>Other acid </bold><break/><bold>(n = 83)</bold></td><td/></tr></thead><tbody><tr><td align=\"left\">Hospital Stay (days)</td><td align=\"center\">8 (4,16)</td><td align=\"center\">8 (3,14)</td><td align=\"center\">7 (3,13)</td><td align=\"center\">0.0419*</td></tr><tr><td align=\"left\">Expired</td><td align=\"center\">6 (6.25)</td><td align=\"center\">18 (6.59)</td><td align=\"center\">7(8.43)</td><td align=\"center\">0.8073</td></tr><tr><td align=\"left\">Time to Expired (days)</td><td align=\"center\">15 (11–16)</td><td align=\"center\">15.5 (11–23)</td><td align=\"center\">22 (13–32)</td><td align=\"center\">--</td></tr><tr><td align=\"left\">ICU Admission</td><td align=\"center\">12 (12.50)</td><td align=\"center\">29 (10.62)</td><td align=\"center\">8 (9.64)</td><td align=\"center\">0.5074</td></tr><tr><td align=\"left\">Systemic Complication</td><td align=\"center\">27 (28.13)</td><td align=\"center\">56 (20.51)</td><td align=\"center\">13 (15.66)</td><td align=\"center\">0.0525</td></tr><tr><td align=\"left\"> Aspiration Pneumonia</td><td align=\"center\">13 (13.54)</td><td align=\"center\">31 (11.36)</td><td align=\"center\">8 (9.64)</td><td align=\"center\">0.5188</td></tr><tr><td align=\"left\"> Respiratory Failure</td><td align=\"center\">10 (10.42)</td><td align=\"center\">21 (7.69)</td><td align=\"center\">6 (7.23)</td><td align=\"center\">0.1874</td></tr><tr><td align=\"left\"> DIC</td><td align=\"center\">4 (4.17)</td><td align=\"center\">10 (3.66)</td><td align=\"center\">4 (4.82)</td><td align=\"center\">0.4754</td></tr><tr><td align=\"left\"> Hepatic</td><td align=\"center\">7 (7.29)</td><td align=\"center\">10 (3.66)</td><td align=\"center\">1 (1.20)</td><td align=\"center\">0.0511</td></tr><tr><td align=\"left\"> Renal</td><td align=\"center\">3 (3.13)</td><td align=\"center\">7 (2.56)</td><td align=\"center\">2 (2.41)</td><td align=\"center\">0.6618</td></tr><tr><td align=\"left\">GI Complication</td><td align=\"center\">36 (37.50)</td><td align=\"center\">76 (27.84)</td><td align=\"center\">15 (18.07)</td><td align=\"center\">0.0818</td></tr><tr><td align=\"left\"> Stricture</td><td align=\"center\">31 (32.29)</td><td align=\"center\">66 (27.84)</td><td align=\"center\">12 (14.46)</td><td align=\"center\">0.1855</td></tr><tr><td align=\"left\"> Bleeding</td><td align=\"center\">7 (7.29)</td><td align=\"center\">13 (4.76)</td><td align=\"center\">3 (3.61)</td><td align=\"center\">0.1776</td></tr><tr><td align=\"left\"> Perforation</td><td align=\"center\">4 (4.17)</td><td align=\"center\">6 (2.20)</td><td align=\"center\">2 (2.41)</td><td align=\"center\">0.0728</td></tr><tr><td align=\"left\"> Fistula</td><td align=\"center\">1 (1.04)</td><td align=\"center\">2 (0.73)</td><td align=\"center\">1 (1.20)</td><td align=\"center\">0.4492</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>* <italic>P </italic>&lt; 0.05 statistical significance</p><p>Data presented as median (range) or N (%), endoscopic grade 0 is not included in the comparison for small contribution and possible confounding</p></table-wrap-foot>", "<table-wrap-foot><p>^†Wald's Chi-Square test</p><p>*<italic>P </italic>&lt; 0.05 statistical significance</p><p>Data presented as median (range) or number (%). Endoscopic grade 0 is not included in the comparison secondary to small contribution.</p></table-wrap-foot>", "<table-wrap-foot><p>* <italic>P </italic>&lt; 0.05 indicates statistical significance.</p></table-wrap-foot>", "<table-wrap-foot><p>^†Wald's Chi-Square test</p><p>* <italic>P </italic>&lt; 0.05 statistical significance</p><p>Data presented as median (range) or number (%).</p></table-wrap-foot>" ]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Gastroesophageal reflux disease (GERD) is a common disorder caused by backflow of stomach contents into the esophagus. As it can cause a wide range of clinical symptoms and potentially serious complications, the epidemiology of GERD has been a subject of much interest in recent years. GERD is frequently diagnosed on the basis of symptoms alone, with the criterion for diagnosis in clinical practice being when reflux symptoms become troublesome to the patient [##REF##16928254##1##]. However, for epidemiological studies, a simple symptom threshold is required to identify those who have GERD. In many studies, this threshold is defined as at least weekly reflux symptoms [##REF##15831922##2##]. GERD is common in the West, with a prevalence of about 10–20%, but the prevalence in Asia is generally lower at approximately 5% [##REF##15831922##2##]. The prevalence of GERD is, however, thought to be increasing [##REF##17142109##3##], with trends in Asia attracting particular interest [##REF##15324383##4##]. There have been few high quality, population-based epidemiological surveys of GERD in Asia, particularly in China [##REF##16616342##5##]. A number of methodological challenges associated with studying the epidemiology of GERD in this region may have contributed to this paucity.</p>", "<p>To identify reflux symptoms accurately, validated patient-completed questionnaires are needed, as clinicians tend to underestimate the presence and severity of reflux symptoms reported by patients [##REF##15654774##6##]. In particular, validated symptom descriptors (e.g. 'burning behind the breastbone') are necessary because terms such as 'heartburn' are known to be poorly understood by patients [##REF##12269973##7##]; this is of particular relevance to Chinese populations, because there is no word for 'heartburn' in Mandarin Chinese beyond specialist medical circles, and a survey in the USA revealed that only 13.2% of East Asian patients understood the term [##REF##12269973##7##].</p>", "<p>Within the Chinese population, language and cultural differences can lead to different communities perceiving and expressing their symptoms differently. In China, Mandarin is the official language, but about half the population does not speak it, particularly those living in rural areas and older people [##UREF##0##8##]. There are thousands of local dialects, many of which are mutually unintelligible when spoken. All use the same writing system, and overall literacy rates in China are high, but literacy among older people, women and those living in rural areas is relatively low; in the 2003 census, over 9.6% of women and 2.1% of men were illiterate or semi-literate [##UREF##1##9##].</p>", "<p>Population surveys can be difficult to implement in China. Telephone surveys may introduce population bias in favour of the more wealthy urban Chinese population who are more likely to have telephones. The utility of postal surveys is limited by the ability of the respondent to understand the terms used [##REF##15162542##10##] which, for questionnaires developed in the West, may be further compounded by cultural conceptual differences. Response rates to telephone or postal questionnaires may be low, potentially introducing responder bias [##REF##12969086##11##,##REF##11101549##12##]. For these reasons, previous population surveys of GERD in China have administered questionnaires using a face-to-face interview technique, in which subjects completed the questionnaire while being assisted by trained interviewers [##REF##15162542##10##,##UREF##2##13##,##REF##16118911##14##]. This technique has achieved high response rates and has enabled terms and definitions to be clarified appropriately for individual respondents.</p>", "<p>In order to investigate the prevalence and impact of GERD in China and facilitate comparisons with other countries, linguistic and psychometric validation of internationally recognized disease-specific and generic patient-reported outcomes instruments is required. The aim of this pilot study was to develop and validate a methodology for the epidemiological study of GERD in China. The feasibility, validity and reliability of several well-designed questionnaires were tested in a Chinese environment using randomized, stratified, multi-stage cluster sampling, a statistical sampling technique adopted by the World Health Organization (WHO) [##UREF##3##15##] that is particularly well suited to the residential and social administration system in China.</p>" ]

[ "<title>Methods</title>", "<title>Setting</title>", "<p>Shanghai, on the east coast of China, is China's largest city. It is divided into 18 districts and one county, each of which is classified as urban, suburban, or rural (Figure ##FIG##0##1##). Each district includes numerous blocks, which include multiple residential areas, and the county covers several towns that govern a number of villages. Broadly speaking, people who live in an urban area have a city lifestyle, while people who live in a rural region lead a farming or country peasant way of life. The suburban lifestyle is intermediate between these two.</p>", "<title>Sampling</title>", "<p>A randomized, stratified, multi-stage cluster sampling methodology was used to select a representative sample of the general population in Shanghai. Huangpu was randomly selected from the nine urban districts, Pudong from the four suburban districts, and Songjiang from the five rural districts and one county of Shanghai. Blocks were randomly selected from districts and residential areas from blocks so that, finally, four residential areas in the urban district, three in the suburban district and two in the rural district were randomly selected (see Figures ##FIG##0##1## and ##FIG##1##2##). The Residential Committee of each residential area supplied detailed household rosters of all adults, and subjects for this study were randomly sampled from these lists.</p>", "<p>Pudong District consists of 26 towns and blocks, and is the biggest district in Shanghai. The residents in this district are widely dispersed and not all the information for each resident could be obtained. As information for all families in Pudong was available, families were randomly sampled from the selected residential areas and the family member with a birthday closest to the investigation date was selected.</p>", "<p>According to the statistical formula n = t²pq/d²(where n, t, p, q and d are sample size, t value, positive rate, negative rate and acceptable error, respectively), assuming a GERD prevalence of 10%, and setting significance at P = 0.05 and acceptable error at 2%, the calculated sample size was 864 [##REF##7580713##16##]. According to the 1 in 10 000 sampling proportion principle and the population size of Shanghai, the target sample size was 1300 respondents. Combining these two figures, a target sample size of 1000 valid respondents was deemed appropriate. Allowing for a 20% non-response rate, the final intended sample size was set at 1200, including 400 subjects from each district.</p>", "<p>Residents under 18 years of age, or residents who were illiterate, had severe visual, hearing or learning disabilities, or major psychiatric illness, were excluded from the survey. Respondents who were not at home after three attempts to administer the questionnaire were considered to be missing.</p>", "<title>Administration of questionnaires</title>", "<p>Local residential committee staff informed residents of the survey and secured their support and understanding. The informed consent of respondents was obtained, and each respondent was free to discontinue participation in the study at any time. The study was approved by the Second Military Medical University Ethics Committee.</p>", "<p>During the fieldwork period from November 2005 to January 2006, respondents completed questionnaires in their own homes or in local residential committee offices. Questionnaires were self-administered, with trained and supervised facilitators on hand to explain any questions that were unclear. The facilitators were social workers at the site, who were trained by supervisors who were professionals and graduate students from the Department of Health Statistics (DoHS), who received training from an epidemiology survey expert from the DoHS and a gastrointestinal specialist from Shanghai Hospital. Quality auditing was performed to ensure all questionnaires were completed properly. A valid questionnaire was one that had been audited and signed by a supervisor.</p>", "<title>Questionnaires</title>", "<p>Each respondent completed five questionnaires in Mandarin (see additional file ##SUPPL##0##1##: GERD questionnaire in English and Mandarin Chinese): a general information questionnaire and translations of four concise, well-validated, internationally recognized and frequently cited disease-specific and generic health questionnaires, chosen to facilitate comparison with other studies and minimize the length of the overall survey: the Reflux Disease Questionnaire (RDQ), the GERD Impact Scale, the Quality of Life in Reflux and Dyspepsia (QOLRAD) questionnaire, and the 36-Item Short-Form Health Survey (SF-36). The general information questionnaire collected information on age, gender, education, income and other general demographic variables.</p>", "<p>The RDQ is a 12-item self-report questionnaire measuring the frequency and severity of upper gastrointestinal symptoms (heartburn, regurgitation and epigastric pain) over the previous week. Symptom frequency and severity are scored on a 6-point Likert scale (0–5, where 5 is the most severe/frequent). A GERD dimension score can be obtained by combining the heartburn and regurgitation scores [##REF##11197287##17##]. Subjects reporting heartburn and/or regurgitation of any frequency during the 1-week recall period of the questionnaire were defined as having GERD. The RDQ was validated for use in clinical trials in two large studies [##REF##17439510##18##,##REF##12739705##19##], and was also recently validated for use as a diagnostic tool in the DIAMOND study (Diagnostic Tool for the Management of Patients with Reflux Disease) [##UREF##4##20##]. A Chinese version of the RDQ was tested in 10 hospitals in mainland China, and was found to identify accurately the presence of symptoms suggestive of GERD experienced over the previous month [##REF##15612657##21##].</p>", "<p>The GERD Impact Scale questionnaire is an eight-item self-report questionnaire designed to aid patient-physician communication in primary care. It assesses the frequency of gastroesophageal reflux symptoms over the past 2 weeks and their impact on everyday activities such as sleep, work, meals and social occasions, and the use of additional medication (other than that prescribed). Four response options for frequency are provided (1–4) where 1 is 'all of the time' and 4 is 'none of the time'. This newly developed tool has demonstrated good psychometric properties [##REF##17539985##22##].</p>", "<p>The GERD-specific version of the QOLRAD questionnaire is a 25-item disease-specific quality-of-life instrument measuring the impact of upper gastrointestinal symptoms over the previous week on five dimensions: emotional well-being, sleep, vitality, eating/drinking, and physical/social functioning [##REF##10027672##23##]. The frequencies of effects are reported using a 7-point Likert scale, with low scores indicating frequent impairment. Its reliability and validity have been extensively documented in studies of patients with upper gastrointestinal symptoms [##REF##10027672##23##, ####REF##14516179##24##, ##REF##11467624##25####11467624##25##].</p>", "<p>The SF-36 is a generic questionnaire assessing health status and well-being over the past 4 weeks. It contains 36 items clustered in eight dimensions: physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, and mental health, plus one item assessing change in health status over the previous year [##REF##1593914##26##]. Item scores for each dimension are coded, summed and transformed to a scale from 0 (worst possible health state) to 100 (best possible health state). Its reliability and validity are widely documented across a range of language versions [##REF##9817134##27##,##REF##9817133##28##].</p>", "<title>Translation and cognitive debriefing</title>", "<p>Apart from the SF-36, where validated Mandarin translations already exist [##REF##12646540##29##], questionnaires were translated and tested in the Department of Medicine, Faculty of Medicine, at the University of Hong Kong. Literal translation of Hong Kong Chinese into mainland Chinese (Mandarin) was undertaken by investigators and a panel of mainland gastroenterologists so that questionnaires were more interpretable by people from mainland China. This process was followed by cognitive debriefing, where five literate volunteers from mainland China who had a diagnosis of GERD (heartburn and/or acid regurgitation over the past year) completed the translated questionnaires and were interviewed to assess their understanding and interpretation. The overall relevance and clarity of the questionnaire were assessed using defined responses (very low; low; moderate; high; very high) and subjects were asked to specify any items that they regarded as irrelevant or unclear. Subjects considered the questions to be relevant and clear (grading: moderate to very high). No additional revisions were required.</p>", "<title>Statistical analysis</title>", "<title>Data management</title>", "<p>Questionnaire responses were coded and double-entered by two independent professional data-entry staff from the DoHS. EpiData software [##UREF##5##30##] was used to check for consistency between the two sets of data entries to ensure data quality. For the RDQ, QOLRAD, and SF-36, where at least 50% of items in a dimension were completed, the mean value of the completed items was used to impute the missing values. Where more than 50% of items were missing, the dimension score was excluded from the analysis [##UREF##6##31##, ####REF##8277801##32##, ##REF##9817132##33####9817132##33##]. For the GERD Impact Scale, if an item score was missing, imputation was not performed and the score was excluded from the analysis.</p>", "<p>SAS 9.1.3 (SAS, Shanghai, China) and SPSS 10.0 software (SPSS Inc., Shanghai, China) were used to complete data analyses. All hypothesis tests used two-side tests and set alpha at 0.05. A two-tailed <italic>P</italic>-value of 0.05 or less was considered to indicate statistical significance. Different groups of subjects were compared by ANOVA for normally distributed continuous data, Fisher's exact test for categorical variables and the Cochran-Mantel-Haenszel test for ranked variables.</p>", "<title>Reliability</title>", "<p>Internal consistency was evaluated using Cronbach's alpha coefficient to determine the extent to which items within each questionnaire were interrelated [##UREF##7##34##]. Cronbach's alpha coefficients for each questionnaire were calculated by correlating all individual item scores with dimension scores and/or the overall score. An alpha coefficient above 0.70 suggests good internal consistency and reliability.</p>", "<p>Test-retest reliability is a measure of the stability of the instrument under different conditions with the same respondent; in this study, it was assessed by retesting 10% of respondents (n = 40 from each region) 2–7 days after the baseline test. Cohen's kappa coefficient and the intraclass correlation coefficient (ICC) were used to analyze the test-retest reliability of the survey instruments. Cohen's kappa coefficient was used in the analysis of categorical and ranked measurements, while ICC was used to analyze quantitative measurements. A test-retest coefficient above 0.70 was considered acceptable [##REF##9812244##35##].</p>", "<title>Construct validity</title>", "<p>Construct validity evaluates whether an instrument actually measures the phenomena that it theoretically predicts; correlation and factor analysis were used to evaluate construct validity in this study. Factor analysis using principal component analysis and quartimax rotation explored whether the factor structure of each questionnaire was supported. Factor loadings larger than 0.50 within one dimension were considered to support the factor construct provided the factor loadings were low across the other dimensions, with cumulative rates used to show the contributions of combinations of principal components [##UREF##8##36##]. Correlation analysis tested the construct validity of questionnaires containing multiple dimensions (i.e. RDQ, QOLRAD and SF-36). The analysis measured the strength of association between dimension scores and the total score for QOLRAD and SF-36 questionnaires, and between item scores and dimension scores for the RDQ. A strong correlation coefficient was considered to be over 0.6, a moderate correlation, 0.3–0.6, and a weak correlation below 0.3 [##UREF##9##37##].</p>", "<p>Convergent validity analyzes whether the postulated dimension of an instrument correlates appreciably with all other dimensions from other instruments that should theoretically be related to it. Convergent validity was investigated in this study by correlating the GERD dimension from the RDQ with SF-36 and QOLRAD dimensions, and SF-36 dimensions with QOLRAD total score. A decrease in health-related quality of life was expected for respondents with GERD symptoms.</p>" ]

[ "<title>Results</title>", "<title>Response rate</title>", "<p>Of the 1200 randomly pre-selected subjects, 1034 agreed to be interviewed (a response rate of 86%). In the Pudong District, a total of 112 respondents' questionnaires were withdrawn from the statistical analysis due to one facilitator's failure to adhere to the study protocol. A further three questionnaires from the Huangpu District were excluded due to incompleteness. Therefore, a total of 919 questionnaires (359 from the urban region, 224 from the suburban region, and 336 from the rural region) were included in the analysis after quality auditing. The mean response rates for items in each questionnaire are provided in Table ##TAB##0##1##.</p>", "<p>Of 120 subjects randomly selected for retest, 113 agreed to be re-interviewed (a 94% response rate). Fourteen questionnaires were rejected because they were not completed in line with the study protocol, leaving 99 questionnaires for inclusion in the retest analysis.</p>", "<title>Respondents</title>", "<p>The respondents' average age was 47 years (ranging from 18 to 77 years); 55% were female and the majority of respondents (85%) were married. Most respondents did not smoke (74%) or drink alcohol (83%). The average BMI was 22.6 kg/m², with a range of 14.4–36.5 kg/m². Level and years of education, current job type and income level all varied significantly between the three regions (p &lt; 0.0001). Education levels and family income were greatest for the urban region and lowest for the rural region (Table ##TAB##1##2##), reflecting the socioeconomic divide that exists between urban and rural China. Forty percent of urban respondents were professionals or technicians, while 73% of rural respondents and 44% of suburban respondents were agricultural or fishery workers.</p>", "<title>Reliability</title>", "<p>In the test-retest analysis, Cohen's kappa coefficients ranged from 0.66 to 1.00 for RDQ dimensions, 0.49 to 1.00 for GERD Impact Scale items, and 0.79 to 1.00 for QOLRAD dimensions. The test-retest ICC ranged from 0.69 to 0.97 for seven dimensions of the SF-36 questionnaire, while one (role-emotional) was close to zero (0.01). Internal consistency (indicated by Cronbach's alpha coefficient) ranged from 0.65 to 0.97 for QOLRAD dimensions. For SF-36, seven dimensions ranged from 0.69 to 0.95, while one (social functioning) was 0.31. The test-retest reliability coefficient and total Cronbach's alpha coefficient for each questionnaire are shown in Table ##TAB##2##3##. All coefficients were ≥ 0.7, demonstrating good reliability and internal consistency for each questionnaire.</p>", "<title>Construct validity</title>", "<p>Each dimension score was highly correlated with the total score for both QOLRAD and SF-36 (p &lt; 0.001), indicating good construct validity. For QOLRAD, Spearman correlation coefficients ranged from 0.77 for physical/social functioning to 0.91 for food and drink problems and for vitality, among respondents reporting symptoms of heartburn and/or regurgitation via the RDQ. For SF-36, Spearman correlation coefficients ranged from 0.53 for social functioning to 0.77 for general health, for the study population as a whole. The RDQ also demonstrated good construct validity (Table ##TAB##3##4##), with each dimension correlating most strongly with the individual items comprising it (Spearman correlation coefficients 0.62–0.94). Regurgitation items correlated strongly with the GERD dimension as expected, but the weaker correlation with heartburn items may have been due to the low prevalence of heartburn in the Shanghai population.</p>", "<p>Factor analysis was used to explore whether the predicted factor structure of the questionnaire was supported. Credible construct validity was demonstrated for the RDQ, GERD Impact Scale and SF-36 questionnaires. All RDQ items correlated as expected in the factor analysis apart from the frequency and severity of 'pain behind breastbone', which correlated more strongly with the epigastric pain dimension than the heartburn dimension (Table ##TAB##4##5##). The cumulative rate of the three factors was 72.1%. All GERD Impact Scale items correlated with factors as expected (Table ##TAB##5##6##). The cumulative rate of the four factors was 78.0%.</p>", "<p>For SF-36, the cumulative rate of the eight factors plus health transition item was 71.3%. Most items correlated with factors as expected (see Table ##TAB##6##7##), with particularly high correlations seen for role-physical and bodily pain dimensions. The physical functioning (PF) items were distributed into two dimensions; PFa included moderate to vigorous activities such as lifting or carrying groceries, climbing several flights of stairs and walking more than one mile, whereas PFb included less strenuous activities such as climbing one flight of stairs, bending, kneeling, walking one or several blocks, and bathing or dressing oneself. The social function dimension was unclear, distributing to mental health and role-emotional dimensions. In addition, two items from the vitality dimension, two from the mental health dimension and one from the physical functioning dimension were distributed into the general health dimension. The three role-emotional items showed a tendency towards distribution into the role-physical dimension, although the correlation coefficients were lower than those for distribution into the expected role-emotional dimension.</p>", "<p>The factor analysis showed that the construct validity of QOLRAD was not as good as expected, as items were not distributed to the appropriate dimensions (Table ##TAB##7##8##).</p>", "<title>Convergent validity</title>", "<p>The RDQ GERD score was negatively correlated with all QOLRAD dimensions; correlations were statistically significant for the QOLRAD dimensions of food and drink problems (p = 0.037, correlation coefficient -0.28) and social functioning (p = 0.003, correlation coefficient -0.39). The RDQ GERD score was also significantly negatively correlated with all dimensions of SF-36 (p ≤ 0.001). SF-36 correlation coefficients ranged from -0.11 (social functioning) to -0.34 (bodily pain). Correlations were negative because health-related quality of life decreases as symptoms and their impact increase.</p>", "<p>The RDQ GERD score correlated most strongly with bodily pain (the SF-36 dimension most impaired by GERD in previous studies), reflecting the fact that GERD is primarily a painful disease. All eight SF-36 dimensions were significantly correlated with the QOLRAD total score (p ≤ 0.001, correlation coefficients ranged from 0.16–0.29), supporting the construct validity of QOLRAD and SF-36.</p>" ]

[ "<title>Discussion</title>", "<p>This pilot study used several well-designed questionnaires, administered together, with the aim of developing and validating a methodology for the epidemiological study of GERD in China. Using a randomized, stratified, multi-stage cluster sampling technique, we validated Chinese translations of the SF-36, QOLRAD questionnaire, GERD Impact Scale and RDQ. In this study, the translated and adapted questionnaires demonstrated reproducibility and internal consistency within the methodology adopted, although responsiveness was not assessed. Each questionnaire had a test-retest reliability coefficient larger than 0.7 and a high Cronbach's alpha coefficient (≥ 0.8), suggesting good reliability. The construct validity of questionnaires was also credible in this survey, although the QOLRAD did not perform well in the factor analysis. This was likely to be due to linguistic and cultural translation problems: facilitators considered that some items were difficult to explain to respondents, particularly for those with a low level of education.</p>", "<p>The sampling and administration techniques contributed substantially to the success of this study. By gaining the support of local residential communities, a high response rate of 86% was achieved, which is likely to prevent significant responder bias. The provision of assistance from trained facilitators helped avoid potential cultural and linguistic confusion, providing a relatively precise interpretation of the items in the questionnaire, and is recommended for future epidemiological studies using this survey instrument in order to ensure accuracy.</p>", "<p>Chinese translations of the SF-36 have previously undergone psychometric validation among Chinese-speaking peoples in mainland China, the USA, Hong Kong and Taiwan [##REF##12646540##29##,##REF##10800980##38##, ####REF##9817130##39##, ##REF##14641915##40##, ##REF##9817131##41####9817131##41##]. These studies demonstrated satisfactory psychometric characteristics for SF-36 in these groups, while highlighting a level of cultural variation between Western and Chinese versions and between the different Chinese cultures. There is a tendency, also reflected in the current study, for the social functioning dimension to perform less well in China [##REF##12646540##29##]; Li and colleagues have commented that this points to the Confucian ideology of collectivism in China, where it is socially unacceptable for Chinese to use 'sickness' as an excuse to avoid working or socializing [##REF##12646540##29##].</p>", "<p>In several previous studies vitality was more strongly associated with mental health than physical health [##REF##12646540##29##,##REF##10800980##38##, ####REF##9817130##39##, ##REF##14641915##40####14641915##40##], which may relate to traditional Chinese medicine, where fatigue associated with depression is conceptualized as a deficiency of vital energy or 'qi'. Although this was not the case in the current study, two items in the vitality dimension were more strongly distributed to general health. These issues illustrate the importance of examining the psychometric validity of instruments in different ethnic groups with cultural differences in language, values and perceptions of health.</p>", "<p>This study has several limitations. Some subjects found the combined questionnaire too long and repetitive: a general information questionnaire, the RDQ, GERD Impact Scale, QOLRAD and SF-36 combined to make a total of 137 items and, on average, the questionnaire took about 20 minutes to complete. Responsiveness to change and known-groups validity were not assessed. Where construct validity was assessed, the different recall periods for individual questionnaires may have weakened convergent correlation results, while the short retest period may distort the reliability analysis where respondents remember their previous responses. The methodology was unable to sample migrant workers, who make up a significant portion of the Shanghai population, as they remain officially registered in their place of origin.</p>" ]

[ "<title>Conclusion</title>", "<p>The experience gained in this pilot study will inform a planned larger study of the epidemiology of GERD across mainland China, which will establish the wider prevalence of GERD symptoms in China using representative study populations and a standardized, well-validated methodology. The survey questionnaire will be reduced in length and simplified, and symptoms will be assessed using the RDQ with a longer recall period (4 weeks). The QOLRAD questionnaire will be removed from the survey, due to its relatively poor performance in the factor analysis. Ideally, responsiveness to change and known-groups validity should be studied to investigate further the validity of the survey instruments. Health-related quality of life will be evaluated using the SF-36, and sleep disturbance will be investigated using the Epworth Sleepiness Scale (ESS). Endoscopic examination of randomly sampled subjects would also be informative, to allow comparison with recent studies conducted in the West [##REF##15932168##42##,##REF##18424568##43##].</p>", "<p>In summary, this study developed and tested a successful survey methodology for the epidemiological study of GERD in China. The questionnaires used demonstrated credible reliability and construct validity, supporting their use in larger epidemiological surveys of GERD in China, and allowing the results of this study to be extrapolated to the general population of East China.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Gastroesophageal reflux disease (GERD) causes a wide range of clinical symptoms and potentially serious complications, but epidemiological data about GERD in China are limited. The aim of this pilot study was to develop and validate a methodology for the epidemiological study of GERD in China.</p>", "<title>Methods</title>", "<p>Regionally stratified, randomized samples of Shanghai residents (n = 919) completed Mandarin translations of the Reflux Disease Questionnaire (RDQ), GERD Impact Scale, Quality of Life in Reflux and Dyspepsia (QOLRAD) questionnaire and 36-item Short Form Health Survey (SF-36). Reliability and construct validity were tested by appropriate statistical analyses.</p>", "<title>Results</title>", "<p>The response rate was 86%. The test-retest reliability coefficients for the RDQ, GERD Impact Scale, QOLRAD and SF-36 were 0.80, 0.71, 0.93 and 0.96, respectively, and Cronbach's alpha coefficients were 0.86, 0.80, 0.98 and 0.90, respectively. Dimension scores were highly correlated with the total scores for the QOLRAD and SF-36, and factor analysis showed credible construct validity for the RDQ, GERD Impact Scale and SF-36. The RDQ GERD score was significantly negatively correlated with QOLRAD dimensions of food and drink problems and social functioning, and was significantly negatively correlated with all dimensions of the SF-36. All eight of the SF-36 dimensions were significantly correlated with the QOLRAD total score.</p>", "<title>Conclusion</title>", "<p>This study developed and tested a successful survey methodology for the investigation of GERD in China. The questionnaires used demonstrated credible reliability and construct validity, supporting their use in larger epidemiological surveys of GERD in China.</p>" ]

[ "<title>Competing interests</title>", "<p>This study was supported by AstraZeneca R&amp;D, Mölndal, Sweden. Writing support was provided by Chris Winchester and Claire Mulligan of Oxford PharmaGenesis and funded by AstraZeneca R&amp;D, Mölndal, Sweden. Jia He has served as the director of the Department of Health Statistics, Second Military Medical University and WHO/TDR Clinical Data Management Center, Shanghai, China, and also served as a director of the Chinese Biomedicine Statistics Institute. Jia He has received research funding from the National Natural Science Foundation of China, WHO and Shanghai Natural Science Foundation. Saga Johansson is an employee of AstraZeneca R&amp;D, Mölndal, Sweden, and Mari-Ann Wallander was an employee of AstraZeneca R&amp;D, Mölndal, Sweden at the time of the study.</p>", "<title>Authors' contributions</title>", "<p>YC and XY participated in the acquisition of data, analysis and interpretation of data, and drafting the article. XQM and RW participated in the analysis and interpretation of data, and drafting and critically revising the article. SJ and MAW participated in the conception and design of the study, and critically revising the article. JH made substantial contributions to the conception and design of the study, supervised all aspects of its implementation, and critically revised the article. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-230X/8/37/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>This study was supported by AstraZeneca R&amp;D, Mölndal, Sweden. We thank the participating general practitioners for their collaboration, and the Centers of Disease Control and Prevention of Huangpu District, Songjiang District and Pudong District in Shanghai for providing the assistance in field work. We thank Dr Chris Winchester and Dr Claire Mulligan, from Oxford PharmaGenesis, who provided medical writing support funded by AstraZeneca. We also thank Dr Benjamin Wong and Dr Xiaohua Jin for translating the questionnaires used in this study.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>The survey sites in Shanghai.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Stratified, multi-stage randomized cluster sampling of urban, suburban and rural districts in Shanghai.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Mean item response rates by questionnaire and by region.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"/><td align=\"center\" colspan=\"4\"><bold>Mean item response rates</bold></td></tr><tr><td/><td colspan=\"4\"><hr/></td></tr><tr><td>Region</td><td align=\"center\">RDQ</td><td align=\"center\">GERD Impact Scale</td><td align=\"center\">QOLRAD</td><td align=\"center\">SF-36</td></tr></thead><tbody><tr><td align=\"left\">Urban (n = 359)</td><td align=\"center\">98.35–98.62%</td><td align=\"center\">98.07–98.35%</td><td align=\"center\">96.97–100%</td><td align=\"center\">98.07–99.45%</td></tr><tr><td align=\"left\">Suburban (n = 224)</td><td align=\"center\">100–100%</td><td align=\"center\">100–100%</td><td align=\"center\">100–100%</td><td align=\"center\">98.21–100%</td></tr><tr><td align=\"left\">Rural (n = 336)</td><td align=\"center\">100–100%</td><td align=\"center\">100–100%</td><td align=\"center\">94.11–100%</td><td align=\"center\">97.92–99.70%</td></tr><tr><td align=\"left\">All regions (n = 919)</td><td align=\"center\">99.35–99.46%</td><td align=\"center\">99.24–99.35%</td><td align=\"center\">98.25–100%</td><td align=\"center\">98.59–99.67%</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Demographics and baseline characteristics of respondents by region.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\">Mean ± SD or number of subjects (%)</td></tr></thead><tbody><tr><td align=\"left\"><bold>Variables</bold></td><td align=\"right\"><bold>Urban (n = 359*)</bold></td><td align=\"right\"><bold>Suburban (n = 224*)</bold></td><td align=\"right\"><bold>Rural (n = 336*)</bold></td><td align=\"right\"><bold>Total (n = 919*)</bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">Age (years)</td><td align=\"right\">45.7 ± 14.5</td><td align=\"right\">45.2 ± 13.1</td><td align=\"right\">49.0 ± 12.2</td><td align=\"right\">46.7 ± 13.4</td></tr><tr><td align=\"left\">Weight (kg)</td><td align=\"right\">63.0 ± 11.0</td><td align=\"right\">61.2 ± 10.1</td><td align=\"right\">59.3 ± 8.2</td><td align=\"right\">61.2 ± 10.0</td></tr><tr><td align=\"left\">Height (cm)</td><td align=\"right\">167.3 ± 8.2</td><td align=\"right\">162.8 ± 7.7</td><td align=\"right\">162.0 ± 6.8</td><td align=\"right\">164.3 ± 8.0</td></tr><tr><td align=\"left\"><bold>Body mass index (kg/m</bold>²)</td><td align=\"right\">22.4 ± 3.0</td><td align=\"right\">23.1 ± 3.3</td><td align=\"right\">22.6 ± 2.7</td><td align=\"right\">22.6 ± 3.0</td></tr><tr><td align=\"left\"><bold>Sex</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Female</td><td align=\"right\">193 (53.8)</td><td align=\"right\">139 (62.1)</td><td align=\"right\">177 (52.7)</td><td align=\"right\">509 (55.4)</td></tr><tr><td align=\"left\"> Male</td><td align=\"right\">166 (46.2)</td><td align=\"right\">85 (38.0)</td><td align=\"right\">159 (47.3)</td><td align=\"right\">410 (44.6)</td></tr><tr><td align=\"left\"><bold>Marital status</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Married</td><td align=\"right\">266 (75.1)</td><td align=\"right\">197 (88.7)</td><td align=\"right\">306 (94.2)</td><td align=\"right\">796 (85.4)</td></tr><tr><td align=\"left\"> Unmarried</td><td align=\"right\">88 (24.9)</td><td align=\"right\">25 (11.3)</td><td align=\"right\">19 (5.9)</td><td align=\"right\">132 (14.7)</td></tr><tr><td align=\"left\"><bold>Maximum education level</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Primary school/uneducated</td><td align=\"right\">4 (1.1)</td><td align=\"right\">61 (27.2)</td><td align=\"right\">189 (56.8)</td><td align=\"right\">254 (27.7)</td></tr><tr><td align=\"left\"> Secondary/high school</td><td align=\"right\">232 (64.6)</td><td align=\"right\">138 (61.6)</td><td align=\"right\">139 (41.7)</td><td align=\"right\">509 (55.6)</td></tr><tr><td align=\"left\"> College graduate or beyond</td><td align=\"right\">123 (34.3)</td><td align=\"right\">25 (11.2)</td><td align=\"right\">5 (1.5)</td><td align=\"right\">153 (16.7)</td></tr><tr><td align=\"left\"> Years of school education</td><td align=\"right\">12.3 ± 2.5</td><td align=\"right\">8.9 ± 3.7</td><td align=\"right\">6.2 ± 3.6</td><td align=\"right\">9.3 ± 4.2</td></tr><tr><td align=\"left\"><bold>Current job</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> Government employee</td><td align=\"right\">20 (5.6)</td><td align=\"right\">1 (0.5)</td><td align=\"right\">1 (0.3)</td><td align=\"right\">22 (2.4)</td></tr><tr><td align=\"left\"> Professional or technician</td><td align=\"right\">144 (40.3)</td><td align=\"right\">18 (8.0)</td><td align=\"right\">12 (3.6)</td><td align=\"right\">174 (19.02)</td></tr><tr><td align=\"left\"> Blue-collar worker</td><td align=\"right\">70 (19.6)</td><td align=\"right\">40 (17.9)</td><td align=\"right\">51 (15.3)</td><td align=\"right\">161 (17.6)</td></tr><tr><td align=\"left\"> Agricultural or fisheries worker</td><td align=\"right\">1 (0.3)</td><td align=\"right\">98 (43.8)</td><td align=\"right\">243 (72.8)</td><td align=\"right\">342 (37.4)</td></tr><tr><td align=\"left\"> Student in school</td><td align=\"right\">30 (8.4)</td><td align=\"right\">7 (3.1)</td><td align=\"right\">4 (1.2)</td><td align=\"right\">41 (4.5)</td></tr><tr><td align=\"left\"> Others</td><td align=\"right\">92 (25.7)</td><td align=\"right\">60 (26.8)</td><td align=\"right\">23 (6.9)</td><td align=\"right\">175 (19.1)</td></tr><tr><td align=\"left\"><bold>Total family income per month</bold>^†</td><td/><td/><td/><td/></tr><tr><td align=\"left\"> less than 1999 Yuan</td><td align=\"right\">178 (50.9)</td><td align=\"right\">124 (57.1)</td><td align=\"right\">232 (69.2)</td><td align=\"right\">534 (59.2)</td></tr><tr><td align=\"left\"> 2000–4999 Yuan</td><td align=\"right\">157 (44.9)</td><td align=\"right\">81 (37.3)</td><td align=\"right\">98 (29.3)</td><td align=\"right\">336 (37.3)</td></tr><tr><td align=\"left\"> 5000–9999 Yuan</td><td align=\"right\">13 (3.7)</td><td align=\"right\">12 (5.4)</td><td align=\"right\">4 (1.2)</td><td align=\"right\">29 (3.2)</td></tr><tr><td align=\"left\"> 10000 Yuan or above</td><td align=\"right\">2 (0.6)</td><td align=\"right\">0 (0)</td><td align=\"right\">1 (0.3)</td><td align=\"right\">3 (0.3)</td></tr><tr><td align=\"left\"><bold>Smoking</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> No</td><td align=\"right\">282 (78.6)</td><td align=\"right\">163 (73.4)</td><td align=\"right\">225 (68.2)</td><td align=\"right\">670 (73.6)</td></tr><tr><td align=\"left\"> Yes</td><td align=\"right\">77 (21.5)</td><td align=\"right\">59 (26.6)</td><td align=\"right\">105 (31.8)</td><td align=\"right\">241 (26.5)</td></tr><tr><td align=\"left\"> Years of smoking</td><td align=\"right\">22.5 ± 11.6</td><td align=\"right\">20.6 ± 12.6</td><td align=\"right\">19.63 ± 11.7</td><td align=\"right\">20.8 ± 11.9</td></tr><tr><td align=\"left\"><bold>Alcohol intake</bold></td><td/><td/><td/><td/></tr><tr><td align=\"left\"> No</td><td align=\"right\">308 (85.8)</td><td align=\"right\">193 (87.3)</td><td align=\"right\">251 (76.1)</td><td align=\"right\">752 (82.6)</td></tr><tr><td align=\"left\"> Yes</td><td align=\"right\">51 (14.2)</td><td align=\"right\">28 (12.7)</td><td align=\"right\">79 (23.4)</td><td align=\"right\">158 (17.4)</td></tr><tr><td align=\"left\"> Years of alcohol intake</td><td align=\"right\">18.7 ± 11.1</td><td align=\"right\">21.06 ± 11.9</td><td align=\"right\">18.26 ± 10.9</td><td align=\"right\">18.69 ± 11.1</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Reliability of questionnaires.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Questionnaire</bold></td><td align=\"left\"><bold>Number of items</bold></td><td align=\"left\"><bold>Test-retest reliability coefficient*</bold></td><td align=\"left\"><bold>Cronbach's alpha coefficient</bold></td></tr></thead><tbody><tr><td align=\"left\">RDQ</td><td align=\"left\">12</td><td align=\"left\">0.80</td><td align=\"left\">0.86</td></tr><tr><td align=\"left\">GERD Impact Scale</td><td align=\"left\">8</td><td align=\"left\">0.71</td><td align=\"left\">0.80</td></tr><tr><td align=\"left\">QOLRAD</td><td align=\"left\">25</td><td align=\"left\">0.93</td><td align=\"left\">0.98</td></tr><tr><td align=\"left\">SF-36</td><td align=\"left\">36</td><td align=\"left\">0.96</td><td align=\"left\">0.90</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Spearman correlation coefficient between RDQ item score and RDQ dimension score.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>RDQ item</bold></td><td align=\"center\"><bold>Heartburn dimension</bold></td><td align=\"center\"><bold>Regurgitation dimension</bold></td><td align=\"center\"><bold>GERD dimension</bold></td><td align=\"center\"><bold>Epigastric pain dimension</bold></td></tr></thead><tbody><tr><td align=\"left\">Burning behind breastbone – severity</td><td align=\"center\"><bold>0.62</bold></td><td align=\"center\">0.34</td><td align=\"center\">0.38</td><td align=\"center\">0.32</td></tr><tr><td align=\"left\">Burning behind breastbone – frequency</td><td align=\"center\"><bold>0.62</bold></td><td align=\"center\">0.34</td><td align=\"center\">0.38</td><td align=\"center\">0.32</td></tr><tr><td align=\"left\">Pain behind breastbone – severity</td><td align=\"center\"><bold>0.93</bold></td><td align=\"center\">0.32</td><td align=\"center\">0.56</td><td align=\"center\">0.59</td></tr><tr><td align=\"left\">Pain behind breastbone – frequency</td><td align=\"center\"><bold>0.93</bold></td><td align=\"center\">0.32</td><td align=\"center\">0.56</td><td align=\"center\">0.59</td></tr><tr><td align=\"left\">Acid taste – severity</td><td align=\"center\">0.32</td><td align=\"center\"><bold>0.91</bold></td><td align=\"center\"><bold>0.84</bold></td><td align=\"center\">0.44</td></tr><tr><td align=\"left\">Acid taste – frequency</td><td align=\"center\">0.32</td><td align=\"center\"><bold>0.91</bold></td><td align=\"center\"><bold>0.84</bold></td><td align=\"center\">0.43</td></tr><tr><td align=\"left\">Movement of materials – severity</td><td align=\"center\">0.42</td><td align=\"center\"><bold>0.72</bold></td><td align=\"center\"><bold>0.67</bold></td><td align=\"center\">0.39</td></tr><tr><td align=\"left\">Movement of materials – frequency</td><td align=\"center\">0.43</td><td align=\"center\"><bold>0.72</bold></td><td align=\"center\"><bold>0.67</bold></td><td align=\"center\">0.39</td></tr><tr><td align=\"left\">Upper stomach burning – severity</td><td align=\"center\">0.54</td><td align=\"center\">0.41</td><td align=\"center\">0.44</td><td align=\"center\"><bold>0.68</bold></td></tr><tr><td align=\"left\">Upper stomach burning – frequency</td><td align=\"center\">0.54</td><td align=\"center\">0.41</td><td align=\"center\">0.44</td><td align=\"center\"><bold>0.68</bold></td></tr><tr><td align=\"left\">Upper stomach pain – severity</td><td align=\"center\">0.58</td><td align=\"center\">0.45</td><td align=\"center\">0.56</td><td align=\"center\"><bold>0.94</bold></td></tr><tr><td align=\"left\">Upper stomach pain – frequency</td><td align=\"center\">0.58</td><td align=\"center\">0.45</td><td align=\"center\">0.56</td><td align=\"center\"><bold>0.94</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Factor analysis matrix of RDQ items in three factors (heartburn, regurgitation and epigastric pain).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Symptom</bold></td><td align=\"left\"><bold>Heartburn</bold></td><td align=\"left\"><bold>Regurgitation</bold></td><td align=\"left\"><bold>Epigastric pain</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Heartburn</bold></td><td/><td/><td/></tr><tr><td align=\"left\"> Burning behind breastbone – severity</td><td align=\"left\"><bold>0.84</bold></td><td align=\"left\">0.22</td><td align=\"left\">0.31</td></tr><tr><td align=\"left\"> Burning behind breastbone – frequency</td><td align=\"left\"><bold>0.84</bold></td><td align=\"left\">0.11</td><td align=\"left\">0.37</td></tr><tr><td align=\"left\"> Pain behind breastbone – severity</td><td align=\"left\">0.25</td><td align=\"left\">0.05</td><td align=\"left\"><bold>0.80</bold></td></tr><tr><td align=\"left\"> Pain behind breastbone – frequency</td><td align=\"left\">0.10</td><td align=\"left\">0.04</td><td align=\"left\"><bold>0.84</bold></td></tr><tr><td align=\"left\"><bold>Regurgitation</bold></td><td/><td/><td/></tr><tr><td align=\"left\"> Acid taste – severity</td><td align=\"left\">-0.09</td><td align=\"left\"><bold>0.89</bold></td><td align=\"left\">0.16</td></tr><tr><td align=\"left\"> Acid taste – frequency</td><td align=\"left\">-0.07</td><td align=\"left\"><bold>0.84</bold></td><td align=\"left\">0.15</td></tr><tr><td align=\"left\"> Movement of materials – severity</td><td align=\"left\">0.33</td><td align=\"left\"><bold>0.72</bold></td><td align=\"left\">0.17</td></tr><tr><td align=\"left\"> Movement of materials – frequency</td><td align=\"left\">0.36</td><td align=\"left\"><bold>0.72</bold></td><td align=\"left\">0.17</td></tr><tr><td align=\"left\"><bold>Epigastric pain</bold></td><td/><td/><td/></tr><tr><td align=\"left\"> Upper stomach burning – severity</td><td align=\"left\">0.31</td><td align=\"left\">0.12</td><td align=\"left\"><bold>0.59</bold></td></tr><tr><td align=\"left\"> Upper stomach burning – frequency</td><td align=\"left\">0.36</td><td align=\"left\">0.01</td><td align=\"left\"><bold>0.63</bold></td></tr><tr><td align=\"left\"> Upper stomach pain – severity</td><td align=\"left\">-0.18</td><td align=\"left\">0.27</td><td align=\"left\"><bold>0.83</bold></td></tr><tr><td align=\"left\"> Upper stomach pain – frequency</td><td align=\"left\">-0.15</td><td align=\"left\">0.14</td><td align=\"left\"><bold>0.88</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Factor analysis matrix of GERD Impact Scale items in four factors.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Symptom (frequency)</bold></td><td align=\"left\"><bold>Regurgitation and effect on eat/sleep/work</bold></td><td align=\"left\"><bold>Heartburn and effect on sleep</bold></td><td align=\"left\"><bold>Additional medication</bold></td><td align=\"left\"><bold>Sore throat/hoarseness</bold></td></tr></thead><tbody><tr><td align=\"left\">Pain behind breastbone</td><td align=\"left\">0.37</td><td align=\"left\"><bold>0.73</bold></td><td align=\"left\">0.18</td><td align=\"left\">-0.28</td></tr><tr><td align=\"left\">Burning behind breastbone</td><td align=\"left\">0.23</td><td align=\"left\"><bold>0.76</bold></td><td align=\"left\">0.00</td><td align=\"left\">0.40</td></tr><tr><td align=\"left\">Acid taste or regurgitation</td><td align=\"left\"><bold>0.83</bold></td><td align=\"left\">0.10</td><td align=\"left\">-0.05</td><td align=\"left\">0.04</td></tr><tr><td align=\"left\">Sore throat or hoarseness due to heartburn or acid reflux</td><td align=\"left\">0.39</td><td align=\"left\">0.21</td><td align=\"left\">0.09</td><td align=\"left\"><bold>0.81</bold></td></tr><tr><td align=\"left\">Difficulty sleeping due to heartburn or acid reflux</td><td align=\"left\"><bold>0.53</bold></td><td align=\"left\"><bold>0.61</bold></td><td align=\"left\">-0.02</td><td align=\"left\">0.20</td></tr><tr><td align=\"left\">Difficulty eating preferred foods due to heartburn or acid reflux</td><td align=\"left\"><bold>0.82</bold></td><td align=\"left\">0.00</td><td align=\"left\">0.25</td><td align=\"left\">0.11</td></tr><tr><td align=\"left\">Difficulty working due to heartburn or acid reflux</td><td align=\"left\"><bold>0.77</bold></td><td align=\"left\">0.31</td><td align=\"left\">0.05</td><td align=\"left\">0.04</td></tr><tr><td align=\"left\">Self-medication for heartburn or acid reflux</td><td align=\"left\">0.29</td><td align=\"left\">0.13</td><td align=\"left\"><bold>0.92</bold></td><td align=\"left\">0.07</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T7\"><label>Table 7</label><caption><p>Factor analysis matrix of SF-36 items in nine factors.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Item</td><td align=\"left\">GH</td><td align=\"left\">RP</td><td align=\"left\">PFa</td><td align=\"left\">PFb</td><td align=\"left\">MH</td><td align=\"left\">RE</td><td align=\"left\">BP</td><td align=\"left\">VT</td><td align=\"left\">HT</td></tr></thead><tbody><tr><td align=\"left\">PF1</td><td align=\"left\"><underline>0.51</underline></td><td align=\"left\">0.10</td><td align=\"left\">-0.03</td><td align=\"left\"><bold>0.65</bold></td><td align=\"left\">-0.03</td><td align=\"left\">-0.01</td><td align=\"left\">0.06</td><td align=\"left\">0.10</td><td align=\"left\">0.08</td></tr><tr><td align=\"left\">PF2</td><td align=\"left\">0.33</td><td align=\"left\">0.18</td><td align=\"left\">0.12</td><td align=\"left\"><bold>0.73</bold></td><td align=\"left\">0.12</td><td align=\"left\">0.12</td><td align=\"left\">-0.07</td><td align=\"left\">0.02</td><td align=\"left\">0.12</td></tr><tr><td align=\"left\">PF3</td><td align=\"left\">0.34</td><td align=\"left\">0.15</td><td align=\"left\">0.20</td><td align=\"left\"><bold>0.72</bold></td><td align=\"left\">0.11</td><td align=\"left\">0.04</td><td align=\"left\">0.12</td><td align=\"left\">0.02</td><td align=\"left\">0.10</td></tr><tr><td align=\"left\">PF4</td><td align=\"left\">0.33</td><td align=\"left\">-0.02</td><td align=\"left\">0.32</td><td align=\"left\"><bold>0.64</bold></td><td align=\"left\">0.14</td><td align=\"left\">0.04</td><td align=\"left\">0.06</td><td align=\"left\">-0.02</td><td align=\"left\">0.23</td></tr><tr><td align=\"left\">PF5</td><td align=\"left\">0.16</td><td align=\"left\">0.11</td><td align=\"left\"><bold>0.81</bold></td><td align=\"left\">0.19</td><td align=\"left\">0.01</td><td align=\"left\">0.10</td><td align=\"left\">0.08</td><td align=\"left\">0.06</td><td align=\"left\">0.04</td></tr><tr><td align=\"left\">PF6</td><td align=\"left\">0.16</td><td align=\"left\">0.02</td><td align=\"left\"><bold>0.57</bold></td><td align=\"left\">0.34</td><td align=\"left\">0.10</td><td align=\"left\">0.13</td><td align=\"left\">0.26</td><td align=\"left\">0.05</td><td align=\"left\">0.14</td></tr><tr><td align=\"left\">PF7</td><td align=\"left\">0.41</td><td align=\"left\">0.03</td><td align=\"left\">0.30</td><td align=\"left\"><bold>0.56</bold></td><td align=\"left\">-0.05</td><td align=\"left\">0.01</td><td align=\"left\">-0.01</td><td align=\"left\">0.11</td><td align=\"left\">-0.23</td></tr><tr><td align=\"left\">PF8</td><td align=\"left\">0.36</td><td align=\"left\">0.04</td><td align=\"left\">0.49</td><td align=\"left\">0.46</td><td align=\"left\">0.06</td><td align=\"left\">-0.11</td><td align=\"left\">-0.07</td><td align=\"left\">-0.04</td><td align=\"left\">-0.15</td></tr><tr><td align=\"left\">PF9</td><td align=\"left\">0.13</td><td align=\"left\">0.13</td><td align=\"left\"><bold>0.88</bold></td><td align=\"left\">0.08</td><td align=\"left\">0.12</td><td align=\"left\">-0.03</td><td align=\"left\">0.01</td><td align=\"left\">-0.02</td><td align=\"left\">-0.01</td></tr><tr><td align=\"left\">PF10</td><td align=\"left\">0.10</td><td align=\"left\">0.12</td><td align=\"left\"><bold>0.89</bold></td><td align=\"left\">0.03</td><td align=\"left\">0.06</td><td align=\"left\">0.00</td><td align=\"left\">-0.06</td><td align=\"left\">0.00</td><td align=\"left\">-0.02</td></tr><tr><td align=\"left\">RP1</td><td align=\"left\">0.20</td><td align=\"left\"><bold>0.91</bold></td><td align=\"left\">0.07</td><td align=\"left\">0.03</td><td align=\"left\">0.10</td><td align=\"left\">0.14</td><td align=\"left\">0.05</td><td align=\"left\">0.03</td><td align=\"left\">0.08</td></tr><tr><td align=\"left\">RP2</td><td align=\"left\">0.18</td><td align=\"left\"><bold>0.90</bold></td><td align=\"left\">0.08</td><td align=\"left\">0.04</td><td align=\"left\">0.09</td><td align=\"left\">0.13</td><td align=\"left\">0.05</td><td align=\"left\">0.03</td><td align=\"left\">0.09</td></tr><tr><td align=\"left\">RP3</td><td align=\"left\">0.18</td><td align=\"left\"><bold>0.88</bold></td><td align=\"left\">0.09</td><td align=\"left\">0.08</td><td align=\"left\">0.10</td><td align=\"left\">0.14</td><td align=\"left\">0.14</td><td align=\"left\">0.03</td><td align=\"left\">0.06</td></tr><tr><td align=\"left\">RP4</td><td align=\"left\">0.18</td><td align=\"left\"><bold>0.82</bold></td><td align=\"left\">0.14</td><td align=\"left\">0.11</td><td align=\"left\">0.10</td><td align=\"left\">0.06</td><td align=\"left\">0.19</td><td align=\"left\">0.02</td><td align=\"left\">0.03</td></tr><tr><td align=\"left\">RE1</td><td align=\"left\">0.17</td><td align=\"left\"><underline>0.58</underline></td><td align=\"left\">-0.01</td><td align=\"left\">0.07</td><td align=\"left\">0.13</td><td align=\"left\"><bold>0.72</bold></td><td align=\"left\">0.04</td><td align=\"left\">0.02</td><td align=\"left\">-0.01</td></tr><tr><td align=\"left\">RE2</td><td align=\"left\">0.18</td><td align=\"left\"><underline>0.59</underline></td><td align=\"left\">0.06</td><td align=\"left\">0.07</td><td align=\"left\">0.12</td><td align=\"left\"><bold>0.72</bold></td><td align=\"left\">0.04</td><td align=\"left\">0.02</td><td align=\"left\">-0.02</td></tr><tr><td align=\"left\">RE3</td><td align=\"left\">0.13</td><td align=\"left\">0.48</td><td align=\"left\">0.07</td><td align=\"left\">0.09</td><td align=\"left\">0.09</td><td align=\"left\"><bold>0.73</bold></td><td align=\"left\">0.05</td><td align=\"left\">0.05</td><td align=\"left\">-0.04</td></tr><tr><td align=\"left\">MH1</td><td align=\"left\">0.19</td><td align=\"left\">0.11</td><td align=\"left\">-0.03</td><td align=\"left\">0.06</td><td align=\"left\"><bold>0.62</bold></td><td align=\"left\">0.13</td><td align=\"left\">0.18</td><td align=\"left\">0.15</td><td align=\"left\">-0.09</td></tr><tr><td align=\"left\">MH2</td><td align=\"left\">0.25</td><td align=\"left\">0.15</td><td align=\"left\">0.14</td><td align=\"left\">0.13</td><td align=\"left\"><bold>0.64</bold></td><td align=\"left\">0.21</td><td align=\"left\">-0.06</td><td align=\"left\">0.08</td><td align=\"left\">0.15</td></tr><tr><td align=\"left\">MH3</td><td align=\"left\"><underline>0.57</underline></td><td align=\"left\">0.05</td><td align=\"left\">0.03</td><td align=\"left\">0.07</td><td align=\"left\">0.37</td><td align=\"left\">-0.08</td><td align=\"left\">-0.03</td><td align=\"left\">-0.08</td><td align=\"left\">-0.25</td></tr><tr><td align=\"left\">MH4</td><td align=\"left\">0.20</td><td align=\"left\">0.12</td><td align=\"left\">0.18</td><td align=\"left\">0.02</td><td align=\"left\"><bold>0.69</bold></td><td align=\"left\">0.11</td><td align=\"left\">-0.07</td><td align=\"left\">0.18</td><td align=\"left\">0.21</td></tr><tr><td align=\"left\">MH5</td><td align=\"left\"><underline>0.63</underline></td><td align=\"left\">0.04</td><td align=\"left\">0.04</td><td align=\"left\">0.11</td><td align=\"left\">0.06</td><td align=\"left\">-0.01</td><td align=\"left\">-0.21</td><td align=\"left\">0.29</td><td align=\"left\">-0.17</td></tr><tr><td align=\"left\">VT1</td><td align=\"left\"><underline>0.76</underline></td><td align=\"left\">0.10</td><td align=\"left\">0.05</td><td align=\"left\">0.27</td><td align=\"left\">0.19</td><td align=\"left\">-0.09</td><td align=\"left\">0.10</td><td align=\"left\">0.01</td><td align=\"left\">-0.17</td></tr><tr><td align=\"left\">VT2</td><td align=\"left\"><underline>0.78</underline></td><td align=\"left\">0.13</td><td align=\"left\">0.05</td><td align=\"left\">0.25</td><td align=\"left\">0.17</td><td align=\"left\">-0.06</td><td align=\"left\">0.08</td><td align=\"left\">0.01</td><td align=\"left\">-0.15</td></tr><tr><td align=\"left\">VT3</td><td align=\"left\">0.27</td><td align=\"left\">0.05</td><td align=\"left\">0.05</td><td align=\"left\">0.04</td><td align=\"left\">0.13</td><td align=\"left\">0.04</td><td align=\"left\">0.08</td><td align=\"left\"><bold>0.86</bold></td><td align=\"left\">0.05</td></tr><tr><td align=\"left\">VT4</td><td align=\"left\">0.37</td><td align=\"left\">0.10</td><td align=\"left\">0.02</td><td align=\"left\">0.10</td><td align=\"left\">0.19</td><td align=\"left\">-0.05</td><td align=\"left\">0.07</td><td align=\"left\"><bold>0.75</bold></td><td align=\"left\">-0.03</td></tr><tr><td align=\"left\">SF1</td><td align=\"left\">0.23</td><td align=\"left\">0.27</td><td align=\"left\">0.16</td><td align=\"left\">-0.01</td><td align=\"left\">0.22</td><td align=\"left\">0.46</td><td align=\"left\">0.26</td><td align=\"left\">-0.18</td><td align=\"left\">0.07</td></tr><tr><td align=\"left\">SF2</td><td align=\"left\">0.27</td><td align=\"left\">0.18</td><td align=\"left\">0.08</td><td align=\"left\">0.06</td><td align=\"left\"><underline>0.64</underline></td><td align=\"left\">-0.11</td><td align=\"left\">0.02</td><td align=\"left\">-0.07</td><td align=\"left\">-0.13</td></tr><tr><td align=\"left\">GH1</td><td align=\"left\"><bold>0.59</bold></td><td align=\"left\">0.15</td><td align=\"left\">0.06</td><td align=\"left\">0.15</td><td align=\"left\">-0.06</td><td align=\"left\">0.10</td><td align=\"left\">0.16</td><td align=\"left\">0.00</td><td align=\"left\">0.43</td></tr><tr><td align=\"left\">GH2</td><td align=\"left\"><bold>0.68</bold></td><td align=\"left\">0.10</td><td align=\"left\">0.02</td><td align=\"left\">0.03</td><td align=\"left\">0.10</td><td align=\"left\">0.12</td><td align=\"left\">0.05</td><td align=\"left\">0.13</td><td align=\"left\">0.13</td></tr><tr><td align=\"left\">GH3</td><td align=\"left\"><bold>0.73</bold></td><td align=\"left\">0.07</td><td align=\"left\">0.19</td><td align=\"left\">-0.03</td><td align=\"left\">0.02</td><td align=\"left\">0.12</td><td align=\"left\">-0.01</td><td align=\"left\">0.02</td><td align=\"left\">0.08</td></tr><tr><td align=\"left\">GH4</td><td align=\"left\"><bold>0.61</bold></td><td align=\"left\">0.05</td><td align=\"left\">-0.01</td><td align=\"left\">0.06</td><td align=\"left\">0.09</td><td align=\"left\">0.05</td><td align=\"left\">0.07</td><td align=\"left\">0.03</td><td align=\"left\">0.44</td></tr><tr><td align=\"left\">GH5</td><td align=\"left\"><bold>0.74</bold></td><td align=\"left\">0.16</td><td align=\"left\">0.09</td><td align=\"left\">0.13</td><td align=\"left\">-0.03</td><td align=\"left\">0.14</td><td align=\"left\">0.16</td><td align=\"left\">0.06</td><td align=\"left\">0.18</td></tr><tr><td align=\"left\">BP1</td><td align=\"left\">0.20</td><td align=\"left\">0.24</td><td align=\"left\">0.07</td><td align=\"left\">0.04</td><td align=\"left\">0.04</td><td align=\"left\">0.08</td><td align=\"left\"><bold>0.86</bold></td><td align=\"left\">0.05</td><td align=\"left\">0.09</td></tr><tr><td align=\"left\">BP2</td><td align=\"left\">0.20</td><td align=\"left\">0.32</td><td align=\"left\">0.07</td><td align=\"left\">0.07</td><td align=\"left\">0.03</td><td align=\"left\">0.06</td><td align=\"left\"><bold>0.83</bold></td><td align=\"left\">0.09</td><td align=\"left\">0.04</td></tr><tr><td align=\"left\">HT</td><td align=\"left\">0.15</td><td align=\"left\">0.27</td><td align=\"left\">0.04</td><td align=\"left\">0.20</td><td align=\"left\">0.03</td><td align=\"left\">-0.06</td><td align=\"left\">0.09</td><td align=\"left\">-0.01</td><td align=\"left\"><bold>0.68</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T8\"><label>Table 8</label><caption><p>Factor analysis matrix of QOLRAD items in five factors.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Item</td><td align=\"center\" colspan=\"5\">Factors</td></tr></thead><tbody><tr><td/><td align=\"left\">1</td><td align=\"left\">2</td><td align=\"left\">3</td><td align=\"left\">4</td><td align=\"left\">5</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\">Q4001</td><td align=\"left\">0.797</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4002</td><td align=\"left\">0.526</td><td/><td/><td align=\"left\">0.784</td><td/></tr><tr><td align=\"left\">Q4003</td><td align=\"left\">0.677</td><td/><td/><td/><td align=\"left\">0.576</td></tr><tr><td align=\"left\">Q4004</td><td align=\"left\">0.874</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4005</td><td align=\"left\">0.808</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4006</td><td align=\"left\">0.852</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4007</td><td align=\"left\">0.879</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4008</td><td align=\"left\">0.829</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4009</td><td align=\"left\">0.826</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4010</td><td align=\"left\">0.903</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4011</td><td align=\"left\">0.867</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4012</td><td align=\"left\">0.912</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4013</td><td align=\"left\">0.890</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4014</td><td align=\"left\">0.812</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4015</td><td align=\"left\">0.931</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4016</td><td align=\"left\">0.736</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4017</td><td align=\"left\">0.879</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4018</td><td align=\"left\">0.954</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4019</td><td align=\"left\">0.940</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4020</td><td align=\"left\">0.516</td><td align=\"left\">0.794</td><td/><td/><td/></tr><tr><td align=\"left\">Q4021</td><td align=\"left\">0.796</td><td/><td align=\"left\">0.557</td><td/><td/></tr><tr><td align=\"left\">Q4022</td><td align=\"left\">0.825</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4023</td><td align=\"left\">0.938</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4024</td><td align=\"left\">0.954</td><td/><td/><td/><td/></tr><tr><td align=\"left\">Q4025</td><td align=\"left\">0.930</td><td/><td/><td/><td/></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>A pilot survey of GERD incidence in general population, China. English and Mandarin Chinese translations of a survey instrument for the study of gastroesophageal reflux disease (GERD) in China, including a general information questionnaire, the Reflux Disease Questionnaire, the Quality of Life in Reflux and Dyspepsia Questionnaire, and the GERD Impact Scale.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>GERD: gastroesophageal reflux disease; QOLRAD: Quality of Life in Reflux and Dyspepsia questionnaire; RDQ: Reflux Disease Questionnaire; SF-36: 36-item Short-Form Health Survey.</p></table-wrap-foot>", "<table-wrap-foot><p>*Totals may not tally exactly where individual subjects have refused to answer a specific question.</p><p>^†2000 Yuan is equivalent to approximately 260 USD, at an approximate exchange rate of 7.7 Yuan = 1 USD (April 2007).</p></table-wrap-foot>", "<table-wrap-foot><p>*Cohen's kappa coefficient for the RDQ, GERD Impact Scale and QOLRAD; intraclass correlation coefficient for SF-36. GERD: gastroesophageal reflux disease; RDQ: Reflux Disease Questionnaire; QOLRAD: Quality of Life in Reflux and Dyspepsia questionnaire; SF-36: 36-Item Short-Form Health Survey.</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold indicate correlation coefficient ≥ 0.6.</p><p>GERD: gastroesophageal reflux disease; RDQ: Reflux Disease Questionnaire</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold indicate correlation coefficient ≥ 0.5.</p><p>RDQ: Reflux Disease Questionnaire.</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold indicate correlation coefficient ≥ 0.5.</p></table-wrap-foot>", "<table-wrap-foot><p>Numbers in bold indicate expected distribution with correlation coefficient ≥ 0.5. Underlined numbers indicate aberrant distribution. BP: bodily pain; GERD: gastroesophageal reflux disease; GH: general health; HT: health transition; MH: mental health; PF: physical function (PFa: strenuous activities; PFb: light activities); RE: role–emotional; RP: role–physical; SF: social function; SF-36: short form-36; VT: vitality.</p></table-wrap-foot>", "<table-wrap-foot><p>QOLRAD: Quality of Life in Reflux and Dyspepsia.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-230X-8-37-1\"/>", "<graphic xlink:href=\"1471-230X-8-37-2\"/>" ]

[ "<media xlink:href=\"1471-230X-8-37-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>As the prevalence of obesity and its related co-morbidities continue to increase worldwide [##REF##15509809##1##], there is considerable effort being devoted to identify genetic pathways and mechanisms that control fat storage. To gain insights into the genetic basis of natural variation in fat storage, we have used <italic>D. melanogaster </italic>as a model system. Like mammals, insects store fat as TAG in neutral lipid droplets that are accumulated in the fat body, the functional equivalent of both mammalian liver and white adipose tissue. <italic>Drosophila </italic>shares many of the components of TAG biosynthesis, degradation, and regulation with mammals, including many of those implicated in human lipodystrophies, diabetes, and obesity [##REF##16011476##2##]. <italic>D. melanogaster </italic>has proven to be an important model system to identify genetic loci that contribute to variation in quantitative traits, including lipid metabolism [##REF##16222063##3##,##REF##16756480##4##]. In contrast to rodent and human mapping efforts where high-resolution mapping is constrained by intensive labor demands and expense [##REF##16524828##5##], in <italic>Drosophila </italic>the transition from chromosomal regions [quantitative trait loci (QTL)] identified by recombination mapping to candidate genes [quantitative trait genes (QTGs)] is made possible through the use of quantitative complementation (QC) tests with deficiency and mutant stocks [##REF##16756480##4##,##REF##15172667##6##]. This approach has been highly effective for identifying genetic loci within QTL that contribute to variation in several <italic>Drosophila </italic>traits, including low heritability traits such as olfactory behavior and life-span [##REF##16756480##4##,##REF##17634590##7##]. The QC test has been also used in mice to investigate the effect of a mutation of the <italic>Rgs2 </italic>gene on anxiety behaviors [##REF##15489855##8##]. Recently, <italic>Drosophila </italic>deficiency mapping has been greatly enhanced by the release and availability of the DrosDel and Exelixis deficiency stocks in which all deficiencies occur in the same genetic background and have molecularly defined breakpoints [##REF##17720900##9##,##REF##14981519##10##]. The availability of Exelixis <italic>P </italic>and <italic>piggyBac </italic>stocks with single gene insertions all in the same co-isogenic background [##REF##14981521##11##] has also significantly improved our ability to identify positional candidate genes within refined QTL regions.</p>", "<p>We previously mapped multiple QTL responsible for natural variation in TAG storage using a population of recombinant inbred (RI) lines derived from two unrelated <italic>Drosophila </italic>strains, <italic>Ore</italic>gon R (<italic>ORE</italic>) and Russian <italic>2b </italic>(<italic>2b</italic>) [##REF##16222063##3##]. In this study we used quantitative deficiency mapping to fine-map two of the TAG QTL, one encompassing the cytological region 27B-30D on chromosome 2 and the other encompassing 63A-65A on chromosome 3. Subsequently, we performed QC tests with single gene mutant stocks to identify four candidate genes influencing TAG levels. One of the genes identified is <italic>uncoupling protein 4c </italic>(<italic>Ucp4c</italic>), which encodes a product involved in uncoupling of oxidative phosphorylation in mitochondria [##REF##15608223##12##]. Notably, two mammalian homologues of <italic>Ucp4c</italic>, ubiquitous UCP2 and skeletal-muscle-specific UCP3, have already been shown to regulate mammalian fatty acid metabolism [##REF##15621064##13##]. In addition, several human population studies have reported a strong association between polymorphic variants in <italic>UCPs </italic>genes and BMI [##REF##11709074##14##]. The remaining three genes are novel candidate genes affecting fat storage: <italic>CG9135</italic>, <italic>CG1399</italic>, and <italic>Laminin A (LanA)</italic>. <italic>CG9135 </italic>and <italic>CG1399 </italic>belong to a family of genes of unknown function [##REF##15608223##12##]. <italic>LanA </italic>encodes a protein belonging to the α subfamily of laminin chains [##REF##15608223##12##]. Laminins are heterotrimeric glycoproteins present in the basement membrane matrix where they play a role in cell-matrix adhesion, migration, growth, and differentiation of various cell types [##REF##10842354##15##]. While in mammals different combinations of five α, four β and three γ chains can assemble into at least 15 diverse laminins [##REF##10842354##15##], <italic>Drosophila </italic>appears to use only one β, oneγ, and two α chains [##REF##15608223##12##]. The <italic>Drosophila </italic>laminin A chain has significant sequence homology with mammalian laminin α5 chain [##REF##7499364##16##]. In humans, laminin α5 is encoded by the <italic>LAMA5 </italic>gene, which spans approximately 78 kb on chromosome 20q13.2-q13.3 [##REF##9271224##17##]. Several genome-wide linkage scans have linked this chromosomal region 20q13.2-q13.3 to variation in body mass index (BMI) and percentage body fat [##REF##16741264##18##]. In addition, QTL affecting body weight and adiposity have been mapped to a region on mouse chromosome 2 that is syntenic with chromosome 20q13.2-q13.3 in humans [##REF##16741264##18##]. Taken together with our results from <italic>Drosophila</italic>, these observations suggested that polymorphisms in <italic>LAMA5 </italic>contribute to natural variation in body weight and adiposity in humans. To explore this hypothesis we examined the association between genetic variants in the human <italic>LAMA5 </italic>gene and phenotypic variation in several anthropometric traits, including those reflecting body composition and lipid profile in a in a cohort of 228 unrelated EA and AA pre-menopausal women. We selected three haplotype-tagging SNPs from the International HapMap project <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.hapmap.org\"/>: rs659822 (T &gt; C) in intron 1, rs2297588 (G &gt; A) in intron 51, and rs944895 (T &gt; C) a non-synonymous SNP in exon 68. Our results imply that genetic variation in the <italic>LAMA5 </italic>gene affects variation in human body composition and lipid profile. However, additional genetic work and functional studies will be necessary to identify causal associations.</p>" ]

[ "<title>Methods</title>", "<title><italic>Drosophila </italic>deficiency and mutant complementation mapping</title>", "<title><italic>Drosophila </italic>stocks</title>", "<p>Deficiency stocks used for the deficiency complementation mapping were obtained from the Bloomington Drosophila Stock Center <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.flybase.org\"/>. All deficiencies used in our study are from the Exelixis and DrosDel collections that have been generated in co-isogenic <italic>w</italic>¹¹¹⁸backgrounds [##REF##17720900##9##,##REF##14981519##10##].</p>", "<p>Mutant stocks were obtained from the Bloomington <italic>Drosophila </italic>Stock Center and from Trudy Mackay at NC State. Except for <italic>LanA</italic>^{<italic>BG</italic>02469}, all the mutations are DrosDel and Exelixis <italic>P </italic>and <italic>piggyBac </italic>insertions in the <italic>w</italic>¹¹¹⁸co-isogenic background. <italic>LanA</italic>^{<italic>BG</italic>02469}is a hypomorphic mutation generated by the insertion in the <italic>w</italic>¹¹¹⁸<italic>;Canton S </italic>strain of a <italic>P</italic>-element that is located 339 bp upstream the coding region of the <italic>LanA </italic>gene. Flies were maintained in vials containing 10 ml of standard cornmeal, agar, sugar, and yeast medium at 25°C.</p>", "<title>Experimental design and phenotypic measurements</title>", "<p>We conducted the QC tests with deficiencies and mutations using <italic>ORE </italic>and <italic>2b</italic>, the parental lines used to establish the mapping population for the recombination mapping study [##REF##16222063##3##]. In our experiments, we crossed virgin females from <italic>ORE </italic>and <italic>2b </italic>to males from each deficiency stock and to males from the <italic>w</italic>¹¹¹⁸strain. These crosses produce four possible genotypes: <italic>ORE</italic>/<italic>Deficiency</italic>, <italic>ORE</italic>/<italic>w</italic>¹¹¹⁸and <italic>2b</italic>/<italic>Deficiency</italic>, <italic>2b</italic>/<italic>w</italic>¹¹¹⁸. We measured four replicate trait values of each genotypic class for each sex using the same experimental design described in [##REF##16222063##3##], with the only exception being the way TAG content was measured. Briefly, we kept each genotypic class of flies in four replicate vials, each containing a group of 10 single-sexed individuals. After 4–5 days, we anesthetized each group of flies and measured live weight to 0.01 mg accuracy with an analytical balance. We then homogenized the flies using the protocol described in. We assayed TAG content spectrophotometrically using a commercially available kit (Sigma-Triglyceride Assay Kit) following the manufacturer's suggested protocol. To account for difference in body weight and total protein content, we used the live weight and total protein content as covariates in the analysis of the data. We measured total proteins for each homogenate using a standard Lowry protein assay.</p>", "<p>We conducted the QC test with mutant stocks using the same experimental design described for deficiencies, with the only exception being that nine replicate trait values of each genotypic class were measured for each sex.</p>", "<title>Statistical analyses</title>", "<p>All quantitative complementation tests to deficiencies were carried out simultaneously. A quantitative failure of <italic>ORE </italic>and <italic>2b </italic>QTL alleles to complement a deficiency was inferred if the difference in the mean trait value between the <italic>ORE </italic>and <italic>2b </italic>alleles over the deficiency was significantly greater than the difference in the mean trait value of the <italic>ORE </italic>and <italic>2b </italic>alleles over <italic>w</italic>¹¹¹⁸[##REF##11063689##35##]. In a three-way factorial analysis of covariance (ANCOVA), these differences are indicated by a line-by-genotype (<italic>L </italic>× <italic>G</italic>) or line-by-genotype-by-sex (<italic>L </italic>× <italic>G </italic>× <italic>S</italic>) interaction terms according to the model: <italic>y </italic>= <italic>μ + L + G + S + LW + PRO + L × G + L × S + L × G × S + E</italic>, in which <italic>μ </italic>is the overall mean, <italic>L </italic>is the fixed main effect of line (<italic>ORE </italic>or <italic>2b</italic>), <italic>S </italic>is the fixed main effect of sex, <italic>G </italic>is the fixed main effect of genotype (<italic>Def </italic>or <italic>w</italic>¹¹¹⁸), <italic>LW </italic>and <italic>PRO </italic>are the covariates live body weight and total protein content, and <italic>E </italic>is the error term. A significant <italic>L </italic>× <italic>G </italic>× <italic>S </italic>interaction term is indicative of a sex-specific failure to complement. The deficiencies that showed a significant failure to complement were confirmed by re-testing nine replicate trait values of each genotypic class for each sex. Bonferroni corrections were performed to control for the effect of multiple comparisons.</p>", "<p>The data from QC tests with mutations were analyzed for each sex separately using the two-way factorial model of ANCOVA: <italic>y </italic>= <italic>μ + L + G + LW + PRO + L × G + E</italic>, in which <italic>μ </italic>is the overall mean, <italic>L </italic>is the fixed main effect of line (<italic>ORE </italic>or <italic>2b</italic>), <italic>G </italic>is the fixed main effect of genotype (<italic>Def </italic>or <italic>w</italic>¹¹¹⁸), <italic>LW </italic>and <italic>PRO </italic>are the covariates live body weight and total protein content, and <italic>E </italic>is the error term. We inferred a quantitative failure of <italic>ORE </italic>and <italic>2b </italic>QTL alleles to complement the mutant allele if the <italic>L </italic>× <italic>G </italic>interaction term was significant. In addition, as no significant difference in TAG content was observed between the parental lines <italic>ORE </italic>and <italic>2b</italic>[##REF##16222063##3##], we also considered a significant <italic>L </italic>term as a failure to complement, if the difference between the parental strains was significant in the mutant background but not in the <italic>w</italic>¹¹¹⁸chromosome background [##REF##16222063##3##]. Bonferroni corrections were performed to control for the effect of multiple comparisons.</p>", "<p>The statistical analyses were carried out using the SAS GLM procedures (Version 9.0; SAS Institute, 2002, Cary, NC, USA).</p>", "<title>Human study</title>", "<title>Subjects</title>", "<p>A total of 228 European-American (n = 101) and African-American (n = 127) women were evaluated for the human association study. Subjects were participants of two ongoing longitudinal studies on the role of metabolism in the etiology of obesity conducted in AA and EA pre-menopausal women at the University of Alabama at Birmingham. Prior to testing, subjects were maintained in a weight-maintenance state for 4 weeks. During the final 2 weeks, meals were provided through the General Clinical Research Center at UAB to ensure weight stability of less than 1% variation and to maintain daily macronutrient intake in the range of 20–23% fat, 16–23% protein, and 55–64% carbohydrate. Subjects were then admitted as inpatients to the GCRC for 4 days, during the follicular phase of the menstrual cycle. All metabolic testing took place during this inpatient period. At the time of testing, subjects were sedentary (no previous history of exercise training), had a BMI range between 24 – 30 kg/m², were nonsmokers, and were not taking any medication known to alter body composition (including hormones). Race was determined by self-reported African-American or Caucasian ancestry in both parents and grandparents.</p>", "<p>The study protocol was approved by the Institutional Review Board for human studies at the University of Alabama at Birmingham. A written informed consent was obtained from all study participants before enrolling in the study.</p>", "<title>Anthropometrical and serum lipid measurements</title>", "<p>Height and body weight were measured in light indoor clothes and without shoes. Blood samples were withdrawn after 12-h overnight fast. Analyses for serum lipids were performed in the Core Laboratory of the General Clinical Research Center and the Clinical Nutrition Research Center (CNRU) at UAB. Total cholesterol, HDL-C, and TAGs were measured with the Ektachem DT II System. With this system, HDL-C is measured after precipitation of low-density lipoprotein cholesterol (LDL-C) and very-low-density lipoprotein cholesterol with dextran sulfate and magnesium chloride. Control sera of low and high substrate concentration are analyzed with each group of samples, and values for these controls must fall within accepted ranges before samples are analyzed. The DT II is calibrated every six months with reagents supplied by the manufacturer. LDL-C was estimated using the Friedewald formula [##REF##4337382##36##].</p>", "<title>Body composition</title>", "<p>Body composition [TFM and LTM] was measured by dual energy X-ray absorptiometry using either a Lunar DPX-L densitometer (LUNAR Radiation Corp., Madison, WI) or a LUNAR Prodigy densitometer in the Department of Nutrition Sciences at UAB. Body composition assessed by these instruments generally differs by a coefficient of variation of 4% or less [##UREF##0##37##]. Subjects were scanned in light clothing while lying flat on their backs with arms at their sides.</p>", "<title>Genotyping</title>", "<p>To test for associations between genetic variants in human <italic>LAMA5 </italic>and phenotypic traits, we selected three of the human <italic>LAMA5 </italic>SNPs identified by the International HapMap project. Using HapMap data release #21a, we estimated that these three SNPs captured 95.6% of common variation (Minor Allele Frequency &gt;0.05, <italic>n </italic>= 23) at an <italic>r</italic>²&gt; 0.8 across <italic>LAMA5 </italic>gene. The genotypes of these polymorphisms were determined by Pyrosequencing technology [##REF##9705713##38##] at the CNRU Genetics Core at UAB.</p>", "<p>To account for the confounding effects of population stratification, we used estimates of genetic admixture as a covariate in statistical models. The genetic admixture estimates were obtained from the genotyping of ancestry informative markers (AIMs) across the human genome. These AIMs are informative for parental ancestry, defined as those long-separated populations that intermixed during historical periods to produce new admixed populations. Genotyping for the measures of genetic admixture was performed at Prevention Genetics <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.preventiongenetics.com\"/> using the McSNP method and agarose gel electrophoresis, as previously described [##REF##11233605##39##]. Molecular techniques for the allelic identification and methodology for genetic admixture application have been described elsewhere[##REF##11150049##40##,##REF##12579416##41##]. Approximately 100 ancestry informative markers were utilized for the study. Information regarding marker sequences, experimental details, and parental population allele frequencies has been submitted to dbSNP <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/SNP/\"/> under the handle PSU-ANTH.</p>", "<title>Data Analyses</title>", "<p>We assessed Hardy-Weinberg equilibrium, estimated haplotype frequencies, and r²linkage disequilibrium coefficients by methods implemented in Arlequin program 3.01 [##UREF##1##42##]. Allele and genotype frequency comparisons between EA and AA samples were performed by the χ²test. To test the effect of each genotyped SNP on trait variation, we performed genotypic associations for dominant, additive, and recessive models using linear regression analysis. Age and genetic admixture were used as covariates in all the analyses. As strong correlations have been shown between fat mass and lipid profile [##REF##12589969##43##], lipoprotein levels were additionally adjusted for TFM and TAGs. TAG levels were also adjusted for TFM. Dummy variables were assigned to code the three genotypes in each model. In the additive model, we used 0, 1 and 2 to code for individuals homozygous for the major allele, heterozygous, and homozygous for the minor allele, respectively. In the dominant and recessive models, we used 0 to code for individuals homozygous for the major and minor alleles, respectively, and 1 to code for individuals carrying at least one copy of the other allele. Pair-wise haplotype-based association analyses were also performed. For all regression models, studentized residuals were evaluated for normality and logarithmic transformations of the dependent variable was performed to improve normality. When normality of the residuals was not obtained after transformations, the observations that were above and below three standard deviations were removed from the analyses. To test for significant differences among means according to genotype, data from the final regression model was analyzed by analysis of variances and mean differences assessed by post-hoc Duncan tests at <italic>P </italic>&lt; 0.05. To control for the effect of multiple comparisons, we performed permutation tests (1000 simulations) to generate empirical <italic>P </italic>values under the null hypotheses of no association between genotypes and traits [##REF##8770605##19##]. All the analyses were performed using SAS (Version 9.0; SAS Institute, 2002, Cary, NC, USA).</p>" ]

[ "<title>Results</title>", "<title>Fine mapping and identification of positional candidate genes for TAG storage in <italic>Drosophila</italic></title>", "<p>We tested the effects of 38 deficiencies that span the QTL intervals at cytological regions 27B-30D and 63A-65A. After Bonferroni corrections for multiple comparisons, seven deficiencies significantly failed to complement the TAG storage phenotypes of <italic>ORE </italic>and <italic>2b </italic>in the 27B-30D QTL region and four deficiencies in the 63A-65A QTL region (Figure ##FIG##0##1##). The combined data therefore revealed multiple sub-QTL regions each containing at least one gene affecting variation in TAG storage (Figure ##FIG##0##1##).</p>", "<p>To identify candidate genes affecting TAG levels we then performed QC tests using crosses of the <italic>ORE </italic>and <italic>2b </italic>parental strains to mutants of 21 of the genes that map in the refined sub-QTL regions (see Additional File ##SUPPL##0##1##: Summary of quantitative complementation tests with mutants of positional candidate genes in <italic>D. melanogaster</italic>). Four of the genes tested showed a quantitative failure to complement, indicating that allelic differences between <italic>ORE </italic>and <italic>2b </italic>strains at these loci contribute to the differences in TAG storage between the two strains: <italic>Ucp4c</italic>, <italic>CG9135</italic>, <italic>CG13993</italic>, and <italic>LanA </italic>(see Additional File ##SUPPL##0##1##: Summary of quantitative complementation tests with mutants of positional candidate genes in <italic>D. melanogaster</italic>).</p>", "<title><italic>Drosophila LanA </italic>influences TAG storage, live weight, and total protein content</title>", "<p>To independently verify the effect of the <italic>LanA </italic>gene on TAG storage, we measured this trait in flies that were homozygous for the insertional mutation <italic>LanA</italic>^{<italic>BG</italic>02469}and non-mutant flies from the co-isogenic control line. We also investigated the effects of the insertion on live body weight and total protein content. For male flies, we found no significant difference between mutant and controls for TAG and live body weight (Figure ##FIG##1##2a## and ##FIG##1##2b##). However, <italic>LanA</italic>^{<italic>BG</italic>02469}male flies had slightly reduced total protein content (<italic>P </italic>= 0.0486) compared to controls (Figure ##FIG##1##2c##). On average, total protein content of <italic>LanA</italic>^{<italic>BG</italic>02469}males was 10% lower than that of controls. While the effect on males was minimal, the <italic>LanA</italic>^{<italic>BG</italic>02469}mutation had a dramatic effect on female traits. Females with the <italic>LanA</italic>^{<italic>BG</italic>02469}mutation had significantly lower TAG storage (<italic>P </italic>= 0.0068), live body weight (<italic>P </italic>= 0.0092), and total protein content (<italic>P </italic>= 0.0352) compared to control flies (Figure ##FIG##1##2a–c##). The reductions in female TAG storage, live weight, and total protein content relative to control flies were 10%, 16%, and 29%, respectively.</p>", "<title>Human <italic>LAMA5 </italic>variants contribute to variation in anthropometric traits, body composition, and serum lipids</title>", "<p>Table ##TAB##0##1## summarizes the baseline characteristics of the human cohort stratified by ethnicity. Significant differences in total fat mass (TFM), serum TAG levels, and high density lipoprotein cholesterol (HDL-C) were observed between EA and AA. EA had higher mean TFM and serum TAGs and AA had higher mean HDL-C (Table ##TAB##0##1##).</p>", "<p>The allele and genotype frequencies for each SNP are shown in Table ##TAB##1##2##. All genotype groups were in Hardy-Weinberg equilibrium. There was no difference in allele or genotype frequencies between EA and AA for SNP rs2297588. However, there was a difference in genotype frequencies between EA and AA for SNP rs944895 and rs659822 (Table ##TAB##1##2##). These differences remained when the two populations were tested for pair-wise linkage disequilibrium (LD) between SNPs. In both populations rs2297588 was in weak LD with rs659822 (EA: r²= 0.16; AA: r²= 0.14) and was more highly lined with rs944895 (EA: r²= 0.38; AA: r²= 0.35), whereas rs944895 was associated with rs659822 in the EA population (r²= 0.37), but not in the AA population.</p>", "<p>We next examined whether the SNPs were independently associated with each trait. As significant differences in genotype frequencies were observed for SNP rs944895 and rs659822 between the two populations, we tested the association between SNPs and each trait using the data separately by ethnicity. Age, genetic admixture, and appropriate potential confounding variables were included in the analysis as covariates. While no association was found between SNP rs2297588 and any of the traits (data not shown), we did find significant associations between SNP rs659822 and height, body weight, TFM, and lean tissue mass (LTM) in EA (Table ##TAB##2##3##) assuming a model of additive effects. When we fit the data to a recessive genetic model we also found a significant association between SNP rs659822 and HDL-C in EA (Table ##TAB##2##3##). On average, EA women that are homozygous for the C allele had short stature, lower mean body weight, TFM, and LTM than those homozygous for the T allele (Table ##TAB##2##3##; <italic>P </italic>&lt; 0.05). EA women that were homozygotes for the C allele also had higher levels of HDL-C than those carrying at least one T allele (Table ##TAB##2##3##; <italic>P </italic>&lt; 0.05). The association between SNP rs659822 and variation in weight and LTM was also observed in AA women (Table ##TAB##2##3##). In this case, however, AA women homozygous for the SNP rs659822 C allele had <italic>higher </italic>mean weight and LTM than those homozygous for the T allele or heterozygous (Table ##TAB##2##3##; <italic>P </italic>&lt; 0.05). Finally, significant associations were observed in AA women between alternative alleles at rs944895 and variation in serum TAG levels and HDL-C assuming the additive and dominant models, respectively (Table ##TAB##2##3##). On average, AA women homozygous for the T allele had lower TAG levels than those homozygous for the C allele and lower HDL-C than those carrying at least one C allele (Table ##TAB##2##3##; <italic>P </italic>&lt; 0.05).</p>", "<p>Except for the association between SNP rs659822 and weight in AA women, all the single-marker associations remained significant at an experiment-wise <italic>P </italic>= 0.05 after allowing for multiple testing by permutation analysis [##REF##8770605##19##]. Pair-wise haplotype-based association analyses did not increase the power of these associations (data not shown).</p>" ]

[ "<title>Discussion</title>", "<p>We performed quantitative deficiency mapping to dissect two previously identified QTL regions influencing variation in TAG storage among a set of RI lines established from two strains of <italic>D. melanogaster</italic>, <italic>ORE </italic>and <italic>2b </italic>[##REF##16222063##3##]. The fine mapping revealed that the two QTL broke down into multiple sub-QTL regions (Fig. ##FIG##0##1##). This indicates that the number of loci influencing variation in TAG levels among these RI lines is much greater than the number suggested by the initial QTL mapping. This finding is consistent with other studies that have fine-mapped QTL for several quantitative traits in <italic>Drosophila </italic>and mice [##REF##16756480##4##,##REF##10645948##20##,##REF##11526390##21##] and corroborates the complexity of the genetic architecture of quantitative traits.</p>", "<p>Several QTL have been associated with BMI, body weight, fat mass, and fat-free mass in human linkage studies [##REF##16741264##18##]. If the complexity observed in model systems turns out to be a common phenomenon also in human traits, then the identification of the genes underlying variation in these traits will remain a challenge. There is increasing evidence that genome-wide association (GWA) studies are a powerful method for identifying genes involved in human complex traits [##REF##17360987##22##]. Taking advantage of the block-like patterns of LD that characterize the human genome [##REF##11967554##23##], these studies rely on the use of hundreds of thousands of \"tagging\" markers that can capture a significant proportion of the genetic variation and provide power to detect associations. However, one limitation of this approach is that linkage of the markers with variants in a number of genes in the block can make it difficult if not impossible to identify the casual variant affecting the trait. In addition, because of the well-known context dependency of allelic effects of QTL on quantitative traits (e.g. epistasis and genotype by environment interaction) [##REF##16756480##4##], association studies in controlled environments and defined genetic background will potentially allow a more detailed picture of the complexity of the genetic architecture of quantitative traits than that provided by human studies. Studies using <italic>D. melanogaster </italic>and other model systems will continue to play an important role in pinpointing potential candidate loci affecting quantitative traits.</p>", "<p>Using QC tests to mutants of positional genes, we identified <italic>Ucp4c</italic>, <italic>CG9135</italic>, <italic>CG13993</italic>, and <italic>LanA </italic>as candidate loci that influence variation in TAG storage between ORE and 2b. Notably, three of the implicated loci, <italic>Ucp4c</italic>, <italic>CG9135</italic>, and <italic>CG13993</italic>, are tightly linked, with <italic>CG9135 </italic>and <italic>CG13993 </italic>being only 9 kb apart [##REF##15608223##12##]. These however represent only a fraction of the genes underlying the QTL effects identified in this study. Together, there are 286 genes currently mapped in the refined QTL regions. Mutant stocks for 99 of these genes are available from the <italic>Drosophila </italic>stock center. Many of these mutants are in different genetic backgrounds making it difficult to distinguish allelic effects on a trait at the tested locus from epistatic effects with genetic background. In this study we therefore chose to focus only on loci with mutations in the same genetic background of their controls. QC tests to all available mutations of the genes mapping within the refined regions are underway.</p>", "<p>Our studies in flies further suggest that the effect of <italic>Drosophila LanA </italic>is not limited to TAG storage, but it extends to body weight and whole-body protein content. The observed result on body weight is interesting since three-week old mice homozygous for a hypomorphic mutation in the <italic>LAMA5 </italic>gene, the mammalian homolog of <italic>LanA</italic>, have smaller size than their controls [##REF##16790509##24##]. Here we report that natural variation in this gene may contribute to the underlying variation in these traits in human populations. We identified a significant association between a T/C variant in the human <italic>LAMA 5 </italic>intron 1 (rs659822) and height, body weight, TFM, LTM, and HDL-C in EA women. EA women homozygous for the less frequent variant (CC) on average had lower body weight, TFM, and LTM than those homozygous for the T allele. The effect of SNP rs659822 on weight and LTM was also observed in AA women. In this case, however, AA women that were homozygous for CC at this SNP had higher weight and LTM than women homozygous TT. The opposite effect of rs659822 genotypes on body weight and LTM in the two ethnic groups is intriguing and might be explained by the complexity of the processes that determine variation in these traits, including allelic epistatic interactions within the <italic>LAMA5 </italic>gene and interactions with other genes and with the environment. In this regard it is important to point out that the genotype frequencies of SNP rs659822 were significantly different across these two groups, with the frequency of the genotype CC being significantly lower in EA women than in AA (Table ##TAB##2##3##). This sensitivity of the allelic effects of SNPs on phenotypic traits has also been observed in disease-marker studies [##REF##17273975##25##] and is implied in QTL studies in plants [##REF##12586715##26##], <italic>Drosophila </italic>[##REF##10924473##27##], and mice [##REF##15166164##28##] that show significant differences in allelic effects on phenotypes depending on the genetic background in which they occur. Lin <italic>et al</italic>. used theoretical modeling to demonstrate that such \"flip-flop\" associations can occur because the lack of consideration of other genetic loci or environmental factors that influence complex traits [##REF##17273975##25##]. They argue that this is particularly important when a non-causal genetic variant that is linked with the causal polymorphism is investigated [##REF##17273975##25##]. Because genotypes of all polymorphic sites in the <italic>LAMA5 </italic>gene were not determined and SNP rs659822 is located in an intron, it is possible that rs659822 is not itself the causal polymorphism, but is in LD with the true causal polymorphism somewhere else in this gene. In our results SNP rs659822 was in weak LD with both rs2297588 (r²= 0.16) and rs944895 (r²= 0.37) in EA and both SNPs were not associated with any of the traits in this ethnic group. This observation suggests that SNP rs659822 is the site with the largest association with the true causal polymorphism. An overview of the pattern of linkage disequilibrium across the <italic>LAMA5 </italic>gene established by the HapMap Project in the CEU population of northern and western European ancestry from Utah showed that SNP rs659822 is in strong LD (r²= 0.73) with a non-synonymous A to G variant in exon 47 (rs2274934) that could be the responsible polymorphism. Notably, this SNP converts the neutral amino-acid asparagine to the negatively charged amino-acid aspartate in one of the laminin EGF-like domains, which have been suggested to act as signals for cellular growth and differentiation [##REF##2666164##29##]. A change in the amino acid structure of this laminin EGF-like domain might explain our finding that variation in <italic>LAMA5 </italic>associates with a pleiotropic effect on both anthropometric traits and body composition.</p>", "<p>We also identified a significant association between a non-synonymous T to C variant in the exon 68 (rs944895) that converts a tryptophan to an arginine in the laminin G (LG)-like 2 domain and variation in serum TAG levels and HDL-C and in AA subjects. AA women homozygous for the less frequent variant (CC) on average had lower serum TAG and HDL-C levels than those homozygous for the T allele. Laminin LG modules have been implicated in interactions with cellular receptors and other extracellular ligands, such as heparan sulfate proteoglycans (HSPGs) [##REF##10963991##30##]. Interestingly, consistent evidence exists that HSPGs play a role in the turnover of lipoproteins, including the uptake of HDL-C in liver [##REF##11212344##31##]. Moreover, cell surface HSPGs contribute to intracellular TAG accumulation in adipocytes [##REF##15636641##32##]. Studies examining the functional effect of rs944895 polymorphism in lipoprotein metabolism will be necessary to understand the mechanisms underlying our findings.</p>", "<p>One limitation of our study is that the human association component involved a fairly small sample size and was restricted only to women. This cohort was chosen because measurements of genetic admixture were available for each individual, which allowed us to adjust for ancestry within ethnic groups and, therefore, limit false-positive results [##REF##17507670##33##]. The human data set was also chosen because it provided detailed measurements of body composition for each individual. Clearly, replication of the results in other human cohorts is necessary [##REF##17554299##34##], but the consistency in genetic effects of this member of the laminin gene family in both the fly and humans supports a generally conserved role for this gene in regulating traits reflecting body composition. This is particularly evident for the effect of the gene on lean tissue mass, which was not only observed in both EA and AA women, but also in male and female <italic>Drosophila</italic>.</p>" ]

[ "<title>Conclusion</title>", "<p>Over the past few years, the number of chromosomal regions that contain one or more genes affecting obesity traits in humans and in mammalian models has dramatically increased [##REF##16741264##18##]. Results from our study indicate that <italic>D. melanogaster </italic>may be a good model to pinpoint those genes with evolutionarily conserved effects on body composition that fall within the large chromosomal regions identified in mammalian QTL studies. Our cross-disciplinary genetic study implicates a member of the laminin gene family as a novel candidate gene affecting variation in body composition traits in natural populations. These observations motivate future studies in independent human populations to verify the effects of this gene.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The objective of the present study was to map candidate loci influencing naturally occurring variation in triacylglycerol (TAG) storage using quantitative complementation procedures in <italic>Drosophila melanogaster</italic>. Based on our results from <italic>Drosophila</italic>, we performed a human population-based association study to investigate the effect of natural variation in <italic>LAMA5 </italic>gene on body composition in humans.</p>", "<title>Results</title>", "<p>We identified four candidate genes that contributed to differences in TAG storage between two strains of <italic>D. melanogaster</italic>, including <italic>Laminin A </italic>(<italic>LanA</italic>), which is a member of the α subfamily of laminin chains. We confirmed the effects of this gene using a viable <italic>LanA </italic>mutant and showed that female flies homozygous for the mutation had significantly lower TAG storage, body weight, and total protein content than control flies. <italic>Drosophila LanA </italic>is closely related to human <italic>LAMA5 </italic>gene, which maps to the well-replicated obesity-linkage region on chromosome 20q13.2-q13.3. We tested for association between three common single nucleotide polymorphisms (SNPs) in the human <italic>LAMA5 </italic>gene and variation in body composition and lipid profile traits in a cohort of unrelated women of European American (EA) and African American (AA) descent. In both ethnic groups, we found that SNP rs659822 was associated with weight (EA: <italic>P </italic>= 0.008; AA: <italic>P </italic>= 0.05) and lean mass (EA: <italic>P= </italic>0.003; AA: <italic>P </italic>= 0.03). We also found this SNP to be associated with height (<italic>P </italic>= 0.01), total fat mass (<italic>P </italic>= 0.01), and HDL-cholesterol (<italic>P </italic>= 0.003) but only in EA women. Finally, significant associations of SNP rs944895 with serum TAG levels (<italic>P </italic>= 0.02) and HDL-cholesterol (<italic>P </italic>= 0.03) were observed in AA women.</p>", "<title>Conclusion</title>", "<p>Our results suggest an evolutionarily conserved role of a member of the laminin gene family in contributing to variation in weight and body composition.</p>" ]

[ "<title>Authors' contributions</title>", "<p>MDL conceived the study, participated in its design and coordination, carried out the <italic>Drosophila </italic>data analysis, and wrote the manuscript. MMC carried out the <italic>Drosophila </italic>complementation tests. KC carried out the human statistical analyses. JRF participated in the design and coordination of the study and the human statistical analyses. KHL carried out the human genotyping. JRF, BAG, and GRH contributed to design and acquisition of human data. BAG and JRF revised critically the manuscript. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Jeff Leips and two anonymous reviewers for comments on earlier versions of the manuscript. This work was supported by NIH grants R01HL80812 (MDL), R01DK49779 (GRH), and R01DK51694 (BAG), General Clinical research Center grant M01RR00032, CNRU grant P30DK56336. Stouffer's Lean Cuisine entrees were provided by the Nestlé Food Co., Solon OH and Smart Ones entrees were provided by H.J. Heinz Foods, Pittsburg, PA.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Quantitative deficiency mapping of <italic>D. melanogaster </italic>TAG QTL</bold>. Long ticks mark sections and short ticks mark subsections of physical maps in the cytological interval 25F5;32B3 on the left (L) arm of chromosome 2 and in the cytological interval 63A6;65E8 on the left arm of chromosome 3. Gray bars represent non-significant deficiencies and red bars correspond to deficiencies with significant failure to complement <italic>ORE </italic>and <italic>2b </italic>QTL for TAG storage. Yellow frames indicate regions where a QTL affecting TAG content between <italic>ORE </italic>and <italic>2b </italic>maps.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Effects of <italic>Drosophila LanA </italic>allele on TAG storage, body weight, and total protein content</bold>. Values represent mean ± SEM of TAG storage (panel a), live body weight (panel b), and total protein content (panel c) for <italic>n </italic>= 9 independent replicates of homozygous <italic>LanA</italic>^{<italic>BG</italic>02469}and wild-type male and female flies.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Characteristics of the human subjects by ethnicity</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Phenotype (unit of measurement)</td><td align=\"center\">European Americans</td><td align=\"center\">African Americans</td></tr><tr><td/><td align=\"center\">(<italic>n </italic>= 101)</td><td align=\"center\">(<italic>n </italic>= 127)</td></tr></thead><tbody><tr><td align=\"left\">Age (yr)</td><td align=\"center\">34.66 ± 6.0</td><td align=\"center\">33.4 ± 5.7</td></tr><tr><td align=\"left\">BMI</td><td align=\"center\">27.56 ± 2.18</td><td align=\"center\">27.50 ± 2.44</td></tr><tr><td align=\"left\">Height (cm)</td><td align=\"center\">165.6 ± 0.6</td><td align=\"center\">163.9 ± 0.6</td></tr><tr><td align=\"left\">Weight (kg)</td><td align=\"center\">75.67 ± 9.1</td><td align=\"center\">73.67 ± 9.0</td></tr><tr><td align=\"left\">Total fat mass (kg)</td><td align=\"center\">32.14 ± 6.9*</td><td align=\"center\">30.29 ± 6.7</td></tr><tr><td align=\"left\">Lean tissue mass (kg)</td><td align=\"center\">40.22 ± 3.6</td><td align=\"center\">39.78 ± 4.4</td></tr><tr><td align=\"left\">Triacylglycerol (mg/dl)</td><td align=\"center\">115.06 ± 57.3***</td><td align=\"center\">67.3 ± 25.6</td></tr><tr><td align=\"left\">Total cholesterol (mg/dl)</td><td align=\"center\">160.24 ± 31.2</td><td align=\"center\">155.86 ± 34.1</td></tr><tr><td align=\"left\">HDL-cholesterol (mg/dl)</td><td align=\"center\">36.14 ± 9.2***</td><td align=\"center\">43.21 ± 10.8</td></tr><tr><td align=\"left\">LDL-cholesterol (mg/dl)</td><td align=\"center\">101.08 ± 26.7</td><td align=\"center\">99.18 ± 31.9</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Allele and genotype frequencies of <italic>LAMA5 </italic>rs659822, rs2297588, and rs944895 polymorphisms in the study sample</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"6\">European Americans</td><td align=\"center\" colspan=\"6\">African Americans</td></tr><tr><td/><td align=\"center\" colspan=\"6\">(<italic>n </italic>= 101)</td><td align=\"center\" colspan=\"6\">(<italic>n </italic>= 127)</td></tr></thead><tbody><tr><td/><td align=\"center\" colspan=\"2\">rs659822</td><td align=\"center\" colspan=\"2\">rs2297588</td><td align=\"center\" colspan=\"2\">rs944895</td><td align=\"center\" colspan=\"2\">rs659822</td><td align=\"center\" colspan=\"2\">rs2297588</td><td align=\"center\" colspan=\"2\">rs944895</td></tr><tr><td colspan=\"13\"><hr/></td></tr><tr><td align=\"left\">Genotype frequency</td><td align=\"center\">TT</td><td align=\"center\">0.455^b***</td><td align=\"center\">GG</td><td align=\"center\">0.524</td><td align=\"center\">TT</td><td align=\"center\">0.416^b**</td><td align=\"center\">TT</td><td align=\"center\">0.229</td><td align=\"center\">GG</td><td align=\"center\">0.551</td><td align=\"center\">TT</td><td align=\"center\">0.260</td></tr><tr><td/><td align=\"center\">TC</td><td align=\"center\">0.416</td><td align=\"center\">GA</td><td align=\"center\">0.446</td><td align=\"center\">TC</td><td align=\"center\">0.495</td><td align=\"center\">TC</td><td align=\"center\">0.543</td><td align=\"center\">GA</td><td align=\"center\">0.417</td><td align=\"center\">TC</td><td align=\"center\">0.520</td></tr><tr><td/><td align=\"center\">CC</td><td align=\"center\">0.129</td><td align=\"center\">AA</td><td align=\"center\">0.030</td><td align=\"center\">CC</td><td align=\"center\">0.089</td><td align=\"center\">CC</td><td align=\"center\">0.228</td><td align=\"center\">AA</td><td align=\"center\">0.032</td><td align=\"center\">CC</td><td align=\"center\">0.220</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">Allele frequency</td><td align=\"center\">T</td><td align=\"center\">0.663^b*</td><td align=\"center\">G</td><td align=\"center\">0.748</td><td align=\"center\">T</td><td align=\"center\">0.664</td><td align=\"center\">T</td><td align=\"center\">0.501</td><td align=\"center\">G</td><td align=\"center\">0.760</td><td align=\"center\">T</td><td align=\"center\">0.520</td></tr><tr><td/><td align=\"center\">C</td><td align=\"center\">0.337</td><td align=\"center\">A</td><td align=\"center\">0.252</td><td align=\"center\">C</td><td align=\"center\">0.336</td><td align=\"center\">C</td><td align=\"center\">0.499</td><td align=\"center\">A</td><td align=\"center\">0.240</td><td align=\"center\">C</td><td align=\"center\">0.480</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">HWE^a</td><td align=\"center\" colspan=\"2\">0.658</td><td align=\"center\" colspan=\"2\">0.117</td><td align=\"center\" colspan=\"2\">0.382</td><td align=\"center\" colspan=\"2\">0.475</td><td align=\"center\" colspan=\"2\">0.149</td><td align=\"center\" colspan=\"2\">0.727</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Mean ± SEM for anthropometric measures, body composition, and serum lipid profile of study subjects stratified according to <italic>LAMA5 </italic>rs659822 or rs944895 genotype and ethnicity.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"4\">European American</td><td align=\"center\" colspan=\"4\">African American</td></tr><tr><td/><td colspan=\"4\"><hr/></td><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">rs659822</td><td align=\"center\">C/C</td><td align=\"center\">C/T</td><td align=\"center\">T/T</td><td align=\"center\"><italic>P</italic>*</td><td align=\"center\">C/C</td><td align=\"center\">C/T</td><td align=\"center\">T/T</td><td align=\"center\"><italic>P</italic></td></tr></thead><tbody><tr><td align=\"left\"> <italic>n</italic></td><td align=\"center\">13</td><td align=\"center\">42</td><td align=\"center\">46</td><td/><td align=\"center\">29</td><td align=\"center\">69</td><td align=\"center\">29</td><td/></tr><tr><td align=\"left\"> BMI</td><td align=\"center\">26.8 ± 0.5</td><td align=\"center\">27.6 ± 0.3</td><td align=\"center\">27.7 ± 0.3</td><td align=\"center\">0.1</td><td align=\"center\">28.2 ± 0.4</td><td align=\"center\">27.2 ± 0.3</td><td align=\"center\">27.4 ± 0.4</td><td align=\"center\">0.3</td></tr><tr><td align=\"left\"> Height (cm)</td><td align=\"center\">162.6 ± 1.2</td><td align=\"center\">164.6 ± 0.8</td><td align=\"center\">167.3 ± 1.1</td><td align=\"center\"><bold>0.02</bold></td><td align=\"center\">164.9 ± 1.2</td><td align=\"center\">164.1 ± 0.8</td><td align=\"center\">162.5 ± 1.4</td><td align=\"center\">0.2</td></tr><tr><td align=\"left\"> Weight (kg)</td><td align=\"center\">69.8 ± 2.3</td><td align=\"center\">74.7 ± 1.3</td><td align=\"center\">78.2 ± 1.4</td><td align=\"center\"><bold>0.008</bold></td><td align=\"center\">76.5 ± 1.7</td><td align=\"center\">73.2 ± 1.1</td><td align=\"center\">71.9 ± 1.5</td><td align=\"center\">0.05</td></tr><tr><td align=\"left\"> Total fat mass (kg)</td><td align=\"center\">28.8 ± 1.9</td><td align=\"center\">31.5 ± 1.0</td><td align=\"center\">33.7 ± 1.0</td><td align=\"center\"><bold>0.01</bold></td><td align=\"center\">31.3 ± 1.2</td><td align=\"center\">30.3 ± 0.9</td><td align=\"center\">29.4 ± 1.1</td><td align=\"center\">0.3</td></tr><tr><td align=\"left\"> Lean tissue mass (kg)</td><td align=\"center\">37.6 ± 0.8</td><td align=\"center\">39.9 ± 0.5</td><td align=\"center\">41.2 ± 0.5</td><td align=\"center\"><bold>0.003</bold></td><td align=\"center\">41.4 ± 0.8</td><td align=\"center\">39.5 ± 0.5</td><td align=\"center\">38.7 ± 0.8</td><td align=\"center\"><bold>0.03</bold></td></tr><tr><td align=\"left\"> Triacylglycerol (mg/dl)</td><td align=\"center\">104.9 ± 11.5</td><td align=\"center\">120.5 ± 11.4</td><td align=\"center\">112.9 ± 6.3</td><td align=\"center\">0.8</td><td align=\"center\">68.1 ± 4.7</td><td align=\"center\">65.8 ± 3.2</td><td align=\"center\">70.3 ± 4.3</td><td align=\"center\">0.6</td></tr><tr><td align=\"left\"> Total cholesterol (mg/dl)</td><td align=\"center\">153.4 ± 6.3</td><td align=\"center\">163.0 ± 4.9</td><td align=\"center\">159.6 ± 4.9</td><td align=\"center\">0.8</td><td align=\"center\">162.3 ± 6.5</td><td align=\"center\">150.1 ± 3.8</td><td align=\"center\">163.1 ± 6.9</td><td align=\"center\">0.6</td></tr><tr><td align=\"left\"> HDL-cholesterol (mg/dl)</td><td align=\"center\">42.4 ± 2.4</td><td align=\"center\">36.0 ± 1.6</td><td align=\"center\">34.5 ± 1.1</td><td align=\"center\"><bold>0.003^a</bold></td><td align=\"center\">46.1 ± 1.8</td><td align=\"center\">41.2 ± 1.3</td><td align=\"center\">45.2 ± 2.1</td><td align=\"center\">0.07^a</td></tr><tr><td align=\"left\"> LDL-cholesterol (mg/dl)</td><td align=\"center\">90.0 ± 5.8</td><td align=\"center\">102.9 ± 4.1</td><td align=\"center\">102.5 ± 4.1</td><td align=\"center\">0.5</td><td align=\"center\">102.7 ± 6.2</td><td align=\"center\">95.8 ± 3.6</td><td align=\"center\">103.8 ± 6.4</td><td align=\"center\">0.9</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">rs944895</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> <italic>n</italic></td><td align=\"center\">9</td><td align=\"center\">50</td><td align=\"center\">42</td><td/><td align=\"center\">28</td><td align=\"center\">66</td><td align=\"center\">33</td><td/></tr><tr><td align=\"left\"> BMI</td><td align=\"center\">26.6 ± 0.7</td><td align=\"center\">27.5 ± 0.3</td><td align=\"center\">27.8 ± 0.3</td><td align=\"center\">0.3</td><td align=\"center\">27.8 ± 0.4</td><td align=\"center\">27.6 ± 0.3</td><td align=\"center\">27.1 ± 0.4</td><td align=\"center\">0.5</td></tr><tr><td align=\"left\"> Height (cm)</td><td align=\"center\">163.1 ± 1.2</td><td align=\"center\">165.6 ± 1.0</td><td align=\"center\">166.0 ± 0.9</td><td align=\"center\">0.3</td><td align=\"center\">163.9 ± 1.4</td><td align=\"center\">164.4 ± 0.8</td><td align=\"center\">163.1 ± 1.2</td><td align=\"center\">0.6</td></tr><tr><td align=\"left\"> Weight (kg)</td><td align=\"center\">70.9 ± 2.8</td><td align=\"center\">75.5 ± 1.3</td><td align=\"center\">76.9 ± 1.3</td><td align=\"center\">0.09</td><td align=\"center\">73.5 ± 1.4</td><td align=\"center\">74.5 ± 1.2</td><td align=\"center\">72.1 ± 1.6</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\"> Total fat mass (kg)</td><td align=\"center\">28.2 ± 2.1</td><td align=\"center\">31.7 ± 1.0</td><td align=\"center\">33.3 ± 1.0</td><td align=\"center\">0.1</td><td align=\"center\">29.9 ± 1.1</td><td align=\"center\">30.7 ± 0.9</td><td align=\"center\">29.7 ± 1.2</td><td align=\"center\">0.5</td></tr><tr><td align=\"left\"> Lean tissue mass (kg)</td><td align=\"center\">38.5 ± 1.1</td><td align=\"center\">40.5 ± 0.6</td><td align=\"center\">40.2 ± 0.5</td><td align=\"center\">0.7</td><td align=\"center\">40.0 ± 0.8</td><td align=\"center\">40.2 ± 0.5</td><td align=\"center\">38.8 ± 0.9</td><td align=\"center\">0.4</td></tr><tr><td align=\"left\"> Triacylglycerol (mg/dl)</td><td align=\"center\">101.8 ± 8.6</td><td align=\"center\">117.3 ± 9.2</td><td align=\"center\">115.2 ± 8.1</td><td align=\"center\">0.9</td><td align=\"center\">78.9 ± 5.1</td><td align=\"center\">65.7 ± 3.1</td><td align=\"center\">60.9 ± 4.0</td><td align=\"center\"><bold>0.02</bold></td></tr><tr><td align=\"left\"> Total cholesterol (mg/dl)</td><td align=\"center\">159.8 ± 7.5</td><td align=\"center\">161.2 ± 4.6</td><td align=\"center\">159.2 ± 4.9</td><td align=\"center\">0.7</td><td align=\"center\">156.5 ± 5.6</td><td align=\"center\">159.4 ± 4.2</td><td align=\"center\">148.3 ± 6.5</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\"> HDL-cholesterol (mg/dl)</td><td align=\"center\">41.2 ± 3.1</td><td align=\"center\">35.1 ± 1.4</td><td align=\"center\">36.3 ± 1.3</td><td align=\"center\">0.5^b</td><td align=\"center\">43.4 ± 2.1</td><td align=\"center\">45.2 ± 1.4</td><td align=\"center\">39.1 ± 1.5</td><td align=\"center\"><bold>0.03^b</bold></td></tr><tr><td align=\"left\"> LDL-cholesterol (mg/dl)</td><td align=\"center\">98.2 ± 8.6</td><td align=\"center\">102.7 ± 3.8</td><td align=\"center\">99.8 ± 4.1</td><td align=\"center\">0.7</td><td align=\"center\">97.4 ± 5.1</td><td align=\"center\">101.1 ± 4.0</td><td align=\"center\">97.0 ± 6.1</td><td align=\"center\">1</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p><bold>Summary of quantitative complementation tests with mutants of positional candidate genes in <italic>D. melanogaster</italic></bold>. The table contains a list of all the positional candidate genes and the corresponding mutant alleles analyzed by quantitative complementation tests. In the table are also reported the cytological positions of the candidate genes and the <italic>P </italic>values for Line and Line × Genotype effects of two-way factorial ANOVAs (see text for further explanation).</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>Values are means ± SD. <italic>P </italic>values for difference between European Americans and African Americans are obtained using Student's <italic>t</italic>-test. *<italic>p </italic>&lt; 0.05 and ***<italic>p </italic>&lt; 0.001.</p></table-wrap-foot>", "<table-wrap-foot><p>^a<italic>P </italic>values of Hardy Weinberg equilibrium (HWE) tests. ^bComparison between racial groups; *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001.</p></table-wrap-foot>", "<table-wrap-foot><p>* <italic>P </italic>values represent the significance of the comparison among genotypes. <italic>P </italic>values without subscript were calculated assuming additive models. <italic>P </italic>values with subscripts (^a) and (^b) were calculated assuming recessive and dominant models, respectively. <italic>P </italic>values significant after permutations tests to correct for multiple comparisons are highlighted in bold case</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2156-9-52-1\"/>", "<graphic xlink:href=\"1471-2156-9-52-2\"/>" ]

[ "<media xlink:href=\"1471-2156-9-52-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Loss of retinal ganglion cells (RGCs) occurs in many pathological situations, and glaucoma is one of the common diseases that lead to RGC loss. A common feature of glaucoma is elevation of intraocular pressure (IOP) that causes progressive axonal degeneration and loss of RGCs. As acute glaucoma is characterised by rapid increase in IOP, acute IOP elevation paradigm in rodents has often been used to study acute IOP elevation-induced retinal ischemic/reperfusion injury and the possible mechanisms underlying acute glaucoma-associated RGC injuries [##REF##14766318##1##, ####REF##1483506##2##, ##REF##10711692##3##, ##REF##16546168##4##, ##REF##16528750##5####16528750##5##].</p>", "<p>It is known that immune responses can influence neuronal survival after injury. Whereas ample evidence pointed to a damaging effect of inflammatory responses of macrophages and T-cells after CNS injury and in autoimmune diseases such as multiple sclerosis and experimental autoimmune encephalomyelitis (EAE) [##REF##1588634##6##, ####REF##1430150##7##, ##REF##2145387##8##, ##REF##7743675##9##, ##REF##8300861##10##, ##REF##8872895##11##, ##REF##11673322##12##, ##REF##12858061##13####12858061##13##], T-cell dependent RGC protection in response to IOP elevation has also been reported in EAE-resistant Fischer 344 (F344) but not EAE-vulnerable Lewis rats [##REF##12147598##14##]. In our earlier study, we found that macrophages, which are another major component of the autoimmune system, responded differently to IOP elevation or optic nerve (ON) injury between F344 and Lewis rats, and such differences led to different extents of RGC survival after IOP elevation or ON injury [##REF##12657687##15##,##REF##18052979##16##]. Macrophage activation in the eye by intravitreal injection of zymosan, a yeast wall preparation, protected RGCs after ON injury whereas the same activation aggravated RGC loss following acute IOP elevation [##REF##12657687##15##, ####REF##18052979##16##, ##REF##17825287##17####17825287##17##]. In addition, under the same condition of either ON injury or acute IOP elevation the same macrophage activation resulted in different extents of RGC survival or loss between F344 and Lewis rats [##REF##18052979##16##,##REF##17825287##17##].</p>", "<p>Phosphatidylinositol 3-kinase (PI3K)/akt and janus kinase (JAK/STAT3) signal pathways are well known to mediate neuronal survival [##UREF##0##18##, ####REF##11591128##19##, ##REF##11749038##20##, ##REF##12019317##21##, ##REF##15936213##22##, ##REF##16168661##23##, ##REF##15998644##24##, ##REF##16417589##25####16417589##25##]. Recently we showed that ON injury or acute IOP elevation activates both pathways in the ganglion cell layer (GCL) [##REF##17869246##26##, ####UREF##1##27##, ##REF##17714182##28####17714182##28##]. However, our recent work also points to paradoxic actions of these two pathways in RGC survival under different pathological conditions. Though both ON injury and acute IOP elevation activate PI3K/akt and JAK/STAT pathways in the GCL, including RGCs, inhibition of these signalling pathways activates macrophages in the eye and contributes to RGC survival after ON injury in F344 rats [##REF##17714182##28##]. However, the same pathway inhibition leads to RGC loss following acute IOP elevation in Sprague Dawley (SPD) rats [##REF##17869246##26##,##UREF##1##27##]. In addition, as mentioned above, we also showed that macrophage activation in the eye by intravitreal injection of zymosan played a protective role in RGCs after ON injury [##REF##12657687##15##,##REF##17714182##28##]. But the same macrophage activation resulted in aggravated RGC loss in an IOP elevation model of the same F344 rat strain [##REF##17825287##17##]. Macrophages thus appear to play an important role in the differences in RGC viability under the two pathological conditions.</p>", "<p>F344 and Lewis rats are inbred strains. They differ in susceptibility to EAE. It is known that the hypothalamic-pituitary-adrenal (HPA) axis modulates autoimmune response and vulnerability to EAE. In contrast to F344 rats, Lewis rats have abnormalities in HPA function. Variation in genotypes that are associated with different disease phenotypes between F344 and Lewis rats have been reported [##REF##11268408##29##]. Furthermore, the greater frequency of CD8⁺regulatory T cells, which functionally inhibit myelin basic protein-reactive T-cells, in F344 than in Lewis rats might contribute to the differing susceptibility to EAE between them [##REF##10229076##30##]. It is currently unknown whether, after acute IOP elevation, 1) inhibition of the PI3K/akt or JAK/STAT pathway aggravates RGC loss in F344 and Lewis rats, 2) autoimmune background influences PI3K/akt and JAK/STAT signaling pathways in RGC survival, and 3) differential actions of macrophages occur in PI3K/akt and JAK/STAT pathway-dependent modulation of RGC survival. PI3K/akt and JAK/STAT pathways play an important role in mediating RGC survival following acute IOP elevation in SPD rats [##REF##17869246##26##,##UREF##1##27##]. Autoimmune background is also known to modulate neuronal viability [##REF##18052979##16##,##REF##17825287##17##]. It is therefore important to clarify the issues as mentioned above. This study, using F344 and Lewis rats, was designed to accomplish these tasks.</p>" ]

[ "<title>Methods</title>", "<p>A total number of 108 young adult (8–10 weeks old) F344 and Lewis rats were used, and each experimental group consisted of 4–6 rats. All experiments conformed to The Chinese University of Hong Kong Animal Experimentation Ethic Committee (AEEC) guidelines and were approved by the AEEC. All possible measures were taken to minimize suffering and limit the number of rats used in this study. All surgery was carried out under anaesthesia with a 1:1 mixture (1.5 ml/kg) of ketamine (100 mg/ml) and xylazine (20 mg/ml).</p>", "<title>Acute IOP elevation and the experimental groups</title>", "<p>The acute IOP elevation procedure has previously been reported [##REF##14638742##39##]. Briefly, a 27-gauge needle was placed in the anterior chamber of the left eye. The needle was connected to a container carrying 500 ml sterile normal saline. The container was raised to a height of 1496 mm above the eye to elevate the IOP to 110 mmHg for 2 hrs. Each strain of rats was allocated to different experimental groups after acute IOP elevation. The first group received no intravitreal injections and served as intact controls. The second group received intravitreal injections of DMSO (3 μl each injection), which is the inhibitor carrier. The third group received intravitreal injections of LY303511 (Calbiochem, San Diego, USA; 2 mM × 3 μl), which was the negative control of PI3k/akt pathway inhibitor LY294002. The fourth and fifth groups received intravitreal injections of PI3k/akt pathway inhibitors LY294002 [2-(4-Morpholinyl)-8-phenyl-1(4H)-benzopyran-4-one hydrochloride, Sigma; 2 mM × 3 μl and KY12420 (Calbiochem, San Diego, USA; 2 mM × 3 μl), respectively. The sixth and seventh groups received intravitreal injections of JAK/STAT pathway inhibitors AG490 [α-Cyano-(3,4-dihydroxy)-N-benzylcinnamide, Calbiochem; USA; 2 mM × 3 μl] and Jak Inhibitor I [2-(1,1-Dimethylethyl)-9-fluoro-3,6-dihydro-7H-benz[h]-imidaz [4,5-f]isoquinolin-7-one; Calbiochem; 2 mM × 3 μl], respectively. Two inhibitors of each pathway, coupled with the available negative control, LY303511, were used in aim to clarify or exclude the possibility of chemical effects of these inhibitors on RGC viability.</p>", "<p>As macrophage activation has been seen to accompany acute IOP elevation and inhibition of PI3k/akt and JAK/STAT pathways, we used clodronate liposomes to remove macrophages in the eye and examined what roles macrophages and the two pathways played in RGC viability. In this part, 1 group received intravitreal injection (3 μl, once only) of clodronate liposomes immediately after acute IOP elevation, 2 groups received immediate intravitreal injection (3 μl, once only) of clodronate liposomes that were followed by 3 intravitreal injections of KY12420 and AG490, respectively, 3, 9 and 15 days later. Both clodronate and liposomes (if prepared of phosphatidylcholine and cholesterol) are not toxic. Liposome-encapsulated clodronate and liposomes containing PBS only (control liposomes) were prepared as previously described [##UREF##2##40##]. Clodronate was a gift of Roche Diagnostics GmbH (Mannheim, Germany). Phosphatidylcholine was obtained from Lipoid GmbH (Ludwigshafen, Germany), and cholesterol purchased from Sigma. Recently we showed that both PBS liposomes and clodronate liposomes applied at this dosage into the eye were not detrimental to RGCs [##REF##17714182##28##,##REF##17724215##31##]. All rats survived for 3 weeks after acute IOP elevation.</p>", "<p>For intravitreal injections of DMSO or the inhibitors, each rat received three posterior chamber eye injections on days 3, 9 and 15 after IOP elevation. Intravitreal injection of 3 μl clodronate liposomes was carried out once only on the day of IOP elevation, which was 3 days prior to pathway inhibitor injection. For the eye injection, the micropipette was deliberately angled to avoid damage to the lens [##REF##10844031##41##].</p>", "<title>Retrograde labeling of viable RGCs</title>", "<p>To retrogradely label viable RGCs, a small piece of gelfoam soaked with 4% FluoroGold (FG, Fluorochrome Inc, Denver, USA) was applied at the newly cut stump of the proximal ON to retrogradely label viable RGCs. Animals survived for another 40 hours to maximize retrograde transport of the dye. Note that RGCs only start to die 5 days after ON axotomy in adult rats [##REF##8027784##42##]. While deeply anaesthetized, the rats were perfused with cold 4% paraformaldehyde in phosphate buffer (0.1 M, pH 7.4). After dissection from the eye-cups, the retinas were post-fixed in 4% paraformaldehyde for 45 min, flat-mounted and temporarily coverslipped in anti-fading medium (Dako Corporation, Carpinteria, CA, USA). The number of FG-labelled RGCs in each field (0.25 × 0.25 mm²), sampled at a fixed distance from one another and in a pattern of grid intersections, was counted throughout the whole retina. A total of 70–80 fields, about 8–10% of the total retinal area, were sampled per retina. The average density of viable RGCs was obtained. This approach avoided problems associated with uneven distribution of RGCs in the retina.</p>", "<p>In a separate experiment, we examined whether intravitreal application of the pathway inhibitors influenced the retrograde transport of FG. One inhibitor of each pathway (AG490 for JAK/STAT pathway and KY12420 for PI3K/akt pathway) was injected intravitreally into eyes of normal rats (n = 3 each group). FG was applied in the same way as above 20 hours after the inhibitor application, and the rats were killed 40 hours after FG application. After counting the number of FG-labeled RGCs, the retinas were immunostained for RGCs using the TUJ1 monoclonal antibody (against βIII-tubulin, BabCO, Richmond, CA, USA). βIII-tubulin has been shown to be an RGC-specific marker in retinal wholemounts [##REF##12657687##15##,##REF##18052979##16##,##REF##17714182##28##,##REF##17724215##31##,##REF##15574731##38##,##REF##14973241##43##,##REF##16210539##44##].</p>", "<title>Immunohistochemical staining of macrophages</title>", "<p>After counting the number of FG-labeled RGCs, retinas were used for immunostaining of macrophages. The retinas were thoroughly washed with PBS and blocked with 10% normal goat serum (NGS), 1% bovine serum albumin (BSA) and 0.2% Triton for 1 hour. They were then immunostained overnight at 4°C with ED1 antibody (1:200, Serotec, Oxford, UK) [##REF##12657687##15##,##REF##17714182##28##], were rinsed with PBS and incubated with conjugated Cy3 (Jackson ImmunoResearch Laboratories, West Grove, PA, USA; 1:400) secondary antibody overnight at 4°C. After 3 washes each for 5 minutes, the retinas were mounted with anti-fading fluorescence mounting medium and examined under the fluorescent microscope. ED1 positive (⁺) cells were counted in the same way as for FG-labeled RGCs.</p>", "<title>Statistical analysis</title>", "<p>Data on RGCs from the different groups were pooled and statistically analysed using Bonferroni test following one-way analysis of variance (ANOVA). Bonferroni test was used to compare mean values among all intra-groups [##REF##12657687##15##,##REF##15574731##38##].</p>" ]

[ "<title>Results</title>", "<title>Effect of inhibition of PI3/akt and JAK/STAT pathways on RGC viability in F344 rats</title>", "<p>Representative photomicrographs showing the appearances of FG-labelled viable RGCs (left column) and ED1⁺macrophages (right column) in normal F344 and Lewis rats or 3 weeks after acute IOP elevation plus various experimental interventions are shown in Figure ##FIG##0##1##. The appearances of FG-labelled viable RGCs 3 weeks after acute IOP elevation alone in both F344 and Lewis rats were previously shown [##REF##17825287##17##]. Compared with normal intact F344 (A) and Lewis (G) rats, significant loss of RGCs was seen 3 weeks after acute IOP elevation and pathway inhibition of PI3K/akt in both strains (C and I, respectively). Clodronate liposomes significantly reduced the number of macrophages in the eye of both strains and, compared with the same strain of rats not receiving clodornate liposomes, significantly enhanced the number of surviving RGCs. However, the extent of surviving RGCs after macrophage removal was still below the intact control, especially in Lewis rats. Similar observations were seen after PI3K/akt pathway inhibition by LY294002 or JAK/STAT pathway inhibition by AG490 and Jak Inhibitor I (images not shown). More surviving RGCs were seen in the central than the peripheral region. No clear change in the retinal thickness was observed before and after the acute IOP elevation [##UREF##1##27##].</p>", "<p>The average numbers ± SEM of surviving RGCs and ED1⁺macrophages were 2356 ± 125/retina and 11 ± 2/retina, respectively, in intact F344 rats (n = 4). The average numbers ( ± SEM) of surviving RGCs in the retinas of the IOP elevation only group (n = 6) and the inhibitor carrier DMSO group (n = 5) were not significantly different from each other (1514 ± 78/retina versus 1314 ± 103/retina; Fig. ##FIG##1##2A##). Intravitreal application of DMSO marginally increased the number of macrophages (81 ± 10/retina versus 137 ± 9/retina) in the eye (Fig. ##FIG##1##2A##). LY303511, the negative control of LY294002 and which contains a single atom substitution in the morpholine ring compared to LY294002 and does not inhibit PI3K even at high concentrations, did not affect RGC survival, but substantially increased the number of macrophages in the eye (n = 5; Fig. ##FIG##1##2A##). Compared with the negative control LY303511 and DMSO groups, significant decreases in RGC survival were observed after intravitreal application of PI3K/akt pathway inhibitor LY294002 or KY12420 (n = 5 in each group; Fig. ##FIG##1##2A##). Concomitant with the decrease in RGC survival was a significant increase in the number of macrophages in the retina (Fig. ##FIG##1##2A##). Significant decrease in the number of surviving RGCs was also seen after intravitreal application of JAK/STAT pathway inhibitor AG490 or Jak Inhibitor I (n = 5 and 6, respectively; Fig. ##FIG##1##2A##). Accompanying the decrease in RGC survival was a significant increase in the number of macrophages in the retina (Fig. ##FIG##1##2A##). These observations are thus similar to what was seen after inhibition of PI3K/akt and JAK/STAT pathways in SPD rats [##REF##17869246##26##,##UREF##1##27##]. Our earlier studies using Western blotting showed that the pathway inhibitors used at these concentrations effectively, though not completely, blocked collective signal transduction of the pathways [##REF##17869246##26##, ####UREF##1##27##, ##REF##17714182##28####17714182##28##].</p>", "<title>Effects of macrophage removal on RGC viability in F344 rats</title>", "<p>We applied a macrophage remover, clodronate liposomes, intravitreally to deplete macrophages in the eye [##REF##17869246##26##, ####UREF##1##27##, ##REF##17714182##28####17714182##28##,##REF##17724215##31##]. As expected, clodronate liposomes applied alone or in combination with KY12420 (n = 5 each group) significantly reduced the number of macrophages in the eye to a level slightly higher than that in DMSO group (Fig. ##FIG##1##2B##). Concomitant with this reduction of macrophages in the eye was significant improvement but not complete recovery in RGC survival in KY12420-treated F344 rats (Fig. ##FIG##1##2B##). Similarly, an increased number of surviving RGCs was also seen after co-application of clodronate liposomes with JAK/STAT pathway inhibitor AG490 (n = 5; Fig. ##FIG##1##2B##). The improvement but not complete recovery of RGC survival after macrophage removal in PI3K/akt or Jak/STAT pathway-inhibited eyes suggested that macrophages and the pathways modulated, in opposite directions, RGC survival after acute IOP elevation in F344 rats.</p>", "<title>Effect of inhibition of PI3K/akt and JAK/STAT pathways on RGC viability in Lewis rats</title>", "<p>The average numbers ± SEM of surviving RGCs and ED1⁺macrophages were 2583 ± 82/retina and 8 ± 1/retina, respectively, in intact Lewis rats (n = 4). The average numbers ( ± SEM) of surviving RGCs and ED1⁺macrophages in the retinas of IOP elevation only (n = 5) and DMSO (n = 4) groups were not significantly different from each other in Lewis rats (Fig. ##FIG##2##3A##). However, the number of surviving RGCs 3 weeks after acute IOP elevation was significantly (6-fold) lower in Lewis than F344 rats (Fig. ##FIG##1##2A## and ##FIG##2##3A##). LY303511 also did not affect RGC survival although it marginally increased the number of macrophages in Lewis rats (n = 5; Fig. ##FIG##2##3##). Even though the levels of RGC survival were already low in the negative control and DMSO groups (Fig. ##FIG##2##3A##), further decrease in RGC survival was still seen after intravitreal application of PI3K/akt pathway inhibitor LY294002 or KY12420 (n = 5 each group). Concomitant with the decrease in RGC survival was a significant increase in the number of macrophages in the retina (Fig. ##FIG##2##3A##). Similarly, intravitreal applications of JAK/STAT pathway inhibitor AG490 or Jak Inhibitor I (n = 5 each group) also resulted in a significant decrease in the number of surviving RGCs and a significant increase in the number of macrophages in the retina (Fig. ##FIG##2##3##).</p>", "<title>Effects of macrophage removal on RGC viability in Lewis rats</title>", "<p>Similar to what occurred in F344 rats, clodronate liposomes applied alone (n = 5) or co-applied with KY12420 (n = 4) or AG490 (n = 5) significantly reduced the number of macrophages in the retina to a level lower than that in the DMSO group (Fig. ##FIG##2##3B##). Concomitant with the reductions of macrophages in the eye was significant improvement but not complete recovery in RGC survival in KY12420- and AG490-treated Lewis rats (Fig. ##FIG##2##3B##). These findings suggested that PI3K/akt and JAK/STAT pathways and macrophages are involved in RGC viability in similar fashion to that in F344 rats following acute IOP elevation.</p>", "<p>To clarify whether the observed reduction of RGC counts after inhibitor application resulted from interfered transport of FG, we carried out another experiment in which both FG and immunohistochemical approaches were used to label RGCs of the same retinas and the numbers of RGCs between the 2 approaches were compared. Compared with the number of TUJ1-immunostained RGCs of the same retinas, there were an average of 15% (n = 3) decrease and 12% (n = 3) increase in the numbers of FG-labeled RGCs in KY12420 and AG490 treatment groups, repsectively. The small differences between the 2 labelling approaches are not statistically significant, indicating that the intravitreal application of the pathway inhibitors does not influence the efficacy of the FG transport. Note that FG was applied 20 hours whereas the data presented below were obtained from rats that received FG 5 days after the administration of the pathway inhibitors. The further delayed application of FG rendered the inhibitors less likely to affect the retrograde transport of FG.</p>" ]

[ "<title>Discussion</title>", "<p>In this study we investigated the roles of PI3K/akt and JAK/STAT pathways and macrophages in RGC viability after acute IOP elevation in F344 and Lewis rats, which are known to have different autoimmune profiles. We show that in both rat strains, inhibition of PI3K/akt or JAK/STAT pathway reduces RGC survival and activates macrophages in the eye. In addition, both macrophage activation and PI3K/akt and JAK/STAT pathways mediate RGC viability, in opposite directions, after acute IOP elevation.</p>", "<p>PI3K/akt and JAK/STAT are known to be the major signalling executors for neuronal survival [##REF##11591128##19##,##REF##11749038##20##,##REF##15998644##24##,##REF##16417589##25##,##REF##10428041##32##, ####REF##10579998##33##, ##REF##10995840##34##, ##REF##11399427##35##, ##REF##14528310##36####14528310##36##]. Whereas PI3K/akt is the common signal transduction pathway underlying neurotrophin-induced biological actions, JAK/STAT is well-documented to be responsible for cytokine-induced effects [##REF##11983158##37##]. Previously we showed that the pathway inhibitors applied at dosages as in this study significantly inhibited signal transduction of the respective pathways [##REF##17869246##26##, ####UREF##1##27##, ##REF##17714182##28####17714182##28##,##REF##15574731##38##]. The clear differences in RGC survival or in macrophage recruitment between eyes treated with LY294002 and with its negative control LY303511 following IOP elevation in both F344 and Lewis rats are similar to what was seen in SPD rats [##REF##17869246##26##,##UREF##1##27##]. These results confirmed that the actions of LY294002 on RGC viability and macrophage recruitment are dependent on PI3k/akt pathway-inhibition. The persistent loss of RGCs after PI3K/akt or JAK/STAT pathway inhibition in the absence of ocular macrophages (following clodronate liposome application) in both strains further verify that these signal transduction pathways mediate RGC survival following acute IOP elevation <italic>independent of </italic>influence of autoimmune background.</p>", "<p>Previously T-cells were shown to play a part in differential protection of RGCs following episcleral and limbal vein cauterization-induced IOP elevation in F344 and Lewis rats [##REF##12147598##14##]. In our earlier study, we showed that macrophage reactions to acute IOP elevation were also different in rats with different autoimmune backgrounds [##REF##17825287##17##]. In the present study we demonstrated that in contrast to the actions on macrophages, autoimmune background did not modulate signal transduction pathways of PI3K/akt and JAK/STAT in RGC survival.</p>" ]

[ "<title>Conclusion</title>", "<p>PI3K/akt and JAK/STAT pathway mediate RGC survival after acute IOP elevation and autoimmune background does not influence the functional roles of these pathways. In addition, PI3K/akt and JAK/STAT pathway inhibition-induced macrophage activation in the eye is detrimental to RGCs following acute IOP elevation.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>We recently showed that whereas inhibition of PI3K/akt or JAK/STAT pathway promoted retinal ganglion cell (RGC) survival after optic nerve (ON) injury in Fischer 344 (F344) rats, the same inhibition resulted in aggravated RGC loss after acute intraocular pressure (IOP) elevation in Sprague Dawley (SPD) rats. In addition, the responses of macrophages to ON injury and acute IOP elevation were different between F344 and Lewis rats, i.e., different autoimmune profiles. Using an acute IOP elevation paradigm in this study, we investigated 1) whether autoimmune background influences PI3K/akt and JAK/STAT functions by examining the effect of PI3K/akt and JAK/STAT pathway inhibition on RGC survival in F344 and Lewis rats, and 2) whether differential actions of macrophages occur in PI3K/akt and JAK/STAT pathways-dependent modulation of RGC survival. IOP elevation was performed at 110 mmHg for 2 hours. PI3K/akt and JAK/STAT pathway inhibitors were applied intravitreally to block their respective pathway signaling transduction. Because macrophage invasion was seen in the eye after the pathway inhibition, to examine the role of these pathways independent of macrophages, macrophages in the retina were removed by intravitreal application of clodronate liposomes. Viable RGCs were retrogradely labelled by FluoroGold 40 hours before animal sacrifice.</p>", "<title>Results</title>", "<p>Similar to what was previously observed, significantly more RGCs were lost in Lewis than F344 rats 3 weeks after acute IOP elevation. As in SPD rats, inhibition of the PI3K/akt or JAK/STAT pathway increased the loss of RGCs in both F344 and Lewis rats. Removal of macrophages in the eye by clodronate liposomes reduced RGC loss due to pathway inhibition in both strains.</p>", "<title>Conclusion</title>", "<p>This study demonstrates that following acute IOP elevation 1) PI3K/akt and JAK/STAT pathways mediate RGC survival in both F344 and Lewis rats, 2) autoimmune responses do not influence the functions of these two pathways, and 3) PI3K/akt and JAK/STAT pathway inhibition-dependent activation of macrophages is detrimental to RGCs.</p>" ]

[ "<title>Abbreviations</title>", "<p>EAE: experimental autoimmune encephalomyelitis; F344: Fischer 344; HPA: hypothalamic-pituitary-adrenal; IOP: intraocular pressure; GCL: ganglion cell layer; JAK: janus kinases; ON: optic nerve; PI3K: phosphatidylinositol 3-kinase; RGC: retinal ganglion cell; SPD: Sprague Dawley; STAT: signal transducers and activators of transcription.</p>", "<title>Authors' contributions</title>", "<p>YH carried out experiments and collected data. ZL carried out the double-labeling experiment. NW participated in the study design. NvR provided reagents (clodronate liposomes). QC designed the study, analyzed the data and drafted the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Profs. Larry Baum and Calvin Pang of The Chinese University of Hong Kong for English editing of this manuscript. This work is supported by The Chinese University of Hong Kong and a grant from National Natural Science Foundation of China (30571990).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Representative fluorescent photomicrographs of retinal wholemounts showing characteristics of retrogradely FG-labeled surviving RGCs (left column) and ED1⁺macrophages (right column).</bold> A and B, normal F344 rat; C and D, after application of pathway inhibitor KY12420 in IOP-elevated F344 rat; E and F, after application of pathway inhibitor KY12420 and clodonate liposomes in IOP-elevated F344 rat; G and H, normal Lewis rat; I and J, after application of pathway inhibitor KY12420 in IOP-elevated Lewis rat; K and L, after application of pathway inhibitor KY12420 and clodonate liposomes in IOP-elevated Lewis rat. More surviving RGCs were seen in F344 than Lewis rats after IOP elevation and pathway inhibition (C versus I). After removal of macrophages by clodronate liposomes, the numbers of surviving RGCs increased in both F344 (E versus C) and Lewis (K versus I) rats. Similar results were obtained after inhibition of JAK/STAT pathway (images not shown). Scale bar = 50 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Average densities (± SEM) of FG-labeled surviving RGCs and ED1⁺macrophages after inhibition of PI3K/akt and JAK/STAT pathways in F344 rats.</bold> Significant decrease in RGC viability and concomitant increase in the number of macrophages were seen following PI3k/akt and JAK/STAT pathway inhibition (A). After macrophage removal (B), pathway inhibition-induced RGC loss was significantly but not completely prevented, indicating that both macrophage and PI3k/akt and JAK/STAT pathways were involved in RGC viability in this strain of rat. *p &lt; 0.05, **p &lt; 0.01 and ***p &lt; 0.001 against DMSO group unless specified.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Average densities (± SEM) of FG-labeled surviving RGCs and ED1⁺macrophages after inhibition of PI3K/akt and JAK/STAT pathways in Lewis rats.</bold> Significant decrease in RGC viability and concomitant increase in the number of macrophages were seen following PI3k/akt and JAK/STAT pathway inhibition (A). After macrophage removal (B), pathway inhibition-induced RGC loss was significantly but not completely prevented, indicating that both macrophage and the pathways were also involved in RGC viability in Lewis rats. Note that the numbers of surviving RGCs were significantly lower in Lewis than F344 rats. *p &lt; 0.05, **p &lt; 0.01 and ***p &lt; 0.001 against DMSO group unless specified.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1471-2202-9-78-1\"/>", "<graphic xlink:href=\"1471-2202-9-78-2\"/>", "<graphic xlink:href=\"1471-2202-9-78-3\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Cyanopeptolins are nonribosomally produced peptides with highly variable composition. The general structure of the cyanopeptolin peptide family encompasses 7 amino acids, including the residue 3-amino-6-hydroxy-2-piperidone (Ahp), where the six C-terminal amino acids form a ring [##UREF##0##1##,##UREF##1##2##] and the N-terminal amino acid frequently is N-modified. The N-terminal amino acid and all positions in the ring except position 2 (threonine) and position 4 (Ahp) can be occupied by variable amino acids, giving rise to a large number of cyanopeptolin variants [##REF##16774586##3##].</p>", "<p>The succession of the modules [##REF##11851476##4##,##REF##7867917##5##] and specificity of A-domain binding pockets in nonribosomal peptide synthetases (NRPSs) [##REF##10712928##6##,##REF##10421756##7##] can give a good prediction of peptide composition and structure. NRPSs do not always perform stringent substrate selection and incorporation [##REF##10421756##7##], thus, relaxed substrate specificity is common in NRPS [##REF##10712928##6##,##REF##9864322##8##,##REF##11851477##9##]. In addition to the common module domains including the adenylation (A)-, condensation (C)- and thiolation (T)-domains, several tailoring domains have been found associated with cyanopeptolin synthetases. Methyltransferases are present in three cyanopeptolin gene clusters from <italic>Anabaena</italic>, <italic>Microcystis </italic>and <italic>Planktothrix </italic>(<italic>apd</italic>, <italic>mcn </italic>and <italic>oci</italic>). Halogenases are found in <italic>apd </italic>and <italic>mcn</italic>, while the tailoring domains responsible for side chain modification of the N-terminal amino acid are unique for each strain (i.e.; formyl transferase in <italic>apd</italic>, sulfotransferase and glyceric acid (GA) transferase in <italic>oci</italic>, absent in <italic>mcn</italic>).</p>", "<p>So far, only cyanopeptolin gene clusters derived from the genera <italic>Anabaena </italic>[##REF##10931313##10##], <italic>Microcystis </italic>[##REF##17464052##11##] and <italic>Planktothrix </italic>[##REF##17921284##12##] have been characterized. They share the same basic domain structure but possess unique tailoring genes and A-domain substrate binding pockets, indicating independent evolution of cyanopeptolin genes within each lineage. Sequence identity is high (approximately 80% in the NRPS module coding regions) between <italic>Microcystis </italic>(<italic>mcn</italic>) and <italic>Planktothrix </italic>(<italic>oci</italic>) cyanopeptolin gene clusters. The more thoroughly investigated microcystin gene clusters show higher sequence identity within a genus than between genera. The same is likely to be the case also for the cyanopeptolin genes.</p>", "<p>Sequence variation in microcystin synthetase clusters has been investigated within strains of the genera <italic>Microcystis </italic>[##REF##11984633##13##,##REF##12700256##14##] and <italic>Planktothrix </italic>[##REF##15870462##15##]. Modifications and reorganizations due to several recombination events have been reported [##REF##12700256##14##, ####REF##15870462##15##, ##UREF##2##16####2##16##], and together with differences in substrate specificity between equivalent A-domains [##REF##12511503##17##, ####REF##15528492##18##, ##REF##17032280##19####17032280##19##] are the reason for the different peptide variants.</p>", "<p><italic>Planktothrix </italic>NIVA CYA 116 (NIVA CYA 116), isolated from a Norwegian lake, produces cyanopeptolin-1138 [##REF##17921284##12##] for which the amino acids configurations are unknown. This peptide was found to be highly similar to oscillapeptin E produced by <italic>Planktothrix </italic>NIES 205 (NIES 205), isolated in Japan [##UREF##3##20##]. Both peptides have the same molecular mass, but slightly different polarities [##REF##17921284##12##]. A different content of L-/D-amino acids in the peptides was suggested as a possible reason for the observed difference [##REF##17921284##12##]. To investigate the genetic basis of the differences between the peptides, we have cloned and sequenced the NIES 205 cyanopeptolin gene cluster and compared it to the previously characterized NIVA CYA 116 gene cluster. This has allowed us to explore NRPS evolution and genetic variations in closely related strains and to investigate to what extent selectional forces operate on these gene clusters.</p>" ]

[ "<title>Methods</title>", "<title>Bacterial cultures</title>", "<p><italic>Planktothrix agardhii </italic>NIVA CYA 116 was isolated in 1983 from Lake Årungen, Norway, and maintained in the NIVA culture collection of Algae. <italic>Planktothrix agardhii </italic>NIES 205 was isolated from Lake Kasumigaura/Ibaraki, Japan in 1982, and maintained in the NIES culture collection [##UREF##3##20##]. Both strains were cultured in Z8 [##REF##4640703##33##] media at ~20°C with 12 hour illumination at about 15 μmol m^-2s^-1in Sanyo versatile environmental test chamber (FG-4P 36–40).</p>", "<title>PCR and sequencing</title>", "<p>DNA from NIES 205 was isolated utilizing Dynabeads (Invitrogen, Carlsbad, USA) [##REF##9067030##34##]. Combinations of PCR primers designed for the cyanopeptolin (<italic>oci</italic>) gene cluster in NIVA CYA 116 [##REF##17921284##12##] were used to amplify regions of a cyanopeptolin gene cluster in NIES 205. These PCR products were sequenced using primer walking. Additional PCR primers were designed to amplify regions between already obtained PCR products. BD Advantage 2 (BD Biosciences, Mountain View, USA) was utilized as polymerase in all PCR amplifications. The PCR products were sequenced using an ABI 3730 sequencer and v3.1 Big Dye solution.</p>", "<title>Sequence analysis and phylogeny</title>", "<p>Open reading frames were identified and translated using Vector NTI (Invitrogen, Carlsbad, USA). Domains and their boundaries were identified using the NRPS database <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.nii.res.in/nrps-pks.html\"/>[##UREF##4##35##], A-domain binding pocket residues identified by aligning the sequences with the GrsA-Phe A-domain [##REF##10712928##6##] and substrate specificity predicted utilizing the NRPS database <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.nii.res.in/nrps-pks.html\"/> and phylogenetic analysis. A-, C-, T- and E- domain protein sequences were aligned using MEGA 3.1 and Neighbor-Joining (NJ) trees were constructed using MEGA 3.1 at default settings (Poisson correction as the amino acid substitution model) [##REF##15260895##36##]. Optimal protein evolution model was found by ProtTest [##REF##15647292##37##]. Trees were constructed utilizing MrBayes [##REF##11524383##38##] 3.0 and 3.1 [##REF##12912839##39##] on the UiO Bioportal <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.bioportal.uio.no\"/>[##UREF##5##40##] with an optimal protein substitution model. Variable substitution rates across sites were accounted for by gamma distribution. The MCMC chains were carried out for 4 million generations and trees were sampled every 100 generations, removing 3000 trees before the MCMC chain reached convergence. In addition, maximum likelihood inferences with RAxML [##REF##16928733##41##] were performed on the E- and C- domain alignments. Similarity calculations were done in Vector NTI. DnaSP [##REF##3444411##42##] was used to calculate Ka/Ks ratio and segregating sites with a sliding window with window length of 50 bp and step size 10 bp.</p>", "<title>Mass spectrometry</title>", "<p>Freeze-dried material of NIVA-CYA116 and NIES 205 was extracted with 50% MeOH (MeOH:water, v/v) and the extracts were subjected to a screening for cyanopeptolins by LC-MS. The instrument included a Waters Acquity UPLC system equipped with an Atlantis column (C18 2.1 × 150 mm, 5 μm particle size) and set to run a linear gradient starting with 80% solvent A (10 mM ammonium acetate, 0.1% acetic acid) and ending with 60% solvent A after 15 min. Solvent B was MeOH with 0.1% acetic acid. The flow rate was 0.2 ml min^-1. The LC system was connected to a Waters Quattro Premier XE tandem quadropole mass spectrometer equipped with an electrospray probe. The detector was run in the positive ion mode at a cone voltage of 50 V. A total ion scan from 600 to 1400 Da was performed during the entire length of the LC gradient.</p>", "<p>The structures of putative cyanopeptolins were analyzed by MS fragmentation studies. MS fragments hold valuable structural information and have been successfully used before to identify and structurally elucidate cyanobacterial oligopeptides including cyanopeptolins [##UREF##6##43##, ####REF##11679328##44##, ##REF##16678305##45####16678305##45##]. Fragmentation experiments were carried out with the hardware configuration described above. The mass spectrometer was run in daughter ion scanning mode and all settings were automatically optimized for fragmentation at 30 eV. Fragments were recorded during the entire length of the LC gradient. The identification of fragments was assisted by the HighChemMassFrontier software version 3.0. This software predicts MS fragmentation patterns on the basis of a putative structure. Comparing predicted and actual fragmentation patterns was used to assess the accuracy of a putative structure. Further hints to the structure were obtained from the occurrence of typical diagnostic ions such as immonium ions and from predictions on the amino acid occurrence made by the genetic analyses.</p>" ]

[ "<title>Results</title>", "<title>NIVA CYA 116 and NIES 205 have similar but not identical peptide profiles</title>", "<p>The major peptides in the two strains consist of HO₃SO-CH₂-CH(OMe)-CO-HTyr-Thr-HTyr-Ahp-Ile-Phe(Me)-Ile ([Table 1, Additional file ##SUPPL##0##1## figure 1] and Rounge <italic>et al </italic>[##REF##17921284##12##]). However, spiking experiments (data not shown) revealed a slight difference in polarity between cyanopeptolin-1138 from NIVA CYA 116 [##REF##17921284##12##] and oscillapeptin E from NIES 205 [##UREF##3##20##]. In contrast to NIVA CYA 116 producing only cyanopeptolins, screening of NIES 205 shows production of additional peptide from other peptide-classes (data not shown).</p>", "<p>Several cyanopeptolin variants were also detected in both strains. LC-MS-MS data identified minute amounts of seven cyanopeptolins in NIVA CYA 116, with variation in the first, third, fifth and/or seventh positions compared to cyanopeptolin-1138/oscillapeptin E [Additional file ##SUPPL##0##1## figure 2]. An earlier study has shown that NIES 205 produce oscillapeptin C, D and E, based on spectroscopic analyses including 2D NMR [##UREF##3##20##]. Our LC-MS-MS analysis of NIES 205 confirmed the production of oscillapeptin D and E, but also identified a cyanopeptolin with the mass 1074, which is found in NIVA CYA 116 as well [Table 1 and Additional file ##SUPPL##0##1## figure 3].</p>", "<p>NIVA CYA 116 and NIES 205 produced similar – but not identical – cyanopeptolin variants. The identified NIVA CYA 116 cyanopeptolins were mainly combinations of Hty/Ile/Leu in positions AA1 and AA3 and Ile/Leu/Val in positions AA5 and AA7. Other unidentified apolar amino acid-like residues were detected in position AA3. In contrast, the only variations observed in the NIES 205 peptides were Hty, Ile/Leu and HcAla in position AA3 (Table ##TAB##0##1##).</p>", "<title>Comparison of the 205-<italic>oci </italic>and 116-<italic>oci </italic>gene clusters</title>", "<p>Anticipating that two strains producing almost identical cyanopeptolins also should contain similar gene clusters, we sequenced a cyanopeptolin gene cluster in NIES 205 (205-<italic>oci</italic>) using primers designed for the cyanopeptolin (<italic>oci</italic>) gene cluster in NIVA CYA 116 (116-<italic>oci</italic>) [##REF##17921284##12##]. The two gene clusters, including the ABC transporter genes and the intergenic spacers, were highly similar (93% identity between the nucleotide sequences), and the domain structures of the encoded synthetases were almost identical; except that 205-<italic>oci </italic>contained an epimerase encoding (E)-domain between T2 and C2 (Figure ##FIG##0##1##). The position of the E-domain corresponds to the Htyr in D-configuration in oscillapeptin E determined by Itou <italic>et al </italic>[##UREF##3##20##]. Both gene clusters included a GA-domain and a sulfotransferase domain. Comparison with cyanopeptolin gene clusters characterized in <italic>Microcystis </italic>(<italic>mcn</italic>) [##REF##17464052##11##] and <italic>Anabaena </italic>(<italic>apd</italic>) [##REF##10931313##10##] (Figure ##FIG##0##1##) showed a higher degree of similarity within the <italic>Planktothrix </italic>genus than between genera (70% identity between OciB and AdpB with the additional methyltransferase excluded and 77% identity between OciC and AdpD). A-domains and A-domain binding pockets signatures were identified from the gene clusters and aligned. The binding pocket signatures in 116-Oci and the corresponding 205-<italic>oci </italic>signatures were identical, except for 116-OciB-A3 (DA<bold>QS</bold>MGAIIK) and 205-OciB-A3 (DA<bold>EG</bold>MGAIIK) (Table ##TAB##0##1##). Corresponding pairs of 205-Oci and 116-Oci A-domains clustered together in phylogenetic analyses that included A-domains from cyanopeptolin [##REF##10931313##10##, ####REF##17464052##11##, ##REF##17921284##12####17921284##12##], microcystin [##REF##12511503##17##,##REF##11033079##21##,##REF##14766543##22##] nostocyclopeptide [##REF##14697508##23##] and nostopeptolide [##REF##12853152##24##] synthetases [Additional file ##SUPPL##0##1## figure 4].</p>", "<p>E-domains are common in cyanobacterial NRPS, found in microcystin, aeruginosin and nostocyclopeptide synthetases, notably, E-domains have until now not been found in cyanopeptolin synthetases. The E-domain produces the D-isomer of the amino acid activated by the upstream A-domain and is also involved in the stereospecific selection of the D-isomer for incorporation in the peptide product. Most E-domains are flanked by T (T_E)- and C-domains with special motives [##REF##11747460##25##,##REF##16182472##26##], and this was the case also in 205-Oci – as shown by the phylogenetic analyses (see Figure ##FIG##1##2##).</p>", "<p>The NIES 205-E-domain is localized downstream of 205-A1 and T2. A phylogenetic analysis of E-domains (Figure ##FIG##1##2##), including E-domains from microcystin synthetase (McyA-E) and nostocyclopeptide synthetase (NcpA-E), showed a close relationship between NcpA-E and 205-OciA-E (72% identity on the DNA and 67% similarity on the protein level).</p>", "<p>Phylogenetic analyses of the C-domains (Figure ##FIG##2##3##), including domains from cyanopeptolin [##REF##10931313##10##, ####REF##17464052##11##, ##REF##17921284##12####17921284##12##], microcystin [##REF##12511503##17##,##REF##11033079##21##,##REF##14766543##22##] nostocyclopeptide [##REF##14697508##23##] and nostopeptolide [##REF##12853152##24##] synthetases, clustered according to presence or absence of an upstream E-domain. The 205-Oci-C2-domain grouped with D-amino acid-specific C-domains, while the other 205-Oci-C domains formed a clade with the corresponding 116-Oci-C-domains.</p>", "<p>The specialized T_E-domains associated with E-domains, show major differences within the core T motif compared to standard T-domains [##REF##11747460##25##]. Comparisons of regular T-domains and T_E-domains, including 205-Oci-T_E2, McnA-T1 and NcpA-T_E1-domain, showed an H/D and L/I difference in addition to a gap in the T_E-domain motif [Additional file ##SUPPL##0##1## figure 5]. N-terminal T-domains, including both 116-T1 and 205-T1, could also be distinguished from T_E-domains and regular T-domains [Additional file ##SUPPL##0##1## figure 5].</p>", "<title>Other genomic regions confirm a close relationship between the <italic>Planktothrix </italic>strains</title>", "<p>Several markers were sequenced to further study the relationship between <italic>Planktothrix </italic>NIVA CYA 116 and NIES 205. The DNA sequences (16S rDNA (1357 bp), a part of <italic>ntcA </italic>(384 bp), a global transcriptional regulator of nitrogen assimilation in cyanobacteria, and the phycocyanin spacer <italic>cpc</italic>BA) displayed 100% identity between the two strains.</p>", "<title>Variation in substitution rates throughout the cyanopeptolin gene clusters</title>", "<p>Investigation of the substitution rates within the 30 kb 116- and 205-<italic>oci </italic>gene cluster alignment can identify both putative recombination events and regions under specific selection pressure. The region containing the epimerization domain (T2, E, C2) was excluded due to too large overall differences to produce a reliable alignment. Figure ##FIG##3##4## shows segregating sites (black lines) and nonsynonymous vs. synonymous substitution rates (red lines) in a sliding window analysis of the alignment. Only a few scattered substitutions can be seen in the first part, containing the ABC transporter, GA, T1, S and C1 domains, and in the last part, containing A6, M, T7, C7, A7, T8 and TE domains. However, the C3 and A3 domains contained several substitutions and the rate of mutations in nonsynonymous sites compared with synonymous sites (Ka/Ks) exceeded 1 – a putative sign of positive selection. A high substitution rate was also observed in a small region in C6 and the last part of A1, but the Ka/Ks ratios did not exceed 1.</p>" ]

[ "<title>Discussion</title>", "<title>Correlation between cyanopeptolin gene clusters and peptides</title>", "<p>The presence of two highly similar NRPS gene clusters (<italic>oci</italic>) in NIVA CYA 116 and NIES 205, and the production of nearly identical peptides by the two strains corroborate the association between the <italic>oci </italic>gene cluster and cyanopeptolin-1138 proposed by Rounge <italic>et al </italic>[##REF##17921284##12##]. This association is further substantiated by high degree of similarity to the cyanopeptolin gene cluster in <italic>Anabaena </italic>(<italic>apd</italic>), where the functional relationship between genes and peptides has been confirmed by a gene knock-out study [##REF##10931313##10##] – as well as similarity to the <italic>Microcystis </italic>cyanopeptolin gene cluster (<italic>mcn</italic>) [##REF##17464052##11##].</p>", "<title>Global dispersal and distribution of cyanopeptolin genes</title>", "<p>Based on the genomic regions studied here, two <italic>Planktothrix </italic>strains, NIVA CYA 116 and NIES 205, appear to be closely related despite the geographical separation. This is in accordance with the sequence comparison of 16S rDNA [##REF##12361260##27##] identifying identical 16S rDNA sequences in Japan, China, The Netherlands, UK, Finland, Sweden and Norway, and thus may indicate a global distribution of closely related <italic>Planktothrix </italic>strains. Since Lake Årungen in Norway host international rowing competitions, a co-transport of this <italic>Planktothrix </italic>genotype with rowing equipment may be feasible. The data presented here do not allow any conclusions about global distribution without a more thorough analysis. The highly specific differences observed in the <italic>oci </italic>gene clusters are, independently of geographic distributions, intriguing. Our analyses indicate that the differences to some extent are due to positive selection at specific amino acid positions.</p>", "<title>Variation in peptide content due to lack of specificity in the A-domains?</title>", "<p>Previous studies have shown that lack of specificity in A-domains leads to activation of several amino acids with similar properties, thus giving rise to the synthesis of a series of related peptides from a single NRPS system [##REF##15700962##28##]. Ile/Leu/Val activating A-domains have been reported in lichenysin biosynthesis [##REF##9864322##8##], and fengycin synthetase [##REF##10438779##29##] among others. It is likely that the 116-Oci-A5- and A7-domains can activate Leu, Ile and Val and that the 116-Oci-A1- and A3-domains, that mainly activates Htyr, also can activate Ile and Leu. Consequently, 116-Oci is responsible for production of all seven cyanopeptolin detected in NIVA CYA 116 in this study. Likewise, 205-Oci probably is responsible for all oscillapeptin variants. The biological significance of a single NRPS complex giving rise to several peptide variants is yet to be determined.</p>", "<p>Six of the seven binding pockets signatures of corresponding A-domains in NIES 205 and NIVA CYA 116 are identical (Table ##TAB##0##1##). If the different peptide profiles observed in the two strains are due to genetic differences in the NRPS genes, they are likely to be due to differences not involving the amino acids constituting the binding pocket signatures. LC-MS-MS-analyses were performed on strains cultivated on the same media, but we cannot completely exclude substrate availability as a contributory cause of variable peptide amount and peptide profile in the strain.</p>", "<title>Module exchange and amino acid configuration</title>", "<p>Over a stretch of total of 30 kb including the ABC transporter, the 116-<italic>oci </italic>and 205-<italic>oci </italic>gene clusters are remarkable similar, except for the modules encoding the T2-(E)-C2 domains. Too low sequence similarity is found between the whole T2-(E)-C2 modules in NIVA CYA 116 and NIES 205 to make a reliable alignment, suggesting that in one of these strains an entire module may have been exchanged through recombination. The E-domain trees (Figure ##FIG##1##2##) show a close relationship between cyanobacterial E-domains.</p>", "<p>Sequence similarity to other E-domains and the distinctive flanking C (Figure ##FIG##2##3##) and T [Additional file ##SUPPL##0##1## figure 5] domains observed by phylogenetic analysis indicate that the Oci-E-domain is an active epimerase, and are responsible for epimerization of Htyr to D-configuration. The configuration of the amino acids in cyanopeptolin-1138 were not determined however, a D-Htyr in oscillapeptin E and a putative L-Htyr in cyanopeptolin-1138 might explain the small difference between the oligopeptides with regard to polarity observed by HPLC analysis, as reported by Rounge <italic>et al. </italic>[##REF##17921284##12##].</p>", "<p>Interestingly, in the corresponding region of the Mcn cyanopeptolin synthetase in <italic>Microcystis </italic>the McnA-T1 and McnB-C2 include motifs suggesting association with an E-domain [##REF##17464052##11##]. In this case, however, no E-domain is present.</p>", "<title>Sequence conservation and selection within cyanopeptolin modules</title>", "<p>The two cyanopeptolin gene clusters (205-<italic>oci </italic>and 116-<italic>oci</italic>) are highly similar also at the third codon position. The first part (ABC-transporter, the spacer, GA-, T1-, S-, and C1-domains) and last part (C4-, A4-, T5-, C5-, A5-, T6-, C6-, M-, T7-, C7-, A7-, T8- and TE domains) of the <italic>Planktothrix </italic>cyanopeptolin gene cluster are nearly identical, despite the geographical distance separating the strains. Mechanisms for such sequence conservation may be frequent homology-driven genetic exchange within a genotype, leading to homogenization – in line with the general models suggested by Rudi <italic>et al</italic>. [##REF##9642201##30##], Gogarten <italic>et al</italic>.[##REF##12446813##31##] and Papke <italic>et al</italic>. [##REF##17715057##32##]. Or alternatively sequence conservation may be due to low evolutionary rates caused by purifying selection or very short time of independent evolution.</p>", "<p>Analysis of segregating sites and rates of nonsynonymous and synonymous nucleotide substitutions (Ka/Ks) indicate that module 3 (T3-, C3- and A3-domains) is different from the remaining domains by displaying higher substitution rates and signs of positive selection at several sites (Ka/Ks higher than 1). This is the module responsible for incorporation of the amino acid at position AA3 in the peptide.</p>", "<p>According to data from Itou <italic>et al </italic>[##UREF##3##20##], a single amino acid replacement in the AA3 position of oscillapeptin E and F alters the protease inhibitory profile, indicating that this position could be pivotal for the inhibitory activity of cyanopeptolins. Positive selection in the third module could thus be expected to increase the adaptability of the inhibitory- or other putative functions of cyanopeptolin.</p>" ]

[ "<title>Conclusion</title>", "<p>The <italic>Planktothrix </italic>strains of Japan and Norway harbor almost identical cyanopeptolin gene clusters and display very similar (but not identical) cyanopeptolin profiles. The notable gene cluster difference is the presence of an epimerase in NIES 205 corresponding to a D-Htyr in ocillapeptin E. Within a single gene cluster we have demonstrated both positive selection and purifying selection, the first promoting new gene cluster variants following recombination, the latter maintaining a high degree of conservation of the major parts of the gene cluster.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Cyanopeptolins are nonribosomally produced heptapetides showing a highly variable composition. The cyanopeptolin synthetase operon has previously been investigated in three strains from the genera <italic>Microcystis</italic>, <italic>Planktothrix </italic>and <italic>Anabaena</italic>. Cyanopeptolins are displaying protease inhibitor activity, but the biological function(s) is (are) unknown. Cyanopeptolin gene cluster variability and biological functions of the peptide variants are likely to be interconnected.</p>", "<title>Results</title>", "<p>We have investigated two cyanopeptolin gene clusters from highly similar, but geographically remote strains of the same genus. Sequencing of a nonribosomal peptide synthetase (NRPS) cyanopeptolin gene cluster from the Japanese strain <italic>Planktothrix </italic>NIES 205 (205-<italic>oci</italic>), showed the 30 kb gene cluster to be highly similar to the <italic>oci </italic>gene cluster previously described in <italic>Planktothrix </italic>NIVA CYA 116, isolated in Norway. Both operons contained seven NRPS modules, a sulfotransferase (S) and a glyceric acid loading (GA)-domain. Sequence analyses showed a high degree of conservation, except for the presence of an epimerase domain in NIES 205 and the regions around the epimerase, showing high substitution rates and Ka/Ks values above 1. The two strains produce almost identical cyanopeptolins, cyanopeptolin-1138 and oscillapeptin E respectively, but with slight differences regarding the production of minor cyanopeptolin variants. These variants may be the result of relaxed adenylation (A)-domain specificity in the nonribosomal enzyme complex. Other genetic markers (16S rRNA, <italic>ntc</italic>A and the phycocyanin <italic>cpc</italic>BA spacer) were identical, supporting that these geographically separated <italic>Planktothrix </italic>strains are closely related.</p>", "<title>Conclusion</title>", "<p>A horizontal gene transfer event resulting in exchange of a whole module-encoding region was observed. Nucleotide statistics indicate that both purifying selection and positive selection forces are operating on the gene cluster. The positive selection forces are acting within and around the epimerase insertion while purifying selection conserves the remaining (major) part of the gene cluster. The presence of an epimerase in the gene cluster is in line with the D-configuration of Htyr, determined experimentally in oscillapeptin E in a previous study.</p>" ]

[ "<title>Authors' contributions</title>", "<p>This work was performed as part of the PhD thesis for TBR. TBR and TR carried out all experimentation and all authors have contributed to the experimental and analytical design. TBR performed the bioinformatics and phylogenetic analysis under supervision of KSJ and TK. TR carried out the peptide analyses. TBR, KSJ (thesis advisor) TK and TR wrote the ms. All authors have read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We are grateful to Ann-Kristin Hansen and Beatriz Decenciere for excellent technical assistance, Ave Tooming-Klunderud for helpful discussions and Randi Skulberg at NIVA and The Microbial Culture Collection at the National Institute for Environmental Studies (NIES) for providing the <italic>Planktothrix </italic>NIES 205 strain. The work was supported by a grant to the project 157338/140 from the Norwegian Research Council.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Comparison of the known cyanopeptolin operons</bold>. The overall structure of cyanopeptolin operons <italic>oci </italic>from <italic>Planktothrix </italic>NIES 205 [GenBank: <ext-link ext-link-type=\"gen\" xlink:href=\"EU109504\">EU109504</ext-link>] and NIVA CYA 116 [GenBank: <ext-link ext-link-type=\"gen\" xlink:href=\"DQ837301\">DQ837301</ext-link>], <italic>mcn </italic>from <italic>Microcystis </italic>[GenBank: <ext-link ext-link-type=\"gen\" xlink:href=\"DQ075244\">DQ075244</ext-link>] and <italic>apd </italic>from <italic>Anabaena </italic>[GenBank: <ext-link ext-link-type=\"gen\" xlink:href=\"AJ269505\">AJ269505</ext-link>]. Gene names, transcription directions and approximate sizes are indicated above each gene cluster. Adenylation (red), condensation (green), thiolation (yellow), epimerization (turquoise), methyltransferase (blue) sulfotransferase (pink), halogenisation (purple) and termination domains (grey) are shown with their abbreviations. The putative activated amino acids are indicated for each A-domain. Amino acids detected in smaller amounts are beneath the major amino acid. Equivalent modules are depicted in light blue and light orange. The ABC transporter is transcribed in the opposite direction in the <italic>oci </italic>and <italic>mcn </italic>operons, and an ABC transporter is predicted downstream of the <italic>apd </italic>operon.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Phylogenetic analyses of E-domains</bold>. The E-domain phylogenetic tree was constructed utilizing MrBayes 3.1., Wag protein substitution model and gamma-shaped distribution. In addition, the bootstrap obtained for NJ (MEGA 3.1) at default settings and ML (RAxML) trees are indicated. Only posterior probability values and bootstrap replica values above 50% (out of 1000 (NJ) and 100 (ML) trees) are shown.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Phylogenetic analyses of C-domains showing groups according to gene cluster and position/function</bold>. The C-domain phylogeny was constructed using Bayesian inference with gamma distribution, 4 mill generations tree sampling every 100 generations and removal of the first 3000. The topologies generated using NJ (MEGA 3.1) and ML (RAxML) analyses show near identical branching patterns-only minor differences are seen within the Apd group. Bayesian posterior probability, NJ (1000 bootstrap values) and ML (100 trees) above 50% are shown. CpRev protein substitution model was used in the Bayesian and ML analyses. Genus origin is shown with first letter abbreviations (P = <italic>Planktothrix</italic>, M = <italic>Microcystis</italic>, A = <italic>Anabaena </italic>and N = <italic>Nostoc</italic>), and the C-domains are labeled in numerical order according to direction of transcription (i.e. seven <italic>oci</italic>, seven <italic>mcn </italic>and six <italic>apd </italic>C-domains). Corresponding Oci C domains group together, except for C2 situated downstream of the 205-E-domain. C1–C4 <italic>apd</italic>, <italic>nos </italic>and <italic>ncp </italic>C-domains do not group according to function</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Distribution of segregating sites and Ka/Ks ratios in the <italic>oci </italic>gene cluster</bold>. The ratios are displayed using the program DnaSP and sliding windows analysis on the alignment of 205-<italic>oci </italic>and 116-<italic>oci</italic>. Window length was 50 bp and step size 10 bp. The distribution of segregation sites (red) and Ka/Ks (black) ratios are shown in correlation with the domain alignment. Module 2 (T2-(E)-C2) has been excluded from the analyses.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Oci A-domains binding pockets and peptide profiles</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\"><bold>Binding pockets</bold></td><td align=\"left\"><bold>OciA-A1</bold></td><td align=\"left\"><bold>OciA-A2</bold></td><td align=\"left\"><bold>OciB-A3</bold></td><td align=\"left\"><bold>OciB-A4</bold></td><td align=\"left\"><bold>OciB-A5</bold></td><td align=\"left\"><bold>OciB-A6</bold></td><td align=\"left\"><bold>OciC-A7</bold></td></tr></thead><tbody><tr><td/><td align=\"left\"><bold>NIVA CYA 116</bold></td><td align=\"left\">DLGFTGAVCK</td><td align=\"left\">DFWNIGMVHK</td><td align=\"left\">DA<bold>QS</bold>MGAIIK</td><td align=\"left\">DVENAGVVTK</td><td align=\"left\">DAFFLGVTFK</td><td align=\"left\">DAWTIAGVCK</td><td align=\"left\">DAFFLGVTFK</td></tr><tr><td/><td align=\"left\"><bold>NIES 205</bold></td><td align=\"left\">DLGFTGAVCK</td><td align=\"left\">DFWNIGMVHK</td><td align=\"left\">DA<bold>EG</bold>MGAIIK</td><td align=\"left\">DVENAGVVTK</td><td align=\"left\">DAFFLGVTFK</td><td align=\"left\">DAWTIAGVCK</td><td align=\"left\">DAFFLGVTFK</td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>NIVA CYA 116</bold></td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>Mass Da</bold></td><td align=\"left\"><bold>Side chain</bold></td><td align=\"left\"><bold>AA 1</bold></td><td align=\"left\"><bold>AA2</bold></td><td align=\"left\"><bold>AA3</bold></td><td align=\"left\"><bold>AA4</bold></td><td align=\"left\"><bold>AA5</bold></td><td align=\"left\"><bold>AA6</bold></td><td align=\"left\"><bold>AA7</bold></td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>1138</bold></td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">HTyr</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1124</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">HTyr</td><td align=\"left\">Ahp</td><td align=\"left\">Val</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1124</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">HTyr</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Val</td></tr><tr><td align=\"left\">1074</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">Ile/Leu</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1010</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">Ile/Leu</td><td align=\"left\">Thr</td><td align=\"left\">Ile/Leu</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1088</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">X</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1122</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">HTyr</td><td align=\"left\">Thr</td><td align=\"left\">Y</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>NIES 205</bold></td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>Mass Da</bold></td><td align=\"left\"><bold>Side chain</bold></td><td align=\"left\"><bold>AA 1</bold></td><td align=\"left\"><bold>AA2</bold></td><td align=\"left\"><bold>AA3</bold></td><td align=\"left\"><bold>AA4</bold></td><td align=\"left\"><bold>AA5</bold></td><td align=\"left\"><bold>AA6</bold></td><td align=\"left\"><bold>AA7</bold></td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\"><bold>1138*</bold></td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">Htyr</td><td align=\"left\">Thr</td><td align=\"left\">Htyr</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1074</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">Htyr</td><td align=\"left\">Thr</td><td align=\"left\">Ile/Leu</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr><tr><td align=\"left\">1128**</td><td align=\"left\">HO₃-SO-CH₂-CH(OMe)-COH</td><td align=\"left\">Htyr</td><td align=\"left\">Thr</td><td align=\"left\">HcAla</td><td align=\"left\">Ahp</td><td align=\"left\">Ile</td><td align=\"left\">Phe(Me)</td><td align=\"left\">Ile</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Peptide structure and NRPS phylogeny. Figure 1: peptide structure of cyanopeptolin 1138. Figure 2: mass spectrometric fragmentation experiments data of NIVA CYA 116. Figure 3: mass spectrometric fragmentation experiments data of NIES 205. Figure 4: NRPS A-domain phylogeny. Figure 5: Sequence analyses of T-domains. Table 1: Accession numbers</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>The binding pocket residues of the NIVA CYA 116 and NIES 205 A-domains were identified by comparison to the <italic>GrsA-Phe </italic>A-domain (Residue 235, 236, 239, 278, 299, 301, 322, 330, 331, 517). The Oci-A3 binding pockets are different (in grey) between the two strains, and the divergent amino acids are shown in bold. The composition of cyanopeptolins produced by NIVA CYA 116 and NIES 205 and their molecular weights (M+H+) are shown with amino acids correlated with the putative binding pockets. HcAla is 3-(4'-hydroxy-2'-cyclohexenyl) alanine, and X and Y is unidentified amino acid derivates. Mutual peptides in NIVA CYA 116 and NIES 205 are highlighted in dark grey and light grey. See [Additional file ##SUPPL##0##1## figure 1, 2 and 3 for the peptide structure and more details on MS data.* peptide named oscillapeptin E and **peptide named oscillapeptin D</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2180-8-141-1\"/>", "<graphic xlink:href=\"1471-2180-8-141-2\"/>", "<graphic xlink:href=\"1471-2180-8-141-3\"/>", "<graphic xlink:href=\"1471-2180-8-141-4\"/>" ]

[ "<media xlink:href=\"1471-2180-8-141-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Aluminum (Al) toxicity is one of the important factors limiting crop productivity in acid soils (pH&lt;5.0) [##UREF##0##1##], which occupy approximately 30% of the world's arable land [##UREF##1##2##]. Under acidic conditions, Al(H₂O)₆³⁺(Al³⁺) is released into the soil solution at levels that inhibit plant root growth and impair water and mineral uptake [##UREF##2##3##]. Despite decades of research on Al resistance, little is known about the mechanisms by which legumes respond to and tolerate Al stress. The model legume, <italic>Medicago truncatula </italic>Gaertn., which is a close relative of alfalfa, has a relatively small diploid genome, short generation time and prolific seed production [##UREF##3##4##] and therefore serves as an ideal model system to study Al toxicity and resistance mechanisms in legumes.</p>", "<p>The root apex is considered to be the primary target of Al toxicity. Exposure of the root apex to Al results in a rapid inhibition of root growth [##UREF##4##5##]. Al disrupts root cell expansion and elongation, prior to inhibiting cell division [##UREF##5##6##] and interferes with a wide range of physical and cellular processes. Inhibition of root growth may occur as a result of Al-induced decrease in cell wall extensibility [##REF##15169940##7##], callose formation [##REF##11080277##8##], inhibition of H⁺-ATPase activity [##REF##12177136##9##], disruption of calcium homeostasis [##UREF##6##10##], stabilization of cortical cell microtubules [##REF##9733535##11##] and/or alteration in chromatin structure by DNA binding [##UREF##7##12##].</p>", "<p>Many plant species exhibit significant genetic variability in their ability to resist and tolerate Al toxicity. <italic>M. truncatula </italic>exhibits a natural variation in tolerance to low pH [##UREF##8##13##] and Al toxicity [##UREF##9##14##]. Current models for Al resistance mechanisms include exclusion of Al from the root apex and internal detoxification of Al transported into the root symplasm [##UREF##5##6##]. Al-induced secretion of organic acid (OA)-chelators is considered to be the primary mechanism of Al exclusion from the root apex. Also, chelation of Al by OAs within the root symplasm has been observed in some plant species [##REF##9662518##15##]. A number of studies have indicated that OA chelation may not be the only mechanism responsible for Al resistance [##UREF##10##16##, ####REF##11244126##17##, ##UREF##11##18##, ##REF##15591441##19####15591441##19##].</p>", "<p>Over the last decade, researchers have debated whether the induced expression of genes or the activation of pre-formed proteins or both are necessary to combat Al toxicity. The biochemical machinery for root Al exclusion via organic acid release appears to be in place before exposure to Al in some species [##REF##12231973##20##,##UREF##12##21##]. In other species a delay in secretion is observed, indicating that gene induction may be required [##REF##10938369##22##, ####REF##12114573##23##, ##UREF##13##24####13##24##]. Several studies have identified genes that are up-regulated under Al stress conditions. However, most of these genes were considered to be general stress response genes since they were induced in response to other stresses (other metal toxicities, low Ca, wounding and oxidative stress) and to similar levels in both Al-resistant and Al-sensitive genotypes [##UREF##14##25##, ####UREF##15##26##, ##REF##12228362##27##, ##REF##9684357##28##, ##REF##9449849##29##, ##REF##12481053##30####12481053##30##].</p>", "<p>In this report, we identified Al-resistant and Al-sensitive <italic>M. truncatula </italic>lines and quantified differences in Al effects on root physiology and gene expression between these lines. Based on our findings we propose that multiple responses including Al exclusion by Al-induced cell death of Al-accumulating cells and organic acid efflux and internal detoxification by OA chelation may contribute towards higher Al resistance in <italic>M. truncatula</italic>.</p>" ]

[ "<title>Methods</title>", "<title>Plant material</title>", "<p>Seeds of 46 accessions of <italic>Medicago truncatula </italic>Gaertn. were obtained from the USDA-Western Regional Plant Introduction Station at Pullman, Washington, and seeds for another eight accessions (inbred lines) were obtained from INP-ENSAT, Toulouse, France. The selected accessions represent collections from different geographical locations and areas where acid soils are known to occur. To develop inbred lines from the USDA collection, one seed from each accession was grown in a greenhouse and self-pollinated. Seeds from these lines were used for subsequent experiments.</p>", "<title>Solution culture experiments</title>", "<p>Six <italic>M. truncatula </italic>seeds from each line were scarified using concentrated sulfuric acid and surface sterilized with 5% (v/v) household beach for 3 min. The seeds were placed at 4°C for 2 d and germinated overnight on 1% agar plates in the dark at room temperature. Seedlings with radicles of about 1 cm in length were sown through the mesh bottoms of polypropylene cups. The cups were placed in precut holes of a plastic insert placed over a plastic tub that held 7.3 L of aerated nutrient solution. The nutrient solution contained: 1.2 mM KNO_3,0.8 mM Ca(NO₃)₂, 0.1 mM NH₄H₂PO₄, 0.2 mM MgSO₄, 10 μM FeNaEDTA, 50 μM KCl, 12.5 μM H₃BO₃, 1 μM MnSO₄, 1 μM ZnSO₄, 0.5 μM CuSO₄, 0.1 μM Na₂MoO₄, and 0.1 μM NiCl₂[##REF##10781104##71##]. The pH of the nutrient solution was adjusted to 4.5 using 1 N HCl. Seedlings were grown for 72 h in a growth chamber (light/dark, 14/10 h) under a light intensity of 440 μmol photons m^-2s^-1. Al treatment was initiated after 72 h by replacing the control growth solution with an identical solution that contained 2.5 μM Al added as AlK(SO₄)₃. The control and treatment solutions were adjusted to pH 4.5. Root growth measurements were made at 0 and 48 h following Al exposure. Relative root growth was calculated as: RRG (%) = (root growth in Al solution/root growth in control solution) × 100. The RRG value of each line was normalized to that of <italic>M. truncatula </italic>Jemalong A17 to account for any variation in solution pH or composition in the different tubs.</p>", "<p>For the dose-response experiments, plants were grown in 0 (control), 1.25, 2.5, 5.0 and 10 μM Al solutions, and root growth measurements were made at 48 h following Al exposure. For the time-course experiments, root growth measurements were made at 0, 12, 24, 48 and 72 h in 0 μM (control) and 2.5 μM Al solutions. These experiments were performed in triplicate.</p>", "<title>Hematoxylin and morin staining</title>", "<p>For hematoxylin staining, control and Al treated roots were rinsed for 30 min in deionized water, with the water replaced twice during rinsing. Roots were then stained with hematoxylin (0.1% w/v hematoxylin, 0.01% w/v KIO₃) for 30 min, and subsequently washed with deionized water for 30 min. For morin staining, control and Al treated roots were washed in MES buffer, pH 5.5, for 10 min, and stained with 100 μM morin in the same buffer for 1 h, as described previously [##REF##8819866##72##]. Morin fluorescence was visualized using an Olympus inverted microscope (IX70, Olympus, NY) with fluorescence attachments.</p>", "<title>Evans blue quantification</title>", "<p>Evans blue is a stain that indicates the loss of plasma membrane integrity of cells. Control and Al treated roots were rinsed with deionized water and stained with Evans blue solution (0.025% [w/v] Evans blue in 100 μM CaCl₂, pH 5.6) for 10 min. The stained roots were washed three times with 100 μM CaCl₂(pH 5.6), until dye no longer eluted from the roots. Evans blue stain retained by cells was quantified as described [##REF##11154329##73##] with minor modifications</p>", "<title>Plant growth conditions, Al treatment and tissue collection for microarrays</title>", "<p>For the microarray experiment, T32 and S70 seedlings were grown in solution culture as described above. Root tips (approximately 0.5 cm in length) from control and 2.5 μM Al treated seedlings were harvested at 12 and 48 h after Al treatment and immediately frozen in liquid nitrogen. Samples were collected from three independent biological replicates and stored at -80°C. To verify phenotype of roots harvested for RNA isolation, root growth measurements of 12 sample roots were made at 0, 12 and 48 h following Al exposure.</p>", "<title>Microarray hybridization and analysis</title>", "<p>Total RNA from control and Al-treated root tips was extracted using the RNeasy Plant Mini Kit (Qiagen, Alameda, CA) following the manufacturer's protocol. RNA was quantified spectrophotometrically and stored at -80°C before use. cDNA synthesis was carried out using a 3DNA Array 900 Expression Array Detection Kit (Genisphere, Inc., Hatsfield, PA) according to the manufacturer's instructions (3DNA Array 900 Expression Array Detection Kit, Appendix A, Genisphere).</p>", "<p>The <italic>Medicago truncatula </italic>AROS (version 1.0) arrays (Operon Biotechnologies Inc., Huntsville, AL) containing 16,086 70 mer probes representing 16,086 <italic>M. truncatula </italic>genes were used for the microarray studies. The 70 mer probes were printed on Telechem Super Amine slides (Sunnyvale, CA) with spot size approximately 100 to 110 μm in diameter. Slides were processed prior to use by rehydrating over a 50° to 55°C water bath for 5 to 10 sec and snap-drying on a 65°C heating block for 5 sec, approximately three to four times. The DNA on the slide was cross linked by exposing the DNA-side-up to 65 mJ in a UV crosslinker. The slides were washed in 1% SDS at room temperature for 5 min, dipped in 100% ethanol for 30 sec with gentle agitation, centrifuged at 1,500 rpm for 2 to 5 min and stored in a light-proof box under cool and dry conditions before use. Microarrays for each time point were hybridized to cDNAs from both Al-treated and control roots, with cDNAs from the two different treatments labeled with Cy5 and Cy3 dyes. Each hybridization was repeated at least six times to account for technical variability, with triplicates of each dye combination to control for dye effects. A modified two-step hybridization reaction was performed as described in the 3DNA Array 900 Expression Array Detection Kit (Genisphere). Slide scanning and data analysis was performed as described in [##REF##16377745##74##].</p>", "<title>Quantitative reverse transcription PCR</title>", "<p>Root tip RNA samples from the three biological replicates that were used for microarray experiments were used for quantitative real-time PCR (q-PCR) assays. Primers for q-PCR reactions were designed using the Primer Express software (v 2.0, Applied Biosystems, Foster City, CA) and are presented in Table ##TAB##3##4##. RNA extraction and PCR conditions are as described previously [##REF##16570662##75##]. For each biological replicate, three q-PCR reactions were run from a cDNA synthesis and the mean values presented. Amplification of 18S ribosomal RNA was used as the endogenous control. The ΔΔCt (threshold cycle) method was used to calculate relative fold changes between Al-treated and control (-Al) cDNA samples. Specificity of the product was confirmed by a single peak in a dissociation curve at the end of the PCR reaction.</p>", "<title>In-well <italic>in situ </italic>PCR on root tip sections</title>", "<p>T32 and S70 seedlings were grown in solution culture as described for the microarray tissue collection and root tips (approximately 0.5 cm in length) were harvested from control (0 μM) and Al (2.5 μM) treated seedlings at 3 and 12 h following Al exposure. <italic>In situ </italic>PCR on root tissue was carried out as described [##REF##10938339##76##] with minor modifications. The root tips were fixed in 4% paraformaldehyde, 0.25% glutaraldehyde, 0.003 N sodium hydroxide, and 1% Tween 20 in 100 mM PIPES buffer (pH 6.8). The MATE exon primer for the reverse transcription reaction was 5'-AGCAATGGAAACTCCAGCAGC-3' and the primers for the PCR reaction were MATE exon forward, 5'-CATCCCTCTCTTGCACCATCA-3'or MATE intron forward, 5'-GCAAAGAGGAACAATGGCGA-3' and MATE exon reverse, 5'-AGCAATGGAAACTCCAGCAGC-3'. The sections were examined under a microscope and photographed with a digital camera (Nikon Coolpix 900).</p>" ]

[ "<title>Results and Discussion</title>", "<title>Identification of Al-resistant and Al-sensitive <italic>M. truncatula</italic></title>", "<p>Plants from 54 <italic>M. truncatula </italic>accessions were screened using a hydroponic assay with 2.5 μM Al concentration. At this Al concentration, the relative root growth (RRG) of the reference <italic>M. truncatula </italic>genotype A17 was 33%. In a previously published study [##REF##18351384##31##], 0.1 N KOH was used to adjust the pH of the Al solutions to 4.5. The addition of base can result in the hydrolysis of Al(H₂O)₆³⁺(Al³⁺) into monomeric species such as Al(H₂O)₅OH²⁺[##UREF##16##32##]. This could have potentially lowered the concentration of the toxic form of Al (Al³⁺) in the solution. In the current study, we avoided the use of base. Therefore, similar levels of root growth inhibition as obtained previously were achieved by using 10-fold lower Al concentrations in the current study.</p>", "<p>The RRG values of the different lines were normalized to that of A17 to rank them according to their level of resistance. Eight lines with normalized values greater than 2.0 were considered Al-resistant and eight lines with values below 0.5 as Al-sensitive (Table ##TAB##0##1##). No correlation was observed between seed size and root growth (data not shown). An Al-resistant line generated from a single seed of the accession PI 384662 from Morocco (designated T32), and an Al-sensitive line similarly derived from the Italian accession PI577613 (designated S70), were selected to study physiological and molecular aspects of Al resistance. T32 showed the highest RRG in Al solution and was the obvious choice for the resistant line. Although S70 was not the most Al-sensitive line in the screen, it was selected because plant to plant variation in root growth in nutrient solution was minimal compared to other Al-sensitive lines and root growth rates of S70 were most similar to that of T32 in control solutions (72 h root growth of T32 in control solutions was 13 mm while that of S70 was 15.8 mm).</p>", "<title>Aluminum dose-response root growth</title>", "<p>Relative root growth of A17, T32, and S70 decreased in an Al dose-dependent manner over 48 h of Al exposure (Figure ##FIG##0##1##). However, differences in Al resistance between T32 and S70 were observed at all Al concentrations evaluated. At lower solution Al concentrations (1.25 and 2.5 μM), T32 exhibited the highest RRG values (120% and 90%, respectively), followed by A17 (70% and 35%, respectively), and S70 (65% and 15%, respectively). The maximum difference in RRG between T32 and S70 was observed at 2.5 μM solution Al concentration.</p>", "<p>Within the first 24 h of Al treatment, root growth inhibition in T32 occurred at all Al concentrations tested except at 1.25 μM Al (Figure ##FIG##1##2a##). In 1.25 μM solution Al concentration the root growth of T32 seedlings was approximately 20% higher than the control seedlings after 24 h. This phenomenon has been observed in wheat, and it was suggested that enhanced root growth might be the result of alleviation of H⁺stress under acidic conditions by Al [##UREF##17##33##]. Alternatively, addition of Al to the nutrient solution may influence the bioavailability of other ions in a manner that stimulates growth [##UREF##18##34##]. Interestingly, it has been shown that the low concentration Al-induced increase in root growth of <italic>Quercus serrata </italic>was not caused by the amelioration of H⁺toxicity by Al [##UREF##19##35##]. In contrast, root growth inhibition occurred at all Al concentrations in S70 at 24 h (Figure ##FIG##1##2b##). By 72 h, recovery of root growth to control rates was observed in T32 at 2.5 μM Al. Depletion of Al from the nutrient solution is not a likely explanation for this result given the large solution volume and small root mass involved. In S70, no recovery was observed and root growth inhibition appeared to be constant throughout the time course of the experiment. The stimulation of root growth at 1.25 μM Al and recovery of root growth at 2.5 μM Al suggests that the Al resistance of T32 is inducible. In an Al-resistant maize cultivar, there was a lag time of more than 4 h before the root tips were efficiently protected against Al toxicity [##UREF##20##36##]. Similarly, in 2.5 μM Al solutions, a lag period between Al stress perception and functional expression of induced Al resistance would explain the observed root growth inhibition and recovery pattern in T32.</p>", "<title>Al accumulation in T32 and S70 root tips</title>", "<p>The degree of hematoxylin staining in root tips provides a semi-quantitative measure of Al content, and is inversely proportional to both the ability of a genotype to exclude Al from the root apex, and its Al resistance [##UREF##21##37##]. The greatest differentiation between T32 and S70 was observed at 2.5 μM Al, at which root tips of T32 exhibited minimal staining and root tips of S70 were more intensely stained (Figure ##FIG##2##3a##). Similar differences were observed at 5 μM Al. However, at 10 μM Al, root tips of both lines were intensely stained, indicating an inability to effectively exclude Al at such high concentrations.</p>", "<p>Roots of T32 and S70 were stained with hematoxylin following different lengths of exposure to 2.5 μM Al to determine whether the recovery in root growth observed in T32 was a consequence of a decrease in Al accumulation in the root tips. Within 12 h of Al treatment, root tips of both lines were lightly stained (Figure ##FIG##2##3b##). By 72 h, no staining was observed in T32. In contrast, root tips of S70 were intensely stained. The increased Al resistance of T32 may depend on an induced ability to exclude Al, since no visible hematoxylin staining was observed in T32 root tips at 72 h. If Al exclusion is inducible in T32, the Al that was initially taken up by the roots would still be present, and would likely be visible by hematoxylin staining. Figure ##FIG##2##3b## shows visible hematoxylin staining approximately 3 mm from the root tip at 48 h of Al treated roots (black arrow), demonstrating that Al had accumulated in root cells prior to root growth recovery. In contrast, S70 root tips showed increased Al accumulation coupled with severe cell damage that extended 1 to 2 mm behind the root tip (Figure ##FIG##2##3b##). This pattern of injury is similar to previous observations in Al-sensitive maize root apices [##UREF##22##38##]. The hematoxylin staining result is concordant with the root growth data, indicating that greater Al accumulation is correlated with greater root growth inhibition in <italic>M. truncatula</italic>.</p>", "<title>Differential expression of genes in response to Al</title>", "<p>The molecular responses underlying differences in Al resistance were investigated using the <italic>M. truncatula </italic>AROS (version 1.0) arrays (Operon Biotechnologies Inc., Huntsville, AL) consisting of probes for approximately 16,000 <italic>M. truncatula </italic>expressed genes. Al-induced gene expression was compared in T32 and S70 after 12 and 48 h of +/- 2.5 μM Al treatment. We selected 12 h since root growth inhibition was observed at that time point in T32. We selected the 48 h time point since root growth rates recovered to that of the controls by 72 h in T32. These time points were chosen to identify transcriptional differences associated with Al-toxicity and resistance responses between the two lines. To detect significant genes with Al-regulated expression and to eliminate those that have inconsistent expression data among replicated experiments, we employed a statistical method adapted specifically for microarrays, which allows estimation of the false discovery rate (FDR) for multiple testing [##REF##11309499##39##]. A delta criterion that allowed a FDR &lt; 0.5% was applied. Genes that satisfied the statistical threshold were identified as significantly up- or down-regulated in Al-treated roots. In addition, we used a 2-fold change cut-off for the significant genes. Normalized and raw data have been submitted to NCBI Gene Expression Omnibus (Accession No. GSE6946). In both lines, the expression of a majority of transcripts appeared unchanged at both time points with Al treatment. As shown in Figure ##FIG##3##4##, more genes were significantly altered by ≥ 2.0-fold in 12 h Al-treated root tips compared to 48 h Al-treated root tips. Additionally, at both time points, a greater number of Al-induced genes were observed in S70 root tips (12 h = 365; 48 h = 287). Since root growth of S70 was inversely correlated with Al accumulation at these time points, the greater number of up-regulated genes in S70 at both time points likely corresponds to greater Al stress perception and may reflect Al toxicity responses. In contrast, the numbers of down-regulated genes were similar in both lines and at both time points (Figure ##FIG##3##4##). It has been suggested that adaptive reprogramming to stressful conditions may require a higher number of down-regulated genes [##REF##15375206##40##]; therefore, the similar numbers of down-regulated genes at both time points in both lines might reflect an overlap in Al stress adaptation responses.</p>", "<p>The genes showing significantly different transcript accumulation patterns in response to Al in T32 and S70 experiments were further compared to determine the number that were up- or down-regulated in response to Al treatment by 2-fold or more in both lines vs. only in one line (Figure ##FIG##3##4##). At the 12 h time point, 257 genes were uniquely expressed in T32 and 420 in S70. By 48 h T32 had 83 uniquely expressed genes and 343 were expressed only in S70. These differences may represent differences in Al stress perception and adaptation in T32 and S70 root tips. The large number of shared genes at the 12 h time point (189) might reflect an overlap in the Al toxicity responses in both lines. A list of selected significant differentially regulated genes is presented in Table ##TAB##1##2##. Functional categorization for all genes was based on Gene Ontology (GO) process information <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.geneontology.org\"/>.</p>", "<p>The Al-regulated expression changes in 12 significant genes were examined for both lines by quantitative reverse-transcription PCR (q-PCR). The q-PCR results showed the same direction of fold change of transcript abundance as the microarray in all three biological replicates for most genes (Table ##TAB##2##3##). In most cases, expression ratios based on q-PCR were higher than those ratios obtained from microarray hybridizations. This difference in expression ratios estimated by the two techniques has been observed previously [##REF##15195948##41##] and reflects the specificity and sensitivity of the q-PCR technique [##REF##15497399##42##]. The ratios (T32/S70) of the mean q-PCR fold change values were similar to the ratios of the microarray fold change values for most genes tested, thereby validating the microarray results.</p>", "<title>Gene expression in response to 12 h of Al treatment in S70 root tips</title>", "<p>After 12 h of Al treatment, the RRG of S70 was approximately 45% (Figure ##FIG##1##2b##) with Al accumulating mainly in the epidermis and outer cortical cells of the root tip (Figure ##FIG##4##5##). Aluminum has been shown to rapidly bind to the pectic matrix in the cell wall, reduce cell wall (CW) extensibility [##REF##15169940##7##,##UREF##23##43##], and consequently inhibit root elongation. Thus, as might be expected, a number of CW-related genes potentially involved in CW loosening including a pectinesterase precursor, an expansin-like protein and a xyloglucan endotransglycosylase, were differentially regulated in response to Al treatment in S70 root tips (Table ##TAB##1##2##). Pectin methylesterases have been shown to increase the Al sensitivity of plants because their ability to demethylate pectin, in addition to altering the sensitivity of the CW to the action of other CW-degrading enzymes [##REF##10368183##44##], might create additional binding sites for Al in the CW [##UREF##24##45##,##UREF##25##46##]. This can occur by increasing the free organic acid moieties (in galacturnoic acid) in the wall, making it more negatively charged. Recently, we showed that the down-regulation of a pectin acetylesterase gene in <italic>M. truncatula </italic>transgenic roots resulted in a modest increase (~20%) in root growth under Al stress conditions compared to wild-type plants [##REF##18351384##31##]. Based on these results it appears that plant cells respond to Al-induced CW stiffening by enhancing the expression of CW loosening enzymes in an attempt at stimulating CW expansion.</p>", "<p>Notable at this time point was the accumulation of gene transcripts encoding reactive oxygen species (ROS) generating enzymes. Genes encoding peroxidases and peroxidase precursors as well as germin-like proteins and carbohydrate oxidase were up-regulated (Table ##TAB##1##2##). Aluminum toxicity has previously been shown to trigger the expression and activity of ROS generating enzymes and ROS accumulation has been shown to positively correlate with Al sensitivity [##REF##11266584##47##,##REF##12482454##48##]. ROS are capable of causing oxidative damage to proteins, DNA, and lipids in plant cells and may ultimately lead to cell death [##REF##15377225##49##]. The enhanced expression of genes encoding ROS generating enzymes suggest that upon Al stress, S70 root tips experience oxidative damage, which could in turn result in complete root growth inhibition (Figure ##FIG##1##2b##). A number of genes coding for ROS generating enzymes were also found to be down-regulated in S70 at 12 h of Al treatment (Table ##TAB##1##2##). It is possible that specific peroxidases may be involved in the Al toxicity response, consequently resulting in the down-regulation of peroxidases involved in other responses, including ones that might be involved in ROS scavenging.</p>", "<p>The observed increase in transcript accumulation of ROS generating genes may reflect ROS accumulation in root tips and therefore may elicit the expression of antioxidant-related genes. Consistent with this hypothesis, an increase in the expression of antioxidant genes was observed in S70 root tips. Genes putatively encoding glutathione S-transferase and thioredoxin were significantly up-regulated (Table ##TAB##1##2##). Also up-regulated were genes encoding tyrosine aminotransferase and 4-hydroxyphenylpyruvate dioxygenase, enzymes involved in the biosynthesis of α-tocopherols, which function as membrane stabilizers and antioxidants that scavenge oxygen free radicals, lipid peroxy radicals, and singlet oxygen [##REF##16008098##50##].</p>", "<p>A number of stresses induce production of ROS and lipid peroxidation, including pathogen attack. Since Al resulted in accumulation of ROS generating gene transcripts in S70 root tips, the resulting ions and oxidative damage might have triggered the up-regulation of a number of pathogen defense-related and membrane-stabilizing genes (Table ##TAB##1##2##). A number of genes encoding isoflavonoid biosynthetic enzymes were uniquely up-regulated in 12 h Al-treated S70 root tips (Table ##TAB##1##2##). The isoflavonoids, which are mostly limited to the subfamily Papilionoideae of the Fabaceae, have been shown to function as phytoalexins [##UREF##26##51##] and antioxidants [##REF##7633567##52##]. Their up-regulation in response to Al stress may represent a unique response of the legume family to Al-induced oxidative stress.</p>", "<p>It has been shown that ROS triggers cell death by apoptosis, necrosis, or mechanisms with features of both [##REF##16760481##53##]. Between 24 and 48 h of Al treatment, cell death of Al-accumulating epidermal and outer cortical cell layers was observed in S70 root tips. Fluorescence observed in root tip cells as a result of morin staining depicts Al-accumulation while both light microscopy of Al-treated root tip cross sections (Figure ##FIG##4##5##) and root tips stained with Evan's blue, which is a dye that measures extent of cell death, indicates cell death (Figure ##FIG##5##6##). Consistent with this phenotypic observation, a number of cell-death associated genes were up-regulated in S70 root tips including cysteine proteinase, senescence associated proteins and genes for CW degrading enzymes that may be necessary for cell separation during programmed cell death. Hypothetically, gene expression data from S70 root tips after 12 h of Al treatment reflects enhanced CW stiffening, severe oxidative damage probably due to significant ROS accumulation and activation of cell death.</p>", "<title>Gene expression in response to 48 h of Al treatment in S70 root tips</title>", "<p>After 48 h of Al treatment, RRG of S70 was approximately 17% (Figure ##FIG##1##2b##). Notably, transcript accumulation of CW-modifying genes was observed at this time point (Table ##TAB##1##2##) suggesting continued CW stiffening from Al treatment. Furthermore, the prolonged induction of caffeic acid O-methyltransferase, involved in lignin biosynthesis only in S70 root tips could contribute to continued Al-induced root elongation inhibition. Genes putatively encoding polygalacturonase, pectate lyases, and β-1, 4-glucanase, which are CW-degrading enzymes, were significantly up-regulated in S70 root tips (Table ##TAB##1##2##). It is plausible that cell separation during the persistent cell death response at 48 h of Al treatment may elicit the prolonged expression of these genes. Interestingly, three genes encoding putative arabinogalactan-proteins (AGP) were uniquely up-regulated in S70 at 48 h of Al treatment. AGPs belong to a class of hydroxyproline-rich glycoproteins that are abundant in the plant CW and membrane [##REF##14645732##54##], with no clear function. Two maize AGPs were found in disintegrating xylem cells and a role in identifying cells committed to PCD was proposed [##REF##7534554##55##]. Furthermore, two AGP genes were identified as showing enhanced expression in Arabidopsis after Al stress [##REF##12177459##56##]. Thus, AGPs may represent a novel facet of the Al toxicity response since they are significantly up-regulated only in the Al-sensitive line and may be involved in modulating cell wall architecture and/or involved in the Al-induced cell death response.</p>", "<p>Accumulation of transcripts for enzymes generating ROS remained high after 48 h of Al treatment. The maintenance of peroxidase transcripts up to 48 h of Al treatment is consistent with previous observations in tobacco cells [##UREF##27##57##] and Arabidopsis [##REF##9449849##29##] in which these genes showed enhanced expression during prolonged Al treatments. A few antioxidant genes including thioredoxin, ascorbate peroxidase, and alternate oxidase were uniquely up-regulated in S70 root tips at 48 h Al treatment. However, transcripts for other antioxidant related genes expressed after 12 h of Al treatment did not show enhanced accumulation at 48 h. The enhanced expression of a greater number of ROS generating genes compared to antioxidant genes at 48 h suggests that the antioxidant capacity of S70 root tips might be insufficient to prevent significant ROS accumulation. Consequently, higher doses of ROS without sufficient scavenging, may lead to greater oxidative damage and necrosis in S70 root tips. Consistent with this hypothesis, the transcripts of four PR-genes and other stress-related genes remained at elevated levels after 48 h of Al treatment suggesting continued oxidative damage. In addition, cell death and senescence-associated genes were uniquely up-regulated in 48 h Al-treated S70 root tips suggesting the longevity and severity of the cell death response. In agreement with the expression data, we observed a ≥ 10-fold extent of cell death in S70 Al-treated root tips compared to control root tips after 48 h of Al treatment (Figure ##FIG##5##6##). In addition, at these time points, Al was observed in some of the inner cortical layers of the root tip as indicated by morin staining (Figure ##FIG##4##5##).</p>", "<p>Collectively, the prolonged expression of genes associated with CW loosening, ROS generation, cell death and CW degradation after 48 h of Al treatment implies that the Al-induced oxidative damage and cell death response resembles a necrotic response, damaging deeper cell layers and ultimately resulting in irreversible root growth inhibition in S70.</p>", "<title>Gene expression in response to 12 h Al treatment in T32 root tips</title>", "<p>At 12 h of Al treatment, the RRG of T32 was approximately 78% (Figure ##FIG##1##2a##) with Al accumulating mainly in the epidermal cell layer of the root tip as indicated by morin staining (Figure ##FIG##4##5##). The inhibition in root growth, although not as severe as in S70, might induce the expression of CW-related genes. Consistent with this hypothesis, CW loosening genes were similarly regulated in S70 and T32 root tips at 12 h of Al treatment (Table ##TAB##1##2##), indicating an overlap in responses to Al toxicity in both lines.</p>", "<p>Transcript accumulation of genes encoding ROS generating enzymes in T32 root tips was similar to that observed in S70; however, the total number of up-regulated genes was lower in T32 root tips (Figure ##FIG##3##4##). A number of antioxidant genes accumulated similarly in both lines (Table ##TAB##1##2##). However, two quinone oxidoreductase genes, a glutathione s-transferase (GST) gene, and a blue copper protein (BCB) precursor were significantly up-regulated only in T32 root tips. Quinone-oxidoreductases, which are involved in the detoxification of reactive aldehydes derived from lipid peroxides [##REF##12514241##58##] have previously been shown to be induced in response to Al treatment in Al-tolerant and Al-sensitive rice roots [##REF##14645395##59##]. Previously, BCB and GST genes were shown to be up-regulated in Arabidopsis in response to Al treatment [##REF##9449849##29##] and plants over-expressing these genes displayed increased resistance to low Al concentrations [##REF##10712528##60##]. Therefore, these genes may represent a resistance response associated with ROS scavenging in response to Al treatment only in Al-resistant root tips. Relative to S70, a greater number of ROS generating genes including peroxidases and peroxidase precursors were down-regulated in T32 (Table ##TAB##1##2##). However, in contrast to S70, antioxidant genes were not down-regulated in T32. In addition, up-regulation of fewer PR-genes, isoflavonoid biosynthetic genes, and stress-related genes (Table ##TAB##1##2##) reflected a lower extent of oxidative damage in T32 root tips. These data suggest that although there appears to be ROS accumulation in response to 12 h Al treatment in T32 root tips, the levels may be lower than that observed in S70.</p>", "<p>A number of cell-death associated genes were uniquely up-regulated in T32 after 12 h of Al treatment (Table ##TAB##1##2##). Expression of these genes is consistent with cell death observed at 24 h of Al treatment (Figure ##FIG##4##5## and ##FIG##5##6##). Interestingly, cell death appeared to be restricted to cells that accumulate Al as visualized by light microscopy of root tip cross sections (Figure ##FIG##4##5##). It has been suggested that low Al concentration treatments induce cell death possibly via a ROS-activated signal transduction pathway [##REF##11378174##61##]. However, exposure to more toxic concentrations of Al may cause necrosis in the root tip cells. Likewise, H₂O₂produced in barley roots, during early phases of Al stress, has been suggested to play a role in the induction of cell death [##REF##15726813##62##]. Therefore, in addition to the observed patterns of expression of ROS generating and scavenging genes, the activation of cell death in Al-accumulating root tip cells indicate lower ROS accumulation in T32 after 12 h Al treatment. Accumulation of low levels of ROS, which although might be insufficient to cause significant oxidative damage, may play a key role in triggering cell death of Al-accumulating cells, as has been demonstrated in cell death responses to other abiotic and biotic stresses [##REF##15377225##49##,##REF##17041898##63##].</p>", "<title>Gene expression in response to 48 h Al treatment in T32 root tips</title>", "<p>After 48 h of 2.5 μM Al treatment, the RRG of T32 recovered to approximately 90% (Figure ##FIG##0##1## and ##FIG##1##2a##). At this time point fewer genes were differentially regulated in response to Al treatment in T32 root tips (Figure ##FIG##3##4##) compared to 12 h of treatment. Notably, fewer ROS generating genes were up-regulated, and up-regulation of a number of antioxidant genes was observed (Table ##TAB##1##2##). Since fewer ROS generating genes were up-regulated, the basal antioxidant capacity may have been sufficient to prevent significant ROS accumulation. Interestingly, there was no significant change in expression of stress-related genes, including PR-proteins and isoflavonoids and cell death genes (Table ##TAB##1##2##) suggesting that the ROS levels may have been insufficient to cause oxidative damage and cell death. In fact, down-regulation of some stress-related genes and senescence-associated genes was observed at this time point (Table ##TAB##1##2##). Moreover, probably as a result of new root tip growth, the extent of Al accumulation and cell death at 48 h was minimal (Figure ##FIG##4##5## and ##FIG##5##6##). Therefore, we speculate that in T32 root tips, the cell death response occurred early on and was aimed at removing Al-accumulating cells leading to a recovery in root growth.</p>", "<p>A continued response to Al stress in T32 root tips after 48 h of Al treatment was indicated by the high transcript accumulation of a putative multidrug and toxin extrusion (MATE) gene (TC105342; MtMATE). Although the expression of this gene was significantly up-regulated at both time points of Al treatment and in both lines (Table ##TAB##1##2##), the prolonged expression of this gene during root growth recovery in the Al-tolerant line made it an interesting candidate for Al resistance studies. We examined whether the spatial expression pattern of this gene played a role in differential Al resistance responses in these lines.</p>", "<title>Differential pattern of expression of MtMATE in T32 and S70</title>", "<p>To determine the spatial distribution of MATE gene expression in response to early (3 h) and later (12 h) time points of Al treatment, <italic>in situ </italic>PCR was carried out on root tip cross sections. In 3 h Al-treated T32 root tips, a positive signal was visible in cells of the endodermis and the regions encompassing the vascular bundles (Figure ##FIG##6##7##). In contrast, in 3 h Al-treated S70 root tips, the signal appeared to be more uniformly distributed over the entire section including the epidermis, cortical cells and vasculature (Figure ##FIG##6##7##). No signal was observed in 3 h control (-Al) T32 and S70 root sections (Figure ##FIG##6##7##). In 12 h Al-treated T32 root tips, a strong signal was visible in the epidermis in addition to the vascular region; however, the signal appeared to be restricted to the epidermis and outer cortical cells in 12 h Al-treated S70 root tips. A positive signal was also observed in the epidermis, cortical cells and vasculature of 12 h control S70 roots (Figure ##FIG##6##7##) indicating the uniform expression of this gene under Al-free conditions. The intron-specific primers gave no positive signals (Figure ##FIG##6##7##). Overall, the localization of MATE expression in Al-treated root tips indicated that the transcript of the MATE gene accumulated most strongly in the vascular region of T32 and mainly in the epidermal and outer cortical layers in S70.</p>", "<p>The MtMATE shares 67% identity with a putative lupin LaMATE (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"AAW30732\">AAW30732</ext-link>; [##REF##16297074##64##]), 63% identity with a rice MATE gene (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"ABB47036\">ABB47036</ext-link>), and 62% identity with the Arabidopsis FRD3 protein (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"NP_187461.1\">NP_187461.1</ext-link>; [##REF##12172022##65##]). Based on studies conducted on different MATE genes it has been hypothesized that this family may be involved in transporting a diverse set of small organic molecules either directly out of the cell or into vacuolar compartments [##REF##12172022##65##, ####REF##11073914##66##, ##REF##11739388##67####11739388##67##]. Recently, FRD3 was shown to be a citrate efflux transporter and Arabidopsis plants ectopically expressing FRD3 had significantly higher amounts of citrate in their root exudates compared to untransformed controls and possessed an enhanced resistance to aluminium [##REF##17351051##68##]. Morin staining revealed presence of Al in the vasculature of T32 root tips at 12 h of Al treatment (Figure ##FIG##4##5##). Taking the differential root growth rates and Al accumulation patterns together with the spatial expression pattern of the MtMATE, it is tempting to speculate that the strong vascular expression of MtMATE in T32 root tips might be involved in transporting Al away from the sensitive growing root tip therefore resulting in lower root growth inhibition in T32. Internal detoxification of Al by formation of organic acid-Al complexes has been previously demonstrated in hydrangea and buckwheat [##REF##9662518##15##,##REF##12223659##69##]. In buckwheat, Al is chelated internally in the root cells by oxalate and translocated via the xylem to leaf cells where these complexes are then stored in vacuoles [##REF##10987553##70##]. Likewise, it is possible that in T32 the MtMATE gene may be involved in the transport of organic acid-Al complexes into the aerial parts of the plant followed by sequestration into vacuoles. In S70, the organic acid efflux or Al-sequestration into vacuoles might be restricted to the root surface as indicated by the strong expression in the epidermal and cortical cells. In addition, it is possible that the observed expression of this gene under Al-free conditions in S70 root tips is in response to low pH or low pH-induced nutrient deficiencies. Interestingly, the LaMATE displays enhanced expression under various nutrient stress conditions including -P, -Fe, -Mn, -N and + Al [##REF##16297074##64##]. Similarly, the FRD3 gene is induced in response to cold stress and during senescence (a search of 2,620 ATH1 Affymetrix chips in <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.genevestigator.ethz.ch/gv/index.jsp\"/>). Alternatively, although Al-induced expression of the MATE gene occurs in both lines, the subsequent activation of organic acid efflux might be delayed or inhibited in S70. Localization of MtMATE to either the plasma membrane or the vacuole would reveal its site of action, and identification of the molecule it transports could permit a direct biochemical test of its function in transport.</p>" ]

[ "<title>Results and Discussion</title>", "<title>Identification of Al-resistant and Al-sensitive <italic>M. truncatula</italic></title>", "<p>Plants from 54 <italic>M. truncatula </italic>accessions were screened using a hydroponic assay with 2.5 μM Al concentration. At this Al concentration, the relative root growth (RRG) of the reference <italic>M. truncatula </italic>genotype A17 was 33%. In a previously published study [##REF##18351384##31##], 0.1 N KOH was used to adjust the pH of the Al solutions to 4.5. The addition of base can result in the hydrolysis of Al(H₂O)₆³⁺(Al³⁺) into monomeric species such as Al(H₂O)₅OH²⁺[##UREF##16##32##]. This could have potentially lowered the concentration of the toxic form of Al (Al³⁺) in the solution. In the current study, we avoided the use of base. Therefore, similar levels of root growth inhibition as obtained previously were achieved by using 10-fold lower Al concentrations in the current study.</p>", "<p>The RRG values of the different lines were normalized to that of A17 to rank them according to their level of resistance. Eight lines with normalized values greater than 2.0 were considered Al-resistant and eight lines with values below 0.5 as Al-sensitive (Table ##TAB##0##1##). No correlation was observed between seed size and root growth (data not shown). An Al-resistant line generated from a single seed of the accession PI 384662 from Morocco (designated T32), and an Al-sensitive line similarly derived from the Italian accession PI577613 (designated S70), were selected to study physiological and molecular aspects of Al resistance. T32 showed the highest RRG in Al solution and was the obvious choice for the resistant line. Although S70 was not the most Al-sensitive line in the screen, it was selected because plant to plant variation in root growth in nutrient solution was minimal compared to other Al-sensitive lines and root growth rates of S70 were most similar to that of T32 in control solutions (72 h root growth of T32 in control solutions was 13 mm while that of S70 was 15.8 mm).</p>", "<title>Aluminum dose-response root growth</title>", "<p>Relative root growth of A17, T32, and S70 decreased in an Al dose-dependent manner over 48 h of Al exposure (Figure ##FIG##0##1##). However, differences in Al resistance between T32 and S70 were observed at all Al concentrations evaluated. At lower solution Al concentrations (1.25 and 2.5 μM), T32 exhibited the highest RRG values (120% and 90%, respectively), followed by A17 (70% and 35%, respectively), and S70 (65% and 15%, respectively). The maximum difference in RRG between T32 and S70 was observed at 2.5 μM solution Al concentration.</p>", "<p>Within the first 24 h of Al treatment, root growth inhibition in T32 occurred at all Al concentrations tested except at 1.25 μM Al (Figure ##FIG##1##2a##). In 1.25 μM solution Al concentration the root growth of T32 seedlings was approximately 20% higher than the control seedlings after 24 h. This phenomenon has been observed in wheat, and it was suggested that enhanced root growth might be the result of alleviation of H⁺stress under acidic conditions by Al [##UREF##17##33##]. Alternatively, addition of Al to the nutrient solution may influence the bioavailability of other ions in a manner that stimulates growth [##UREF##18##34##]. Interestingly, it has been shown that the low concentration Al-induced increase in root growth of <italic>Quercus serrata </italic>was not caused by the amelioration of H⁺toxicity by Al [##UREF##19##35##]. In contrast, root growth inhibition occurred at all Al concentrations in S70 at 24 h (Figure ##FIG##1##2b##). By 72 h, recovery of root growth to control rates was observed in T32 at 2.5 μM Al. Depletion of Al from the nutrient solution is not a likely explanation for this result given the large solution volume and small root mass involved. In S70, no recovery was observed and root growth inhibition appeared to be constant throughout the time course of the experiment. The stimulation of root growth at 1.25 μM Al and recovery of root growth at 2.5 μM Al suggests that the Al resistance of T32 is inducible. In an Al-resistant maize cultivar, there was a lag time of more than 4 h before the root tips were efficiently protected against Al toxicity [##UREF##20##36##]. Similarly, in 2.5 μM Al solutions, a lag period between Al stress perception and functional expression of induced Al resistance would explain the observed root growth inhibition and recovery pattern in T32.</p>", "<title>Al accumulation in T32 and S70 root tips</title>", "<p>The degree of hematoxylin staining in root tips provides a semi-quantitative measure of Al content, and is inversely proportional to both the ability of a genotype to exclude Al from the root apex, and its Al resistance [##UREF##21##37##]. The greatest differentiation between T32 and S70 was observed at 2.5 μM Al, at which root tips of T32 exhibited minimal staining and root tips of S70 were more intensely stained (Figure ##FIG##2##3a##). Similar differences were observed at 5 μM Al. However, at 10 μM Al, root tips of both lines were intensely stained, indicating an inability to effectively exclude Al at such high concentrations.</p>", "<p>Roots of T32 and S70 were stained with hematoxylin following different lengths of exposure to 2.5 μM Al to determine whether the recovery in root growth observed in T32 was a consequence of a decrease in Al accumulation in the root tips. Within 12 h of Al treatment, root tips of both lines were lightly stained (Figure ##FIG##2##3b##). By 72 h, no staining was observed in T32. In contrast, root tips of S70 were intensely stained. The increased Al resistance of T32 may depend on an induced ability to exclude Al, since no visible hematoxylin staining was observed in T32 root tips at 72 h. If Al exclusion is inducible in T32, the Al that was initially taken up by the roots would still be present, and would likely be visible by hematoxylin staining. Figure ##FIG##2##3b## shows visible hematoxylin staining approximately 3 mm from the root tip at 48 h of Al treated roots (black arrow), demonstrating that Al had accumulated in root cells prior to root growth recovery. In contrast, S70 root tips showed increased Al accumulation coupled with severe cell damage that extended 1 to 2 mm behind the root tip (Figure ##FIG##2##3b##). This pattern of injury is similar to previous observations in Al-sensitive maize root apices [##UREF##22##38##]. The hematoxylin staining result is concordant with the root growth data, indicating that greater Al accumulation is correlated with greater root growth inhibition in <italic>M. truncatula</italic>.</p>", "<title>Differential expression of genes in response to Al</title>", "<p>The molecular responses underlying differences in Al resistance were investigated using the <italic>M. truncatula </italic>AROS (version 1.0) arrays (Operon Biotechnologies Inc., Huntsville, AL) consisting of probes for approximately 16,000 <italic>M. truncatula </italic>expressed genes. Al-induced gene expression was compared in T32 and S70 after 12 and 48 h of +/- 2.5 μM Al treatment. We selected 12 h since root growth inhibition was observed at that time point in T32. We selected the 48 h time point since root growth rates recovered to that of the controls by 72 h in T32. These time points were chosen to identify transcriptional differences associated with Al-toxicity and resistance responses between the two lines. To detect significant genes with Al-regulated expression and to eliminate those that have inconsistent expression data among replicated experiments, we employed a statistical method adapted specifically for microarrays, which allows estimation of the false discovery rate (FDR) for multiple testing [##REF##11309499##39##]. A delta criterion that allowed a FDR &lt; 0.5% was applied. Genes that satisfied the statistical threshold were identified as significantly up- or down-regulated in Al-treated roots. In addition, we used a 2-fold change cut-off for the significant genes. Normalized and raw data have been submitted to NCBI Gene Expression Omnibus (Accession No. GSE6946). In both lines, the expression of a majority of transcripts appeared unchanged at both time points with Al treatment. As shown in Figure ##FIG##3##4##, more genes were significantly altered by ≥ 2.0-fold in 12 h Al-treated root tips compared to 48 h Al-treated root tips. Additionally, at both time points, a greater number of Al-induced genes were observed in S70 root tips (12 h = 365; 48 h = 287). Since root growth of S70 was inversely correlated with Al accumulation at these time points, the greater number of up-regulated genes in S70 at both time points likely corresponds to greater Al stress perception and may reflect Al toxicity responses. In contrast, the numbers of down-regulated genes were similar in both lines and at both time points (Figure ##FIG##3##4##). It has been suggested that adaptive reprogramming to stressful conditions may require a higher number of down-regulated genes [##REF##15375206##40##]; therefore, the similar numbers of down-regulated genes at both time points in both lines might reflect an overlap in Al stress adaptation responses.</p>", "<p>The genes showing significantly different transcript accumulation patterns in response to Al in T32 and S70 experiments were further compared to determine the number that were up- or down-regulated in response to Al treatment by 2-fold or more in both lines vs. only in one line (Figure ##FIG##3##4##). At the 12 h time point, 257 genes were uniquely expressed in T32 and 420 in S70. By 48 h T32 had 83 uniquely expressed genes and 343 were expressed only in S70. These differences may represent differences in Al stress perception and adaptation in T32 and S70 root tips. The large number of shared genes at the 12 h time point (189) might reflect an overlap in the Al toxicity responses in both lines. A list of selected significant differentially regulated genes is presented in Table ##TAB##1##2##. Functional categorization for all genes was based on Gene Ontology (GO) process information <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.geneontology.org\"/>.</p>", "<p>The Al-regulated expression changes in 12 significant genes were examined for both lines by quantitative reverse-transcription PCR (q-PCR). The q-PCR results showed the same direction of fold change of transcript abundance as the microarray in all three biological replicates for most genes (Table ##TAB##2##3##). In most cases, expression ratios based on q-PCR were higher than those ratios obtained from microarray hybridizations. This difference in expression ratios estimated by the two techniques has been observed previously [##REF##15195948##41##] and reflects the specificity and sensitivity of the q-PCR technique [##REF##15497399##42##]. The ratios (T32/S70) of the mean q-PCR fold change values were similar to the ratios of the microarray fold change values for most genes tested, thereby validating the microarray results.</p>", "<title>Gene expression in response to 12 h of Al treatment in S70 root tips</title>", "<p>After 12 h of Al treatment, the RRG of S70 was approximately 45% (Figure ##FIG##1##2b##) with Al accumulating mainly in the epidermis and outer cortical cells of the root tip (Figure ##FIG##4##5##). Aluminum has been shown to rapidly bind to the pectic matrix in the cell wall, reduce cell wall (CW) extensibility [##REF##15169940##7##,##UREF##23##43##], and consequently inhibit root elongation. Thus, as might be expected, a number of CW-related genes potentially involved in CW loosening including a pectinesterase precursor, an expansin-like protein and a xyloglucan endotransglycosylase, were differentially regulated in response to Al treatment in S70 root tips (Table ##TAB##1##2##). Pectin methylesterases have been shown to increase the Al sensitivity of plants because their ability to demethylate pectin, in addition to altering the sensitivity of the CW to the action of other CW-degrading enzymes [##REF##10368183##44##], might create additional binding sites for Al in the CW [##UREF##24##45##,##UREF##25##46##]. This can occur by increasing the free organic acid moieties (in galacturnoic acid) in the wall, making it more negatively charged. Recently, we showed that the down-regulation of a pectin acetylesterase gene in <italic>M. truncatula </italic>transgenic roots resulted in a modest increase (~20%) in root growth under Al stress conditions compared to wild-type plants [##REF##18351384##31##]. Based on these results it appears that plant cells respond to Al-induced CW stiffening by enhancing the expression of CW loosening enzymes in an attempt at stimulating CW expansion.</p>", "<p>Notable at this time point was the accumulation of gene transcripts encoding reactive oxygen species (ROS) generating enzymes. Genes encoding peroxidases and peroxidase precursors as well as germin-like proteins and carbohydrate oxidase were up-regulated (Table ##TAB##1##2##). Aluminum toxicity has previously been shown to trigger the expression and activity of ROS generating enzymes and ROS accumulation has been shown to positively correlate with Al sensitivity [##REF##11266584##47##,##REF##12482454##48##]. ROS are capable of causing oxidative damage to proteins, DNA, and lipids in plant cells and may ultimately lead to cell death [##REF##15377225##49##]. The enhanced expression of genes encoding ROS generating enzymes suggest that upon Al stress, S70 root tips experience oxidative damage, which could in turn result in complete root growth inhibition (Figure ##FIG##1##2b##). A number of genes coding for ROS generating enzymes were also found to be down-regulated in S70 at 12 h of Al treatment (Table ##TAB##1##2##). It is possible that specific peroxidases may be involved in the Al toxicity response, consequently resulting in the down-regulation of peroxidases involved in other responses, including ones that might be involved in ROS scavenging.</p>", "<p>The observed increase in transcript accumulation of ROS generating genes may reflect ROS accumulation in root tips and therefore may elicit the expression of antioxidant-related genes. Consistent with this hypothesis, an increase in the expression of antioxidant genes was observed in S70 root tips. Genes putatively encoding glutathione S-transferase and thioredoxin were significantly up-regulated (Table ##TAB##1##2##). Also up-regulated were genes encoding tyrosine aminotransferase and 4-hydroxyphenylpyruvate dioxygenase, enzymes involved in the biosynthesis of α-tocopherols, which function as membrane stabilizers and antioxidants that scavenge oxygen free radicals, lipid peroxy radicals, and singlet oxygen [##REF##16008098##50##].</p>", "<p>A number of stresses induce production of ROS and lipid peroxidation, including pathogen attack. Since Al resulted in accumulation of ROS generating gene transcripts in S70 root tips, the resulting ions and oxidative damage might have triggered the up-regulation of a number of pathogen defense-related and membrane-stabilizing genes (Table ##TAB##1##2##). A number of genes encoding isoflavonoid biosynthetic enzymes were uniquely up-regulated in 12 h Al-treated S70 root tips (Table ##TAB##1##2##). The isoflavonoids, which are mostly limited to the subfamily Papilionoideae of the Fabaceae, have been shown to function as phytoalexins [##UREF##26##51##] and antioxidants [##REF##7633567##52##]. Their up-regulation in response to Al stress may represent a unique response of the legume family to Al-induced oxidative stress.</p>", "<p>It has been shown that ROS triggers cell death by apoptosis, necrosis, or mechanisms with features of both [##REF##16760481##53##]. Between 24 and 48 h of Al treatment, cell death of Al-accumulating epidermal and outer cortical cell layers was observed in S70 root tips. Fluorescence observed in root tip cells as a result of morin staining depicts Al-accumulation while both light microscopy of Al-treated root tip cross sections (Figure ##FIG##4##5##) and root tips stained with Evan's blue, which is a dye that measures extent of cell death, indicates cell death (Figure ##FIG##5##6##). Consistent with this phenotypic observation, a number of cell-death associated genes were up-regulated in S70 root tips including cysteine proteinase, senescence associated proteins and genes for CW degrading enzymes that may be necessary for cell separation during programmed cell death. Hypothetically, gene expression data from S70 root tips after 12 h of Al treatment reflects enhanced CW stiffening, severe oxidative damage probably due to significant ROS accumulation and activation of cell death.</p>", "<title>Gene expression in response to 48 h of Al treatment in S70 root tips</title>", "<p>After 48 h of Al treatment, RRG of S70 was approximately 17% (Figure ##FIG##1##2b##). Notably, transcript accumulation of CW-modifying genes was observed at this time point (Table ##TAB##1##2##) suggesting continued CW stiffening from Al treatment. Furthermore, the prolonged induction of caffeic acid O-methyltransferase, involved in lignin biosynthesis only in S70 root tips could contribute to continued Al-induced root elongation inhibition. Genes putatively encoding polygalacturonase, pectate lyases, and β-1, 4-glucanase, which are CW-degrading enzymes, were significantly up-regulated in S70 root tips (Table ##TAB##1##2##). It is plausible that cell separation during the persistent cell death response at 48 h of Al treatment may elicit the prolonged expression of these genes. Interestingly, three genes encoding putative arabinogalactan-proteins (AGP) were uniquely up-regulated in S70 at 48 h of Al treatment. AGPs belong to a class of hydroxyproline-rich glycoproteins that are abundant in the plant CW and membrane [##REF##14645732##54##], with no clear function. Two maize AGPs were found in disintegrating xylem cells and a role in identifying cells committed to PCD was proposed [##REF##7534554##55##]. Furthermore, two AGP genes were identified as showing enhanced expression in Arabidopsis after Al stress [##REF##12177459##56##]. Thus, AGPs may represent a novel facet of the Al toxicity response since they are significantly up-regulated only in the Al-sensitive line and may be involved in modulating cell wall architecture and/or involved in the Al-induced cell death response.</p>", "<p>Accumulation of transcripts for enzymes generating ROS remained high after 48 h of Al treatment. The maintenance of peroxidase transcripts up to 48 h of Al treatment is consistent with previous observations in tobacco cells [##UREF##27##57##] and Arabidopsis [##REF##9449849##29##] in which these genes showed enhanced expression during prolonged Al treatments. A few antioxidant genes including thioredoxin, ascorbate peroxidase, and alternate oxidase were uniquely up-regulated in S70 root tips at 48 h Al treatment. However, transcripts for other antioxidant related genes expressed after 12 h of Al treatment did not show enhanced accumulation at 48 h. The enhanced expression of a greater number of ROS generating genes compared to antioxidant genes at 48 h suggests that the antioxidant capacity of S70 root tips might be insufficient to prevent significant ROS accumulation. Consequently, higher doses of ROS without sufficient scavenging, may lead to greater oxidative damage and necrosis in S70 root tips. Consistent with this hypothesis, the transcripts of four PR-genes and other stress-related genes remained at elevated levels after 48 h of Al treatment suggesting continued oxidative damage. In addition, cell death and senescence-associated genes were uniquely up-regulated in 48 h Al-treated S70 root tips suggesting the longevity and severity of the cell death response. In agreement with the expression data, we observed a ≥ 10-fold extent of cell death in S70 Al-treated root tips compared to control root tips after 48 h of Al treatment (Figure ##FIG##5##6##). In addition, at these time points, Al was observed in some of the inner cortical layers of the root tip as indicated by morin staining (Figure ##FIG##4##5##).</p>", "<p>Collectively, the prolonged expression of genes associated with CW loosening, ROS generation, cell death and CW degradation after 48 h of Al treatment implies that the Al-induced oxidative damage and cell death response resembles a necrotic response, damaging deeper cell layers and ultimately resulting in irreversible root growth inhibition in S70.</p>", "<title>Gene expression in response to 12 h Al treatment in T32 root tips</title>", "<p>At 12 h of Al treatment, the RRG of T32 was approximately 78% (Figure ##FIG##1##2a##) with Al accumulating mainly in the epidermal cell layer of the root tip as indicated by morin staining (Figure ##FIG##4##5##). The inhibition in root growth, although not as severe as in S70, might induce the expression of CW-related genes. Consistent with this hypothesis, CW loosening genes were similarly regulated in S70 and T32 root tips at 12 h of Al treatment (Table ##TAB##1##2##), indicating an overlap in responses to Al toxicity in both lines.</p>", "<p>Transcript accumulation of genes encoding ROS generating enzymes in T32 root tips was similar to that observed in S70; however, the total number of up-regulated genes was lower in T32 root tips (Figure ##FIG##3##4##). A number of antioxidant genes accumulated similarly in both lines (Table ##TAB##1##2##). However, two quinone oxidoreductase genes, a glutathione s-transferase (GST) gene, and a blue copper protein (BCB) precursor were significantly up-regulated only in T32 root tips. Quinone-oxidoreductases, which are involved in the detoxification of reactive aldehydes derived from lipid peroxides [##REF##12514241##58##] have previously been shown to be induced in response to Al treatment in Al-tolerant and Al-sensitive rice roots [##REF##14645395##59##]. Previously, BCB and GST genes were shown to be up-regulated in Arabidopsis in response to Al treatment [##REF##9449849##29##] and plants over-expressing these genes displayed increased resistance to low Al concentrations [##REF##10712528##60##]. Therefore, these genes may represent a resistance response associated with ROS scavenging in response to Al treatment only in Al-resistant root tips. Relative to S70, a greater number of ROS generating genes including peroxidases and peroxidase precursors were down-regulated in T32 (Table ##TAB##1##2##). However, in contrast to S70, antioxidant genes were not down-regulated in T32. In addition, up-regulation of fewer PR-genes, isoflavonoid biosynthetic genes, and stress-related genes (Table ##TAB##1##2##) reflected a lower extent of oxidative damage in T32 root tips. These data suggest that although there appears to be ROS accumulation in response to 12 h Al treatment in T32 root tips, the levels may be lower than that observed in S70.</p>", "<p>A number of cell-death associated genes were uniquely up-regulated in T32 after 12 h of Al treatment (Table ##TAB##1##2##). Expression of these genes is consistent with cell death observed at 24 h of Al treatment (Figure ##FIG##4##5## and ##FIG##5##6##). Interestingly, cell death appeared to be restricted to cells that accumulate Al as visualized by light microscopy of root tip cross sections (Figure ##FIG##4##5##). It has been suggested that low Al concentration treatments induce cell death possibly via a ROS-activated signal transduction pathway [##REF##11378174##61##]. However, exposure to more toxic concentrations of Al may cause necrosis in the root tip cells. Likewise, H₂O₂produced in barley roots, during early phases of Al stress, has been suggested to play a role in the induction of cell death [##REF##15726813##62##]. Therefore, in addition to the observed patterns of expression of ROS generating and scavenging genes, the activation of cell death in Al-accumulating root tip cells indicate lower ROS accumulation in T32 after 12 h Al treatment. Accumulation of low levels of ROS, which although might be insufficient to cause significant oxidative damage, may play a key role in triggering cell death of Al-accumulating cells, as has been demonstrated in cell death responses to other abiotic and biotic stresses [##REF##15377225##49##,##REF##17041898##63##].</p>", "<title>Gene expression in response to 48 h Al treatment in T32 root tips</title>", "<p>After 48 h of 2.5 μM Al treatment, the RRG of T32 recovered to approximately 90% (Figure ##FIG##0##1## and ##FIG##1##2a##). At this time point fewer genes were differentially regulated in response to Al treatment in T32 root tips (Figure ##FIG##3##4##) compared to 12 h of treatment. Notably, fewer ROS generating genes were up-regulated, and up-regulation of a number of antioxidant genes was observed (Table ##TAB##1##2##). Since fewer ROS generating genes were up-regulated, the basal antioxidant capacity may have been sufficient to prevent significant ROS accumulation. Interestingly, there was no significant change in expression of stress-related genes, including PR-proteins and isoflavonoids and cell death genes (Table ##TAB##1##2##) suggesting that the ROS levels may have been insufficient to cause oxidative damage and cell death. In fact, down-regulation of some stress-related genes and senescence-associated genes was observed at this time point (Table ##TAB##1##2##). Moreover, probably as a result of new root tip growth, the extent of Al accumulation and cell death at 48 h was minimal (Figure ##FIG##4##5## and ##FIG##5##6##). Therefore, we speculate that in T32 root tips, the cell death response occurred early on and was aimed at removing Al-accumulating cells leading to a recovery in root growth.</p>", "<p>A continued response to Al stress in T32 root tips after 48 h of Al treatment was indicated by the high transcript accumulation of a putative multidrug and toxin extrusion (MATE) gene (TC105342; MtMATE). Although the expression of this gene was significantly up-regulated at both time points of Al treatment and in both lines (Table ##TAB##1##2##), the prolonged expression of this gene during root growth recovery in the Al-tolerant line made it an interesting candidate for Al resistance studies. We examined whether the spatial expression pattern of this gene played a role in differential Al resistance responses in these lines.</p>", "<title>Differential pattern of expression of MtMATE in T32 and S70</title>", "<p>To determine the spatial distribution of MATE gene expression in response to early (3 h) and later (12 h) time points of Al treatment, <italic>in situ </italic>PCR was carried out on root tip cross sections. In 3 h Al-treated T32 root tips, a positive signal was visible in cells of the endodermis and the regions encompassing the vascular bundles (Figure ##FIG##6##7##). In contrast, in 3 h Al-treated S70 root tips, the signal appeared to be more uniformly distributed over the entire section including the epidermis, cortical cells and vasculature (Figure ##FIG##6##7##). No signal was observed in 3 h control (-Al) T32 and S70 root sections (Figure ##FIG##6##7##). In 12 h Al-treated T32 root tips, a strong signal was visible in the epidermis in addition to the vascular region; however, the signal appeared to be restricted to the epidermis and outer cortical cells in 12 h Al-treated S70 root tips. A positive signal was also observed in the epidermis, cortical cells and vasculature of 12 h control S70 roots (Figure ##FIG##6##7##) indicating the uniform expression of this gene under Al-free conditions. The intron-specific primers gave no positive signals (Figure ##FIG##6##7##). Overall, the localization of MATE expression in Al-treated root tips indicated that the transcript of the MATE gene accumulated most strongly in the vascular region of T32 and mainly in the epidermal and outer cortical layers in S70.</p>", "<p>The MtMATE shares 67% identity with a putative lupin LaMATE (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"AAW30732\">AAW30732</ext-link>; [##REF##16297074##64##]), 63% identity with a rice MATE gene (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"ABB47036\">ABB47036</ext-link>), and 62% identity with the Arabidopsis FRD3 protein (GenBank accession no. <ext-link ext-link-type=\"gen\" xlink:href=\"NP_187461.1\">NP_187461.1</ext-link>; [##REF##12172022##65##]). Based on studies conducted on different MATE genes it has been hypothesized that this family may be involved in transporting a diverse set of small organic molecules either directly out of the cell or into vacuolar compartments [##REF##12172022##65##, ####REF##11073914##66##, ##REF##11739388##67####11739388##67##]. Recently, FRD3 was shown to be a citrate efflux transporter and Arabidopsis plants ectopically expressing FRD3 had significantly higher amounts of citrate in their root exudates compared to untransformed controls and possessed an enhanced resistance to aluminium [##REF##17351051##68##]. Morin staining revealed presence of Al in the vasculature of T32 root tips at 12 h of Al treatment (Figure ##FIG##4##5##). Taking the differential root growth rates and Al accumulation patterns together with the spatial expression pattern of the MtMATE, it is tempting to speculate that the strong vascular expression of MtMATE in T32 root tips might be involved in transporting Al away from the sensitive growing root tip therefore resulting in lower root growth inhibition in T32. Internal detoxification of Al by formation of organic acid-Al complexes has been previously demonstrated in hydrangea and buckwheat [##REF##9662518##15##,##REF##12223659##69##]. In buckwheat, Al is chelated internally in the root cells by oxalate and translocated via the xylem to leaf cells where these complexes are then stored in vacuoles [##REF##10987553##70##]. Likewise, it is possible that in T32 the MtMATE gene may be involved in the transport of organic acid-Al complexes into the aerial parts of the plant followed by sequestration into vacuoles. In S70, the organic acid efflux or Al-sequestration into vacuoles might be restricted to the root surface as indicated by the strong expression in the epidermal and cortical cells. In addition, it is possible that the observed expression of this gene under Al-free conditions in S70 root tips is in response to low pH or low pH-induced nutrient deficiencies. Interestingly, the LaMATE displays enhanced expression under various nutrient stress conditions including -P, -Fe, -Mn, -N and + Al [##REF##16297074##64##]. Similarly, the FRD3 gene is induced in response to cold stress and during senescence (a search of 2,620 ATH1 Affymetrix chips in <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.genevestigator.ethz.ch/gv/index.jsp\"/>). Alternatively, although Al-induced expression of the MATE gene occurs in both lines, the subsequent activation of organic acid efflux might be delayed or inhibited in S70. Localization of MtMATE to either the plasma membrane or the vacuole would reveal its site of action, and identification of the molecule it transports could permit a direct biochemical test of its function in transport.</p>" ]

[ "<title>Conclusion</title>", "<p>One of the most widely studied mechanisms of Al resistance is the Al exclusion and/or internal detoxification via organic acids (OA), which serve as Al chelators. However, induction of OA biosynthetic genes was not observed in this study. This finding was not surprising since, to date, no strong evidence exists for Al-induced expression of any of the enzymes catalyzing OA synthesis and metabolism [##UREF##5##6##]. Indeed, it is possible that OA biosynthetic enzymes are regulated translationally or post-translationally. In the present study we compared physiological and molecular differences between an Al- resistant and sensitive line, which enabled us to identify novel facets of Al resistance in <italic>Medicago truncatula</italic>. A number of Al-inducible genes with potential roles in Al resistance were identified in this study. For example, the Al-inducible MATE gene might be involved in organic acid exudation and internal detoxification of Al in T32, supporting the idea of an Al resistance mechanism involving organic acids in <italic>M. truncatula</italic>. Additionally, cell death of Al-accumulating cells in T32 represents a unique aspect of Al resistance in legumes. Our results provide a valuable data set for future studies targeted at investigating additional Al resistance responses.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Aluminum (Al) toxicity is an important factor limiting crop production on acid soils. However, little is known about the mechanisms by which legumes respond to and resist Al stress. To explore the mechanisms of Al toxicity and resistance in legumes, we compared the impact of Al stress in Al-resistant and Al-sensitive lines of the model legume, <italic>Medicago truncatula </italic>Gaertn.</p>", "<title>Results</title>", "<p>A screen for Al resistance in 54 <italic>M. truncatula </italic>accessions identified eight Al-resistant and eight Al-sensitive lines. Comparisons of hydroponic root growth and root tip hematoxylin staining in an Al-resistant line, T32, and an Al-sensitive line, S70, provided evidence that an inducible Al exclusion mechanism occurs in T32. Transcriptional events associated with the Al resistance response were analyzed in T32 and S70 after 12 and 48 h Al treatment using oligonucleotide microarrays. Fewer genes were differentially regulated in response to Al in T32 compared to S70. Expression patterns of oxidative stress-related genes, stress-response genes and microscopic examination of Al-treated root tips suggested a lower degree of Al-induced oxidative damage to T32 root tips compared to S70. Furthermore, genes associated with cell death, senescence, and cell wall degradation were induced in both lines after 12 h of Al treatment but preferentially in S70 after 48 h of Al treatment. A multidrug and toxin efflux (MATE) transporter, previously shown to exude citrate in <italic>Arabidopsis</italic>, showed differential expression patterns in T32 and S70.</p>", "<title>Conclusion</title>", "<p>Our results identified novel genes induced by Al in Al-resistant and sensitive <italic>M. truncatula </italic>lines. In T32, transcription levels of genes related to oxidative stress were consistent with reactive oxygen species production, which would be sufficient to initiate cell death of Al-accumulating cells thereby contributing to Al exclusion and root growth recovery. In contrast, transcriptional levels of oxidative stress-related genes were consistent with excessive reactive oxygen species accumulation in S70 potentially resulting in necrosis and irreversible root growth inhibition. In addition, a citrate-exuding MATE transporter could function in Al exclusion and/or internal detoxification in T32 based on Al-induced transcript localization studies. Together, our findings indicate that multiple responses likely contribute to Al resistance in <italic>M. truncatula</italic>.</p>" ]

[ "<title>Authors' contributions</title>", "<p>DC and DAS conceived the study and wrote most of the paper. DC and DFG conceived the physiological characterization of the Al resistant and sensitive lines, while DC and DAS conceived the molecular characterization of the two lines. NS performed the statistical analyses of the microarray data and uploaded the data onto Gene Omnibus. KAV improved the overall quality of the manuscript. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Dr. David Galbraith (University of Arizona) for printing of microarrays and Dr. Dasharath P. Lohar (University of Minnesota) for assistance with microarray slide scanning. We also thank Dr. Mark Sanders at the University of Minnesota – College of Biological Sciences, Imaging Center, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.cbs.umn.edu/ic/\"/> for assistance with fluorescence microscopy. We acknowledge support from the University of Minnesota Super Computing Institute for data analysis.</p>", "<p>This work was partially supported by the National Science Foundation Plant Genome Project (award no. 0110206). Mention of trade names or commercial products in the article is solely for the purpose of providing specific information and does not imply recommendations or endorsement by the U.S. Department of Agriculture.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Effect of Al-dose on root growth in <italic>M. truncatula</italic>.</bold> RRG ± SE of T32, A17 and S70 seedlings grown at 1.25, 2.5, 5 and 10 μM Al for 48 h.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Effect of Al-dose and time on root growth of <italic>M. truncatula</italic>.</bold> Cumulative root growth of seedlings exposed to 0, 1.25, 2.5, 5 and 10 μM Al for 12, 24, 48 and 72 h. Data represent the mean root growth values ± SE of eight seedlings from three independent experiments. (a) T32 seedlings. (b) S70 seedlings.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Al-accumulation in <italic>M. truncatula </italic>root apices.</bold> (a) Hematoxylin staining of T32 and S70 seedlings exposed to a range of Al concentrations for 48 h. (b) Hematoxylin staining of root apices of <italic>M. truncatula </italic>grown in 2.5 μM Al solution for 0 to 72 h. Scale bar represents 500 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Genes with significantly altered expression in Al-treated root tips compared to control root tips in T32 and S70.</bold> (a) 12 h Al treatment. (b) 48 h Al treatment.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Effect of Al on surface cell layer morphology and localization of Al by morin in transverse sections taken 1.5 to 2 cm behind root tips of <italic>M. truncatula </italic>lines.</bold> Smooth surface of transversal sections of T32 (a) and S70 (k) roots grown in 0 μM Al solution. Recovery from Al-induced damage as a result of new root growth in T32 root apices (b-e) exposed to 2.5 μM Al for 12, 24, 48 and 72 h. Damaged outer epidermal and outer cortical cell layers as a result of no new root growth in S70 root apices (l-o) exposed to 2.5 μM Al. Black scale bar = 100 μm. Minimal background fluorescence observed in cells of T32 (f) and S70 (p) root apices grown in 0 μM Al solution. Bright blue fluorescence indicates morin staining in cells of T32 (g-j) and S70 (q-t) root apices grown in 2.5 μM Al solution for 12, 24, 48 and 72 h. White scale bar = 100 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Measurement of cell death by Evans blue uptake in <italic>M. truncatula </italic>root apices.</bold> Relative Evans blue uptake (OD₆₀₀for Al treated root tips/OD₆₀₀for control (-Al) root tips) in root tips of <italic>M. truncatula </italic>lines T32 and S70 grown in 0 μM and 2.5 μM Al solutions for 12, 24, 48 and 72 h.</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>MtMATE gene expression in Al-treated and control T32 and S70 root tips.</bold> IC denotes <italic>in situ </italic>PCR using intron-specific primers. The images shown are representative of at least three independent experiments.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Mean relative root growth (n = 6) of <italic>M. truncatula </italic>lines after 2 d of growth in 2.5 μM Al solution.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Line Designation</td><td align=\"left\">Accession Number</td><td align=\"left\">Country of Origin</td><td align=\"center\">Relative root growth (RRG)</td><td align=\"center\">(±)SE</td><td align=\"center\"><italic>P-</italic>value (*&lt;0.05 **&lt;0.01)</td><td align=\"center\">RRG (normalized to A17)</td></tr></thead><tbody><tr><td align=\"center\" colspan=\"7\"><underline>USDA Collection</underline></td></tr><tr><td align=\"center\">A32 (T32)</td><td align=\"left\">PI 384662</td><td align=\"left\">Morocco</td><td align=\"center\">0.93</td><td align=\"center\">0.05</td><td align=\"center\">0.001 **</td><td align=\"center\">2.92</td></tr><tr><td align=\"center\">A43</td><td align=\"left\">PI 577628</td><td align=\"left\">Spain</td><td align=\"center\">0.91</td><td align=\"center\">0.09</td><td align=\"center\">0.000 **</td><td align=\"center\">2.85</td></tr><tr><td align=\"center\">A41</td><td align=\"left\">PI 319045</td><td align=\"left\">Spain</td><td align=\"center\">0.88</td><td align=\"center\">0.05</td><td align=\"center\">0.000 **</td><td align=\"center\">2.75</td></tr><tr><td align=\"center\">A84</td><td align=\"left\">W6 6050</td><td align=\"left\">Tunisia</td><td align=\"center\">0.88</td><td align=\"center\">0.17</td><td align=\"center\">0.000 **</td><td align=\"center\">2.74</td></tr><tr><td align=\"center\">A10</td><td align=\"left\">PI 197361</td><td align=\"left\">Australia</td><td align=\"center\">0.81</td><td align=\"center\">0.11</td><td align=\"center\">0.000 **</td><td align=\"center\">2.52</td></tr><tr><td align=\"center\">A62</td><td align=\"left\">PI 464815</td><td align=\"left\">Turkey</td><td align=\"center\">0.80</td><td align=\"center\">0.28</td><td align=\"center\">0.001 **</td><td align=\"center\">2.50</td></tr><tr><td align=\"center\">A47</td><td align=\"left\">W6 6099</td><td align=\"left\">Portugal</td><td align=\"center\">0.71</td><td align=\"center\">0.09</td><td align=\"center\">0.000 **</td><td align=\"center\">2.20</td></tr><tr><td align=\"center\">A36</td><td align=\"left\">PI 516937</td><td align=\"left\">Morocco</td><td align=\"center\">0.67</td><td align=\"center\">0.13</td><td align=\"center\">0.000 **</td><td align=\"center\">2.08</td></tr><tr><td align=\"center\">A85</td><td align=\"left\">W6 6110</td><td align=\"left\">Italy</td><td align=\"center\">0.63</td><td align=\"center\">0.11</td><td align=\"center\">0.000 **</td><td align=\"center\">1.97</td></tr><tr><td align=\"center\">A55</td><td align=\"left\">W6 6000</td><td align=\"left\">France</td><td align=\"center\">0.60</td><td align=\"center\">0.07</td><td align=\"center\">0.000 **</td><td align=\"center\">1.88</td></tr><tr><td align=\"center\">A34</td><td align=\"left\">PI 516927</td><td align=\"left\">Morocco</td><td align=\"center\">0.60</td><td align=\"center\">0.08</td><td align=\"center\">0.000 **</td><td align=\"center\">1.87</td></tr><tr><td align=\"center\">A77</td><td align=\"left\">W6 6012</td><td align=\"left\">Italy</td><td align=\"center\">0.59</td><td align=\"center\">0.09</td><td align=\"center\">0.001 *</td><td align=\"center\">1.85</td></tr><tr><td align=\"center\">A91</td><td align=\"left\">PI 577617</td><td align=\"left\">Greece</td><td align=\"center\">0.59</td><td align=\"center\">0.03</td><td align=\"center\">0.000 **</td><td align=\"center\">1.84</td></tr><tr><td align=\"center\">A65</td><td align=\"left\">PI 577434</td><td align=\"left\">Tunisia</td><td align=\"center\">0.58</td><td align=\"center\">0.08</td><td align=\"center\">0.001 **</td><td align=\"center\">1.81</td></tr><tr><td align=\"center\">A100</td><td align=\"left\">W6 5983</td><td align=\"left\">Cyprus</td><td align=\"center\">0.56</td><td align=\"center\">0.10</td><td align=\"center\">0.003 **</td><td align=\"center\">1.75</td></tr><tr><td align=\"center\">A50</td><td align=\"left\">PI 577608</td><td align=\"left\">France</td><td align=\"center\">0.55</td><td align=\"center\">0.15</td><td align=\"center\">0.018 *</td><td align=\"center\">1.70</td></tr><tr><td align=\"center\">A11</td><td align=\"left\">PI 243884</td><td align=\"left\">Australia</td><td align=\"center\">0.54</td><td align=\"center\">0.12</td><td align=\"center\">0.012 *</td><td align=\"center\">1.69</td></tr><tr><td align=\"center\">A28</td><td align=\"left\">PI 384636</td><td align=\"left\">Morocco</td><td align=\"center\">0.52</td><td align=\"center\">0.06</td><td align=\"center\">0.005 **</td><td align=\"center\">1.63</td></tr><tr><td align=\"center\">A12</td><td align=\"left\">PI 442892</td><td align=\"left\">Australia</td><td align=\"center\">0.50</td><td align=\"center\">0.09</td><td align=\"center\">0.020 *</td><td align=\"center\">1.56</td></tr><tr><td align=\"center\">A88</td><td align=\"left\">PI 577599</td><td align=\"left\">Greece</td><td align=\"center\">0.49</td><td align=\"center\">0.13</td><td align=\"center\">0.052</td><td align=\"center\">1.54</td></tr><tr><td align=\"center\">A3</td><td align=\"left\">PI 190084</td><td align=\"left\">Australia</td><td align=\"center\">0.49</td><td align=\"center\">0.09</td><td align=\"center\">0.028 *</td><td align=\"center\">1.53</td></tr><tr><td align=\"center\">A87</td><td align=\"left\">PI 566887</td><td align=\"left\">Greece</td><td align=\"center\">0.48</td><td align=\"center\">0.21</td><td align=\"center\">0.183</td><td align=\"center\">1.49</td></tr><tr><td align=\"center\">A89</td><td align=\"left\">PI 577601</td><td align=\"left\">Greece</td><td align=\"center\">0.47</td><td align=\"center\">0.12</td><td align=\"center\">0.087</td><td align=\"center\">1.46</td></tr><tr><td align=\"center\">A101</td><td align=\"left\">W6 5984</td><td align=\"left\">Cyprus</td><td align=\"center\">0.44</td><td align=\"center\">0.06</td><td align=\"center\">0.083</td><td align=\"center\">1.38</td></tr><tr><td align=\"center\">A21</td><td align=\"left\">PI 577641</td><td align=\"left\">Australia</td><td align=\"center\">0.42</td><td align=\"center\">0.10</td><td align=\"center\">0.210</td><td align=\"center\">1.31</td></tr><tr><td align=\"center\">A15</td><td align=\"left\">PI 469099</td><td align=\"left\">Australia</td><td align=\"center\">0.38</td><td align=\"center\">0.07</td><td align=\"center\">0.438</td><td align=\"center\">1.19</td></tr><tr><td align=\"center\">A40</td><td align=\"left\">PI 244285</td><td align=\"left\">Spain</td><td align=\"center\">0.38</td><td align=\"center\">0.07</td><td align=\"center\">0.427</td><td align=\"center\">1.18</td></tr><tr><td align=\"center\">A66</td><td align=\"left\">PI 577619</td><td align=\"left\">Tunisia</td><td align=\"center\">0.35</td><td align=\"center\">0.15</td><td align=\"center\">0.787</td><td align=\"center\">1.10</td></tr><tr><td align=\"center\">A5</td><td align=\"left\">PI 190089</td><td align=\"left\">Australia</td><td align=\"center\">0.34</td><td align=\"center\">0.05</td><td align=\"center\">0.852</td><td align=\"center\">1.06</td></tr><tr><td/><td align=\"left\">A17</td><td align=\"left\">Australia</td><td align=\"center\">0.33</td><td align=\"center\">0.03</td><td align=\"center\">NA</td><td align=\"center\">1.00</td></tr><tr><td align=\"center\">A92</td><td align=\"left\">PI 577618</td><td align=\"left\">Greece</td><td align=\"center\">0.31</td><td align=\"center\">0.11</td><td align=\"center\">0.818</td><td align=\"center\">0.97</td></tr><tr><td align=\"center\">A93</td><td align=\"left\">PI 577604</td><td align=\"left\">Cyprus</td><td align=\"center\">0.30</td><td align=\"center\">0.07</td><td align=\"center\">0.690</td><td align=\"center\">0.94</td></tr><tr><td align=\"center\">A18</td><td align=\"left\">PI 517257</td><td align=\"left\">Australia</td><td align=\"center\">0.28</td><td align=\"center\">0.16</td><td align=\"center\">0.633</td><td align=\"center\">0.88</td></tr><tr><td align=\"center\">A82</td><td align=\"left\">W6 6047</td><td align=\"left\">Tunisia</td><td align=\"center\">0.28</td><td align=\"center\">0.03</td><td align=\"center\">0.418</td><td align=\"center\">0.87</td></tr><tr><td align=\"center\">A17</td><td align=\"left\">PI 469102</td><td align=\"left\">Australia</td><td align=\"center\">0.27</td><td align=\"center\">0.05</td><td align=\"center\">0.374</td><td align=\"center\">0.85</td></tr><tr><td align=\"center\">A42</td><td align=\"left\">PI 319051</td><td align=\"left\">Spain</td><td align=\"center\">0.23</td><td align=\"center\">0.08</td><td align=\"center\">0.000 **</td><td align=\"center\">0.72</td></tr><tr><td align=\"center\">A76</td><td align=\"left\">W6 5964</td><td align=\"left\">Italy</td><td align=\"center\">0.23</td><td align=\"center\">0.04</td><td align=\"center\">0.112</td><td align=\"center\">0.71</td></tr><tr><td align=\"center\">A19</td><td align=\"left\">PI 566888</td><td align=\"left\">Australia</td><td align=\"center\">0.19</td><td align=\"center\">0.07</td><td align=\"center\">0.044 *</td><td align=\"center\">0.60</td></tr><tr><td align=\"center\">A90</td><td align=\"left\">PI 577602</td><td align=\"left\">Greece</td><td align=\"center\">0.17</td><td align=\"center\">0.08</td><td align=\"center\">0.026 *</td><td align=\"center\">0.53</td></tr><tr><td align=\"center\">A70 (S70)</td><td align=\"left\">PI 577613</td><td align=\"left\">Italy</td><td align=\"center\">0.15</td><td align=\"center\">0.02</td><td align=\"center\">0.002 **</td><td align=\"center\">0.48</td></tr><tr><td align=\"center\">A60</td><td align=\"left\">PI 577614</td><td align=\"left\">Malta</td><td align=\"center\">0.15</td><td align=\"center\">0.10</td><td align=\"center\">0.028 *</td><td align=\"center\">0.48</td></tr><tr><td align=\"center\">A7</td><td align=\"left\">PI 190091</td><td align=\"left\">Australia</td><td align=\"center\">0.15</td><td align=\"center\">0.09</td><td align=\"center\">0.018 *</td><td align=\"center\">0.48</td></tr><tr><td align=\"center\">A31</td><td align=\"left\">PI 384660</td><td align=\"left\">Morocco</td><td align=\"center\">0.15</td><td align=\"center\">0.04</td><td align=\"center\">0.012 *</td><td align=\"center\">0.47</td></tr><tr><td align=\"center\">A4</td><td align=\"left\">PI 190087</td><td align=\"left\">Australia</td><td align=\"center\">0.14</td><td align=\"center\">0.04</td><td align=\"center\">0.004 **</td><td align=\"center\">0.44</td></tr><tr><td align=\"center\">A56</td><td align=\"left\">PI 493295</td><td align=\"left\">Portugal</td><td align=\"center\">0.13</td><td align=\"center\">0.07</td><td align=\"center\">0.005 **</td><td align=\"center\">0.40</td></tr><tr><td align=\"center\">A48</td><td align=\"left\">PI 535739</td><td align=\"left\">Libya</td><td align=\"center\">0.12</td><td align=\"center\">0.05</td><td align=\"center\">0.002 **</td><td align=\"center\">0.39</td></tr><tr><td align=\"center\">A79</td><td align=\"left\">W6 6025</td><td align=\"left\">Italy</td><td align=\"center\">0.08</td><td align=\"center\">0.06</td><td align=\"center\">0.001 **</td><td align=\"center\">0.26</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\" colspan=\"7\"><underline>French Collection</underline></td></tr><tr><td/><td align=\"left\">DZA45.5</td><td align=\"left\">Algeria</td><td align=\"center\">0.61</td><td align=\"center\">0.08</td><td align=\"center\">0.000 **</td><td align=\"center\">1.91</td></tr><tr><td/><td align=\"left\">TN8.3</td><td align=\"left\">Tunisia</td><td align=\"center\">0.41</td><td align=\"center\">0.04</td><td align=\"center\">0.132</td><td align=\"center\">1.28</td></tr><tr><td/><td align=\"left\">TN1.11</td><td align=\"left\">Tunisia</td><td align=\"center\">0.35</td><td align=\"center\">0.03</td><td align=\"center\">0.656</td><td align=\"center\">1.10</td></tr><tr><td/><td align=\"left\">F83005.9</td><td align=\"left\">France</td><td align=\"center\">0.33</td><td align=\"center\">0.14</td><td align=\"center\">0.941</td><td align=\"center\">1.04</td></tr><tr><td/><td align=\"left\">F8005.5</td><td align=\"left\">France</td><td align=\"center\">0.30</td><td align=\"center\">0.03</td><td align=\"center\">0.586</td><td align=\"center\">0.93</td></tr><tr><td/><td align=\"left\">A20</td><td align=\"left\">Australia</td><td align=\"center\">0.25</td><td align=\"center\">0.05</td><td align=\"center\">0.207</td><td align=\"center\">0.80</td></tr><tr><td/><td align=\"left\">DZA315.16</td><td align=\"left\">Algeria</td><td align=\"center\">0.24</td><td align=\"center\">0.03</td><td align=\"center\">0.099</td><td align=\"center\">0.74</td></tr><tr><td/><td align=\"left\">TN6.18</td><td align=\"left\">Tunisia</td><td align=\"center\">0.19</td><td align=\"center\">0.11</td><td align=\"center\">0.124</td><td align=\"center\">0.59</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Selected genes differentially regulated by ≥ 2.0-fold or ≤ 0.5-fold in at least one <italic>M. truncatula </italic>line in response to Al treatment.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">TIGR TC</td><td align=\"left\">Tentative Annotation</td><td align=\"center\">GO process iD</td><td align=\"center\" colspan=\"2\">Fold Change T32</td><td align=\"center\" colspan=\"2\">Fold Change S70</td></tr></thead><tbody><tr><td/><td align=\"left\"><bold>Cell Wall Modification</bold></td><td/><td align=\"center\">12 h</td><td align=\"center\">48 h</td><td align=\"center\">12 h</td><td align=\"center\">48 h</td></tr><tr><td/><td/><td/><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">TC96658</td><td align=\"left\">Xyloglucan endotransglucosylase putative</td><td align=\"center\">Carbohydrate metabolism GO:0005975</td><td align=\"center\">2.2</td><td align=\"center\">2.9</td><td align=\"center\">5.3</td><td align=\"center\">10.7</td></tr><tr><td align=\"left\">TC100486</td><td align=\"left\">Xyloglucan endotransglycosylase putative</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">2.3</td><td align=\"center\">0.9</td><td align=\"center\">1.3</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC95073</td><td align=\"left\">Polygalacturonase like protein</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">2.6</td><td align=\"center\">0.6</td><td align=\"center\">4.3</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC96355</td><td align=\"left\">Polygalacturonase</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">1.1</td><td align=\"center\">2.3</td><td align=\"center\">ND</td><td align=\"center\">4.1</td></tr><tr><td align=\"left\">TC111920</td><td align=\"left\">Polygalacturonase PG1 putative</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">1.4</td><td align=\"center\">2.8</td><td align=\"center\">1.5</td><td align=\"center\">3.7</td></tr><tr><td align=\"left\">TC110038</td><td align=\"left\">Pectinesterase putative</td><td align=\"center\">Cell wall modification GO:0042545</td><td align=\"center\">2.0</td><td align=\"center\">1.1</td><td align=\"center\">1.3</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC94920</td><td align=\"left\">Probable pectinesterase precursor</td><td align=\"center\">Cell wall modification</td><td align=\"center\">2.2</td><td align=\"center\">0.8</td><td align=\"center\">4.5</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC107655</td><td align=\"left\">Xyloglucanase inhibitor putative</td><td align=\"center\">Unknown</td><td align=\"center\">1.3</td><td align=\"center\">1.3</td><td align=\"center\">4.4</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC94309</td><td align=\"left\">Xyloglucanase inhibitor putative</td><td align=\"center\">Unknown</td><td align=\"center\">1.1</td><td align=\"center\">0.9</td><td align=\"center\">2.0</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC94310</td><td align=\"left\">Xyloglucanase inhibitor putative</td><td align=\"center\">Unknown</td><td align=\"center\">1.1</td><td align=\"center\">0.8</td><td align=\"center\">2.1</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC98964</td><td align=\"left\">Caffeic acid O-methyltransferase</td><td align=\"center\">Lignin biosynthesis GO:0009809</td><td align=\"center\">1.3</td><td align=\"center\">0.9</td><td align=\"center\">1.5</td><td align=\"center\">2.0</td></tr><tr><td align=\"left\">TC107848</td><td align=\"left\">Caffeic acid O-methyltransferase II</td><td align=\"center\">Lignin biosynthesis</td><td align=\"center\">1.2</td><td align=\"center\">1.2</td><td align=\"center\">2.1</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC100394</td><td align=\"left\">Caffeic acid O-methyltransferase</td><td align=\"center\">Lignin biosynthesis</td><td align=\"center\">1.1</td><td align=\"center\">ND</td><td align=\"center\">2.1</td><td align=\"center\">2.8</td></tr><tr><td align=\"left\">TC94484</td><td align=\"left\">Expansin</td><td align=\"center\">Cell expansion GO:0009831</td><td align=\"center\">1.5</td><td align=\"center\">1.5</td><td align=\"center\">2.0</td><td align=\"center\">3.7</td></tr><tr><td align=\"left\">TC109283</td><td align=\"left\">Expansin</td><td align=\"center\">Cell expansion</td><td align=\"center\">1.4</td><td align=\"center\">1.5</td><td align=\"center\">1.4</td><td align=\"center\">3.0</td></tr><tr><td align=\"left\">TC100685</td><td align=\"left\">Pectate lyase</td><td align=\"center\">Unknown</td><td align=\"center\">1.4</td><td align=\"center\">1.8</td><td align=\"center\">1.2</td><td align=\"center\">4.7</td></tr><tr><td align=\"left\">TC96079</td><td align=\"left\">Pectate lyase</td><td align=\"center\">Unknown</td><td align=\"center\">1.4</td><td align=\"center\">1.8</td><td align=\"center\">1.9</td><td align=\"center\">4.6</td></tr><tr><td align=\"left\">TC108882</td><td align=\"left\">β-1,4-glucanase</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">1.3</td><td align=\"center\">1.5</td><td align=\"center\">ND</td><td align=\"center\">10.6</td></tr><tr><td align=\"left\">TC108539</td><td align=\"left\">Arabinogalactan protein-like</td><td align=\"center\">Cell adhesion GO:0007155</td><td align=\"center\">0.6</td><td align=\"center\">1.1</td><td align=\"center\">1.0^ns</td><td align=\"center\">3.8</td></tr><tr><td align=\"left\">TC94068</td><td align=\"left\">Fasciclin-like AGP 14</td><td align=\"center\">Cell adhesion</td><td align=\"center\">ND</td><td align=\"center\">1.1</td><td align=\"center\">1.0</td><td align=\"center\">2.3</td></tr><tr><td align=\"left\">TC108519</td><td align=\"left\">Fasciclin-like AGP 14</td><td align=\"center\">Cell adhesion</td><td align=\"center\">0.6</td><td align=\"center\">1.5</td><td align=\"center\">ND</td><td align=\"center\">6.9</td></tr><tr><td align=\"left\">TC104866</td><td align=\"left\">Pectinesterase like protein</td><td align=\"center\">Cell wall modification</td><td align=\"center\">0.5</td><td align=\"center\">1.3</td><td align=\"center\">0.3</td><td align=\"center\">0.5</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Oxidative Stress-ROS Generation</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC95154</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress GO:0006979</td><td align=\"center\">6.3</td><td align=\"center\">3.9</td><td align=\"center\">16.4</td><td align=\"center\">3.0</td></tr><tr><td align=\"left\">TC103581</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">5.2</td><td align=\"center\">2.5</td><td align=\"center\">9.9</td><td align=\"center\">2.6</td></tr><tr><td align=\"left\">TC108789</td><td align=\"left\">Peroxidase 11 precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">4.2</td><td align=\"center\">3.5</td><td align=\"center\">7.6</td><td align=\"center\">2.4</td></tr><tr><td align=\"left\">TC97623</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.6</td><td align=\"center\">3.1</td><td align=\"center\">ND</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC107670</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">3.0</td><td align=\"center\">1.6</td><td align=\"center\">4.3</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC108447</td><td align=\"left\">Peroxidase 2</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.9</td><td align=\"center\">0.4</td><td align=\"center\">2.3</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC95164</td><td align=\"left\">Peroxidase 55 precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.0</td><td align=\"center\">0.9</td><td align=\"center\">3.2</td><td align=\"center\">1.9</td></tr><tr><td align=\"left\">TC111928</td><td align=\"left\">Peroxidase precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.6</td><td align=\"center\">2.9</td><td align=\"center\">2.4</td><td align=\"center\">2.8</td></tr><tr><td align=\"left\">TC103214</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.4</td><td align=\"center\">0.7</td><td align=\"center\">1.4</td><td align=\"center\">2.4</td></tr><tr><td align=\"left\">TC101009</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.6</td><td align=\"center\">0.9</td><td align=\"center\">ND</td><td align=\"center\">2.8</td></tr><tr><td align=\"left\">TC108315</td><td align=\"left\">Cationic peroxidase 2 precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.1</td><td align=\"center\">0.9</td><td align=\"center\">1.9</td><td align=\"center\">2.7</td></tr><tr><td align=\"left\">TC111871</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.4</td><td align=\"center\">1.4</td><td align=\"center\">2.4</td><td align=\"center\">2.3</td></tr><tr><td align=\"left\">TC94676</td><td align=\"left\">Peroxidase precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.2</td><td align=\"center\">1.2</td><td align=\"center\">2.2</td><td align=\"center\">2.5</td></tr><tr><td align=\"left\">TC108988</td><td align=\"left\">Germin-like protein precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.9</td><td align=\"center\">ND</td><td align=\"center\">1.6</td><td align=\"center\">0.5</td></tr><tr><td align=\"left\">TC100563</td><td align=\"left\">Germin-like protein</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.6</td><td align=\"center\">ND</td><td align=\"center\">2.3</td><td align=\"center\">1.1</td></tr><tr><td align=\"left\">TC94265</td><td align=\"left\">Germin-like protein</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.9^ns</td><td align=\"center\">0.6</td><td align=\"center\">2.1</td><td align=\"center\">1.9^ns</td></tr><tr><td align=\"left\">TC107416</td><td align=\"left\">Carbohydrate oxidase</td><td align=\"center\">Electron transport GO:0006118</td><td align=\"center\">1.2</td><td align=\"center\">1.4</td><td align=\"center\">4.3</td><td align=\"center\">1.7</td></tr><tr><td align=\"left\">TC103024</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.4</td><td align=\"center\">0.3</td><td align=\"center\">0.4</td><td align=\"center\">0.1</td></tr><tr><td align=\"left\">TC100904</td><td align=\"left\">Peroxidase precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.2</td><td align=\"center\">0.2</td><td align=\"center\">0.1</td><td align=\"center\">0.2</td></tr><tr><td align=\"left\">TC102226</td><td align=\"left\">Peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.3</td><td align=\"center\">ND</td><td align=\"center\">0.1</td><td align=\"center\">0.2</td></tr><tr><td align=\"left\">TC104806</td><td align=\"left\">Probable peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.4</td><td align=\"center\">0.3</td><td align=\"center\">1.5</td><td align=\"center\">0.4</td></tr><tr><td align=\"left\">TC106851</td><td align=\"left\">Peroxidase 2</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.4</td><td align=\"center\">0.5</td><td align=\"center\">0.6</td><td align=\"center\">0.5</td></tr><tr><td align=\"left\">TC108234</td><td align=\"left\">Peroxidase precursor</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.2</td><td align=\"center\">0.3</td><td align=\"center\">0.2</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC96817</td><td align=\"left\">Germin-like protein</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.5^ns</td><td align=\"center\">1.4</td><td align=\"center\">0.3</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC100175</td><td align=\"left\">Lipoxygenase</td><td align=\"center\">Jasmonic acid biosynthesis GO:0009695</td><td align=\"center\">0.4</td><td align=\"center\">0.4</td><td align=\"center\">ND</td><td align=\"center\">1.1</td></tr><tr><td align=\"left\">TC100188</td><td align=\"left\">Lipoxygenase LoxN2</td><td align=\"center\">Jasmonic acid biosynthesis</td><td align=\"center\">0.7</td><td align=\"center\">0.5</td><td align=\"center\">0.5</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC100155</td><td align=\"left\">Lipoxygenase</td><td align=\"center\">Jasmonic acid biosynthesis</td><td align=\"center\">0.6</td><td align=\"center\">0.3</td><td align=\"center\">0.5</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC100171</td><td align=\"left\">Lipoxygenase</td><td align=\"center\">Jasmonic acid biosynthesis</td><td align=\"center\">0.6</td><td align=\"center\">0.3</td><td align=\"center\">0.5</td><td align=\"center\">0.8</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Oxidative Stress- ROS Scavenging</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC94929</td><td align=\"left\">Quinone-oxidoreductase QR1</td><td align=\"center\">Threonine catabolism GO:0006567</td><td align=\"center\">2.0</td><td align=\"center\">1.2</td><td align=\"center\">1.8</td><td align=\"center\">0.9^ns</td></tr><tr><td align=\"left\">TC110730</td><td align=\"left\">Quinone-oxidoreductase QR1</td><td align=\"center\">Threonine catabolism</td><td align=\"center\">2.2</td><td align=\"center\">1.3</td><td align=\"center\">1.3</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC107874</td><td align=\"left\">NADH-ubiquinone oxidoreductase</td><td align=\"center\">Electron transport</td><td align=\"center\">1.1^ns</td><td align=\"center\">2.3</td><td align=\"center\">0.3</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC95262</td><td align=\"left\">Blue copper protein precursor</td><td align=\"center\">Electron transport</td><td align=\"center\">3.1</td><td align=\"center\">1.6</td><td align=\"center\">1.9</td><td align=\"center\">1.3^ns</td></tr><tr><td align=\"left\">TC103046</td><td align=\"left\">Thioredoxin-like 4</td><td align=\"center\">Electron transport</td><td align=\"center\">2.1</td><td align=\"center\">1.3</td><td align=\"center\">5.3</td><td align=\"center\">1.8</td></tr><tr><td align=\"left\">TC96215</td><td align=\"left\">Thioredoxin H2</td><td align=\"center\">Electron transport</td><td align=\"center\">0.6</td><td align=\"center\">2.4</td><td align=\"center\">0.4</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC104708</td><td align=\"left\">Thioredoxin H2</td><td align=\"center\">Electron transport</td><td align=\"center\">ND</td><td align=\"center\">2.4</td><td align=\"center\">1.3^ns</td><td align=\"center\">3.0</td></tr><tr><td align=\"left\">TC104047</td><td align=\"left\">Thioredoxin 3</td><td align=\"center\">Electron transport</td><td align=\"center\">0.9</td><td align=\"center\">2.3</td><td align=\"center\">0.8</td><td align=\"center\">3.8</td></tr><tr><td align=\"left\">BM813626</td><td align=\"left\">Ascorbate peroxidase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">0.7</td><td align=\"center\">0.9</td><td align=\"center\">1.6</td><td align=\"center\">2.6</td></tr><tr><td align=\"left\">TC101862</td><td align=\"left\">Alternative oxidase 3</td><td align=\"center\">Alternative respiration GO:0010230</td><td align=\"center\">1.3</td><td align=\"center\">0.8</td><td align=\"center\">1.7</td><td align=\"center\">2.0</td></tr><tr><td align=\"left\">TC95582</td><td align=\"left\">Tyrosine aminotransferase</td><td align=\"center\">Vitamin E biosynthesis GO:0010189</td><td align=\"center\">1.5</td><td align=\"center\">2.5</td><td align=\"center\">8.3</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC100815</td><td align=\"left\">4-hydroxyphenylpyruvate dioxygenase</td><td align=\"center\">Vitamin E biosynthesis</td><td align=\"center\">1.2</td><td align=\"center\">1.1</td><td align=\"center\">2.3</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC108214</td><td align=\"left\">Glutathione S-transferase GST 5</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.2</td><td align=\"center\">ND</td><td align=\"center\">1.4</td><td align=\"center\">1.4</td></tr><tr><td align=\"left\">TC100556</td><td align=\"left\">Glutathione-S-transferase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">2.2</td><td align=\"center\">1.1</td><td align=\"center\">2.3</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC105598</td><td align=\"left\">Probable glutathione S-transferase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.3</td><td align=\"center\">1.4</td><td align=\"center\">2.3</td><td align=\"center\">1.0^ns</td></tr><tr><td align=\"left\">TC95231</td><td align=\"left\">Probable glutathione S-transferase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.3</td><td align=\"center\">1.0</td><td align=\"center\">2.1</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC106943</td><td align=\"left\">Glutathione S-transferase GST 8</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.3</td><td align=\"center\">1.0^ns</td><td align=\"center\">2.1</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC94362</td><td align=\"left\">Glutathione S-transferase GST 8</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.2</td><td align=\"center\">1.2</td><td align=\"center\">2.0</td><td align=\"center\">1.0</td></tr><tr><td align=\"left\">TC106973</td><td align=\"left\">Glutathione S-transferase</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.1</td><td align=\"center\">1.3</td><td align=\"center\">3.3</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC95247</td><td align=\"left\">Glutathione S-transferase GST 14</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.0^ns</td><td align=\"center\">0.7</td><td align=\"center\">2.2</td><td align=\"center\">0.2</td></tr><tr><td align=\"left\">TC95380</td><td align=\"left\">Glutathione S-transferase GST 15</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">ND</td><td align=\"center\">1.2</td><td align=\"center\">0.5</td><td align=\"center\">0.8</td></tr><tr><td align=\"left\">TC108817</td><td align=\"left\">Glutathione S-transferase GST 11</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">ND</td><td align=\"center\">1.7</td><td align=\"center\">0.7</td><td align=\"center\">0.4</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Pathogenesis-Related (PR) Proteins</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC93997</td><td align=\"left\">PR-protein PR-4</td><td align=\"center\">Defense response GO:0006952</td><td align=\"center\">2.6</td><td align=\"center\">1.7</td><td align=\"center\">5.0</td><td align=\"center\">2.1</td></tr><tr><td align=\"left\">BQ138448</td><td align=\"left\">PR- protein</td><td align=\"center\">Defense response</td><td align=\"center\">ND</td><td align=\"center\">1.3</td><td align=\"center\">2.3</td><td align=\"center\">3.2</td></tr><tr><td align=\"left\">TC101688</td><td align=\"left\">PR-protein 4A</td><td align=\"center\">Defense response</td><td align=\"center\">0.6</td><td align=\"center\">1.0^ns</td><td align=\"center\">2.7</td><td align=\"center\">1.4</td></tr><tr><td align=\"left\">TC94004</td><td align=\"left\">PR-protein 4A</td><td align=\"center\">Defense response</td><td align=\"center\">0.6</td><td align=\"center\">0.9</td><td align=\"center\">2.7</td><td align=\"center\">1.6</td></tr><tr><td align=\"left\">TC94274</td><td align=\"left\">Thaumatin-like protein PR-5b precursor</td><td align=\"center\">Response to pathogen GO:0042828</td><td align=\"center\">1.3</td><td align=\"center\">1.0</td><td align=\"center\">2.1</td><td align=\"center\">1.8</td></tr><tr><td align=\"left\">TC107543</td><td align=\"left\">Thaumatin-like protein</td><td align=\"center\">Response to pathogen</td><td align=\"center\">1.6</td><td align=\"center\">1.1</td><td align=\"center\">2.7</td><td align=\"center\">1.9</td></tr><tr><td align=\"left\">TC96745</td><td align=\"left\">PR-protein homolog</td><td align=\"center\">Defense response</td><td align=\"center\">1.5</td><td align=\"center\">1.2</td><td align=\"center\">1.6</td><td align=\"center\">2.4</td></tr><tr><td align=\"left\">TC102065</td><td align=\"left\">β-1,3-glucanase (putative)</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">2.4</td><td align=\"center\">0.5</td><td align=\"center\">2.3</td><td align=\"center\">3.0</td></tr><tr><td align=\"left\">TC96253</td><td align=\"left\">β-1,3-glucanase like protein</td><td align=\"center\">Carbohydrate metabolism</td><td align=\"center\">2.3</td><td align=\"center\">1.3</td><td align=\"center\">2.0</td><td align=\"center\">0.9</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Isoflavonoid Biosynthesis</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC94931</td><td align=\"left\">Cytochrome P450</td><td align=\"center\">Electron transport</td><td align=\"center\">2.5</td><td align=\"center\">1.4</td><td align=\"center\">2.2</td><td align=\"center\">1.6^ns</td></tr><tr><td align=\"left\">TC101508</td><td align=\"left\">Isoflavone 2'-hydroxylase</td><td align=\"center\">Electron transport</td><td align=\"center\">1.6</td><td align=\"center\">1.0^ns</td><td align=\"center\">2.6</td><td align=\"center\">1.5</td></tr><tr><td align=\"left\">TC95424</td><td align=\"left\">Isoflavone 3'-hydroxylase</td><td align=\"center\">Electron transport</td><td align=\"center\">1.8</td><td align=\"center\">0.9</td><td align=\"center\">3.8</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC96039</td><td align=\"left\">Isoflavone reductase related protein</td><td align=\"center\">Response to oxidative stress</td><td align=\"center\">1.8</td><td align=\"center\">0.9</td><td align=\"center\">3.1</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">TC106939</td><td align=\"left\">Isoflavone synthase putative</td><td align=\"center\">Electron transport</td><td align=\"center\">1.3</td><td align=\"center\">ND</td><td align=\"center\">2.2</td><td align=\"center\">1.0^ns</td></tr><tr><td align=\"left\">TC97999</td><td align=\"left\">Cytochrome P450 monooxygenase</td><td align=\"center\">Electron transport</td><td align=\"center\">1.2</td><td align=\"center\">0.9</td><td align=\"center\">2.1</td><td align=\"center\">1.4</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Stress Response</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC108137</td><td align=\"left\">ABA-responsive protein-like</td><td align=\"center\">Response to desiccation GO:0009269</td><td align=\"center\">1.7</td><td align=\"center\">1.4</td><td align=\"center\">2.7</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC108387</td><td align=\"left\">Abscisic acid-responsive protein</td><td align=\"center\">Response to desiccation</td><td align=\"center\">1.8</td><td align=\"center\">1.2</td><td align=\"center\">2.5</td><td align=\"center\">2.0</td></tr><tr><td align=\"left\">TC106508</td><td align=\"left\">Abscisic stress ripening protein homolog</td><td align=\"center\">Response to desiccation</td><td align=\"center\">1.3</td><td align=\"center\">1.3</td><td align=\"center\">2.6</td><td align=\"center\">2.7</td></tr><tr><td align=\"left\">BG454018</td><td align=\"left\">Late embryogenesis abundant protein</td><td align=\"center\">Response to desiccation</td><td align=\"center\">5.5</td><td align=\"center\">0.8^ns</td><td align=\"center\">12.9</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">TC94387</td><td align=\"left\">Late embryogenesis abundant protein 2</td><td align=\"center\">Response to desiccation</td><td align=\"center\">1.5</td><td align=\"center\">1.1</td><td align=\"center\">4.2</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC94389</td><td align=\"left\">Late embryogenesis abundant protein 2</td><td align=\"center\">Response to desiccation</td><td align=\"center\">1.8</td><td align=\"center\">1.2</td><td align=\"center\">5.1</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC94508</td><td align=\"left\">Seed maturation protein LEA 4</td><td align=\"center\">Response to desiccation</td><td align=\"center\">1.9</td><td align=\"center\">1.0</td><td align=\"center\">4.6</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC101519</td><td align=\"left\">Patatin-like protein 1</td><td align=\"center\">Lipid metabolism GO:0006629</td><td align=\"center\">3.6</td><td align=\"center\">0.7</td><td align=\"center\">6.6</td><td align=\"center\">0.5</td></tr><tr><td align=\"left\">TC101298</td><td align=\"left\">Glucosyl transferase</td><td align=\"center\">Metabolism GO:0008152</td><td align=\"center\">0.5</td><td align=\"center\">0.6</td><td align=\"center\">2.0</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC94863</td><td align=\"left\">Glucosyltransferase putative</td><td align=\"center\">Metabolism</td><td align=\"center\">1.6</td><td align=\"center\">0.8</td><td align=\"center\">2.3</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC100689</td><td align=\"left\">Glucosyltransferase-6</td><td align=\"center\">Metabolism</td><td align=\"center\">1.6</td><td align=\"center\">1.5</td><td align=\"center\">2.0</td><td align=\"center\">1.5</td></tr><tr><td align=\"left\">TC110504</td><td align=\"left\">Glucosyltransferase-7</td><td align=\"center\">Metabolism</td><td align=\"center\">1.4</td><td align=\"center\">1.4</td><td align=\"center\">6.3</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC103147</td><td align=\"left\">Tumor-related protein</td><td align=\"center\">Unknown</td><td align=\"center\">0.5</td><td align=\"center\">0.7</td><td align=\"center\">2.3</td><td align=\"center\">4.2</td></tr><tr><td align=\"left\">TC107043</td><td align=\"left\">ER6 protein (universal stress protein)</td><td align=\"center\">Response to stress GO:0006950</td><td align=\"center\">0.3</td><td align=\"center\">1.2</td><td align=\"center\">0.7</td><td align=\"center\">2.8</td></tr><tr><td align=\"left\">TC110393</td><td align=\"left\">Heavy metal domain containing protein</td><td align=\"center\">Metal ion transport GO:0030001</td><td align=\"center\">0.6</td><td align=\"center\">0.9</td><td align=\"center\">0.9^ns</td><td align=\"center\">4.0</td></tr><tr><td align=\"left\">TC103767</td><td align=\"left\">Universal stress protein</td><td align=\"center\">Response to stress</td><td align=\"center\">1.1^ns</td><td align=\"center\">0.8</td><td align=\"center\">1.4</td><td align=\"center\">3.1</td></tr><tr><td align=\"left\">TC95896</td><td align=\"left\">Dehydration responsive element binding</td><td align=\"center\">Regulation of transcription GO:0006355</td><td align=\"center\">1.6</td><td align=\"center\">ND</td><td align=\"center\">3.5</td><td align=\"center\">0.7</td></tr><tr><td align=\"left\">TC110815</td><td align=\"left\">AP2 domain transcription factor</td><td align=\"center\">Regulation of transcription</td><td align=\"center\">1.1</td><td align=\"center\">1.2</td><td align=\"center\">2.4</td><td align=\"center\">0.9^ns</td></tr><tr><td align=\"left\">TC111267</td><td align=\"left\">Probable WRKY transcription factor 23</td><td align=\"center\">Regulation of transcription</td><td align=\"center\">1.5</td><td align=\"center\">1.3</td><td align=\"center\">2.4</td><td align=\"center\">1.4</td></tr><tr><td align=\"left\">TC102282</td><td align=\"left\">Probable WRKY transcription factor 28</td><td align=\"center\">Regulation of transcription</td><td align=\"center\">1.6</td><td align=\"center\">1.4</td><td align=\"center\">2.0</td><td align=\"center\">1.3^ns</td></tr><tr><td align=\"left\">TC101761</td><td align=\"left\">Putative WRKY4 transcription factor</td><td align=\"center\">Regulation of transcription</td><td align=\"center\">1.3</td><td align=\"center\">1.0^ns</td><td align=\"center\">3.2</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">TC97324</td><td align=\"left\">WRKY-type DNA binding protein</td><td align=\"center\">Regulation of transcription</td><td align=\"center\">1.8</td><td align=\"center\">1.3</td><td align=\"center\">3.5</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC103586</td><td align=\"left\">ZPT2</td><td align=\"center\">Regulation of transcription GO:0045449</td><td align=\"center\">2.9</td><td align=\"center\">ND</td><td align=\"center\">3.5</td><td align=\"center\">ND</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Cell Death</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC103771</td><td align=\"left\">Ethylene up-regulated gene ER66</td><td align=\"center\">Ethylene signaling pathway GO:0009873</td><td align=\"center\">2.6</td><td align=\"center\">1.2</td><td align=\"center\">3.8</td><td align=\"center\">2.3</td></tr><tr><td align=\"left\">TC105302</td><td align=\"left\">Subtilisin-like proteinase</td><td align=\"center\">Proteolysis and peptidolysis GO:0006508</td><td align=\"center\">2.4</td><td align=\"center\">1.3</td><td align=\"center\">1.9</td><td align=\"center\">1.4</td></tr><tr><td align=\"left\">TC95356</td><td align=\"left\">probable serine proteinase</td><td align=\"center\">Proteolysis and peptidolysis</td><td align=\"center\">2.3</td><td align=\"center\">1.1^ns</td><td align=\"center\">1.8</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC103618</td><td align=\"left\">Subtilisin-like protease</td><td align=\"center\">Proteolysis and peptidolysis</td><td align=\"center\">2.3</td><td align=\"center\">1.2</td><td align=\"center\">1.8</td><td align=\"center\">1.2</td></tr><tr><td align=\"left\">TC103261</td><td align=\"left\">Papain-like cysteine proteinase</td><td align=\"center\">Proteolysis and peptidolysis</td><td align=\"center\">2.8</td><td align=\"center\">0.9</td><td align=\"center\">4.7</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC101194</td><td align=\"left\">T1N15.5</td><td align=\"center\">Apoptosis GO:0006915</td><td align=\"center\">2.0</td><td align=\"center\">1.1</td><td align=\"center\">1.5</td><td align=\"center\">0.9</td></tr><tr><td align=\"left\">TC112103</td><td align=\"left\">Subtilisin-type protease</td><td align=\"center\">Proteolysis and peptidolysis</td><td align=\"center\">1.8</td><td align=\"center\">0.9</td><td align=\"center\">1.1^ns</td><td align=\"center\">2.3</td></tr><tr><td align=\"left\">TC107719</td><td align=\"left\">Putative cell death associated protein</td><td align=\"center\">Unknown</td><td align=\"center\">0.9</td><td align=\"center\">1.1</td><td align=\"center\">0.8</td><td align=\"center\">2.2</td></tr><tr><td align=\"left\">TC107153</td><td align=\"left\">Cystatin</td><td align=\"center\">Cysteine protease inhibitor GO:0004869</td><td align=\"center\">1.8</td><td align=\"center\">1.2</td><td align=\"center\">2.4</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC94966</td><td align=\"left\">Cystatin</td><td align=\"center\">Cysteine protease inhibitor</td><td align=\"center\">0.4</td><td align=\"center\">0.9^ns</td><td align=\"center\">0.4</td><td align=\"center\">1.6</td></tr><tr><td align=\"left\">BI310700</td><td align=\"left\">Cystatin</td><td align=\"center\">Cysteine protease inhibitor</td><td align=\"center\">0.4</td><td align=\"center\">1.0</td><td align=\"center\">0.4</td><td align=\"center\">1.7</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Senescence</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC101276</td><td align=\"left\">Rhodanese-like family protein</td><td align=\"center\">Aging GO:0007568</td><td align=\"center\">2.3</td><td align=\"center\">1.4</td><td align=\"center\">2.0</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC101956</td><td align=\"left\">Senescence-associated protein sen1</td><td align=\"center\">Aging</td><td align=\"center\">2.1</td><td align=\"center\">0.8</td><td align=\"center\">5.2</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC107982</td><td align=\"left\">Probable senescence-related protein</td><td align=\"center\">Aging</td><td align=\"center\">1.2</td><td align=\"center\">ND</td><td align=\"center\">3.4</td><td align=\"center\">1.5</td></tr><tr><td align=\"left\">TC107460</td><td align=\"left\">Ntdin</td><td align=\"center\">Aging</td><td align=\"center\">1.4</td><td align=\"center\">1.1</td><td align=\"center\">2.1</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC94722</td><td align=\"left\">Putative senescence-associated protein</td><td align=\"center\">Aging</td><td align=\"center\">0.1</td><td align=\"center\">1.8</td><td align=\"center\">0.3</td><td align=\"center\">5.6</td></tr><tr><td align=\"left\">TC107766</td><td align=\"left\">SRG1 protein</td><td align=\"center\">Aging</td><td align=\"center\">0.8</td><td align=\"center\">0.4</td><td align=\"center\">0.8</td><td align=\"center\">0.8</td></tr><tr><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td align=\"left\"><bold>Unknown/Miscellaneous</bold></td><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">TC105342</td><td align=\"left\">MATE</td><td align=\"center\">Unknown</td><td align=\"center\">39.8</td><td align=\"center\">33.9</td><td align=\"center\">51.3</td><td align=\"center\">23.7</td></tr><tr><td align=\"left\">TC102211</td><td align=\"left\">GAST-1 protein precursor</td><td align=\"center\">Response to gibberellic acid stimulus</td><td align=\"center\">2.2</td><td align=\"center\">2.1</td><td align=\"center\">1.9</td><td align=\"center\">1.3</td></tr><tr><td align=\"left\">TC111698</td><td align=\"left\">COBRA-like gene</td><td align=\"center\">Unknown</td><td align=\"center\">16.3</td><td align=\"center\">1.7</td><td align=\"center\">18.8</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC95697</td><td align=\"left\">F-box protein</td><td align=\"center\">Unknown</td><td align=\"center\">5.0</td><td align=\"center\">1.1^ns</td><td align=\"center\">1.4</td><td align=\"center\">ND</td></tr><tr><td align=\"left\">TC108263</td><td align=\"left\">E3 ubiquitin ligase SCF complex</td><td align=\"center\">Protein catabolism GO:0006511</td><td align=\"center\">2.2</td><td align=\"center\">1.4</td><td align=\"center\">1.7</td><td align=\"center\">1.5</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Real-time PCR validation of microarray results.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td/><td/><td/><td align=\"center\" colspan=\"2\">qPCR fold change</td><td align=\"center\" colspan=\"2\">Ratio (T32/S70)</td></tr><tr><td/><td/><td/><td/><td/><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">TIGR TC</td><td align=\"left\">Annotation</td><td align=\"center\">Time (h)</td><td align=\"center\"><italic>M. truncatula </italic>line</td><td align=\"center\">Microarray fold change</td><td align=\"center\">Mean</td><td align=\"center\">SE</td><td align=\"center\">Array</td><td align=\"center\">qPCR</td></tr></thead><tbody><tr><td align=\"left\">TC105342</td><td align=\"left\">MATE</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">39.8</td><td align=\"center\">44.0</td><td align=\"center\">7.8</td><td align=\"center\">0.8</td><td align=\"center\">0.7</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">51.3</td><td align=\"center\">67.4</td><td align=\"center\">6.4</td><td/><td/></tr><tr><td align=\"left\">TC95697</td><td align=\"left\">F-box protein</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">5.0</td><td align=\"center\">13.7</td><td align=\"center\">4.0</td><td align=\"center\">3.6</td><td align=\"center\">4.4</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">1.4</td><td align=\"center\">3.1</td><td align=\"center\">0.2</td><td/><td/></tr><tr><td align=\"left\">TC103586</td><td align=\"left\">ZPT-2</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">2.9</td><td align=\"center\">2.4</td><td align=\"center\">0.2</td><td align=\"center\">0.8</td><td align=\"center\">0.4</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">3.5</td><td align=\"center\">6.1</td><td align=\"center\">0.9</td><td/><td/></tr><tr><td align=\"left\">TC111698</td><td align=\"left\">COBRA-like gene</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">16.3</td><td align=\"center\">24.7</td><td align=\"center\">0.6</td><td align=\"center\">0.9</td><td align=\"center\">0.5</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">18.8</td><td align=\"center\">53.7</td><td align=\"center\">16.4</td><td/><td/></tr><tr><td align=\"left\">TC93997</td><td align=\"left\">PR-protein PR-4</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">2.6</td><td align=\"center\">2.5</td><td align=\"center\">0.3</td><td align=\"center\">0.5</td><td align=\"center\">0.5</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">5.0</td><td align=\"center\">5.0</td><td align=\"center\">1.1</td><td/><td/></tr><tr><td align=\"left\">TC100486</td><td align=\"left\">Xyloglucan endotransglycosylase</td><td align=\"center\">12</td><td align=\"center\">T32</td><td align=\"center\">2.3</td><td align=\"center\">2.2</td><td align=\"center\">0.1</td><td align=\"center\">1.8</td><td align=\"center\">1.6</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">1.3</td><td align=\"center\">1.4</td><td align=\"center\">0.3</td><td/><td/></tr><tr><td align=\"left\">TC96658</td><td align=\"left\">Xyloglucan endotransglycosylase</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">2.9</td><td align=\"center\">3.7</td><td align=\"center\">1.0</td><td align=\"center\">0.3</td><td align=\"center\">0.1</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">10.7</td><td align=\"center\">38.3</td><td align=\"center\">5.6</td><td/><td/></tr><tr><td align=\"left\">TC102211</td><td align=\"left\">GAST-1</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">2.1</td><td align=\"center\">7.2</td><td align=\"center\">0.4</td><td align=\"center\">1.6</td><td align=\"center\">0.3</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">1.3</td><td align=\"center\">25.8</td><td align=\"center\">5.7</td><td/><td/></tr><tr><td align=\"left\">TC111920</td><td align=\"left\">Polygalacturonase PG1 putative</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">2.8</td><td align=\"center\">2.5</td><td align=\"center\">0.2</td><td align=\"center\">0.8</td><td align=\"center\">0.6</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">3.7</td><td align=\"center\">4.0</td><td align=\"center\">0.5</td><td/><td/></tr><tr><td align=\"left\">TC103771</td><td align=\"left\">Ethylene up- regulated gene ER66</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">1.2</td><td align=\"center\">1.3</td><td align=\"center\">0.2</td><td align=\"center\">0.5</td><td align=\"center\">0.3</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">2.3</td><td align=\"center\">4.6</td><td align=\"center\">0.8</td><td/><td/></tr><tr><td align=\"left\">TC95154</td><td align=\"left\">Peroxidase</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">3.9</td><td align=\"center\">1.2</td><td align=\"center\">0.1</td><td align=\"center\">1.3</td><td align=\"center\">0.4</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">3.0</td><td align=\"center\">2.9</td><td align=\"center\">0.1</td><td/><td/></tr><tr><td align=\"left\">TC100155</td><td align=\"left\">Lipoxygenase</td><td align=\"center\">48</td><td align=\"center\">T32</td><td align=\"center\">0.5</td><td align=\"center\">0.4</td><td align=\"center\">0.0</td><td align=\"center\">0.7</td><td align=\"center\">0.6</td></tr><tr><td/><td/><td/><td align=\"center\">S70</td><td align=\"center\">0.7</td><td align=\"center\">0.6</td><td align=\"center\">0.1</td><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Primer sequences used for quantitative RT-PCR.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">TIGR TC</td><td align=\"left\">Forward Primer</td><td align=\"left\">Reverse Primer</td></tr></thead><tbody><tr><td align=\"left\">TC105342</td><td align=\"left\">5'-CATCCCTCTCTTGCACCATCA-3'</td><td align=\"left\">5'-TTTCCACTTCTTGTTGGGTTCA-3'</td></tr><tr><td align=\"left\">TC102211</td><td align=\"left\">5'-TCCAGCTCCACAACCTAGCA-3'</td><td align=\"left\">5'-TGCATCGTGGTCCACATTCT-3'</td></tr><tr><td align=\"left\">TC95697</td><td align=\"left\">5'-GGTGTCGAAGGTGGCCATAG-3'</td><td align=\"left\">5'-TCAGCACGACCGTAAAATCTTG-3'</td></tr><tr><td align=\"left\">TC100486</td><td align=\"left\">5'-CATCTGGAAGCCACAACACATTA-3'</td><td align=\"left\">5'-GTTGGTTCTTTGGGAATGGAATAC-3'</td></tr><tr><td align=\"left\">TC11192</td><td align=\"left\">5'-AGTGCAACTGTTGCTTGCACAA-3'</td><td align=\"left\">5'-CCATAAGCATTCCAACAAAAAGG-3'</td></tr><tr><td align=\"left\">TC96658</td><td align=\"left\">5'-GCTGAGGTGGGTGCAGAAGA-3'</td><td align=\"left\">5'-GAGACTAAGAGTGAGTGCATTCAACTG-3'</td></tr><tr><td align=\"left\">TC93997</td><td align=\"left\">5'-GTGGTCAAGCTTCTTGTGGAAAG-3'</td><td align=\"left\">5'-CAACCCTCCATTGCTGCATT-3'</td></tr><tr><td align=\"left\">TC103771</td><td align=\"left\">5'-TGGCAGGGAGAGGACAGTTG-3'</td><td align=\"left\">5'-CGGCTGGTGTTCTACCAGAAG-3'</td></tr><tr><td align=\"left\">TC95154</td><td align=\"left\">5'-GTAGCTCTGTCAGGAGGGCATAC-3'</td><td align=\"left\">5'-AACGAAGGGTCCACGTCATG-3'</td></tr><tr><td align=\"left\">TC100155</td><td align=\"left\">5'-TTGAGATTTCTTCTGCAGTTTACAAGA-3'</td><td align=\"left\">5'-GGAAGAGGGATCCTCAACAGCCTA-3'</td></tr><tr><td align=\"left\">TC101956</td><td align=\"left\">5'-ACCTCATAGTGGGTTGCCAAA-3'</td><td align=\"left\">5'-ATAACCTCCTCCCATGTTGTACACA-3'</td></tr><tr><td align=\"left\">TC103586</td><td align=\"left\">5'-TGAATGCAAAACGTGCAACA-3'</td><td align=\"left\">5'-TGAGTTCTTCACCTTCAGCTAGTTTC-3'</td></tr><tr><td align=\"left\">18s rDNA</td><td align=\"left\">5'-CCTCAAACTTCCGTGGCCTAA-3'</td><td align=\"left\">5'-TAACGAACGAGACCTCAGCCTG-3'</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>RRG, Ratio of root growth in 2.5 μM Al solution to root growth in 0 μM Al solution; SE, standard error of the mean; <italic>P-</italic>value, significance comparing mean relative root growth for each line with that of A17. Student's t-test (assuming equal variance) using a two-tailed distribution was employed for the statistical test.</p></table-wrap-foot>", "<table-wrap-foot><p>TIGR TC, The Institute for Genomic Research Tentative Consensus sequence ID version 8.0; Tentative Annotation, based on TIGR/NCBI tBLASTx tool; GO = Gene Ontology; Fold Change = ratio of transcript abundance in Al treatment/transcript abundance in control (-Al) treatment; ns = not significant; ND = not detected.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2229-8-89-1\"/>", "<graphic xlink:href=\"1471-2229-8-89-2\"/>", "<graphic xlink:href=\"1471-2229-8-89-3\"/>", "<graphic xlink:href=\"1471-2229-8-89-4\"/>", "<graphic xlink:href=\"1471-2229-8-89-5\"/>", "<graphic xlink:href=\"1471-2229-8-89-6\"/>", "<graphic xlink:href=\"1471-2229-8-89-7\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Filamentous fungi influence modern society primarily as hazardous pathogens and providers of drug leads and enzymes for the biotechnological companies. The wide interest in filamentous fungi has led to the sequencing and annotation of more than 30 fungal genomes, with another 130 on the way <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/Genomes/\"/>. This resource constitutes a huge potential for future advances in the basic understanding and industrial exploitation of fungal biology.</p>", "<p>A key limiting factor in future work will be the speed by which site-directed genome modifications, such as gene deletion, promoter replacement, fusion of coding sequences with reporter genes (eg. GFP) or the introduction of epitope tags can be performed and verified. Site directed modifications in filamentous fungi can be carried out by homologous recombination and is typically achieved by introducing a DNA fragment containing two homologous recombination sequences (HRS) flanking a selection marker. The HRS's are identical to the sequences surrounding the target locus in the genome and are typically amplified by PCR. Homologous recombination between the vector DNA and the genome results in a replacement of the target DNA with the selection marker. The length of HRS required to obtain a satisfactory frequency of homologous recombination varies between fungal species. Contrary to <italic>Saccharomyces cerevisiae</italic>, where 30 bp is sufficient, many filamentous fungi require longer HRS [##REF##16801547##1##], eg <italic>Fusarium graminearum </italic>needs 400 bp [##REF##15780665##2##] 1500 bp is reported for <italic>Aspergillus niger </italic>[##REF##17275117##3##] and around 1000 bp for <italic>Neurospora crassa </italic>[##REF##17320431##4##]. The necessity of including sequences in the range of 1 kb [##REF##12589439##5##] makes restriction enzyme and ligation dependent cloning inefficient. Several laboratories have solved this problem by dividing the replacement constructs into two, a technique known as bipartite gene-targeting or split-marker recombination [##REF##8948099##6##, ####UREF##0##7##, ##REF##16289954##8####16289954##8##]. In this technique, the two HRS's are fused with two thirds of either the 3' or 5'end of the selection marker gene, by fusion-PCR [##REF##3045756##9##]. Targeted gene replacement in the fungus is then achieved by a triple homologous recombination between the two PCR fragments and the genomic target, resulting in the formation of a functional selection marker gene and replacement of the targeted locus. The advantage of this technique is that vector construction can be omitted and the PCR products used directly. The technique also increases the efficiency of homologous integration compared to traditional techniques [##UREF##0##7##]. However, integration of unspecific products generated during the required fusion PCR reactions may give secondary mutations that are difficult to identify. The technique is typically used in combination with protoplast based transformation, which can be difficult or even impossible in some fungal species. Another example of a vector construction system is the one developed for high-throughput knockout of genes in <italic>Neurospora crassa</italic>. Recombinational cloning of the two required HRS with a selection marker gene and a vector backbone is carried out in yeast, followed by PCR amplification of the two HRS and selection marker gene [##REF##16801547##1##]. The amplified DNA is then transformed into <italic>N. crassa </italic>by electroporation, a technique for which no protocols are available for the majority of fungal species.</p>", "<p>The <italic>Agrobacterium tumefaciens </italic>mediated transformation (ATMT) technology [##REF##9743116##10##] has the advantage of being independent of protoplast formation and can be used directly on a wide variety of fungal species and tissue types [##REF##11010906##11##]. ATMT has been widely used for random insertional mutagenesis in eg. <italic>Magnaporthe oryzae </italic>[##REF##17353894##12##], <italic>Leptosphaeria maculans </italic>[##REF##16979359##13##] and <italic>Fusarium oxysporum </italic>[##UREF##1##14##]. The transformation frequency reported for <italic>F. oxysporum </italic>is between 300–500 transformants per 10⁶spores. We have shown that ATMT is an excellent method for site-directed genome modifications in <italic>F. graminearum</italic>, with 200 transformants per 10⁶spores, with 60% targeted integrations, using 2 kb HRS's [##REF##16879655##15##]. As ATMT requires both HRS to be present in the same vector, two successive <italic>Escherichia coli </italic>based cloning steps, using four unique cutting enzymes to ensure directionality, are needed. The dependency of unique cutting restriction enzymes complicates the design process and limits the placement of the HRS's [##REF##12589439##5##,##REF##16879655##15##]. A single step vector construction strategy, independent of restriction enzyme sites, would give complete freedom in choice of replacement sites in the genome (Figure ##FIG##0##1##). This requires an efficient and reliable method for directional four fragment cloning, allowing fusion of the two HRS's on each side of the selection marker gene and to the vector backbone. In recent years new techniques have been developed for highly efficient directional cloning of PCR products into unique restriction sites of vectors, independent of the short overhangs (0–4 bp) generated by standard endonucleases. Examples are the Xi-cloning, In-Fusion cloning, Ligase independent cloning (LIC-PCR), Recombinational cloning and USER Friendly cloning techniques [##UREF##2##16##, ####UREF##3##17##, ##REF##2235490##18##, ##REF##15489321##19##, ##UREF##4##20####4##20##].</p>", "<p>The USER (uracil-specific excision reagent) Friendly cloning technique (New England Biolabs) allows directional cloning of PCR products, independently of restriction enzyme cleavage of the PCR amplicon and DNA ligase for fusion of the amplicon with the vector ends. Instead, vector-specific overhangs (in this paper 9 bp) containing a single 2-deoxyuridine nucleoside, are included in the 5' end of each primer designed to amplify the desired genomic target (Figure ##FIG##1##2A##). The resulting PCR amplicon (double stranded) is subsequently treated with the USER enzyme mix (Uracil DNA glycosylase and DNA glycosylase-lyase Endo VIII) to create unique 3' single-stranded extensions (Figure ##FIG##1##2B##). Compatible overhangs (9 bp) in the vector are generated by the combined digestion with a standard restriction enzyme (<italic>PacI</italic>) and a nicking enzyme (<italic>Nt.BbvCI</italic>), where the spacing of the respective recognition sites determines the length of the 3' single stranded overhangs (Figure ##FIG##1##2C##). Annealing of the digested vector and the USER-treated PCR amplicons enables the formation of a stable recombinant molecule that can be used directly in chemical transformation of <italic>E. coli </italic>without prior ligation (Figure ##FIG##1##2D##). The DNA pieces are covalently linked by the formation of phosphodiester bonds <italic>in vivo</italic>, most likely catalyzed by the endogenous <italic>E. coli </italic>DNA repair system (Figure ##FIG##1##2E##).</p>", "<p>In the present study, we designed four new vectors, adapted to the USER Friendly cloning technology. Here we show that the technology can be used to generate a large number of targeted gene replacement and overexpression vectors for high throughput functional analysis of fungal genes.</p>" ]

[ "<title>Methods</title>", "<title>Reagents and enzymes</title>", "<p>Restriction enzymes, T4 DNA polymerase, T4 DNA ligase and Calf Intestinal Phosphatase (CIP) and the USER enzyme mix were purchased from New England Biolabs (Ipswich, MA, USA).</p>", "<p>Production of amplicons for the USER Friendly cloning reactions were performed with PfuTurbo^®C_xHotstart DNA polymerase (Stratagene, Cedar Creek, TX, US). The <italic>gpdA </italic>promoter from <italic>Aspergillus nidulans </italic>was amplified with Phusion DNA polymerase (Finnzymes, Espoo, Finland). Screening of <italic>E. coli </italic>transformants was performed with Sigma Taq DNA polymerase (Sigma Aldrich). All PCR reactions were performed using an Eppendorf MasterCycler EP, using the temperature gradient mode for optimization. Sequencing was performed at GATC Biotech (Constance, Germany). Oligos for construction of the USER cloning sites (UCS) were purchased as HPLC purified oligos from Invitrogen (Carlsbad, CA, US). Primers for replacement and overexpression of <italic>Fusarium graminearum </italic>genes were designed based on the <italic>F. graminearum </italic>genome sequence from the Broad Institute <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.broad.mit.edu/annotation\"/> and annotations at the <italic>F. graminearum </italic>Genome DataBase (FGDB) [##REF##16381910##21##] using Vector NTI 10 (Invitrogen). Primers were purchased from Eurofins MWG|operon (Ebersberg, Germany).</p>", "<p>If not specified otherwise all enzymes and kits were used as recommended by the manufacturer.</p>", "<title>Preparation of DNA</title>", "<p>For production of genomic DNA from <italic>F. graminearum</italic>, the PH-1 wild type strain was grown in liquid YPG medium [##REF##12135578##22##] for three days at 25°C in darkness with stir at 150 rpm. The gDNA was purified following the procedure described by Malz [##REF##15809006##23##]. Plasmid DNA was purified using the Miniprep and Maxiprep kits from QIAgen (Chatsworth, CA, USA). Digested plasmids and PCR products were purified using the GFX purification kit from GE Healthcare. DNA concentrations were measured using a NanoDrop ND-1000 spectrophotometer (Wilmington, DE, US).</p>", "<title>Construction of pAg1-H3E for in locus overexpression</title>", "<p>To allow overexpression of genes, we constructed a variant of the pAg1-H3 vector [##REF##12589439##5##], in which the <italic>gpdA </italic>promoter from <italic>Aspergillus nidulans </italic>was inserted pointing towards the left border (LB) sequence (Figure ##FIG##2##3##). The <italic>A. nidulans gpdA </italic>promoter was amplified from pPgpd-DsRed [##REF##12799012##24##] using the primers PgpdA-A1/-A2 [see Additional file ##SUPPL##0##1##] and mixed with <italic>SmaI </italic>digested pAg1-H3 (Figure ##FIG##3##4##). The primers contain 30 bp 5' overhangs that are identical to the blunt <italic>SmaI </italic>generated vector ends of pAg-H3. Directional cloning was carried out according to the Xi-cloning procedure described in [##UREF##2##16##], with 50 ng <italic>SmaI </italic>digested vector and 150 ng insert, both dephosphorylated and GFX purified. Correct transformants were identified by kanamycin resistance and colony PCR. The orientation of the insert was verified by sequencing with the RF-1 primer.</p>", "<title>Construction of the USER vectors, pRF-HU2 and pRF-HU2E, for targeted replacement</title>", "<p>To construct vectors with two unique UCS's flanking the selection marker genes, oligos [see Additional file ##SUPPL##0##1##] U2(LB)up/down, U2(RB)up/down and U2(LB)Eup/Edown were mixed to a final concentration of 10 mM each, heated to 90°C for 5 minutes and then cooled to room temperature for annealing of complementary sequences. The ends of the oligos include overhangs that allow directional cloning into the <italic>ApaI</italic>/<italic>SacI </italic>(Left Border) and <italic>SpeI</italic>/<italic>HindIII </italic>(Right Border) sites of the pAg1-H3 vector and into the <italic>KpnI</italic>/<italic>XmaI </italic>(LB) and <italic>SpeI</italic>/<italic>HindIII </italic>(RB) sites of the pAg1-H3E vector.</p>", "<p><italic>ApaI </italic>and <italic>SacI </italic>digested pAg1-H3 vector was GFX-purified and mixed in a 1:5 molar ratio with the double stranded U2(LB)up/down insert and ligated by using T4 DNA ligase. The subsequent transformation of <italic>E. coli </italic>resulted in pAg1-HU(LB). <italic>SpeI </italic>and <italic>HindIII </italic>digested pAg1-HU(LB) was mixed with the double stranded U2(RB)up/down insert and treated as described above. The resulting vector pRF-HU2 (Figure ##FIG##4##5## and ##FIG##5##6##) was sequenced using RF-1 and RF-2 primers.</p>", "<p>Similarly, U2(LB)Eup/Edown was ligated into <italic>KpnI </italic>and <italic>XmaI </italic>digested pAg1-H3E, resulting in pAg1-HUE(LB). The resulting vector was then digested with <italic>SpeI </italic>and <italic>HindIII</italic>, mixed with U2(RB)up/down and ligated, resulting in pRF-HU2E (Figure ##FIG##4##5## and ##FIG##5##6##) [see Additional file ##SUPPL##1##2##].</p>", "<title>Construction of pRF-HU and pRF-HUE for random integration</title>", "<p>For cloning of single PCR amplicons, vectors with only a single UCS were generated. The intermediate vectors (pAg1-HU(LB) and pAg1-HUE(LB)) from the construction of pRF-HU2 and pRF-HU2E, both contain two <italic>PacI </italic>sites, one in the introduced UCS at the LB and one in the RB Multiple Cloning Site (MCS). To allow USER Friendly cloning of single PCR amplicons it was necessary to remove the <italic>PacI </italic>site in the RB MCS. Vectors were digested with <italic>SmaI </italic>and <italic>HindIII </italic>and the resulting ends were polished, using T4 DNA polymerase, and self ligated using T4 DNA ligase. The resulting vectors, pRF-HU and pRF-HUE contain a single USER cloning site at their LB (Figure ##FIG##4##5## and ##FIG##5##6##) [see Additional file ##SUPPL##1##2##].</p>", "<title>The USER Friendly cloning reaction and testing of the system</title>", "<p>The constructed USER vectors were digested with <italic>PacI </italic>/<italic>Nt.BbvC IB</italic>, GFX purified and diluted to a concentration ranging from 40–50 ng/μl (Figure ##FIG##5##6##). The cloning efficiency of the vector system was tested by constructing replacement and <italic>in locus </italic>overexpression vectors for 12 different genes (<italic>PKS1</italic>, <italic>PKS2</italic>, <italic>PKS3 </italic>(<italic>PGL1</italic>), <italic>PKS5</italic>, <italic>PKS6</italic>, <italic>PKS7</italic>, <italic>PKS8</italic>, <italic>PKS9</italic>, <italic>PKS10</italic>, <italic>PKS11, PKS14 </italic>and <italic>PKS15</italic>) and replacement vectors for an additional five genes (<italic>pglJ</italic>, <italic>pglM</italic>, <italic>pglX</italic>, <italic>pglL </italic>and <italic>pglV</italic>) from <italic>Fusarium graminearum</italic>. The test inserts were amplified using three different primer pairs for each of the genes, <italic>geneX</italic>-O1/O2, -O3/O4 and -A3/A4 primer pairs (Figure ##FIG##6##7## and [see Additional file ##SUPPL##0##1##]) with <italic>F. graminearum </italic>PH-1 gDNA as template.</p>", "<p>The designed gene specific primers included 9 bp long 2-Deoxyuridine containing overhangs, O1 = 5'-GGTCTTAA<bold>U</bold>, O2 = 5'-GGCATTAA<bold>U</bold>, O3 = 5'-GGACTTAA<bold>U</bold>, O4 = 5'-GGGTTTAA<bold>U</bold>, A3 = 5'-GGACTTAA<bold>U</bold>, A4 = 5'-GGGTTTAA<bold>U</bold>, which ensured directionality in the cloning reactions (Figure ##FIG##6##7##). The USER Friendly cloning technique does not require purification of the amplicons prior to cloning and the PCR reactions were therefore used directly, with a DNA concentration ranging from 6 – 15 ng/μl.</p>", "<p>For cloning of two PCR amplicons the following components were mixed in a 0.2 ml PCR tube: 1 μl USER enzyme mix (1.0 unit), 10 μl of insert no. 1, 10 μl of insert no. 2 and 200 ng of digested and purified vector in a total reaction volume of 25 μl adjusted with MilliQ water [see Additional file ##SUPPL##2##3##]. For single fragment cloning the <italic>geneX</italic>-A3/A4 fragment was mixed with 1 μl USER enzyme mix and 200 ng pRF-HU or pRF-HUE vectors in a reaction volume of 15 μl. The USER reactions were incubated for 20 minutes at 37°C, followed by 20 minutes at 25°C. The entire volume of the USER cloning reactions were used to transform 50 μl of freshly prepared chemical competent <italic>E. coli </italic>cells (10⁶cfu./μg DNA), following the transformation guidelines described in [##UREF##4##20##]. Transformants were selected by adding 25 μg/ml kanamycin to the medium.</p>", "<p>The construction of pRF-HU2::<italic>PKS1 </italic>and pRF-HU2E::<italic>PKS1 </italic>vectors were performed in triplicate, using different batches of vector, enzyme and PCR amplicons. Negative controls were performed by replacing the PCR amplicons with MilliQ water.</p>", "<title>Verification of the inserts and their orientation</title>", "<p>The resulting <italic>E. coli </italic>transformants for the two <italic>PKS1 </italic>vectors were analysed with the insert specific primer pair to determine the cloning efficiency. All positive transformants were then analysed with primer combinations revealing the orientation of the inserts in the vectors (ex. <italic>PKS1</italic>-O1/RF-2 and RF-1/<italic>PKS1</italic>-O4 or RF-3/<italic>PKS1</italic>-A4). The cloning efficiency was calculated as the number of transformants that contained both inserts in the correct orientation divided by the total number of transformants obtained in the cloning reaction. The size of the vectors was determined by restriction enzyme digestion. The two inserts in the pRF-HU2:<italic>PKS1 </italic>vector were sequenced using the RF-1 and RF-2 primers and the two inserts in the pRF-HU2E::<italic>PKS1 </italic>with the RF-2 and RF-3 primers.</p>", "<p>For the other 27 vectors (16 × pRF-HU2 and 11 × pRF-HU2E) that were constructed by USER cloning, ten transformants were picked randomly for each construct and screened with the insert specific primer pairs. The cloning efficiency was calculated as the number of transformants that contained both inserts divided by the number of screened transformants. The size of the individual vectors was evaluated by restriction enzyme digestion, to confirm the cloning efficiency.</p>" ]

[ "<title>Results and Discussion</title>", "<p>The annotation of the sequenced fungal genomes has revealed a plethora of predicted proteins which do not show homology to any previously characterized proteins. In <italic>F. graminearum </italic>PH-1 alone, 8091 out of 13938 (58%) putative genes fall into the categories \"Conserved hypothetical protein\" or \"Hypothetical protein\" [##REF##16381910##21##]. Functional characterisation of these putative genes and proteins, to determine their importance for cellular processes related to pathology and synthesis of bioactive secondary metabolites, relies on efficient replacement and overexpression strategies. Implementation of the single step vector construction strategy shown in Figure ##FIG##0##1## has the potential to accelerate this research.</p>", "<p>The strategy is dependent on a four fragment cloning step, which is laborious and has a very low success rate using classical cloning techniques. The Xi-cloning and In-Fusion technologies allow for four fragment cloning, but had a very low success rate in our experiments (unpublished results). The yeast based construction of gene replacement cassettes for transformation of <italic>N. crassa</italic>, Colot and co-works [##REF##16801547##1##], also allows for efficient four fragment cloning. However, it is dependent on a final PCR based amplification step which increases the risk of unintended mutations in the HRS. These could affect the expression and functionality of the genes surrounding the target locus and sequencing of the integration site would be required to ensure that no unintended mutations have been introduced. The finding that the proofreading PfuTurbo Cx DNA polymerase [##REF##17000637##25##] can amplify templates containing uracil made the USER Friendly cloning technology attractive for our purpose. The use of Proofreading DNA polymerase is essential when making targeted genome modifications in fungi, due to the close spacing of fungal genes [##REF##16322742##26##], which often means that the HRS extends into neighbouring genes or their regulatory sequences. USER Friendly cloning has been used for the directional fusion of multiple PCR amplicons in a single cloning step, but only into a single site of the recipient vector [##REF##17389646##27##]. To test whether the USER Friendly cloning technique would allow the simultaneous cloning of two PCR amplicons into different sites of a recipient vector, vectors with two UCS's were needed. For this purpose we designed two new 26 bp long UCS's with <italic>PacI </italic>and <italic>Nt.Bbv.CI </italic>sites. These were cloned into the ATMT vectors pAg1-H3 and pAg1-H3E, resulting in pRF-HU, pRF-HU2, pRF-HUE and pRF-HU2E (Figure ##FIG##4##5##), according to the cloning strategy shown in Figure ##FIG##3##4##. The 26 bp long UCS's are significantly shorter than those utilized in the commercial USER Friendly cloning kit [##UREF##4##20##] and those reported in [##REF##17389646##27##]. This is an advantage if the vectors have to be modified by the addition of reporter genes or change of the selection marker gene, as shorter 5' overhangs on the primers will be required. Digestion of the new vectors, containing two UCS's, with <italic>PacI </italic>and <italic>Nt.Bbv.CI </italic>results in two fragments with four unique 9 bp long single stranded 3' overhangs, each consisting of seven constant base pairs and two variable bases (Figure ##FIG##1##2C##). The two variable bases in each overhang provide directionality in the cloning reaction, thereby ensuring correct assembly of the DNA fragments during cloning.</p>", "<p>Cloning of a single PCR amplicon was carried out to verify that the designed UCS's were functional. Three independent cloning experiments in which the PCR amplified PKS1-A3/A4 fragment was introduced into the pRF-HU or pRF-HUE vector were performed, resulting in an average cloning efficiency of 95.9% and 95.4% respectively, with an average of 104.7 and 64.7 colonies per transformation (Table ##TAB##0##1##). The cloning efficiencies for the new and shorter UCS's are very similar to those reported in the commercial system [##UREF##4##20##].</p>", "<p>The construction of the vectors, by four fragment cloning, for targeted replacement and <italic>in locus </italic>overexpression of <italic>PKS1 </italic>was performed in triplicate and the resulting transformants were screened by PCR. Construction of the targeted replacement vector pRF-HU2::<italic>PKS1 </italic>resulted in an average of 56.3 colonies of which 85.2% tested positive for the two inserts (Table ##TAB##0##1##). Construction of the overexpression vector pRF-HU2E::<italic>PKS1 </italic>resulted in an average of 47.3 colonies of which 82.4% were correct. All transformants that tested positive for the inserts also displayed the desired orientation in the vector. The negative controls all resulted in zero colonies. Construction of the seventeen different vectors, including <italic>PKS1</italic>, for targeted gene replacement (pRF-HU2) in <italic>F. graminearum </italic>resulted in an average cloning efficiency of 84.1% (+/- 5%) determined by analyses of ten transformants for each of the constructs. The twelve vectors constructed for <italic>in locus </italic>overexpression (pRF-HU2E vectors), including <italic>PKS1</italic>, resulted in an average cloning efficiency of 80.0% (+/- 6%) determined by screening ten transformants for each construct. Based on these results, fusion of two PCR amplicons with two vector fragments by USER Friendly cloning proved to be very efficient as also suggested by the successful fusion of multiple PCR amplicons by Geu-Flores and co-workers [##REF##17389646##27##].</p>", "<p>The presence of the same UCS's in the four vectors allow the reuse of primers for different constructs, e.g. replacement and over-expression, thereby reducing the number of primers that are required for the full analysis of a given target gene. This was exploited for the test vectors where the <italic>geneX</italic>-O1/O2 product is reused for both replacement and overexpression vectors. The designed O1/O2 primer pair amplifies the promoter sequence of the respective target genes, the O3/O4 primers amplifies the 5' end of the coding sequences including the start codon, and the A3/A4 primers amplifies the terminator region of the respective genes (Figure ##FIG##6##7A##). For construction of targeted gene replacement vectors, pRF-HU2 was mixed with <italic>geneX</italic>-O1/O2 and <italic>geneX</italic>-A3/A4. These are required to give homologous recombination with the fungal genome resulting in the replacement of the coding sequence of the target gene (Figure ##FIG##6##7B##). Vectors for <italic>in locus </italic>over-expression (promoter insertion) were constructed by mixing pRF-HU2E with <italic>geneX</italic>-O1/O2 and <italic>geneX</italic>-O3/O4, so that homologous recombination with the target locus inserts the <italic>A. nidulans gdpA </italic>promoter in front of the start codon of the target gene (Figure ##FIG##6##7C##).</p>", "<p>An additional advantage of the single step construction strategy is that all vector constructs can utilize the same tested vector preparation, which is not the case for the classical two step cloning strategy where cloning of the second insert is dependent on the preparation and digestion of the vector construction in the first cloning step. Besides minimizing the time expenditure for vector construction, the four fragment cloning offers increased flexibility in the choice of selection marker, since the digested vector-backbone can be purified and the hph cassette (Figure ##FIG##6##7B## and ##FIG##6##7C##) replaced with other antibiotic selection markers as zeocin or geneticin. This is of high relevance in repeated transformation of hygromycin resistant mutants. Our average vector construction time with the USER Friendly cloning system is three to four days, compared to 14 days with Xi-cloning and 20 days with classical cloning techniques. Furthermore the single step construction strategy only requires a single verification process, whereas two are required for the classical techniques. The constructed vectors are compatible with both <italic>A. tumefaciens </italic>mediated transformation and protoplast based transformation of fungi.</p>", "<p>The developed USER Friendly cloning system combined with <italic>A. tumefaciens </italic>mediated transformation, PCR based screening methods [##REF##14719830##28##,##REF##16879655##15##] and quantitative Real-Time PCR to determine the gene copy number [##REF##17080302##29##] can be perfected to give a realistic high throughput system for large scale functional studies of genes in filamentous fungi.</p>" ]

[ "<title>Results and Discussion</title>", "<p>The annotation of the sequenced fungal genomes has revealed a plethora of predicted proteins which do not show homology to any previously characterized proteins. In <italic>F. graminearum </italic>PH-1 alone, 8091 out of 13938 (58%) putative genes fall into the categories \"Conserved hypothetical protein\" or \"Hypothetical protein\" [##REF##16381910##21##]. Functional characterisation of these putative genes and proteins, to determine their importance for cellular processes related to pathology and synthesis of bioactive secondary metabolites, relies on efficient replacement and overexpression strategies. Implementation of the single step vector construction strategy shown in Figure ##FIG##0##1## has the potential to accelerate this research.</p>", "<p>The strategy is dependent on a four fragment cloning step, which is laborious and has a very low success rate using classical cloning techniques. The Xi-cloning and In-Fusion technologies allow for four fragment cloning, but had a very low success rate in our experiments (unpublished results). The yeast based construction of gene replacement cassettes for transformation of <italic>N. crassa</italic>, Colot and co-works [##REF##16801547##1##], also allows for efficient four fragment cloning. However, it is dependent on a final PCR based amplification step which increases the risk of unintended mutations in the HRS. These could affect the expression and functionality of the genes surrounding the target locus and sequencing of the integration site would be required to ensure that no unintended mutations have been introduced. The finding that the proofreading PfuTurbo Cx DNA polymerase [##REF##17000637##25##] can amplify templates containing uracil made the USER Friendly cloning technology attractive for our purpose. The use of Proofreading DNA polymerase is essential when making targeted genome modifications in fungi, due to the close spacing of fungal genes [##REF##16322742##26##], which often means that the HRS extends into neighbouring genes or their regulatory sequences. USER Friendly cloning has been used for the directional fusion of multiple PCR amplicons in a single cloning step, but only into a single site of the recipient vector [##REF##17389646##27##]. To test whether the USER Friendly cloning technique would allow the simultaneous cloning of two PCR amplicons into different sites of a recipient vector, vectors with two UCS's were needed. For this purpose we designed two new 26 bp long UCS's with <italic>PacI </italic>and <italic>Nt.Bbv.CI </italic>sites. These were cloned into the ATMT vectors pAg1-H3 and pAg1-H3E, resulting in pRF-HU, pRF-HU2, pRF-HUE and pRF-HU2E (Figure ##FIG##4##5##), according to the cloning strategy shown in Figure ##FIG##3##4##. The 26 bp long UCS's are significantly shorter than those utilized in the commercial USER Friendly cloning kit [##UREF##4##20##] and those reported in [##REF##17389646##27##]. This is an advantage if the vectors have to be modified by the addition of reporter genes or change of the selection marker gene, as shorter 5' overhangs on the primers will be required. Digestion of the new vectors, containing two UCS's, with <italic>PacI </italic>and <italic>Nt.Bbv.CI </italic>results in two fragments with four unique 9 bp long single stranded 3' overhangs, each consisting of seven constant base pairs and two variable bases (Figure ##FIG##1##2C##). The two variable bases in each overhang provide directionality in the cloning reaction, thereby ensuring correct assembly of the DNA fragments during cloning.</p>", "<p>Cloning of a single PCR amplicon was carried out to verify that the designed UCS's were functional. Three independent cloning experiments in which the PCR amplified PKS1-A3/A4 fragment was introduced into the pRF-HU or pRF-HUE vector were performed, resulting in an average cloning efficiency of 95.9% and 95.4% respectively, with an average of 104.7 and 64.7 colonies per transformation (Table ##TAB##0##1##). The cloning efficiencies for the new and shorter UCS's are very similar to those reported in the commercial system [##UREF##4##20##].</p>", "<p>The construction of the vectors, by four fragment cloning, for targeted replacement and <italic>in locus </italic>overexpression of <italic>PKS1 </italic>was performed in triplicate and the resulting transformants were screened by PCR. Construction of the targeted replacement vector pRF-HU2::<italic>PKS1 </italic>resulted in an average of 56.3 colonies of which 85.2% tested positive for the two inserts (Table ##TAB##0##1##). Construction of the overexpression vector pRF-HU2E::<italic>PKS1 </italic>resulted in an average of 47.3 colonies of which 82.4% were correct. All transformants that tested positive for the inserts also displayed the desired orientation in the vector. The negative controls all resulted in zero colonies. Construction of the seventeen different vectors, including <italic>PKS1</italic>, for targeted gene replacement (pRF-HU2) in <italic>F. graminearum </italic>resulted in an average cloning efficiency of 84.1% (+/- 5%) determined by analyses of ten transformants for each of the constructs. The twelve vectors constructed for <italic>in locus </italic>overexpression (pRF-HU2E vectors), including <italic>PKS1</italic>, resulted in an average cloning efficiency of 80.0% (+/- 6%) determined by screening ten transformants for each construct. Based on these results, fusion of two PCR amplicons with two vector fragments by USER Friendly cloning proved to be very efficient as also suggested by the successful fusion of multiple PCR amplicons by Geu-Flores and co-workers [##REF##17389646##27##].</p>", "<p>The presence of the same UCS's in the four vectors allow the reuse of primers for different constructs, e.g. replacement and over-expression, thereby reducing the number of primers that are required for the full analysis of a given target gene. This was exploited for the test vectors where the <italic>geneX</italic>-O1/O2 product is reused for both replacement and overexpression vectors. The designed O1/O2 primer pair amplifies the promoter sequence of the respective target genes, the O3/O4 primers amplifies the 5' end of the coding sequences including the start codon, and the A3/A4 primers amplifies the terminator region of the respective genes (Figure ##FIG##6##7A##). For construction of targeted gene replacement vectors, pRF-HU2 was mixed with <italic>geneX</italic>-O1/O2 and <italic>geneX</italic>-A3/A4. These are required to give homologous recombination with the fungal genome resulting in the replacement of the coding sequence of the target gene (Figure ##FIG##6##7B##). Vectors for <italic>in locus </italic>over-expression (promoter insertion) were constructed by mixing pRF-HU2E with <italic>geneX</italic>-O1/O2 and <italic>geneX</italic>-O3/O4, so that homologous recombination with the target locus inserts the <italic>A. nidulans gdpA </italic>promoter in front of the start codon of the target gene (Figure ##FIG##6##7C##).</p>", "<p>An additional advantage of the single step construction strategy is that all vector constructs can utilize the same tested vector preparation, which is not the case for the classical two step cloning strategy where cloning of the second insert is dependent on the preparation and digestion of the vector construction in the first cloning step. Besides minimizing the time expenditure for vector construction, the four fragment cloning offers increased flexibility in the choice of selection marker, since the digested vector-backbone can be purified and the hph cassette (Figure ##FIG##6##7B## and ##FIG##6##7C##) replaced with other antibiotic selection markers as zeocin or geneticin. This is of high relevance in repeated transformation of hygromycin resistant mutants. Our average vector construction time with the USER Friendly cloning system is three to four days, compared to 14 days with Xi-cloning and 20 days with classical cloning techniques. Furthermore the single step construction strategy only requires a single verification process, whereas two are required for the classical techniques. The constructed vectors are compatible with both <italic>A. tumefaciens </italic>mediated transformation and protoplast based transformation of fungi.</p>", "<p>The developed USER Friendly cloning system combined with <italic>A. tumefaciens </italic>mediated transformation, PCR based screening methods [##REF##14719830##28##,##REF##16879655##15##] and quantitative Real-Time PCR to determine the gene copy number [##REF##17080302##29##] can be perfected to give a realistic high throughput system for large scale functional studies of genes in filamentous fungi.</p>" ]

[ "<title>Conclusion</title>", "<p>The constructed pRF-HU2 and pRF-HU2E vectors allow for the simultaneous directional cloning of two inserts in a four fragment assembly with an efficiency of 84.1% and 80.0%, respectively. These results show that the single step four fragment USER Friendly cloning method provides a good alternative to existing vector construction techniques. Vector construction for targeted replacement of genes is reduced to design of two primer pairs, which will permit automation of the experimental design as required for high-throughput knockout projects [##REF##16801547##1##]. The promoters that drive the hygromycin resistance gene in the designed vectors are probably inefficient in basidiomycotes but favourite vectors can easily be converted to USER compatible vectors simply by introducing the two new UCS's into their MCS's.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The rapid increase in whole genome fungal sequence information allows large scale functional analyses of target genes. Efficient transformation methods to obtain site-directed gene replacement, targeted over-expression by promoter replacement, in-frame epitope tagging or fusion of coding sequences with fluorescent markers such as GFP are essential for this process. Construction of vectors for these experiments depends on the directional cloning of two homologous recombination sequences on each side of a selection marker gene.</p>", "<title>Results</title>", "<p>Here, we present a USER Friendly cloning based technique that allows single step cloning of the two required homologous recombination sequences into different sites of a recipient vector. The advantages are: A simple experimental design, free choice of target sequence, few procedures and user convenience. The vectors are intented for <italic>Agrobacterium tumefaciens </italic>and protoplast based transformation technologies. The system has been tested by the construction of vectors for targeted replacement of 17 genes and overexpression of 12 genes in <italic>Fusarium graminearum</italic>. The results show that four fragment vectors can be constructed in a single cloning step with an average efficiency of 84% for gene replacement and 80% for targeted overexpression.</p>", "<title>Conclusion</title>", "<p>The new vectors designed for USER Friendly cloning provided a fast reliable method to construct vectors for targeted gene manipulations in fungi.</p>" ]

[ "<title>Abbreviations</title>", "<p>ATMT: <italic>Agrobacterium </italic><italic>tumefaciens </italic>mediated transformation; LB: left border of T-DNA (transfer DNA); MCS: multiple cloning site; PCR: polymerase chain reaction; <italic>PKS</italic>: polyketide synthase encoding gene; RB: right border of T-DNA (transfer DNA); UCS: USER cloning site; USER: Uracil Specific Excision Reaction.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>RF conceived the study, performed experiments and analyses, wrote and edited the manuscript. JAA performed validating experiments and analyses. MBK designed and constructed the pAg1-HUE vector. HG contributed to the writing of the manuscript and to the experimental design. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We are grateful to Hussam Hassan Nour El Din Auis and Klaus S. Albertsen for introducing us to the USER Friendly cloning technique and for valuable suggestions. We would also like to thank technician Pia Petersen for her excellent work with the vector construction. The research was funded by 'The Danish Ministry of Food, Agriculture and Fisheries', the 'PhD Research School for Biotechnology' (FOBI) and the 'Faculty of Life Sciences' at the 'University of Copenhagen', Denmark.</p>", "<p>Vector sequences and protocols can be found as on the BMC molecular biology web-page [see Additional file ##SUPPL##1##2##] [see Additional file ##SUPPL##2##3##] to the article or on <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.RasmusFrandsen.dk\"/>. Vectors will be shared upon request.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Strategies for construction of replacement vectors</bold>. On the left, the classical strategy for construction of replacement vectors is shown. It consists of two successive restriction and ligation based cloning steps. On the right the single four fragment USER friendly cloning method is shown. The figures are not drawn to scale. <italic>hph </italic>= <italic>hygromycin phospho-transferase expression cassette (selection marker)</italic>.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>The USER Friendly cloning strategy for single step construction of replacement vectors</bold>. <bold>A) </bold>Amplification of the two homologous recombination sequences (HRS) with primers that contain 5' deoxyuridine extensions. <bold>B) </bold>Treatment of the PCR amplicons with USER enzyme mix, resulting in the generation of unique 3' single stranded overhangs. The USER enzyme solution is a mixture of Uracil DNA glycosylase and DNA glycosylase-lyase Endo VIII. The Uracil DNA glycosylase recognises the 2'-Deoxyuridine base in the primer portion of the PCR amplicon and excises the uracil nucleobase, resulting in an abasic position [##REF##6287922##30##]. The presence of an abasic site in the DNA permit the DNA glycosylase-lyase Endo VIII to break the phosphodiester backbone at both the 3' and 5' sides of the abasic position, resulting in a single strand break [##REF##9405426##31##]. The resulting short 5' stretch of the original primer then dissociates, leaving the PCR fragment with a 9 bp long 3' single stranded overhang. <bold>C) </bold>Design of the USER vector for targeted gene replacement in fungi, with two unique USER cloning sites (LB and RB). Each of the UCS's consists of a <italic>PacI </italic>site (Red), two <italic>Nt.BbvCI sites </italic>(blue) and two times two unique base pairs (yellow, green, gray and pink) ensuring directional cloning of the inserts. Digestion of the vector results in the generation of two DNA fragments with four unique 9 bp long 3' overhangs. <bold>D) </bold>Mixing and annealing of the two vector DNA fragments and the two inserts. The four unique 3' overhangs ensures correct annealing between the four DNA fragments. <bold>E) </bold>Transformation into <italic>E. coli</italic>, where covalent bonds are formed between the base-paired DNA fragments. <bold>F) </bold>Screening for correct transformants by colony-PCR using the HRS specific primer pairs that were used in step A. The figures are not drawn to scale.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Expression vector</bold>. The replacement vector pAg1-H3 was converted to an expression vector by introducing the <italic>Aspergillus nidulans gpdA </italic>promoter (PgpdA), into the LB multiple cloning site.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Construction of USER compatible vectors</bold>. Flow chart for the different components used during construction of the USER compatible vectors. The UCS at the left (LB) and right (RB) borders were ordered as complementary oligomers with additional bases at the ends to make them compatible with the vector ends following digestion with the used restriction enzymes.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>The constructed vectors for USER Friendly cloning</bold>. The constructed USER vector <bold>(A) </bold>pRF-HU2 (6323 bp), <bold>(B) </bold>pRF-HU2E (8696 bp), <bold>(C) </bold>pRF-HU (6336 bp) and <bold>(D) </bold>pRF-HUE (8709 bp). pRF-HU2 and pRF-HU2E were designed for single step directional cloning of two PCR amplicons to allow targeted gene replacement in filamentous fungi. The pRF-HU and pRF-HUE vectors were designed for construction of vectors for random integration into the fungal genome by non-homologous recombination. The LB UCS is identical in all four vectors, and the RB UCS is identical in the vectors for two fragment cloning. This allows for the reuse of primers with all four vectors. <italic>LB </italic>= left border, <italic>pTrpC </italic>= Tryptophan promoter form <italic>Aspergillus nidulans</italic>, <italic>hph </italic>= hygromycin phosphor transferase, <italic>TtrpC </italic>= Tryptophan terminator from <italic>A. nidulans</italic>, <italic>RB </italic>= right border, <italic>oriV </italic>= origin of replication in <italic>E. coli</italic>, <italic>KanR </italic>= kanamycin resistance, <italic>TrfA </italic>= replication initiation gene (broad-host-range), <italic>PgpdA </italic>= glyceraldehyde-3-phosphate dehydrogenase promoter from <italic>A. nidulans</italic>. Forward primers: RF-1 and RF-3; Reverse primers: RF-2.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold><italic>PacI/Nt.Bbv.CI </italic>digested and GFX purified vectors</bold>. The designed vectors digested with <italic>PacI/Nt.BbvCI </italic>and GFX-purified from solution. Lane 1–6: 2log ladder, pRF-HU, pRF-HU2, pRF-HUE, pRF-HU2E and 2log ladder. Expected sizes of bands: pRF-HU (6336 bp), pRF-HU2 (2489 bp and 3834 bp), pRF-HUE (8709 bp) and pRF-HU2E (3840 bp and 4856 bp).</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>Placement of the three primer pairs, relative to the target gene</bold>. The designed vectors allow for the reuse of primer pairs for multiple constructs, eg. targeted replacement and <italic>in locus </italic>overexpression. (<bold>A) </bold>Placement of the three primer pairs. (<bold>B</bold>) Construction of the vector for targeted gene replacement and homologous recombination with the genomic target. (<bold>C</bold>) Construction of the vector for <italic>in locus </italic>overexpression and homologous recombination with the genomic target, resulting in insertion of the <italic>gpdA </italic>promoter in front of the coding sequence for the target gene.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Testing of USER Friendly cloning for single step four fragment cloning</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td/><td/><td align=\"center\" colspan=\"3\"><bold>No. of correct colonies/total no. of colonies</bold></td><td align=\"center\"><bold>Average</bold></td></tr><tr><td colspan=\"3\"/><td colspan=\"3\"><hr/></td><td colspan=\"1\"><hr/></td></tr><tr><td align=\"left\"><bold>Vector</bold></td><td align=\"left\"><bold>Insert 1</bold></td><td align=\"left\"><bold>Insert 2</bold></td><td align=\"center\">1.</td><td align=\"center\">2.</td><td align=\"center\">3.</td><td/></tr></thead><tbody><tr><td align=\"left\">pRF-HU</td><td align=\"left\">PKS1-A1/A2</td><td align=\"left\">na</td><td align=\"center\">87/91</td><td align=\"center\">100/103</td><td align=\"center\">114/120</td><td align=\"center\">104.7 (95.9%)</td></tr><tr><td align=\"left\">pRF-HUE</td><td align=\"left\">PKS1-O1/O2</td><td align=\"left\">na</td><td align=\"center\">59/61</td><td align=\"center\">60/63</td><td align=\"center\">66/70</td><td align=\"center\">64.7 (95.4%)</td></tr><tr><td align=\"left\">pRF-HU2</td><td align=\"left\">PKS1-A1/A2</td><td align=\"left\">PKS1-A3/A4</td><td align=\"center\">47/53</td><td align=\"center\">52/61</td><td align=\"center\">45/55</td><td align=\"center\">56.3 (85.2%)</td></tr><tr><td align=\"left\">pRF-HU2E</td><td align=\"left\">PKS1-O1/O2</td><td align=\"left\">PKS1-O3/O4</td><td align=\"center\">38/48</td><td align=\"center\">39/45</td><td align=\"center\">40/49</td><td align=\"center\">47.3 (82.4%)</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional File 1</title><p>Table S1 – Oligonucleotides used in this study. The primer pairs used in the study.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional File 2</title><p>Vector sequences. The vector sequences in GenBank format.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional File 3</title><p>Protocols for USER Friendly cloning.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>USER cloning: Results from three independent replicates where one or two PCR amplicons are cloned into the designed USER vectors. All transformants were first tested for the presence of the desired insert and then for the orientation of the insert in the vector. All transformants that were positive for inserts also had the correct orientation. The negative control reactions, where no PCR amplicons were added to the reactions, resulted in zero colonies.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2199-9-70-1\"/>", "<graphic xlink:href=\"1471-2199-9-70-2\"/>", "<graphic xlink:href=\"1471-2199-9-70-3\"/>", "<graphic xlink:href=\"1471-2199-9-70-4\"/>", "<graphic xlink:href=\"1471-2199-9-70-5\"/>", "<graphic xlink:href=\"1471-2199-9-70-6\"/>", "<graphic xlink:href=\"1471-2199-9-70-7\"/>" ]

[ "<media xlink:href=\"1471-2199-9-70-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2199-9-70-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2199-9-70-S3.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Approximately 98% of the human transcriptome is non-protein-coding RNA (ncRNA) [##REF##11713189##1##,##REF##14505360##2##]. The fraction of ncRNA believed to be functional in cells was once limited to the well-characterised transfer and ribosomal RNAs. However, this fraction has recently been expanded to include microRNAs (miRNAs), a class of short, single-stranded RNAs that target, through nucleotide complementarity, specific messenger RNAs, enabling them to negatively modulate gene expression. First characterised in 1993, miRNAs were initially shown to be involved in the control of developmental timing in <italic>Caenhorhabditis elegans </italic>[##REF##8252621##3##]. Now, 15 years later, 541 human miRNAs have been submitted to the most recent edition of the online miRNA sequence repository, miRBase [##REF##16381832##4##,##REF##14681370##5##]. A very small proportion of identified miRNAs have verified roles, in processes such as cell proliferation [##REF##15944709##6##] and apoptosis [##REF##16166262##7##]. It may be some time before the full catalogue of biologically-functional miRNAs is compiled but the involvement of miRNAs in the regulation of cancer-related genes at the post-transcriptional level has already led to miRNAs being hailed as a novel class of tumour suppressor genes and oncogenes and the coining of the term \"oncomiR\" [reviewed in [##REF##17028598##8##] and [##REF##16557279##9##]]. Further elucidating our limited understanding of the mechanisms of metastasis [##REF##12778135##10##,##REF##17110329##11##]; the spread of cancer cells from the primary neoplasm to distant organs, has become a major focus in miRNA studies [##REF##18185580##12##, ####REF##17898713##13##, ##REF##18176954##14####18176954##14##]. Gene signatures from these studies will contribute to our understanding of the multi-step processes of metastasis and may also enable advanced indication of the likelihood of tumour invasion and metastasis based on the characteristics of the primary tumour.</p>", "<p>The expression of miRNAs has been studied using traditional, semi-quantitative methods such as northern blotting [##REF##15003116##15##], bead-based flow-cytometry [##REF##15944708##16##] and microarray technology [##REF##15345052##17##]. However, by far the method of choice for expression quantitation is real-time quantitative PCR (RQ-PCR) due to its sensitivity, wide dynamic range and low template requirements. The technique has itself been revolutionised in recent years with the development of stem-loop primers that specifically convert the mature, functional miRNA into its DNA complement [##REF##16314309##18##]. Furthermore, a multiplex stem-loop RQ-PCR format is currently being refined to allow multiple miRNAs to be transcribed simultaneously [##REF##16434699##19##,##REF##16529715##20##].</p>", "<p>To produce reliable relative RQ-PCR data, corrections must be made for variation between reactions introduced during the steps from sample preparation to amplification. Incorporating an endogenous control (EC) gene into the experimental design is an effective method of normalising the data but candidate ECs must be tested on a representative number of the sample population if not the entire sample set [##REF##18042273##21##, ####REF##16060372##22##, ##REF##11086195##23####11086195##23##]. Use of an unreliable EC may lead to inaccurate, unreliable results and previous studies show that mRNA expression can be made to appear up- or down-regulated by one order of magnitude based solely on the choice of EC [##REF##18042273##21##].</p>", "<p>Using the Medical Subject Heading (MeSH) terms microRNAs, neoplasm and reverse transcriptase polymerase chain reaction, a recent PubMed search returned 42 articles, 5 of which detailed miRNA RQ-PCR expression profiling studies using human neoplastic breast samples. The EC(s) used in these studies were <italic>let-7a </italic>and <italic>miR-16 </italic>[##REF##16784538##24##], <italic>U6 </italic>small nuclear RNA (snRNA) and tRNA for initiator methionine [##REF##15210942##25##], <italic>18S rRNA </italic>[##REF##17194750##26##], glyceraldehyde-3-phosphate dehydrogenase (<italic>GAPDH</italic>) [##REF##17980029##27##] and in one article, the EC used for RQ-PCR analysis was not given [##REF##17889832##28##]. There is currently no consensus on suitable ECs for quantitative analysis of miRNA by RQ-PCR in human breast tissue. Concern has been expressed regarding the use of ribosomal RNAs in normalisation strategies as they can be expressed at much greater levels than the target RNA making it very difficult to quantify an rRNA and a rare transcript in the same RNA dilution [##REF##16060372##22##,##REF##11013345##29##,##REF##12184808##30##]. Moreover, there is evidence of rRNA deregulation in apoptosis [##REF##10788523##31##]. It is also clear that the traditionally-used but seldom validated <italic>GAPDH </italic>and β-actin (<italic>ABTB</italic>) genes are not suitable endogenous controls for some studies [##REF##12496918##32##, ####REF##3664468##33##, ##REF##3114226##34####3114226##34##]. Our aim was to identify from a panel of RNA species similar to miRNAs, suitable EC candidates for miRNA analysis by RQ-PCR.</p>", "<p>The expression of eight small RNAs was determined in 36 fresh-frozen breast tissues; three small nucleolar RNAs (snoRNAs, <italic>RNU19, RNU48 </italic>and <italic>Z30</italic>) and five miRNAs (<italic>let-7a, miR-10b, miR-16, miR-21 </italic>and <italic>miR-26b</italic>). The five miRNAs were chosen as candidate ECs for this study based on their known expression in human breast tissue and/or their previous use as an EC gene for miRNA RQ-PCR analysis [##REF##16784538##24##]. The three snoRNA genes were selected from a panel of ten commercially available TaqMan control assays. SnoRNAs, found within the nucleolus, range from 60–300 nt in length and chemically modify rRNA [##REF##9512526##35##], small nuclear RNA (snRNA) [##REF##10490628##36##] and mRNA [##REF##11106375##37##] through their recognition of short sequences in the target molecule and recruitment of associated proteins to the site. MiR-30*, previously referred to as miR-30a-3p, targets RNA involved in several cancer-related biological processes [##REF##16239240##38##] and was chosen as a target gene to investigate the effect of EC gene selection on relative quantitation. Downregulation of miR-30* has previously been shown to increase transcription of mRNAs involved in processes such as angiogenesis (thrombospondin I, cysteine-rich, angiogenic inducer) and cell cycle transition (cyclin-dependent kinase 6) [##REF##16239240##38##]. Samples consisted of malignant (n = 21), benign (n = 5) and normal (n = 5) breast tissues. Malignant tumour tissues were representative of all tumour grades and hormone receptor states. The malignant breast tumour tissues were divided into three groups depending on the patient's disease progression in the five years following removal of the primary tumour; tumours from patients who did not develop metastases (metastases-free, MF, n = 13), those from patients who developed bone metastases (BM, n = 7) and those from patients who developed visceral and bone metastases (VBM, n = 6).</p>" ]

[ "<title>Methods</title>", "<title>Tissue Cohort</title>", "<p>Primary breast tumour tissues (n = 31) were obtained from patients during primary curative resection, at Galway University Hospital, Galway, Ireland. Samples were categorised into benign (n = 5) or malignant groups (n = 26) according to standard histopathological parameters. The malignant breast tumour tissues were divided into three groups depending on the patient's disease progression in the five years following removal of the primary tumour; tumours from patients who did not develop metastases (metastases-free, MF, n = 13), those from patients who developed bone metastases (BM, n = 7) and those from patients who developed visceral and bone metastases (VBM, n = 6).</p>", "<p>Clinical data relating to the malignant tumour tissues used in this study are shown in Table ##TAB##2##3##. RNA from normal tissues (n = 5), recovered from patients undergoing reduction mastopexy surgery were used as calibrator samples for RQ-PCR analysis. Tissues were immediately snap-frozen in liquid nitrogen and stored at -80°C until RNA extraction. Prior written and informed consent was obtained from each patient and the study was approved by the ethics review board of Galway University Hospital. Clinical data were obtained from the Breast Cancer Database at the Department of Surgery, Galway University Hospital.</p>", "<title>RNA Extraction</title>", "<p>Approximately 100 mg of tissue was homogenised in 1–2 mL QIAzol (Qiagen, Crawley, UK) using a bench-top homogeniser (Polytron PT1600E, Kinematica AG, Littau-Luzem, Switzerland. Large (&gt; 200 nt) and small RNA (&lt; 200 nt) fractions were isolated separately using the RNeasy^®Plus Mini Kit and RNeasy MinElute^®Cleanup Kit (Qiagen, West Sussex, UK) according to the Supplementary Protocol: Purification of miRNA from animal cells. A portion of the purified large and small RNA was aliquotted for quantitative and qualitative analysis using NanoDrop1000^®spectrophotometry and the Agilent 2100 Bioanalyzer respectively. The remaining RNA was stored at -80°C until further use.</p>", "<title>RNA Analysis</title>", "<p>MicroRNA concentration and purity were assessed using the NanoDrop1000^®spectrophotometer (NanoDrop Technologies Inc, Wilmington, DE, USA). The small-RNA enriched fraction was analysed using the Small RNA Assay with the Agilent 2100 Bioanalyzer (Fig. ##FIG##3##4##) (Agilent Technologies, Palo Alto, CA, USA). For this assay, samples were diluted to 1 ng/μL, within the quantitative and qualitative range of the assay. Integrity of the large RNA fraction (&gt; 200 nt) was assessed using the RNA 6000 Nano LabChip Series II Assay (Agilent Technologies). An RNA integrity number (RIN) is generated for each sample based on the ratio of ribosomal bands and also the presence or absence of degradation products on the electrophoretic image. A threshold value of RIN ≥ 7 was applied.</p>", "<title>Candidate Endogenous Control Genes</title>", "<p>The small nuclear and small nucleolar genes were chosen from the ten Human TaqMan MicroRNA Assay Controls available from Applied Biosystems (Foster city, CA, USA) at the time of study. The five miRNA genes were selected based on their known expression in breast cancer tissues and/or based on their previous use as an EC gene in a breast cancer study [##REF##16784538##24##]. Known functions of the candidates are listed in Table ##TAB##3##4##.</p>", "<title>cDNA Synthesis and RQ-PCR</title>", "<p>Each reaction was primed using a gene-specific stem-loop primer. The primer and probe sequences for let-7a, miR-10b, miR-16, miR-26b and miR-30* were as previously published [##REF##16314309##18##]. Where sequences were available, primers were obtained from MWG Biotech (Ebersberg, Germany). Otherwise, assays containing the RT stem-loop primer and the PCR primers and probes were used (Applied Biosystems, Foster City, CA, USA). Small RNA (5 ng) was transcribed using MultiScribe Reverse Transcriptase (Applied Biosystems). The reaction was performed using a GeneAmp PCR system 9700 thermal cycler (Applied Biosystems). An RT-negative control was included in each batch of reactions. The PCR reactions were carried out in a final volume of 20 μL using an ABI Prism 7000 Sequence Detection System (Applied Biosystems). Briefly, reactions consisted of 1.33 μL cDNA, 1× TaqMan Universal PCR Master mix, No AmpErase UNG, 0.2 μM TaqMan^®Probe (Applied Biosystems), 1.5 μM forward primer and 0.7 μM reverse primer. The PCR reactions were initiated with a 10 min incubation at 95°C followed by 40 cycles of 95°C for 15 sec and 60°C for 60 sec. cDNA, synthesised from pooled normal breast tissue, was included on each 96-well plate as an interassay control and calibrator. All reactions were performed in triplicate. The threshold standard deviation for intra- and inter-assay replicates was 0.3. PCR amplification efficiencies were calculated for each candidate EC RQ-PCR assay using the formula E = (10^-1/slope-1) × 100, using the slope of the plot, Ct versus log input of cDNA. PCR amplification efficiencies for each EC candidate are shown in Table ##TAB##3##4##.</p>", "<title>Data Analysis</title>", "<p>Relative quantities (Q.rel) for each candidate EC gene were calculated from cycle threshold (C_t) values scaled to a calibrator sample (pool of 5 normal tissues) and corrected for efficiency of amplification (E) according to the formula: Q.rel. = E^-ΔCt, with ΔCt = average Ct test sample-average Ct calibrator sample. To calculate the expression of the target gene miR-30* relative to each of the EC candidates, the ΔΔCt method was used, with ΔΔCt = (Ct target gene, test sample-Ct endogenous control gene, test sample)-(Ct target gene, calibrator sample-Ct endogenous control gene, calibrator sample). Again, quantities were corrected for efficiency of amplification and the errors were calculated as previously described [##REF##12184808##30##].</p>", "<p>Stability of EC expression was analysed using two freely-available programmes; geNorm and NormFinder. GeNorm (vs. 3.4) is a Visual Basic Application for Excel that calculates a gene-stability measure (M) for all candidate EC genes in a given set of samples and determines the most reliable pair of ECs, showing greatest stability of expression ratio across samples. It is based on a pair-wise comparison model. NormFinder [##REF##15289330##54##], an excel-add-in, uses an ANOVA-based model to estimate intra- and inter-group variation. It combines these estimates to produce a stability value for each candidate. NormFinder indicates the single most stable EC and EC pair where the stability of the latter is greater than that of the single EC. Prior to geNorm and NormFinder analysis, Ct values were converted into Q.rel values (E = ^-ΔCt), as detailed above. For Normfinder analysis samples were grouped into metastases free (MF, n = 13), bone metastases (BM, n = 7), visceral and bone metastases (VBM, n = 6) and benign (BEN, n = 5) as described above. Statistical analyses were performed using Minitab (vs 15; Minitab Ltd., Coventry, UK). Distribution of data was determined using the Anderson-Darling normality test and parametric tests were used where appropriate. Levene's statistic was used to assess if there was a significant difference in variance between genes. The equivalence test was used to assess whether genes were equivalently expressed between tumour (benign and malignant) and normal breast tissues and between malignant and benign breast tissues [##REF##15519565##41##]. ANOVA, Fisher's least significant difference tests and Kruskal Wallis tests were applied to determine the effect of EC on target gene expression. P values &lt; 0.05 were considered statistically significant.</p>" ]

[ "<title>Results</title>", "<title>RNA analysis</title>", "<p>Concentrations of small RNA ranged from 45–431 ng μL^-1. The distribution of miRNA yields (RNA in the 10–35 nt range) across the various malignant groups, benign and normal tissues was determined using the Agilent Small RNA Assay (Table ##TAB##0##1##). Percentage of miRNA in the small RNA fraction ranged from 12%–98%. For the majority of samples, miRNA comprised 26–75% of total small RNA. High miRNA yields (&gt; 75% miRNA) were seen in samples from the BM and MF groups. Low yields (&lt; 25% miRNA) were seen in all groups apart from the normal tissue group. The large RNA samples, extracted separately but at the same time as the small RNA used for this study, all had an RNA integrity number (RIN) ≥ 7.</p>", "<title>Relative Expression Quantitation</title>", "<p>The threshold cycle (C_t) is the amplification cycle number at which the fluorescence generated within a reaction rises above a defined threshold fluorescence [##REF##17406449##39##]. The eight candidate ECs displayed a wide expression range with C_tvalues between 18 and 36. MiR-16 and miR-21 showed relatively high expression with median Cts of 21, while let-7a, miR-10b, miR-26b and RNU48 were moderately abundant with median Cts of between 23 and 27. Z30 had lower abundance with a median C_tof 29. RNU19 expression was very low in these samples with Cts ranging from 26.2 to 38.9. It was decided to exclude RNU19 from further analysis due to its low expression. Ct values were converted to relative quantities (Q.Rel) using the formula: E^-ΔCt, where E = PCR amplification efficiency and ΔCt = average Ct, test sample-average Ct, calibrator sample. There was no significant difference in variance between genes (P &gt; 0.05, Fig. ##FIG##0##1B##). The relative quantities did not differ significantly between the MF, BM, VBM and BEN groups for any of the candidate ECs (P &gt; 0.05; Fig. ##FIG##0##1A##). As NormFinder and geNorm assume candidates are not differentially expressed between groups, this analysis is necessary to validate use of these methodologies [##REF##16600798##40##]. Equivalent expression between the tumour tissues (benign and malignant) and the normal breast tissues (used as the calibrator) was confirmed for each of the seven candidate ECs using the equivalence test and a fold change cut-off of 3[##REF##15519565##41##]. All genes, with the exception of Z30, were also equivalently expressed between the malignant and benign tumour groups using a fold change cut-off of 3.</p>", "<title>Stability Candidate EC Expression</title>", "<p>Stability of the candidate ECs was examined using geNorm and NormFinder. The ranking of the candidates, as determined by these programmes, is shown in Table ##TAB##1##2##. The lower the stability value, the higher the gene stability. With a stability value of 0.312, NormFinder selected let-7a as the most stably expressed single gene. The best combination of two genes, let-7a and RNU48, further reduced the NormFinder stability value to 0.221. Two out of the seven genes showed geNorm stability measures (M) below the default limit of 1.5 and the programme identified let-7a and miR-16 as the most stable pair of ECs (M = 0.978).</p>", "<title>Effect of EC on Relative Quantity of <italic>miR-30*</italic></title>", "<p>To assess the effect of EC on relative quantitation of the target gene, miR-30*, this miRNA was normalised using each of the candidate EC genes in turn. Depending on the normaliser, miR-30* expression was either significantly different between tissue groups (P &lt; 0.05) or no differences were detected. When normalised using miR-26b, ranked in the top four mosts Table ##TAB##2##3## andidates by both geNorm and NormFinder (Table ##TAB##1##2##), no differences were detected between tissue groups. Normalisation to all other individual ECs detected significant differences between the BM and VBM tissue groups. Only normalisation with RNU48 detected a significant difference in miR-30* expression between the MF and VBM tissue groups. GeNorm selected let-7a and miR-16 as the most stable EC pair and let-7a was selected as the single most stable EC gene using NormFinder. Thus the effect of using either let-7a as a single gene or using the recommended EC pair, let-7a and miR-16, on miR-30* expression was assessed. Significant differences in miR-30* expression were detected between tissue groups using either the one EC (P = 0.007) or the two EC (P = 0.01) approach, however the BM and MF tissue groups were found to be significantly different using the EC pair, let-7a and miR-16 but this was not detected when let-7a was used as the sole EC gene. The lowest pairwise variation value (V) was generated using the top five genes from the panel, indicating that this would be the most stable EC gene set to use. MiR-30* was normalised using the top two EC genes and using the top five EC genes to assess what effect this would have on miR-30* relative quantification. Significant differences in miR-30* expression were detected between the tissue groups using either the top two ECs (P = 0.01) or the top five ECs (P = 0.002, Fig. ##FIG##1##2B##), however the <italic>post-hoc </italic>analyses varied slightly in that the two gene normalisation detected a difference between the BEN and MF tissue groups not detected by the five EC gene approach. Conversely, the 5 gene approach identified a significant difference in miR-30* expression between the MF and VBM tissues, not detected when using the most stable pair. Both normalisation strategies did detect significant differences between the BM vs MF groups, the BM vs VBM groups and the BEN vs VBM groups.</p>" ]

[ "<title>Discussion</title>", "<p>In recent years, miRNAs have emerged as key players in tightly-controlled biological processes such as proliferation [##REF##15944709##6##], apoptosis [##REF##16166262##7##,##REF##16024602##42##] and tumour invasion [##REF##17898713##13##]. MiRNAs, first implicated in malignancy in 2002 [##REF##12434020##43##], are known to be deregulated and/or mutated in numerous cancers including breast cancer [##REF##18193036##44##] and there is evidence to suggest that miRNA expression profiles may be more accurate in classifying breast cancer subtypes than mRNA expression profiles [##REF##15944708##16##].</p>", "<p>Adaptation of traditional RNA isolation and reverse transcription protocols has facilitated the application of RQ-PCR to the study of miRNA expression. Mature miRNAs were amplified and quantified using PCR for the first time in 2005 [##REF##16314309##18##,##REF##16244135##45##] and recent developments include a 220-plex RQ-PCR allowing the analysis of multiple miRNAs from single cells [##REF##16434699##19##]. The high sensitivity of RQ-PCR demands appropriate normalisation to correct for non-biological variation and the use of EC genes remains the most commonly used method. The issue of carefully selecting and validating EC genes has already been discussed for a number of experimental systems in the context of RQ-PCR for mRNA [##REF##18042273##21##,##REF##11013345##29##,##REF##12413463##46##] however, this issue has not yet been addressed in relation to the relative quantitation of miRNA in breast tissue. This issue is particularly pertinent to the area of miRNA studies utilising RQ-PCR since it is still common practice to synthesise a gene-specific cDNA for each sample, using miRNA-specific primers, thereby introducing additional non-biological variation not accrued during the synthesis of cDNA from mRNA when using random or oligo-dT primers.</p>", "<p>This paper describes the first systematic assessment of candidate ECs for the normalisation of miRNA RQ-PCR data in breast cancer. In the rapidly evolving field of miRNA reasearch, consensus has not yet been reached on how best to tackle this issue. Numerous RNA species, including rRNAs, tRNAs, snRNAs and miRNAs have previously been used as ECs in miRNA RQ-PCR studies of the breast. Concern has been expressed regarding the use of rRNAs in normalisation strategies as they can be expressed at much greater levels than the target RNA making it very difficult to quantify a rRNA and a rare transcript in the same RNA dilution [##REF##16060372##22##,##REF##11013345##29##,##REF##12184808##30##]. Moreover, a role for rRNA in apoptosis [##REF##10788523##31##] and cancer [##REF##16243810##47##] has been reported. A proportion of snRNAs and snoRNAs may exhibit tissue-specific and developmental regulation [##REF##11726556##48##] emphasising the need for validation of commercially-available control assays. U6 snRNA (RNU6B), commonly used to normalise miRNA RQ-PCR data [##REF##15172979##49##,##REF##17346547##50##] was found to be less stably expressed than let-7a and miR-16, the EC pair proposed by this study [##REF##18375788##51##].</p>", "<p>This is the first report detailing the percentage of miRNA retrieved in small RNA-enriched fractions of primary breast tissue. RNAs detected using the Agilent small RNA assay include miRNAs, smaller ribosomal RNAs such as the 5.85S (154 nt) and 5S (117 nt) subunits, transfer RNAs (73–93 nt) and snoRNAs (60–300 nt). Perhaps unsurprisingly, we found the proportion of miRNA in the small RNA sample ranged from 12–98%. The varying miRNA yields were well distributed amongst the tissue groups. The variation in ratio was not dependent on the type of tissue, on the RNA extraction or on the total yield of the RNA. In this laboratory we also found a much lower proportion of miRNA, ranging from 1–5%, in small RNA extracted from commonly used breast cancer cell lines such as MCF-7, SK-BR-3, T47D and ZR-75-1 (data not shown). A suitable EC gene will have to reflect such changes in the global miRNA population. The variation in miRNA yields and ratios may reflect genomic alterations, common in cancer (reviewed in [##REF##12637148##52##]. It has been shown previously that miRNA frequently map to such regions of instability [##REF##14973191##53##]. This finding raises concerns over how much of the small RNA used for cDNA reactions and other applications is actually the RNA species of interest, and this is especially relevant in studies employing non-miRNA ECs.</p>", "<p>Normfinder and geNorm were used to identify suitable ECs for the relative quantitation of miRNA in fresh-frozen primary breast tissue. There was no effect of tissue group on scaled EC expression (P &gt; 0.05, Fig. ##FIG##0##1##). As previously stated [##REF##18042273##21##] this is an important validation prior to use of geNorm and NormFinder as these models assume candidates are not differentially expressed between experimental groups. The absence of a significant difference in EC expression between groups does not necessarily equate to equivalent expression. Equivalence of expression was assessed using the equivalence test [##REF##15519565##41##]. Equivalent expression between the independent tumour and normal breast tissues was confirmed for all ECs using a fold change cut-off of 3. Equivalent expression between the malignant and benign tumour groups was also assessed and was confirmed for all ECs with the exception of Z30 using the same cut-off. Using the benign, MF, BM and VBM subgroups, NormFinder calculated the intra- and intergroup variations and identified let-7a as the single most stable EC with a stability value of 0.312. However, the use of more than one EC is believed to increase the accuracy of quantitation compared to the use of a single EC [##REF##12184808##30##,##REF##15289330##54##,##REF##15331581##55##] and use of let-7a alone would therefore not be recommended. The EC gene pair, let-7a and RNU48 had an improved NormFinder stability value of 0.221.</p>", "<p>GeNorm generates a gene-stability measure (M) which may be defined as the average pairwise variation (V) for one candidate EC gene compared to all other candidate EC genes. Stepwise exclusion of the gene with the highest M value results in recalculation of M values for the remaining genes and ultimately, the identification of the most stable pair [##REF##12184808##30##]. The wide range in M values depicts the high variability detected in candidate EC gene stability (Table ##TAB##1##2##). The differences in miR-30* expression detected between the tissue groups varied greatly depending on which single EC was used for normalisation. For example, in the BEN and BM breast tissues, the expression of miR-30* could be made to appear up- or down-regulated relative to normal breast tissue depending on the EC gene used (Fig. ##FIG##1##2A##). These results draw particular attention to the potential effect of EC choice on the outcome of a study and demonstrates the need for validation of candidate ECs to produce reliable expression data. In geNorm, a normalisation factor (NF) is generated for each sample using the geometric average of the expression of the most stable EC genes. The pairwise variation value, V is the variation between two sequential NFs (V_n/n+1, where n = the number of ECs used). The recommended pairwise variation of 0.15 is a guideline value and is not intended as an absolute cut-off. This guideline value may not always be achievable [##REF##16324220##56##] but should be considered, particularly if small expression differences are to be measured. The lowest pairwise variation value was achieved when the top 5 candidate genes were used as ECs (0.220, Fig. ##FIG##2##3B##). Let-7a and miR-16 were identified as the most stable pair of EC genes using geNorm. Significant differences in miR-30* expression were detected between the tissue groups using either the top two ECs (P = 0.01) or the top five ECs (P = 0.002, Fig. ##FIG##1##2B##). The <italic>post-hoc </italic>analyses revealed both normalisation approaches detected significant differences between the BM vs MF groups, the BM vs VBM groups and the BEN vs VBM groups but each approach detected an additional intergroup difference not detected by the other approach. The number of genes to use in a normalisation strategy is in most cases, a trade off between required resolution and practicality and for most purposes the EC gene combination let-7a and miR-16 should suffice. Both genes had the lowest stability values, as determined by geNorm and NormFinder (Table ##TAB##1##2##).</p>", "<p>A tumour suppressor role for let-7a in lung tissues seems likely due to its widespread downregulation in tumour versus normal lung tissues as well as the identification of an oncogenic target, RAS, in this tissue [##REF##15766527##57##]. However, it is unclear whether let-7a is implicated in breast cancer since the results of recent studies have been equivocal [##REF##15766527##57##]. Whilst deletion of the <italic>miR-16 </italic>gene has been implicated in the development of chronic lymphocytic leukemia [##REF##16166262##7##], a specific role for this miRNA in breast cancer has not been identified. From a panel of 345 miRNAs, miR-16 was selected in the top 15 most stably-expressed miRNAs across 40 normal human tissue types [##REF##17565689##58##]. A microarray study [##REF##18375788##51##] which looked at the expression of 287 miRNAs in various normal and tumour tissues, not including breast tissue, selected a panel of suitable EC genes based on a number of criteria including high and consistent expression of the miRNA across the tissues. Depending on the tissue sample set, both let-7a and miR-16 were ranked in the top 10–15 most stably-expressed miRNAs, supporting the findings of the present study.</p>", "<p>The tissues used in this study are clinically and pathologically diverse (see Table ##TAB##2##3##) making this study of interest to a broad spectrum of the breast cancer research community. Recent findings would suggest that, unlike mRNAs, the miRNA fraction present in FFPE tissues is relatively unaffected by the fixation process and that miRNAs extracted from these tissues may be accurately profiled using RQ-PCR [##REF##17980029##27##]. Thus, the ECs identified in this study may also prove useful for miRNA RQ-PCR analysis of FFPE breast tissues.</p>" ]

[ "<title>Conclusion</title>", "<p>MiRNA expression studies utilising RQ-PCR should begin with the careful selection of appropriate ECs for normalisation to ensure accurate quantitation of this very exciting class of molecules. This study indicates an appropriate strategy to validate ECs for any miRNA RQ-PCR study and has identified a reliable two-gene normaliser for use in breast cancer studies. We recommend the combined use of Let-7a and miR-16 in this context.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>The discovery of microRNAs (miRNAs) added an extra level of intricacy to the already complex system regulating gene expression. These single-stranded RNA molecules, 18–25 nucleotides in length, negatively regulate gene expression through translational inhibition or mRNA cleavage. The discovery that aberrant expression of specific miRNAs contributes to human disease has fueled much interest in profiling the expression of these molecules. Real-time quantitative PCR (RQ-PCR) is a sensitive and reproducible gene expression quantitation technique which is now being used to profile miRNA expression in cells and tissues. To correct for systematic variables such as amount of starting template, RNA quality and enzymatic efficiencies, RQ-PCR data is commonly normalised to an endogenous control (EC) gene, which ideally, is stably-expressed across the test sample set. A universal endogenous control suitable for every tissue type, treatment and disease stage has not been identified and is unlikely to exist, so, to avoid introducing further error in the quantification of expression data it is necessary that candidate ECs be validated in the samples of interest. While ECs have been validated for quantification of mRNA expression in various experimental settings, to date there is no report of the validation of miRNA ECs for expression profiling in breast tissue. In this study, the expression of five miRNA genes (<italic>let-7a, miR-10b, miR-16</italic>, <italic>miR-21 </italic>and <italic>miR-26b</italic>) and three small nucleolar RNA genes (<italic>RNU19, RNU48 </italic>and <italic>Z30</italic>) was examined across malignant, benign and normal breast tissues to determine the most appropriate normalisation strategy. This is the first study to identify reliable ECs for analysis of miRNA by RQ-PCR in human breast tissue.</p>" ]

[ "<title>Authors' contributions</title>", "<p>PAD performed the experiments, was responsible for data analyses and drafted the manuscript. REM contributed throughout the experiment, critically reviewed the manuscript and participated in data analysis. AL contributed to RQ-PCR analysis and preliminary data analysis. MJK participated clinically in sample provision and in critical examination of the manuscript. NM conceived, designed and supervised experimental work and manuscript editing. All authors read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge the National Breast Cancer Research Institute (NBCRI) for their continued financial support. AJL is supported by a Clinician Scientist fellowship award from Molecular Medicine Ireland. We gratefully acknowledge Ms. Emer Hennessy for continued technical assistance and for curation of the Department of Surgery, BioBank, NUIG. We also wish to thank Ms. Catherine Curran for collation of clinical and histological data.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Relative quantity of each candidate EC</bold>. <bold>(A) </bold>Quantity of the candidate endogenous control genes let-7a, miR-10b, miR-21, miR-16, miR-26b, RNU48 and Z30, relative to calibrator (normal tissues) and corrected for amplification efficiency (Q. rel = E^-ΔCt), in the benign (BEN, clear ), bone metastases (BM, dark), metastases free (MF, dashed) and visceral and bone metastases (VBM, shaded) groups. The boxes show the interquartile range and median, whiskers indicate the range and outliers are depicted with the symbol (*). No difference was found within gene between the tissue subgroups (P&gt;0.05) thus establishing the validity of EC comparison. <bold>(B) </bold>Variation associated with candidate endogenous control genes. Relative quantity of each gene is relative to calibrator (normal tissues) and corrected for amplification efficiency (Q.rel = E^-ΔCt). There was no significant difference in variance associated with relative gene expression (P &gt; 0.05).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>GeNorm analysis of candidate ECs</bold>. <bold>(A) </bold>Average expression stability of the EC candidates as calculated using GeNorm. A stability value (M) was calculated for each candidate EC. The least stable gene with the highest M value was automatically excluded and M values recalculated for the remaining ECs, ultimately resulting in a stability value for the two most stable ECs. <bold>(B) </bold>Determination of the optimal number of ECs for normalisation. The V value defines the pairwise variation between two sequential normalisation factors. GeNorm indicated optimal normalisation of gene expression could be achieved using the top five most stable ECs.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Boxplot of miR-30* relative quantities in benign (BEN, clear), bone metastases (BM, dark), metastases free (MF, dashed) and visceral and bone metastases (VBM, shaded) tissues using different normalisation strategies. (Q. rel = E ^-ΔΔCt). The boxes represent the interquartile range. The line drawn through the boxes represents the median. Whiskers extend to the highest and lowest values in the data set. <bold>(A) </bold>miR-30* normalised using each EC individually. MiR-30* expression was significantly different between the tissue subgroups (P &lt; 0.05) except when using miR-26b as a single EC. <bold>(B) </bold>miR-30* normalised using geNorm's top two recommended ECs (2 × ECs = let-7a and miR-16) and geNorm's top five recommended ECs (5 × ECs = let-7a, miR-16, miR-26b, miR-21 and RNU48). miR-30* was differentially expressed between groups using either the top 2 or the top 5 most stable ECs (p &lt; 0.05). A significant difference was detected between the MF and VBM groups using the 5 EC gene approach, this was not detected when using the top 2 ECs for normalization.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Results of Agilent Bioanalyser Small RNA assay</bold>. <bold>(A) </bold>Virtual gel-numbered samples refer to malignant breast tissues (as per Table 2), L = Ladder, N = Normal breast tissue, BEN = benign breast tissue. The lower marker is visible at 4 nt. Samples with a large percentage (&gt; 75%) of miRNA (10–35 nt) include the samples BEN1, 19 and 25, the latter two belonging to the bone metastases (BM) patient group. The high intensity band in samples 9, 15, 17, 20, BEN1 and BEN2 between 60 and 80 nt represents high recovery of tRNA (73–93 nt). In general, these samples had a lower percentage of miRNA. <bold>(B) </bold>Electropherogram. Numbered samples refer to malignant breast tissues (as per Table 2), BEN = benign breast tissue.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>miRNA yield from small RNA-enriched fractions according to tissue group</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Tissue group\\Percentage of miRNA in small RNA-enriched fraction</td><td align=\"center\"><bold>1–25%</bold></td><td align=\"center\"><bold>26–50%</bold></td><td align=\"center\"><bold>51–75%</bold></td><td align=\"center\"><bold>76–100%</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>MF</bold></td><td align=\"center\">3</td><td align=\"center\">4</td><td align=\"center\">3</td><td align=\"center\">3</td></tr><tr><td align=\"left\"><bold>BM</bold></td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">3</td></tr><tr><td align=\"left\"><bold>VBM</bold></td><td align=\"center\">1</td><td align=\"center\">5</td><td align=\"center\">0</td><td align=\"center\">0</td></tr><tr><td align=\"left\"><bold>BEN</bold></td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">0</td></tr><tr><td align=\"left\"><bold>Normal</bold></td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">4</td><td align=\"center\">0</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold><italic>Total</italic></bold></td><td align=\"center\">6</td><td align=\"center\">13</td><td align=\"center\">11</td><td align=\"center\">6</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Ranking of candidate EC gene and choice of best pair of EC genes by NormFinder and geNorm programmes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Rank</bold></td><td align=\"center\" colspan=\"2\"><bold>NormFinder^a</bold></td><td align=\"center\" colspan=\"2\"><bold>geNorm^b</bold></td></tr><tr><td/><td colspan=\"4\"><hr/></td></tr><tr><td/><td align=\"left\"><bold>Gene</bold></td><td align=\"left\"><bold>Stability</bold></td><td align=\"left\"><bold>Gene</bold></td><td align=\"left\"><bold>Stability (M)</bold></td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">let-7a</td><td align=\"left\">0.312</td><td align=\"left\">let-7a</td><td align=\"left\">1.427</td></tr><tr><td align=\"left\">2</td><td align=\"left\">miR-16</td><td align=\"left\">0.379</td><td align=\"left\">miR-16</td><td align=\"left\">1.473</td></tr><tr><td align=\"left\">3</td><td align=\"left\">RNU48</td><td align=\"left\">0.401</td><td align=\"left\">miR-26b</td><td align=\"left\">1.538</td></tr><tr><td align=\"left\">4</td><td align=\"left\">miR-26b</td><td align=\"left\">0.425</td><td align=\"left\">RNU48</td><td align=\"left\">1.567</td></tr><tr><td align=\"left\">5</td><td align=\"left\">miR-10b</td><td align=\"left\">0.435</td><td align=\"left\">miR-10b</td><td align=\"left\">1.667</td></tr><tr><td align=\"left\">6</td><td align=\"left\">miR-21</td><td align=\"left\">0.601</td><td align=\"left\">miR-21</td><td align=\"left\">1.692</td></tr><tr><td align=\"left\">7</td><td align=\"left\">Z30</td><td align=\"left\">0.624</td><td align=\"left\">Z30</td><td align=\"left\">2.272</td></tr><tr><td align=\"left\">Best combination</td><td align=\"left\">let-7a/RNU48</td><td align=\"left\">0.221</td><td align=\"left\">let-7a/miR-16</td><td align=\"left\">0.978</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Clinical and pathological data on malignant tumour samples where available</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><italic>Patient</italic><break/><italic>Number</italic></td><td align=\"left\"><italic>Patient</italic><break/><italic>Age</italic></td><td align=\"left\"><italic>Menopausal</italic><break/><italic>status</italic></td><td align=\"left\"><italic>Size</italic><break/><italic>(mm)</italic></td><td align=\"left\"><italic>T</italic></td><td align=\"left\"><italic>N</italic></td><td align=\"left\"><italic>M</italic></td><td align=\"left\"><italic>Grade</italic></td><td align=\"left\"><italic>ER</italic></td><td align=\"left\"><italic>PR</italic></td><td align=\"left\"><italic>HER2/</italic><break/><italic>neu</italic></td><td align=\"left\"><italic>Subtype</italic></td><td align=\"left\"><italic>Metastatic</italic><break/><italic>grouping</italic></td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">41</td><td align=\"left\">Pre</td><td align=\"left\">25</td><td align=\"left\">2</td><td align=\"left\">0</td><td align=\"left\">0</td><td/><td align=\"left\">P</td><td/><td/><td align=\"left\">Luminal A/B</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">2</td><td align=\"left\">50</td><td align=\"left\">Pre</td><td align=\"left\">35</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">3</td><td align=\"left\">38</td><td align=\"left\">Post</td><td align=\"left\">35</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">4</td><td align=\"left\">43</td><td align=\"left\">Pre</td><td align=\"left\">10</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">5</td><td align=\"left\">49</td><td align=\"left\">Post</td><td align=\"left\">20</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">6</td><td align=\"left\">78</td><td align=\"left\">Post</td><td align=\"left\">20</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">7</td><td align=\"left\">51</td><td align=\"left\">Post</td><td align=\"left\">18</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td/><td align=\"left\">N</td><td/><td align=\"left\">N</td><td align=\"left\">LuminalA/Basal</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">8</td><td align=\"left\">75</td><td align=\"left\">Post</td><td align=\"left\">36</td><td align=\"left\">4</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td/><td/><td align=\"left\">Luminal A/B</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">9</td><td align=\"left\">59</td><td align=\"left\">Post</td><td align=\"left\">50</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">10</td><td align=\"left\">53</td><td align=\"left\">Post</td><td align=\"left\">85</td><td align=\"left\">3</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">Basal</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">11</td><td align=\"left\">43</td><td align=\"left\">Pre</td><td align=\"left\">50</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">12</td><td align=\"left\">69</td><td align=\"left\">Post</td><td align=\"left\">35</td><td align=\"left\">4</td><td align=\"left\">2</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">VBM</td></tr><tr><td align=\"left\">13</td><td align=\"left\">66</td><td align=\"left\">Post</td><td align=\"left\">12</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">14</td><td align=\"left\">58</td><td align=\"left\">Post</td><td align=\"left\">20</td><td align=\"left\">4</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">15</td><td align=\"left\">58</td><td align=\"left\">Post</td><td align=\"left\">15</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">VBM</td></tr><tr><td align=\"left\">16</td><td align=\"left\">70</td><td align=\"left\">Post</td><td align=\"left\">20</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">MF</td></tr><tr><td align=\"left\">17</td><td align=\"left\">52</td><td align=\"left\">Post</td><td align=\"left\">25</td><td align=\"left\">4</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">Luminal B</td><td align=\"left\">VBM</td></tr><tr><td align=\"left\">18</td><td align=\"left\">78</td><td align=\"left\">Post</td><td/><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">0</td><td/><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">19</td><td align=\"left\">61</td><td align=\"left\">Post</td><td align=\"left\">33</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">Luminal B</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">20</td><td align=\"left\">48</td><td align=\"left\">Pre</td><td align=\"left\">30</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">VBM</td></tr><tr><td align=\"left\">21</td><td align=\"left\">50</td><td align=\"left\">Pre</td><td align=\"left\">30</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">N</td><td align=\"left\">N</td><td/><td align=\"left\">Basal/HER-2</td><td align=\"left\">VBM</td></tr><tr><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\">22</td><td align=\"left\">51</td><td align=\"left\">Post</td><td align=\"left\">20</td><td align=\"left\">1</td><td/><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">P</td><td/><td/><td align=\"left\">Luminal A/B</td><td align=\"left\">VBM</td></tr><tr><td align=\"left\">23</td><td align=\"left\">69</td><td align=\"left\">Post</td><td align=\"left\">40</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">24</td><td align=\"left\">58</td><td align=\"left\">Post</td><td align=\"left\">21</td><td align=\"left\">4</td><td/><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">N</td><td align=\"left\">N</td><td align=\"left\">P</td><td align=\"left\">HER-2</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">25</td><td align=\"left\">61</td><td align=\"left\">Post</td><td align=\"left\">35</td><td align=\"left\">2</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">P</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">Luminal A</td><td align=\"left\">BM</td></tr><tr><td align=\"left\">26</td><td align=\"left\">64</td><td align=\"left\">Post</td><td align=\"left\">15</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">P</td><td align=\"left\">N</td><td align=\"left\">P</td><td align=\"left\">Luminal B</td><td align=\"left\">BM</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Details of candidate endogenous control (EC) genes and their PCR amplification efficiencies</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Name</bold></td><td align=\"left\"><bold>Mature</bold><break/><bold>length</bold><break/><bold>(nt)</bold></td><td align=\"left\"><bold>RNA</bold><break/><bold>species</bold></td><td align=\"left\"><bold>Accession</bold><break/><bold>number</bold></td><td align=\"left\"><bold>Function</bold></td><td align=\"left\"><bold>Reference</bold></td><td align=\"left\"><bold>PCR</bold><break/><bold>Amplification</bold><break/><bold>efficiency (%)</bold></td></tr></thead><tbody><tr><td align=\"left\">let-7a</td><td align=\"left\">22</td><td align=\"left\">miRNA</td><td align=\"left\">MI0000060*</td><td align=\"left\">Negatively regulates RAS oncogene</td><td align=\"left\">[##REF##15766527##57##]</td><td align=\"left\">96.3</td></tr><tr><td align=\"left\">miR-10b</td><td align=\"left\">22</td><td align=\"left\">miRNA</td><td align=\"left\">MI0000267 *</td><td align=\"left\">No functionally-verified targets</td><td/><td align=\"left\">104.1</td></tr><tr><td align=\"left\">miR-16</td><td align=\"left\">22</td><td align=\"left\">miRNA</td><td align=\"left\">MI0000070 *</td><td align=\"left\">Negatively regulates B-cell lymphoma mRNA in chronic lymphocytic leukaemia patients</td><td align=\"left\">[##REF##16166262##7##]</td><td align=\"left\">104.3</td></tr><tr><td align=\"left\">miR-21</td><td align=\"left\">22</td><td align=\"left\">miRNA</td><td align=\"left\">MI0000077 *</td><td align=\"left\">Antiapoptotic, negatively regulates apoptosis-related genes</td><td align=\"left\">[##REF##16024602##42##]</td><td align=\"left\">96.8</td></tr><tr><td align=\"left\">miR-26b</td><td align=\"left\">22</td><td align=\"left\">miRNA</td><td align=\"left\">MI0000084 *</td><td align=\"left\">No functionally-verified targets</td><td/><td align=\"left\">98.1</td></tr><tr><td align=\"left\">RNU19</td><td align=\"left\">198</td><td align=\"left\">snoRNA</td><td align=\"left\">X94290 **</td><td align=\"left\">May be involved in pre-rRNA processing</td><td align=\"left\">[##REF##9630250##59##, ####REF##9182768##60##, ##REF##8657112##61####8657112##61##]</td><td align=\"left\">99.2</td></tr><tr><td align=\"left\">RNU48</td><td align=\"left\">63</td><td align=\"left\">snoRNA</td><td align=\"left\">NR_002745 **</td><td align=\"left\">Guides the 2'O-ribose methylation of 28S rRNA</td><td align=\"left\">[##REF##12215523##62##]</td><td align=\"left\">108.9</td></tr><tr><td align=\"left\">Z30</td><td align=\"left\">97</td><td align=\"left\">snoRNA</td><td align=\"left\">AJ007733 **</td><td align=\"left\">Guides the methylation of the Am47 residue in U6 snRNA</td><td align=\"left\">[##REF##11842100##63##]</td><td align=\"left\">104.1</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Extracted RNA, enriched for small RNA, was analysed using the Agilent Small RNA Assay. The percentage of miRNA (10–35 nt) in each small RNA-enriched sample (&lt; 200 nt) was determined.</p><p><bold>Abbreviations: </bold>MF = metastases free, BM = bone metastases, VBM = visceral and bone metstases, BEN = benign.</p></table-wrap-foot>", "<table-wrap-foot><p>Greater expression stability is indicated by a lower stability value (M). Results for seven EC candidates are given as RNU19 was excluded from analysis due to its low expression in the breast tissues. For NormFinder analysis, breast tissue samples were grouped into metastases-free (MF), bone metastases (BM), visceral and bone metastases (VBM) and benign (BEN). The stability is calculated from the intra- and inter-group variation and the best combination of EC genes is also given. ^bGeNorm stability is based on an estimate of the pairwise variation (M).</p></table-wrap-foot>", "<table-wrap-foot><p>T, N and M refer to the primary tumor size, nodal status and distant metastases status according to the TNM breast cancer classification system. ER: = oestrogen receptor status; PR: = progesterone receptor status and HER2/<italic>neu </italic>= v-erb-b2 erythroblastic leukaemia viral oncogene status. Where data was not available for ER, PR and HER-2, possible subtype based on available hormone receptor status is given. Metastatic groupings refer to patient status five years after presentation; patients were either metastases-free (MF), had developed bone metastases (BM) or had developed visceral and bone metastases (VBM).</p></table-wrap-foot>", "<table-wrap-foot><p>*mirBase database accession number ** Entrez gene ID</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2199-9-76-1\"/>", "<graphic xlink:href=\"1471-2199-9-76-2\"/>", "<graphic xlink:href=\"1471-2199-9-76-3\"/>", "<graphic xlink:href=\"1471-2199-9-76-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>RNA polymerase III (RNA pol III) is the largest of the eukaryotic DNA dependent RNA polymerases and transcribes many of the genes involved in mRNA processing (U6 snRNA) and protein translation (tRNA), thereby regulating the growth rate of a cell [##REF##12381659##1##]. RNA pol III activity has been demonstrated to be deregulated in a variety of cancers, irrespective of tissue type (reviewed in [##REF##15094770##2##, ####REF##14687785##3##, ##REF##15688068##4####15688068##4##]). Like all eukaryotic RNA polymerases, RNA pol III cannot recognize target promoter elements directly. Proper initiation by RNA pol III requires the transcription factor TFIIIB [##REF##12381659##1##,##REF##17073756##5##]. In higher eukaryotes, two forms of TFIIIB have been identified thus far [##REF##10921893##6##, ####REF##11040218##7##, ##REF##11121026##8####11121026##8##]. The form of TFIIIB required for proper initiation from gene internal RNA pol III promoters is comprised of TBP, Bdp1, and Brf1 [##REF##8943358##9##,##REF##7624363##10##]. Proper initiation from gene external RNA pol III promoters requires TBP, Bdp1, and Brf2 [##REF##10921893##6##, ####REF##11040218##7##, ##REF##11121026##8####11121026##8##].</p>", "<p>TFIIIB is a molecular target of regulation by a wide variety of tumor suppressors, including p53 [##REF##12165852##11##, ####REF##12082526##12##, ##REF##12773395##13##, ##REF##9606193##14##, ##REF##8943363##15####8943363##15##], ARF [##REF##17439968##16##], PTEN [##REF##18391023##17##], RB [##REF##12734418##18##,##REF##9169441##19##], and the RB-related pocket proteins [##REF##10330166##20##], as well as the oncogene c-myc [##REF##12734418##18##,##REF##12529648##21##] and the mitogen-activated protein kinase ERK [##REF##12743036##22##]. RNA pol III and TFIIIB activity have also been demonstrated to be negatively regulated by other proteins, such as Maf1 [##REF##18377933##23##, ####REF##17499043##24##, ##REF##17205138##25##, ##REF##17505538##26####17505538##26##]. Maf1 is a common component of at least three signaling pathways leading to repression of RNA pol III transcription: the DNA damage signaling pathway, the secretory defect signaling pathway, and the target of rapamycin (TOR) signaling pathway (reviewed in [##REF##17027482##27##,##REF##17174096##28##]). More recently, RNA pol III transcription has also been demonstrated to be negatively regulated by the chemopreventative agent EGCG [##REF##17624304##29##].</p>", "<p>Taken together, these data suggest that deregulation of TFIIIB-mediated transcription may be an important step in tumor development. Thus, we hypothesized that the observed specific elevation of RNA pol III transcription products in cancer (reviewed in [##REF##15094770##2##,##REF##15688068##4##,##REF##9499432##30##]) may be a result of alterations in expression of the RNA pol III initiation factor TFIIIB. Here, we report that the TFIIIB subunits Brf1 and Brf2 are differentially expressed in a variety of cancer cell lines. We further demonstrate that the Brf1 and Brf2 promoters differ in activity in cancer cell lines, and VAI transcription is universally elevated, as compared to U6 snRNA transcription, in breast, prostate and cancer cell lines.</p>" ]

[ "<title>Methods</title>", "<title>Cell Lines and Culture</title>", "<p>C33A, Caski, HeLa, RKO, SiHa, DU145, ZR75-1, MCF-7, MDA-MB-453, MDA-MB-231, and MDA-MB-468 cells were obtained from the American Type Culture Collection (Rockville, MD). Cells were cultured in DMEM or RPMI supplemented with FCS (5% v/v), nonessential amino acids (100 mM), L-glutamine (5 mM), streptomycin (100 μg/ml), and penicillin (100 units/ml; all from BioWhittaker, Walkersville, MD). Cells were grown at 37°C in a humidified atmosphere of 95% air and 5% CO₂.</p>", "<title>Total RNA Isolation</title>", "<p>Total RNA was extracted from the subconfluent 100 mm dishes of the cancer cell lines indicated using TRIzol Reagent (Life Technologies, Inc.), according to the manufacturer's protocol. The RNA was DNase (Ambion) treated and ethanol precipitated prior to cDNA synthesis. Isolated RNA was electrophoresed through 1.0% agarose-formaldehyde gels to verify the quality of the RNA, and RNA concentrations were determined from absorbance measurements at 260 and 280 nm.</p>", "<title>Semiquantitative RT-PCR Analysis</title>", "<p>Aliquots of total cellular RNA (1.0 μg) were subjected to first-strand cDNA synthesis using Superscript II reverse transcriptase (Life Technologies, Inc.), and the cDNA was diluted five times with water and 1μl of the diluted cDNA was used for each PCR reaction. PCR amplifications were performed using a Techgene TC312 DNA thermal cycler. The PCR primer sets used in this study are shown in Table ##TAB##0##1##. The PCR reaction conditions were individually optimized for each gene product tested in this study. For each gene product, the cycle number was adjusted so that the reactions fell within the linear range of product amplification. The β-actin gene was used as a loading control. PCR products were analyzed by electrophoresis through 1.2% agarose gels containing 0.1 mg/ml of ethidium bromide, and the gels were photographed using a UVP BioDocit system.</p>", "<title>Cloning of the human Brf1 promoter</title>", "<p>Gene2Promoter analysis software program of Genomatix Suite <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.genomatix.de\"/> was utilized to identify a putative promoter for human Brf1. Putative transcription factor sites within the human Brf1 promoter were identified using MatInspector [##REF##15860560##53##] of the Genomatix Suite. PCR primers flanking the Brf1 promoter sequence were designed with KpnI and BglII restriction sites and used to PCR amplify the promoter sequence from human genomic DNA and cloned into the KpnI and BglII sites of the promoterless pGL3 Basic vector (Promega).</p>", "<title>Luciferase Assays</title>", "<p>Increasing concentrations of Brf1-pGL3 and Brf2-pGL3 [##REF##17624304##29##] were transiently transfected using TransIT-LT1 (Mirus), as per the manufacturer's protocol in HeLa, MCF-7 and DU145 cells. pGL3-VAI and pGL3-U6 luciferase assays were performed as previously described [##REF##17505538##26##]. In brief, the human U6 and VAI promoters were cloned into the promoterless pGL3 vector, generating pGL3-VAI and pGL3-U6. The dual-luciferase reporter assay system (Promega) was used to monitor luciferase activity in HeLa, DU 145 and MCF-7 cells as per the manufacturer's recommendations, using a Sirius single tube luminometer (Berthold). A Renilla luciferase vector (Promega) was co-transfected in all transfections to monitor transfection efficiency. Luciferase experiments were performed in triplicate or quadruplicate, repeated three independent times, and the data presented are representative experiments. All luciferase results are reported as relative light units (RLU): the average of the Photinus pyralis firefly activity observed divided by the average of the activity recorded from Renilla luciferase vector and graphed using GraphpadPrism3.03 (San Diego California USA).</p>", "<title>Western Blots</title>", "<p>HeLa, MCF-7 and DU145 cells were harvested and nuclear extract was prepared as previously described [##REF##11040218##7##]. Nuclear extract (25 μg) was separated on 10% SDS-PAGE gels, semi dry transferred to nitrocellulose, blocked 1 hour room temperature using nonfat milk in Phosphate Buffered Saline (PBS), pH 7.5. The blot(s) were incubated in primary antibodies: anti-actin (Santa Cruz), anti-Brf1 (CS407) or anti-Brf2 (CS1228) polyclonal antibodies, overnight at 4 degrees. The blot(s) were washed in 1× PBS and then incubated in secondary antibody at room temperature, then developed using ECF (for anti-rabbit-AP) or TMB substrate (Promega) (for anti-goat-HRP, Amersham) and photodocumented using a BioDocit system (UVP).</p>" ]

[ "<title>Results and Discussion</title>", "<title>The TFIIIB subunits Brf1 and Brf2 are differentially expressed in cancer cell lines</title>", "<p>Accurate initiation of transcription by RNA pol III requires TFIIIB. Two of the TFIIIB subunits, Brf1 and Brf2, are structurally related and are required for accurate transcription by RNA pol III [##REF##12381659##1##,##REF##11040218##7##]. Brf1 is required for transcription from gene internal promoters (tRNA), whereas Brf2 is required for transcription from gene external RNA pol III promoters (U6 snRNA). Hence, we sought to determine if Brf1 and Brf2 expression is elevated in a variety of cancer cell lines, contributing to the previously observed increase of RNA pol III transcripts in cancer. We obtained a variety of cervical, colorectal, breast, and prostate cancer cell lines from the ATCC, isolated total RNA from asynchronous cells, and by RT-PCR determined the expression levels of Brf1 and Brf2 using gene specific primers (Table ##TAB##0##1##). Primers for β-actin (Table ##TAB##0##1##) were used as a control, Figure ##FIG##0##1A##. Strikingly, the TFIIIB subunits Brf1 and Brf2 are differentially expressed in breast, cervical and prostate cancer cell lines (Figure ##FIG##0##1B## and ##FIG##0##1C##). We then speculated that the observed differences in Brf1 and Brf2 expression is a consequence of alterations in mRNA stability or may be a result of differential activity of the Brf1 and Brf2 promoters.</p>", "<title>The Brf1 and Brf2 promoters differ in activity in breast, cervical and prostate cancer cell lines</title>", "<p>To determine if the observed differences in Brf1 and Brf2 expression is a result of differences in transcription initiation, we set out to directly compare the activities of the Brf1 and Brf2 promoters. We have previously cloned the human Brf2 promoter [##REF##17624304##29##], and using a similar strategy we cloned the human Brf1 promoter. Using Gene2Promoter software of the Genomatix Suite, we identified a putative promoter for Brf1, Figure ##FIG##1##2A##. We subsequently amplified this putative promoter by PCR and sub-cloned it into a promoterless pGL3-Basic vector, generating Brf1-pGL3. As expected, Brf1-pGL3 was able to drive luciferase expression in a DNA concentration-dependent manner in all three cell lines tested: HeLa, DU145 and MCF-7 (Figure ##FIG##1##2##). These cell lines were selected since they all differentially expressed Brf1 and Brf2. HeLa cells expressed higher levels of Brf2 than Brf1, Figure ##FIG##0##1##. MCF-7 cells expressed higher levels of Brf1, as compared to Brf2, Figure ##FIG##0##1##. The DU145 cell line expressed only slightly higher levels of Brf1, as compared to Brf2 (Figure ##FIG##0##1##). Strikingly, in all three cell lines tested, the Brf2 promoter activity was significantly higher than the Brf1 promoter, Figure ##FIG##1##2B–D##, irrespective of Brf1 and Brf2 mRNA expression levels previously determined (Figure ##FIG##0##1##).</p>", "<p>We cannot currently rule out the possibility that the observed lower Brf1 promoter activity is a consequence of enhancer sequences missing in the Brf1pGL3 construct used in these studies. However, analysis of the Brf1 promoter reveals several cis-acting elements which may negatively regulate expression of Brf1. The Brf1 promoter contains several binding sites for Krüppel-like zinc finger transcription factors similar to Sp1, classified into structural subfamilies derived from variant sequences within their N-terminal domains and termed KLF (Krüppel-like factor) [##REF##16266294##31##]. The Brf1 promoter has three binding sites for the tumor suppressor ZF9, also known as KLF6 [##REF##12915879##32##], which could negatively regulate expression from the Brf1 promoter. Also, the Brf1 promoter contains multiple KLF3 binding sites, previously identified as a CtBp-mediated repressor protein [##REF##16266294##31##]. In addition, two ZF5 cis-regulatory elements also are found within the Brf1 promoter. ZF5 is a ubiquitous Kruppel-like zinc protein originally identified as a negative regulator of the c-myc promoter [##REF##7744698##33##]. Taken together, these observations suggest that negative regulation of the Brf1 promoter may account for the consistently lower levels of Brf1 promoter activity as compared to Brf2 in all cell lines tested (Figure ##FIG##1##2##).</p>", "<p>The Brf1 promoter also contains binding sites for transcription factors which could positively regulate Brf1 expression. For example, the Brf1 promoter contains a Myc/Max binding site. Sansom et al, demonstrated using a double mutant for Myc that Brf1 was no longer transcriptionally upregulated in the absence of functional Myc [##REF##17377531##34##]. However, it is unclear if regulation of Brf1 expression by Myc is a direct or indirect effect [##REF##17377531##34##]. The Brf1 promoter also contains several binding sites for nuclear respiratory factor 1(NRF1), which has been implicated in the upregulation of genes involved in fundamental cellular activities [##REF##11134350##35##] and mitochondrial respiratory function [##REF##16987018##36##]. Additionally, the Brf1 promoter contains a binding site for Zic2, a transcriptional activator that plays a role in mammalian forebrain development [##REF##18068128##37##]. The Brf1 promoter also contains an immediate early growth response (EGR1) binding site. EGR1 is required for programmed cell death or apoptosis in both normal and tumor cells, but has also been determined to stimulate the differentiation of several cell types [##REF##12065847##38##]. Hence, positive and negative regulation of Brf1 expression may be a key event in regulating the growth rate of a cell.</p>", "<title>VAI transcription is universally higher than U6 snRNA transcription, in breast, prostate and cancer cell lines</title>", "<p>The interesting observations that the Brf2 promoter is more active than the Brf1 promoter in all cell lines tested and that Brf1 and Brf2 mRNA are differentially expressed in cervical, breast and prostate cancer cell lines led us to speculate what effects these observations have on protein expression levels of Brf1 and Brf2. Thus, we determined the endogenous protein levels of Brf1 and Brf2 in HeLa, MCF-7 and DU145 cells (Figure ##FIG##2##3A##). The Brf1 protein levels did not vary considerably in the breast, cervical and prostate lines tested (Figure ##FIG##2##3A##). However, the Brf2 protein expression levels differed significantly between the cervical, breast and prostate cancer cell lines tested, as compared to β-actin (Figure ##FIG##2##3A##).</p>", "<p>We then speculated what effect Brf1 and Brf2 protein concentrations had on VAI and U6 snRNA transcription levels in breast, prostate and cervical cancer cell lines. To address this issue we transiently transfected asynchronous HeLa, MCF-7, and DU145 cells with increasing concentrations of the U6 snRNA (pGL3-U6) and the VAI (pGL3-VAI) promoters [##REF##17505538##26##]. In all three cell lines tested, VAI transcription levels were higher than U6 snRNA, Figure ##FIG##2##3B–D##. This result was surprising as we have previously observed that Brf1 and Brf2 are differentially expressed (Figure ##FIG##0##1##) and the U6 specific TFIIIB subunit Brf2 promoter activity was significantly higher than Brf1 promoter activity in all three cell lines tested (Figure ##FIG##1##2##). Although the Brf1 protein levels did not vary much in HeLa, MCF-7 and DU-145 cells, VAI transcription levels in these cancer cell lines varied considerably. VAI transcription was approximately five fold higher in HeLa cells (Figure ##FIG##2##3B##), as compared to DU-145 (Figure ##FIG##2##3C##) and MCF-7 cells (Figure ##FIG##2##3D##). One possible reason that the observed VAI transcription levels did not correlate well with Brf1 protein levels is that cancer cells may already express Brf1 levels far above limiting concentrations for RNA pol III transcription. Interestingly, there is a correlation between Brf2 protein levels (Figure ##FIG##2##3A##) and the activity of the U6 promoter in HeLa (Figure ##FIG##2##3B##), DU-145 (Figure ##FIG##2##3C##) and MCF-7 (Figure ##FIG##2##3D##) cells.</p>", "<p>We speculate the differences in Brf1 and Brf2 mRNA expression and promoter activities, as well as the observed differences in TFIIIB-mediated RNA pol III transcription is a consequence of differences in Brf1 and Brf2 mRNA stability. Differences in Brf1 and Brf2 mRNA stability may, in part, account for the differences in the endogenous protein levels of Brf1 and Brf2 observed in Figure ##FIG##2##3A##, as compared to mRNA expression levels in Figure ##FIG##0##1B–C##.</p>", "<p>Modulation of mRNA stability provides a rapid mechanism for regulating protein levels, independent of transcription initiation. A major mechanism controlling the rate of mRNA turnover is the regulation of destabilizing cis-regulatory elements within a given transcript [##REF##17916044##39##]. mRNA destabilizing cis-regulatory elements have been localized as coding region determinant (CRD) sequences [##REF##1559612##40##, ####REF##1448102##41##, ##REF##8657122##42##, ##REF##17198736##43####17198736##43##], or as the more common AU-rich elements (ARE) in the 3'UTR [##REF##15460540##44##] of a transcript. These AU-rich elements are heterogenous in terms of length, AU-content and 3'UTR location. However, AREs may be classified based on sequence criteria [##REF##8657122##42##,##REF##8578590##45##,##REF##9234718##46##]. Class I AREs contain multiple canonical AUUUA sites within the 3' UTR and Class II contains multiple AUUUA sites which may overlap resulting in an AUUUAUUUA sequence. The Class III AREs have U-rich regions in the 3'UTRs, without a canonical AUUUA site.</p>", "<p>Using the ElDorado software of the Genomatix suite we identified 3'UTRs for Brf1 and Brf2 (data not shown). The 3'UTRs of Brf1 and Brf2 were AU-rich, 25% and 52% respectively, but do not appear to contain classical Class I or Class II AU-rich elements. However, it remains to be experimentally determined if the significant AU-content of the 3'UTR of Brf2 plays a role in regulating Brf2 mRNA turnover.</p>", "<p>We cannot currently rule out the possibility that Brf1 and Brf2 mRNA stability is regulated by coding region determinant elements as previously described for c-fos [##REF##1448102##41##], c-myc [##REF##1559612##40##,##REF##17198736##43##], and MnSOD [##REF##11489890##47##]. Using Align X (Invitrogen), we aligned the coding sequences of Brf1 (ntds 1666–1858) and Brf2 (ntds 1257–1456) with a c-myc nucleotide sequence corresponding to a 60 amino acid region (372–412) previously defined as a coding region determinant [##REF##1559612##40##,##REF##17198736##43##] (Figure ##FIG##3##4##). Strikingly, within the coding regions for the c-terminus of Brf1 and Brf2, there was a high degree of sequence identity with the coding determinant region of c-myc: Brf1 was 50.5% identical and Brf2 50.1%. We will experimentally determine whether these regions indeed influence Brf1 and Brf2 mRNA stability, ultimately providing an additional mechanism for regulation of basal RNA pol III transcription factors.</p>" ]

[ "<title>Results and Discussion</title>", "<title>The TFIIIB subunits Brf1 and Brf2 are differentially expressed in cancer cell lines</title>", "<p>Accurate initiation of transcription by RNA pol III requires TFIIIB. Two of the TFIIIB subunits, Brf1 and Brf2, are structurally related and are required for accurate transcription by RNA pol III [##REF##12381659##1##,##REF##11040218##7##]. Brf1 is required for transcription from gene internal promoters (tRNA), whereas Brf2 is required for transcription from gene external RNA pol III promoters (U6 snRNA). Hence, we sought to determine if Brf1 and Brf2 expression is elevated in a variety of cancer cell lines, contributing to the previously observed increase of RNA pol III transcripts in cancer. We obtained a variety of cervical, colorectal, breast, and prostate cancer cell lines from the ATCC, isolated total RNA from asynchronous cells, and by RT-PCR determined the expression levels of Brf1 and Brf2 using gene specific primers (Table ##TAB##0##1##). Primers for β-actin (Table ##TAB##0##1##) were used as a control, Figure ##FIG##0##1A##. Strikingly, the TFIIIB subunits Brf1 and Brf2 are differentially expressed in breast, cervical and prostate cancer cell lines (Figure ##FIG##0##1B## and ##FIG##0##1C##). We then speculated that the observed differences in Brf1 and Brf2 expression is a consequence of alterations in mRNA stability or may be a result of differential activity of the Brf1 and Brf2 promoters.</p>", "<title>The Brf1 and Brf2 promoters differ in activity in breast, cervical and prostate cancer cell lines</title>", "<p>To determine if the observed differences in Brf1 and Brf2 expression is a result of differences in transcription initiation, we set out to directly compare the activities of the Brf1 and Brf2 promoters. We have previously cloned the human Brf2 promoter [##REF##17624304##29##], and using a similar strategy we cloned the human Brf1 promoter. Using Gene2Promoter software of the Genomatix Suite, we identified a putative promoter for Brf1, Figure ##FIG##1##2A##. We subsequently amplified this putative promoter by PCR and sub-cloned it into a promoterless pGL3-Basic vector, generating Brf1-pGL3. As expected, Brf1-pGL3 was able to drive luciferase expression in a DNA concentration-dependent manner in all three cell lines tested: HeLa, DU145 and MCF-7 (Figure ##FIG##1##2##). These cell lines were selected since they all differentially expressed Brf1 and Brf2. HeLa cells expressed higher levels of Brf2 than Brf1, Figure ##FIG##0##1##. MCF-7 cells expressed higher levels of Brf1, as compared to Brf2, Figure ##FIG##0##1##. The DU145 cell line expressed only slightly higher levels of Brf1, as compared to Brf2 (Figure ##FIG##0##1##). Strikingly, in all three cell lines tested, the Brf2 promoter activity was significantly higher than the Brf1 promoter, Figure ##FIG##1##2B–D##, irrespective of Brf1 and Brf2 mRNA expression levels previously determined (Figure ##FIG##0##1##).</p>", "<p>We cannot currently rule out the possibility that the observed lower Brf1 promoter activity is a consequence of enhancer sequences missing in the Brf1pGL3 construct used in these studies. However, analysis of the Brf1 promoter reveals several cis-acting elements which may negatively regulate expression of Brf1. The Brf1 promoter contains several binding sites for Krüppel-like zinc finger transcription factors similar to Sp1, classified into structural subfamilies derived from variant sequences within their N-terminal domains and termed KLF (Krüppel-like factor) [##REF##16266294##31##]. The Brf1 promoter has three binding sites for the tumor suppressor ZF9, also known as KLF6 [##REF##12915879##32##], which could negatively regulate expression from the Brf1 promoter. Also, the Brf1 promoter contains multiple KLF3 binding sites, previously identified as a CtBp-mediated repressor protein [##REF##16266294##31##]. In addition, two ZF5 cis-regulatory elements also are found within the Brf1 promoter. ZF5 is a ubiquitous Kruppel-like zinc protein originally identified as a negative regulator of the c-myc promoter [##REF##7744698##33##]. Taken together, these observations suggest that negative regulation of the Brf1 promoter may account for the consistently lower levels of Brf1 promoter activity as compared to Brf2 in all cell lines tested (Figure ##FIG##1##2##).</p>", "<p>The Brf1 promoter also contains binding sites for transcription factors which could positively regulate Brf1 expression. For example, the Brf1 promoter contains a Myc/Max binding site. Sansom et al, demonstrated using a double mutant for Myc that Brf1 was no longer transcriptionally upregulated in the absence of functional Myc [##REF##17377531##34##]. However, it is unclear if regulation of Brf1 expression by Myc is a direct or indirect effect [##REF##17377531##34##]. The Brf1 promoter also contains several binding sites for nuclear respiratory factor 1(NRF1), which has been implicated in the upregulation of genes involved in fundamental cellular activities [##REF##11134350##35##] and mitochondrial respiratory function [##REF##16987018##36##]. Additionally, the Brf1 promoter contains a binding site for Zic2, a transcriptional activator that plays a role in mammalian forebrain development [##REF##18068128##37##]. The Brf1 promoter also contains an immediate early growth response (EGR1) binding site. EGR1 is required for programmed cell death or apoptosis in both normal and tumor cells, but has also been determined to stimulate the differentiation of several cell types [##REF##12065847##38##]. Hence, positive and negative regulation of Brf1 expression may be a key event in regulating the growth rate of a cell.</p>", "<title>VAI transcription is universally higher than U6 snRNA transcription, in breast, prostate and cancer cell lines</title>", "<p>The interesting observations that the Brf2 promoter is more active than the Brf1 promoter in all cell lines tested and that Brf1 and Brf2 mRNA are differentially expressed in cervical, breast and prostate cancer cell lines led us to speculate what effects these observations have on protein expression levels of Brf1 and Brf2. Thus, we determined the endogenous protein levels of Brf1 and Brf2 in HeLa, MCF-7 and DU145 cells (Figure ##FIG##2##3A##). The Brf1 protein levels did not vary considerably in the breast, cervical and prostate lines tested (Figure ##FIG##2##3A##). However, the Brf2 protein expression levels differed significantly between the cervical, breast and prostate cancer cell lines tested, as compared to β-actin (Figure ##FIG##2##3A##).</p>", "<p>We then speculated what effect Brf1 and Brf2 protein concentrations had on VAI and U6 snRNA transcription levels in breast, prostate and cervical cancer cell lines. To address this issue we transiently transfected asynchronous HeLa, MCF-7, and DU145 cells with increasing concentrations of the U6 snRNA (pGL3-U6) and the VAI (pGL3-VAI) promoters [##REF##17505538##26##]. In all three cell lines tested, VAI transcription levels were higher than U6 snRNA, Figure ##FIG##2##3B–D##. This result was surprising as we have previously observed that Brf1 and Brf2 are differentially expressed (Figure ##FIG##0##1##) and the U6 specific TFIIIB subunit Brf2 promoter activity was significantly higher than Brf1 promoter activity in all three cell lines tested (Figure ##FIG##1##2##). Although the Brf1 protein levels did not vary much in HeLa, MCF-7 and DU-145 cells, VAI transcription levels in these cancer cell lines varied considerably. VAI transcription was approximately five fold higher in HeLa cells (Figure ##FIG##2##3B##), as compared to DU-145 (Figure ##FIG##2##3C##) and MCF-7 cells (Figure ##FIG##2##3D##). One possible reason that the observed VAI transcription levels did not correlate well with Brf1 protein levels is that cancer cells may already express Brf1 levels far above limiting concentrations for RNA pol III transcription. Interestingly, there is a correlation between Brf2 protein levels (Figure ##FIG##2##3A##) and the activity of the U6 promoter in HeLa (Figure ##FIG##2##3B##), DU-145 (Figure ##FIG##2##3C##) and MCF-7 (Figure ##FIG##2##3D##) cells.</p>", "<p>We speculate the differences in Brf1 and Brf2 mRNA expression and promoter activities, as well as the observed differences in TFIIIB-mediated RNA pol III transcription is a consequence of differences in Brf1 and Brf2 mRNA stability. Differences in Brf1 and Brf2 mRNA stability may, in part, account for the differences in the endogenous protein levels of Brf1 and Brf2 observed in Figure ##FIG##2##3A##, as compared to mRNA expression levels in Figure ##FIG##0##1B–C##.</p>", "<p>Modulation of mRNA stability provides a rapid mechanism for regulating protein levels, independent of transcription initiation. A major mechanism controlling the rate of mRNA turnover is the regulation of destabilizing cis-regulatory elements within a given transcript [##REF##17916044##39##]. mRNA destabilizing cis-regulatory elements have been localized as coding region determinant (CRD) sequences [##REF##1559612##40##, ####REF##1448102##41##, ##REF##8657122##42##, ##REF##17198736##43####17198736##43##], or as the more common AU-rich elements (ARE) in the 3'UTR [##REF##15460540##44##] of a transcript. These AU-rich elements are heterogenous in terms of length, AU-content and 3'UTR location. However, AREs may be classified based on sequence criteria [##REF##8657122##42##,##REF##8578590##45##,##REF##9234718##46##]. Class I AREs contain multiple canonical AUUUA sites within the 3' UTR and Class II contains multiple AUUUA sites which may overlap resulting in an AUUUAUUUA sequence. The Class III AREs have U-rich regions in the 3'UTRs, without a canonical AUUUA site.</p>", "<p>Using the ElDorado software of the Genomatix suite we identified 3'UTRs for Brf1 and Brf2 (data not shown). The 3'UTRs of Brf1 and Brf2 were AU-rich, 25% and 52% respectively, but do not appear to contain classical Class I or Class II AU-rich elements. However, it remains to be experimentally determined if the significant AU-content of the 3'UTR of Brf2 plays a role in regulating Brf2 mRNA turnover.</p>", "<p>We cannot currently rule out the possibility that Brf1 and Brf2 mRNA stability is regulated by coding region determinant elements as previously described for c-fos [##REF##1448102##41##], c-myc [##REF##1559612##40##,##REF##17198736##43##], and MnSOD [##REF##11489890##47##]. Using Align X (Invitrogen), we aligned the coding sequences of Brf1 (ntds 1666–1858) and Brf2 (ntds 1257–1456) with a c-myc nucleotide sequence corresponding to a 60 amino acid region (372–412) previously defined as a coding region determinant [##REF##1559612##40##,##REF##17198736##43##] (Figure ##FIG##3##4##). Strikingly, within the coding regions for the c-terminus of Brf1 and Brf2, there was a high degree of sequence identity with the coding determinant region of c-myc: Brf1 was 50.5% identical and Brf2 50.1%. We will experimentally determine whether these regions indeed influence Brf1 and Brf2 mRNA stability, ultimately providing an additional mechanism for regulation of basal RNA pol III transcription factors.</p>" ]

[ "<title>Conclusion</title>", "<p>We have demonstrated that the TFIIIB subunits Brf1 and Brf2 are differentially expressed at the mRNA level in a variety of cancer cells (Figure ##FIG##0##1##). We also show that the Brf2 promoter is more active than the Brf1 promoter in the breast, prostate and cervical cell lines tested (Figure ##FIG##1##2B–D##). Brf1-dependent VAI transcription was significantly higher than the Brf2-dependent U6 snRNA transcription in HeLa, DU-145 and MCF-7 cell lines (Figure ##FIG##2##3B–D##). Surprisingly, the Brf1 protein levels did not vary considerably in HeLa, MCF-7 and DU-145 cells (Figure ##FIG##2##3A##), yet Brf1 mRNA expression varied considerably in the cancer cell lines tested (Figure ##FIG##0##1B##). Thus, Brf1 promoter activity (Figure ##FIG##1##2B–D##) and Brf1 protein expression (Figure ##FIG##2##3A##) levels did not correlate well with Brf1-dependent transcription levels (Figure ##FIG##2##3B–D##).</p>", "<p>Interestingly, we have observed that Brf2 protein levels (Figure ##FIG##2##3A##) may correlate with U6 snRNA transcription rates in the breast, cervical and prostate cancer cell lines tested (Figure ##FIG##2##3B–D##). Hence, we speculate that since Brf2 has been shown to be amplified in breast cancers and has been proposed to be a candidate oncogene [##REF##15897872##48##,##REF##17096335##49##], strict regulation of Brf2 expression could be critical in preventing the oncogenic phenotype. Also, Brf1 expression has been demonstrated to be induced in cervical cells infected with papilloma virus [##REF##15592529##50##] and cardiomyocytes undergoing hypertrophy [##REF##16541106##51##,##REF##17938580##52##]. In addition, Brf1 has been shown to be a direct target of activation by c-myc and ERK [##REF##12529648##21##,##REF##12743036##22##], both known to play a key role in cancer pathogenesis. Taken together, we reason that deregulation of Brf1 and Brf2 expression could be a key mechanism responsible for the observed deregulation of RNA pol III transcription in cancer cells.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>RNA polymerase (pol) III transcription is specifically elevated in a variety of cancers and is a target of regulation by a variety of tumor suppressors and oncogenes. Accurate initiation by RNA pol III is dependent on TFIIIB. In higher eukaryotes, two forms of TFIIIB have been characterized. TFIIIB required for proper initiation from gene internal RNA pol III promoters is comprised of TBP, Bdp1, and Brf1. Proper initiation from gene external RNA pol III promoters requires TBP, Bdp1, and Brf2. We hypothesized that deregulation of RNA polymerase III transcription in cancer may be a consequence of altered TFIIIB expression</p>", "<title>Results</title>", "<p>Here, we report: (1) the TFIIIB subunits Brf1 and Brf2 are differentially expressed in a variety of cancer cell lines: (2) the Brf1 and Brf2 promoters differ in activity in cancer cell lines, and (3) VAI transcription is universally elevated, as compared to U6, in breast, prostate and cervical cancer cells.</p>", "<title>Conclusion</title>", "<p>Deregulation of TFIIIB-mediated transcription may be an important step in tumor development. We demonstrate that Brf1 and Brf2 mRNA are differentially expressed in a variety of cancer cells and that the Brf2 promoter is more active than the Brf1 promoter in all cell lines tested. We also demonstrate, that Brf1-dependent VAI transcription was significantly higher than the Brf2-dependent U6 snRNA transcription in all cancer cell lines tested. The data presented suggest that Brf2 protein expression levels correlate with U6 promoter activity in the breast, cervical and prostate cell lines tested. Interestingly, the Brf1 protein levels did not vary considerably in HeLa, MCF-7 and DU-145 cells, yet Brf1 mRNA expression varied considerably in breast, prostate and cervical cancer cell lines tested. Thus, Brf1 promoter activity and Brf1 protein expression levels did not correlate well with Brf1-dependent transcription levels. Taken together, we reason that deregulation of Brf1 and Brf2 expression could be a key mechanism responsible for the observed deregulation of RNA pol III transcription in cancer cells.</p>" ]

[ "<title>Authors' contributions</title>", "<p>SC was responsible for RT-PCR analysis, western blot and manuscript preparation. JJ cloned the Brf1 promoter and sequence alignments. IV conducted RNA pol III luciferase assays. LS conceived and coordinated study, performed Brf1 and Brf2 promoter luciferase assays, and drafted manuscript. All authors have read and approved the final manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Nouria Hernandez for Brf1 and Brf2 antibodies and for critically reading this manuscript. This work was supported in part by the Henry Luce foundation (L. Schramm, S. Cabarcas), a St. John's University faculty growth grant (L. Schramm) and by the Department of Education's Graduate Assistance in Areas of National Need (GAANN) Grant P200A010130 (I. Veras).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>The TFIIIB subunits Brf1 and Brf2 are differentially expressed in cancer cell lines</bold>. Total RNA was isolated from asynchronous growing Caski, HeLa, RKO, SIHA, Du 145, ZR75-1, MCF-7, MDA-MB-453, MDA-MB-231, and MDA-MB-468 cells. After first strand cDNA synthesis, diluted cDNA was used in PCR using the primers depicted in Table 1. The mRNA expression of (A) β-actin, (B) Brf1, and (C) Brf2 are shown. The expected sizes of the PCR products of the different TFIIIB subunits are depicted.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>The Brf1 and Brf2 promoters differ in activity in breast, cervical and prostate cancer cell lines</bold>. (A) Schematic representation of the Brf1 promoter identified. The empty pGL3 vector (300 ng), as well as increasing concentrations of Brf1-pGL3 (100 ng, 200 ng, 300 ng) and Brf2-pGL3 (100 ng, 200 ng, 300 ng) were transiently transfected into asynchronous (A) HeLa, (B) DU145, and (C) MCF-7 cells. All luciferase assay results are expressed as relative light units (RLU): the average of the Photinus pyralis firefly activity observed divided by the average of the activity recorded from the Renilla luciferase vector. Experiments were done in triplicate, repeated three times, and representative experiments are depicted.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>VAI transcription is higher than U6 snRNA transcription in HeLa, DU145, and MCF-7 cells</bold>. The empty pGL3 vector (300 ng), as well as increasing concentrations of pGL3-U6 (100 ng, 200 ng, 300 ng) and pGL3-VAI (100 ng, 200 ng, 300 ng) were transiently transfected into asynchronous (A) HeLa, (B) DU145, and (C) MCF-7 cells. All luciferase assay results are expressed as relative light units (RLU): the average of the Photinus pyralis firefly activity observed divided by the average of the activity recorded from the Renilla luciferase vector. Experiments were done in triplicate, repeated three times, and representative experiments are depicted. (D) Western blot analysis of Brf1 and Brf2 protein levels in HeLa, MCF-7 and DU145 cells. 25 μg of nuclear extract was immunoblotted with anti-Brf1 (CS1043) and anti-Brf2 (CS1228) antibodies. As loading control, membrane was also immunoblotted with an anti-actin antibody, bottom panel. Arrows depict migration of actin, Brf1 and Brf2.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Brf1 and Brf2 have a high sequence similarity to the codon determinant region of c-myc</bold>. (A) Schematic representation of Brf1, Brf2 and c-myc. Structural features are indicated. Location of nucleotide sequences aligned (red text) in lower panel are indicated by red brackets. (B) Sequence alignment of the codon determinant region of c-myc, Brf1 and Brf2. Identical amino acids in all three sequences are depicted in yellow. Sequences identical in two of the three sequences are highlighted in blue. Consensus sequence is indicated.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Primers used for semiquantitative RT-PCR analyses</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Gene</bold></td><td align=\"left\"><bold>Forward Primer</bold></td><td align=\"left\"><bold>Reverse Primer</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>β-actin</bold></td><td align=\"left\">5'-tagcggggttcacccacactgtgccccatcta-3'</td><td align=\"left\">5'-ctagaagcatttgcggtggaccgatggaggg-3'</td></tr><tr><td align=\"left\"><bold>Brf1</bold></td><td align=\"left\">5'ggcattgatgacctggagat-3'</td><td align=\"left\">5'accagaggcctcaacctttt-3'</td></tr><tr><td align=\"left\"><bold>Brf2</bold></td><td align=\"left\">5'cagaagtggagacccgagag-3'</td><td align=\"left\">5' cagggagggttagggacact-3'</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1471-2199-9-74-1\"/>", "<graphic xlink:href=\"1471-2199-9-74-2\"/>", "<graphic xlink:href=\"1471-2199-9-74-3\"/>", "<graphic xlink:href=\"1471-2199-9-74-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>With the successful application of the <italic>Drosophila melanogaster P </italic>element as a tool for the creation of transgenic fruit flies, researchers had high hopes for the stable introduction of transgenes into germlines [##REF##6289436##1##]. Unfortunately, <italic>P </italic>element mobility was determined to be restricted only to <italic>D</italic>.<italic>melanogaster </italic>and very closely related species [##UREF##0##2##]. The ensuing search for novel mobile elements that are active within a wide range of species led to the classification and characterization of the <italic>hAT</italic>, <italic>Tc1-mariner</italic>, and <italic>piggyBac </italic>families of mobile elements [##UREF##1##3##]. The <italic>piggyBac </italic>transposon is a short repeat, class II mobile element originally isolated as the causative agent of the Few Polyhedra plaque morphology mutations of <italic>Autographa california </italic>nuclear polyhedrosis virus (AcNPV) [##REF##2549707##4##]. It is the archetype of its own family and the only fully active transposable element in that family that is currently in use as a transgenic vector. The wild-type <italic>piggyBac </italic>element is 2.4 kb long and ends in a 5' CCC...GGG 3' configuration with asymmetric terminal and subterminal repeats. The sub-terminal repeats are 19 bp in length and lie 3 bp and 31 bp inside of the perfect inverted terminal repeats (ITRs) on the 5' and 3' end respectively [##REF##2549707##4##]. The protein catalyzing the movement of <italic>piggyBac </italic>is encoded within a single open reading frame (ORF) of 1783 bp, with a length of 594 amino acids and a predicated mass of 68 kDa [##REF##2549707##4##,##REF##8765680##5##]. As a class II mobile element, <italic>piggyBac </italic>operates via a DNA intermediate in a cut-and-paste mechanism [##REF##10394918##6##]. In this scenario, the transposable element, delineated by transposase-specific ITRs is excised by the transposase and reinserted into a new location. In the case of <italic>piggyBac</italic>, the bias for individual sites chosen during reinsertion does not follow any clearly defined rules. Although the only sequence requirement for a new insertion event is the presence of a TTAA sequence in the DNA, there is a clear preference for certain TTAA sites over others as shown by inter-plasmid transposition assays [##REF##16877528##7##].</p>", "<p>The <italic>piggyBac </italic>element has been used to transform the species <italic>Mus musculus </italic>[##REF##16096065##8##], <italic>Tribolium castaneum </italic>[##REF##12974948##9##], <italic>Anopheles gambiae </italic>[##REF##11903629##10##], <italic>Ceratitis capita </italic>[##REF##9636182##11##], <italic>Drosophila melanogaster </italic>[##REF##10634970##12##], <italic>Bactrocera dorsalis </italic>[##REF##11122469##13##], <italic>Musca domestica </italic>[##REF##11422506##14##], <italic>Lucilia cuprina </italic>[##REF##11841497##15##], <italic>Bicyclus anynana </italic>[##REF##15503989##16##], <italic>Aedes aegypti </italic>[##REF##11966878##17##,##REF##11583926##18##], <italic>Anopheles albimanus </italic>[##REF##12144693##19##], <italic>Anopheles stephensi </italic>[##REF##11805082##20##], <italic>Bombyx mori </italic>[##REF##10625397##21##], <italic>Athalia rosae </italic>[##REF##12650693##22##], <italic>Drosophila willistoni </italic>[##UREF##2##23##], <italic>Pectinophora gossypiella </italic>[##REF##10886417##24##], <italic>Anastrepha suspensa </italic>[##REF##11164342##25##], <italic>Aedes fluviatilis </italic>[##REF##17160283##26##], <italic>Harmonia axyridis </italic>[##REF##16907837##27##], <italic>Schistosoma mansoni </italic>[##UREF##3##28##], and the causative agent of malaria, <italic>Plasmodium falciparum </italic>[##REF##16260745##29##]. Plasmid-based mobility assays have also shown <italic>piggyBac </italic>to be active in human and other primate cells [##REF##16096065##8##,##REF##17028963##30##], in <italic>Zea maize </italic>cells [##UREF##4##31##], <italic>Spodoptera frugiperda </italic>cells [##REF##8765680##5##], and in the embryos of <italic>Aedes triseriatus </italic>[##REF##11370874##32##], <italic>Heliothis virescens </italic>[##REF##16983664##33##], and <italic>Danio rerio </italic>[##REF##17028963##30##], although none of these species have yet been transformed with <italic>piggyBac</italic>.</p>", "<p>Recently, Mitra et al. [##UREF##5##34##] have defined <italic>piggyBac </italic>mediated transposition as involving several discrete steps. First, the transposase creates 3' nicks at each end of the terminal repeats just internal of the 'TTAA'. The free 3'-OH attacks the complimentary strand, four nucleotides downstream of the initial nick, just outside of the 'TTAA' repeat, forming a transient hairpin structure and releasing the transposon ends. The transposase quickly resolves these hairpin structures into 5' 'TTAA' overhangs on either side of the excision product. For reinsertion, the transposase joins the excised element to a new 'TTAA' target site in a staggered pattern, completing the transposition reaction. This mechanism accounts for both precise excision and target site duplication.</p>", "<p>For all transposable elements, there are certain requirements for transposition, namely the recognition and binding of the terminal repeats, double stranded DNA breakage (DSB), and reinsertion of the element into a target, as well as possibly the repair of the excision site, which may or may not involve host factors [##UREF##1##3##]. DNA manipulating enzymes, such as integrases, recombinases, resolvases, endonucleases, and transposases must meet one or more of these requirements in order to successfully catalyze their respective reactions. With this commonality in function comes some similarity in mechanism and structure. One of the most widespread of these features is the 'DDE/DDD' motif first identified and designated in retroviral and retrotransposon integrases [##REF##1314954##35##]. This motif has since been identified among many different families of DNA manipulating enzymes, from certain nucleases to the enzymes that carry out V(D)J recombination and even the human RNAi enzyme, Ago2 [##REF##9184211##36##, ####REF##10431195##37##, ##REF##12399484##38##, ##REF##8302872##39##, ##REF##11729156##40##, ##REF##7912831##41##, ##REF##10601032##42##, ##REF##10601033##43##, ##REF##9037046##44##, ##REF##7923356##45##, ##REF##15284456##46##, ##REF##10911996##47####10911996##47##]. 'DDE/DDD' has been implicated as the active site for such enzymes by providing carboxyl groups used to recruit metal ions as essential cofactors. These residues are required to precisely position the metal ions, usually magnesium or manganese, used to recruit nucleophilic groups to the catalytic center of their respective enzymes.</p>", "<p>Sarkar et al. published an extensive computational analysis of the <italic>piggyBac </italic>element and related sequences [##REF##12955498##48##] that demonstrated the widespread occurrence of the <italic>piggyBac </italic>family of elements. While no actual experiments were performed by Sarkar et al., they proposed a 'DDD' motif for <italic>piggyBac</italic>, similar to a paper published in 1996 in which Bigot et al. speculated the existence of a 'DSE' motif in <italic>hAT </italic>elements based on sequence alignments. Sarkar et al. based their proposal on weak matches for two <italic>piggyBac </italic>related proteins to the bacterial <italic>IS</italic>4/5 transposase family DDE motif. This alignment suggested the first two of these aspartates are D268, and D346. While this similarity with the <italic>IS</italic>4/5 transposases did not yield a hit for the third member of the 'DDE' triad, Sarkar et al. speculated that the third member was an aspartate at D447.</p>", "<p>In this report, we align very closely related members of the <italic>piggyBac </italic>family across kingdoms and identify several highly conserved regions. We propose that a direct relationship exists between the degree of conservation of a particular feature, and its necessity to catalyze transposition, as they are favored at the time of horizontal transmission. To this end, we only considered the proteins most closely related to <italic>piggyBac </italic>in our alignment. However, it should be made clear, when considering the results of our alignment, aside from <italic>piggyBac </italic>itself, only one other family member has been shown to be a functional element: Xtr-Uribo2_PCR_Iv1b (Genbank Accession: <ext-link ext-link-type=\"gen\" xlink:href=\"BAF82025\">BAF82025</ext-link>) from the <italic>Xenopus </italic>family, which catalyzes movement in GP293 cells [##REF##17934208##49##]. Therefore, we are careful to judge the relevance of any well conserved feature primarily upon its presence in either <italic>piggyBac </italic>or Uribo-2.</p>", "<p>Finally, we mutate the three aspartates identified by Sarkar et al. as well as D450, another highly conserved residue close to the third proposed aspartate, which may also contribute to the catalytic center of the transposase. We test these site-directed mutant transposases for excision activity in two different donor plasmids and report our results.</p>" ]

[ "<title>Methods</title>", "<title>Sequence retrieval and alignment</title>", "<p>The predicted <italic>piggyBac </italic>translated protein was used to scan GenBank [##REF##18073190##50##] in a protein-BLAST search of the non-redundant database. Hits that were not from <italic>Trichoplusia ni </italic>were chosen for a multiple sequence alignment in ClustalW [##REF##7984417##70##]. The resulting .msf alignment was input into the BoxShade server in order to more easily identify the conserved regions.</p>", "<title>Plasmid Construction</title>", "<p>pXL-BacII-SV40 was constructed by amplifying the SV40 terminator sequence from pMT/V5-HisA (Invitrogen, Carlsbad, CA) with the primers: Sense: 5' TGTGCGGCCGCAGTCTAGAAAAGGATCCTAGATCATAATCAGCCATACCACATTTGTAGAGG 3' and antisense: 5' TGGGAGCTCATAAGCCGTATCGATAAGCTTTAAGATACATTGATG 3' with <italic>Pfx </italic>high-fidelity polymerase (Invitrogen) according to manufacturer protocol. The PCR reaction was separated on .9% agarose gel stained with 10 μg/ml ethidium bromide and the band corresponding to the SV40 fragment was isolated with the Wizard SV Gel Purification System (Invitrogen). The fragment was then cut with <italic>Bam</italic>HI (New England Biolabs (NEB), Ipswitch, MA) and <italic>Cla</italic>I (NEB) and ligated into the vector pXL-BacII [##REF##11683259##71##] at the same sites to form pXL-BacII-SV40. The plasmid was sequenced to verify accuracy.</p>", "<p>To create pCR2.1-<italic>piggyBac</italic>{SV40}, the <italic>piggyBac</italic>{SV40} fragment was amplified from pXL-BacII-SV40 with the primers: Sense: 5' <underline>AAACCCAAAGGTACCGAGCTCGGATCCACTAGTAACGGCCGCCAGTGTGCTGGAATTCGGGG<bold>TT</bold></underline><bold>AA</bold>CCCTAGAAAGATAATCATATTGTGACG 3' and Antisense: 5' <underline>CCCAAACCCGCGGCCGCCAGTGTGATGGATATCTGCAGAATTCGGGG<bold>TT</bold></underline><bold>AA</bold>CCCTAGAAAGATAGTCTGCGTAAAATTG 3' using <italic>Pfx </italic>high-fidelity polymerase. The 'TTAA' sites delineating the ends of the <italic>piggyBac </italic>donor fragment are in bold while the sequences remaining behind after precise excision are underlined. The fragment corresponding to <italic>piggyBac</italic>{SV40} was band-isolated as described above and cut with the restriction enzymes <italic>Acc</italic>65I (NEB) and <italic>Not</italic>I (NEB) This fragment was then ligated into the vector pCR2.1-Topo (Invitrogen) at the same sites. The plasmid was sequenced to verify accuracy.</p>", "<p>The various mutants of the <italic>piggyBac </italic>open reading frame were prepared by Bio Basic Inc. (Biobasic Inc., Ontario, Canada) in the vector backbone phsp-pBac [##REF##10634970##12##] according to the specifications listed in Table ##TAB##0##1##.</p>", "<title>Blue/White colony screen</title>", "<p>The blue/white colony screen was developed to enable us to determine, by visual inspection, which colonies had undergone precise excision. The <italic>piggyBac</italic>{SV40} cassette was inserted at a 'TTAA' site in the pCR2.1 backbone, in the midst of the lacZ ORF. The <italic>piggyBac </italic>expression plasmid and the pCR2.1-<italic>piggyBac</italic>{SV40} are co-transfected into <italic>D. melanogaster </italic>Schneider2 (S2) cells and incubated. The plasmids are recovered by Hirt extraction and transformed into <italic>E. coli</italic>. In the presence of the cassette, the lacZ ORF is interrupted, yielding a white colony phenotype on kanamycin containing media with IPTG and 5-bromo-4-chloro-3-indolyl-b-D-galactoside (X-gal). However, when precise <italic>piggyBac</italic>-catalyzed excision occurs in this vector, the lacZ ORF is restored and the subsequent <italic>E. coli </italic>colony will possess a blue phenotype (Fig. ##FIG##9##10##). Plating on kanamycin containing media ensures that only donor plasmids will develop into colonies, and helper expression plasmids will not lead to false white colonies. By comparing the number of blue colonies to the number of total (blue+white) colonies, we can extrapolate the excision frequency. That is, the number of excision events occurring out of the total number of potential excision events.</p>", "<p>10⁶S2 cells were allowed to adhere to the bottom of a 9.6 cm²cell culture well and were transfected with .4 μg of phsp-pBac helper plasmid and .4 μg of pCR2.1-<italic>piggyBac</italic>{SV40} donor plasmid with Transfectin liposomal transfection reagent (Bio-Rad Laboratories, Hercules, CA) according to manufacturer protocol in minimal S2 media (Gibco, Carlsbad, CA). The cell/transfection media mixture was allowed to sit at room temperature overnight. The next morning, the transfection media was aspirated from the cells and replaced with complete S2 media (Minimal S2 supplemented with 10% FBS, .1 mg/mL streptomycin, and .25 μg/mL amphotericin). The cells were heat-shocked to induce phsp-pBac promoter activation at 37°C for 60 minutes. The cells were then moved to a 28°C incubator for 48 hours prior to harvesting.</p>", "<p>Plasmid DNA was isolated from the S2 cells according to the standard Hirt LMW DNA extraction protocol [##REF##4291934##72##]. Additional steps taken were as follows: Following the centrifugation of the lysate, the DNA-containing supernatant was removed, extracted once in phenol:chloroform:isoamyl alcohol (25:24:1) and washed once with chloroform:isoamyl alcohol (24:1). DNA was precipitated with 2 volumes 100% ethanol and 1/10 volume 3 M sodium acetate (pH 4.5) and stored at -20°C overnight. DNA was pelleted by centrifugation at 14,000 rpm at 4°C and the supernatant aspirated. The pellet was washed 3 times with 70% ethanol to remove the excess salt from the Hirt extraction buffers, dried, and resuspended in 40 μl of nuclease-free water. 1 μl of the Hirt extraction DNA was mixed in 21 μl nuclease-free water and transformed by electroporation into 3 μl <italic>E coli</italic>. DH10B cells (Invitrogen) in a 1 mm gap electroporation cuvette according to manufacturer protocol. 150 μl of S.O.C. medium was pipetted directly into the electroporation cuvette and mixed well by pipetting. Cells were allowed to recover at 37°C for 30 minutes prior to plating. 10 μl and 100 μl portions of this cell-media mixture were spread onto LB-Kanamycin plates prepared with 4 μl 100 μg/μl IPTG and 70 μl 20 mg/ml X-gal. The plates were incubated overnight at 37°C and scored by counting the number of blue colonies on the plate spread with 100 μl cell-media mixture and the total number of colonies on the plate spread with 10 μl of the cell-media mixture.</p>", "<title>PCR verification of excision events</title>", "<p>A portion of the blue colonies were screened for excision events to verify accuracy of the test. Briefly, a 20 μl total volume PCR was prepared with a final concentration of 50 mM KCl, 10 mM Tris pH 8.3, 1.5 mM MgCl₂, 5 units of <italic>Taq </italic>polymerase, and 10 pmol of each standard M13 primers: sense 5' GTAAAACGACGGCCAGTG 3' and antisense: 5' GGAAACAGCTATGACCATG 3'. The colony was taken directly from the plate and resuspended into the 20 μl PCR reaction by pipetting. 10 μl of the thermocycled PCR reaction was separated on .9% agarose stained with 10 μg/ml ethidium bromide.</p>", "<title>Restriction analysis colony screen</title>", "<p>The REN digestion excision assay follows pre-established methods, using the plasmid pBKOα [##REF##11370874##32##] (Fig. ##FIG##8##9##). pBKOα and a <italic>piggyBac </italic>expression helper plasmid are cotransfected into S2 cells and incubated. Plasmid DNA is recovered by modified Hirt extraction as detailed in the blue/white colony screen section of methods and transformed into <italic>E. coli </italic>cells. A portion of this recovered plasmid is digested with <italic>Bgl</italic>II to remove any helper and non-excised donor plasmids and plated on LB-Amp/X-gal/IPTG plates. Because excision removes the lacZ gene, white colonies are scored as excision events. A portion of the undigested Hirt extraction is also transformed and plated on LB-Amp/X-gal/IPTG plates and the number of blue colonies is scored as the total number of potential donor plasmids.</p>", "<p>10⁶S2 cells were allowed to adhere to the bottom of a 9.6 cm²cell culture well and transfected with 0.5 μg of phsp-pBac helper plasmid and 0.5 μg of pBKOα donor plasmid with Transfectin liposomal transfection reagent (Bio-Rad) according to manufacturer protocol in minimal S2 media (Gibco). Two wells were transfected per helper-donor pair. The transfection media remained on the cells overnight and was replaced with Schneider's complete media. At 24 hours post transfection the cells were heat shocked for 1 hour at 37°C. At 24 hours post heat shock the cells were harvested by Hirt extraction as detailed above and resuspended in 10 μl water. At this time the two individual samples were pooled and 2 μl of the DNA sample was digested with high activity <italic>Bgl</italic>II restriction enzyme (NEB) for 4 hours at 37°C, ethanol precipitated as above and resuspended in 22 μl water. The entire sample was transformed by electroporation into 3 μl <italic>E. coli </italic>DH10B (Invitrogen) in a 1 mm gap cuvette and recovered in 75 μl S.O.C. media (Invitrogen). 50 μl of sample was immediately plated onto two LB-Ampicillin plates prepared with IPTG and X-gal and incubated at 37°C for 16 hours. White colonies were picked and cultured overnight in 3 ml LB-Ampicillin broth. The DNA was extracted by crude boiling mini-prep and digested with <italic>Hind</italic>III restriction enzyme (NEB) and run on a 0.8% agarose gel to screen for positive excision events.</p>", "<p>For the background control 1 μl of the pooled Hirt extracted DNA was resuspended in 21 μl of water and transformed into 3 μl of DH10B <italic>E. coli </italic>and recovered in 75 μl of S.O.C. media. 5 μl of this preparation was immediately plated on two LB-Ampicillin agar plates containing IPTG and X-gal and incubated at 37°C for 16 hours and the blue colonies were counted.</p>", "<title><italic>piggyBac </italic>antibody</title>", "<p>5 ml of rabbit anti-serum was obtained from Proteintech Group, Inc. after injection with truncated <italic>piggyBac </italic>protein. The antiserum was subjected to 50% ammonium sulfate precipitation for 60 minutes at 4°C and centrifuged at 10,000 g for 60 minutes. After resuspending the ammonium sulfate pellet in 20 mM K₂HPO₄pH 6.8, 50% ammonium sulfate precipitation was performed again. After centrifugation, the resulting pellet was resuspended again and underwent buffer exchange in 20 mM K₂HPO₄using a Centriprep YM-50 (Fisher Scientific, St. Louis, MO) according to manufacturer's protocol. This was followed by concentration of the IgG protein fraction using a Centricon YM-50 (Fisher Scientific). The concentrated IgG fraction was further purified using a 15.5 mL DEAE Affi-Gel Blue Gel Column (Bio-Rad Laboratories, Hercules, CA) according to manufacturer's protocol. The elution buffer was 20 mM K₂HPO₄, 0.02% sodium azide pH 6.8. The eluted IgG anti-<italic>piggyBac </italic>antibody was concentrated using a Centricon YM-50 to a final concentration of 16.57 mg/mL as determined by optical density spectrophotometry at 280 nm on a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies Inc., Wilmington, DE). Anti-<italic>piggyBac </italic>antibody function was verified through western blotting of known positive and negative protein samples (data not shown).</p>", "<title>Western Blot</title>", "<p>S2 Cells were co-transfected as described above along with two additional samples containing 1 μg of either a mutant helper, phsp-pBac, as a positive control or a non-<italic>piggyBac </italic>expression plasmid as a negative control. 48 hours post-induction, the cells were collected and pelleted by centrifugation at 3,000 rpm for 2 minutes. This was followed by two 1 ml washes with 1× PBS. The resulting cell pellets were lysed by resuspending in 100 μl 2× Laemmli Sample Buffer containing 10 mM benzamidine, 10 mM sodium fluoride, 100 mM sodium vanadate, 1 mM phenylmethanesulphonylfluoride (PMSF), 25 μg/ml leupeptin, 25 μg/ml aprotinin, and 25 μg/mL pepstatin. The whole cell lysates were then sonicated on ice for 15 seconds. The protein concentration was measured by optical density spectrophotometry at 280 nm on a Nanodrop ND-1000 spectrophotometer.</p>", "<p>The whole cell lysates were prepared for electrophoresis on a 1.0 mm thick 7.5% acrylamide SDS-PAGE gel by diluting 125 μg of total protein to a total volume of 25 μl using 2× Laemmli sample buffer. This was followed by heating for 5 minutes at 95°C with 1.25 μl 2-mercaptoethanol to completely denature the protein. The samples were loaded onto two separate gels with 5 samples per gel and electrophoresed at 100V using 1× Tris-glycine plus 0.1% SDS as the running buffer. The protein standards used were Invitrogen's Benchmark Prestained protein ladder. After electrophoresis was complete, the separated proteins were transferred to a Hybond-ECL nitrocellulose membrane (Amersham Biosciences, Piscataway, NJ) using the Bio-Rad Mini Trans-Blot Cell and Module for 1 hour at 350 mAmps. 1× Tris-glycine with 20% methanol was the transfer buffer.</p>", "<p>Following transfer, the membranes were stained with Ponceau stain and subsequently destained with 5% acetic acid and 1× PBS washes (images not shown). The blots were blocked using 1× PBS plus 5% non fat dry milk for 2 hours while shaking at room temperature. The blots were subsequently probed for <italic>piggyBac </italic>protein expression using a 1/1000 dilution of anti-<italic>piggyBac</italic>, purification described above, or for actin using anti-actin I-19 (Santa Cruz Biotechnology, Santa Cruz, CA) in a 1/500 dilution with 1× PBS plus 0.1% Tween-20 (PBS-T) and 5% non-fat milk for one hour while shaking at room temperature. After the primary incubation, the blots were washed four times for five minutes each with 1× PBS-T. The secondary antibody, ECL rabbit IgG, HRP-linked whole antibody (Amersham Biosciences) or donkey anti-goat IgG-HRP (Santa Cruz Biotechnology), respectively, was added in a 1/5000 dilution with 1XPBS-T and 5% non-fat dry milk for one hour at room temperature while shaking. This was followed by washing with 1× PBS-T four times for five minutes each. The blots were developed with Pierce's SuperSignal West Dura Extended Duration Substrate kit (Pierce, Rockford, IL) according to manufacture protocol except 0.5 ml of each substrate was used per blot.</p>", "<title>Statistical analysis</title>", "<p>Data are expressed as a mean of three replicates +/- standard. ANOVA test was performed using GraphPad Prism 3.0 software. All values were adjusted to a positive control setting of 100%. Means were considered statistically significant when p-values less than 0.05 were obtained with the Dunnett's post-test. Statistical significance is indicated on all data figures as asterisks above bars.</p>" ]

[ "<title>Results</title>", "<title>Sequence alignment</title>", "<p>We performed a GenBank [##REF##18073190##50##] search for proteins closest in similarity to the wild-type <italic>Trichoplusia ni piggyBac </italic>transposase sequence. We chose hits from a wide variety of organisms for a sequence alignment by ClustalW (Table ##TAB##0##1##). We then exported the sequence alignment file and entered it into the BoxShade server [##UREF##6##51##] to more easily visualize any conserved residues or groups of residues.</p>", "<p>The sequence alignments (Fig. ##FIG##0##1##, ##FIG##1##2##, ##FIG##2##3##, ##FIG##3##4##, ##FIG##4##5##, ##FIG##5##6##, ##FIG##6##7##) immediately revealed several highly conserved features. Starting at the N-terminus of the transposase alignment, we noticed four conserved acidic residues: D32, D38, E45, and D49 (Fig. ##FIG##0##1##). The presence of either an aspartate or a glutamate at these positions does not seem to matter even within families; the acidic charge is the only conserved feature we can distinguish.</p>", "<p>The core of the transposase possesses clusters of conserved amino acids with very well defined borders for each conserved stretch. The first conserved cluster we identified begins shortly downstream of a conserved proline, P131, and may mark the beginning of a functional domain in <italic>piggyBac </italic>transposase family members. The next clusters of conservation lie roughly from P131 – N152, E175 – K190, and V207 – D228 (Fig. ##FIG##1##2##, ##FIG##2##3##). The region between D239 – Y259, while not particularly conserved in <italic>piggyBac </italic>itself, is conserved in other members of the family. Additionally, the next proline from this cluster, P261, starts another highly conserved region which includes the first member of the proposed 'DDD' triad, D268 (Fig. ##FIG##3##4##).</p>", "<p>The next group of conserved residues contains the second aspartate, D346 and an absolutely conserved glycine at position 369. G369 marks the start of the well conserved motif 'GTVRxNKRxIP' (Fig. ##FIG##4##5##). This motif ends with P379, possibly delineating the end of a functional domain. This motif is not present in its entirety in Uribo-2. However, the analogous sequence of Uribo-2 'GTINRNRKxLP' does preserve similar features.</p>", "<p>Downstream from this region is another conserved group that starts with a highly conserved proline at position 433. P433 is only a short distance from D447 and D450, the last two aspartates tested in our study, and is the start of another motif: 'PxxxxxxYxxxxGGVDxxD.' The aspartates in this motif are D447 and D450, respectively (Fig. ##FIG##4##5##, ##FIG##5##6##).</p>", "<p>A cysteine-rich domain overlapping with the <italic>piggyBac </italic>nuclear localization signal (NLS) is positioned at the C-terminus of <italic>piggyBac</italic>. The spacing between these cysteines is well conserved among <italic>piggyBac </italic>family members when present, even though the intervening amino acids are not. Additional cysteines also lie within this region, conforming to a novel zinc-finger domain in <italic>piggyBac </italic>[##UREF##7##52##,##REF##9923704##53##]. A basic amino charge at R568 is also well conserved (Fig. ##FIG##6##7##).</p>", "<title>Excision assay</title>", "<p>The excision activity of a nonautonomous <italic>piggyBac </italic>element from the donor plasmids pBKOα [##REF##11370874##32##] was assessed for 8 mutant transposases relative to the wild-type transposase (Fig. ##FIG##7##8##; Fig. ##FIG##8##9##). Plasmid DNA was extracted from transfected cell cultures and transformed into <italic>E. coli </italic>cells. As with previous assays [##REF##11370874##32##], the number of non-excised plasmids was reduced by restriction digestion of a site unique to the donor element. The large number of colonies precluded analysis of every transformant, but a representative cross section was chosen for analysis by restriction enzyme digestion. Positive events were further screened by sequence analysis. Only events that showed precise excision were tallied.</p>", "<p>In order to obtain the largest amount of data and to ascertain if differences in the donor plasmid had any effect on excision efficiency, a second assay employing a blue/white colony screen was developed using the Topo-TA vector backbone, pCR2.1-Topo (Invitrogen, Carlsbad, CA) to make the donor plasmid pCR2.1-<italic>piggyBac</italic>{SV40}. Precise excision events would restore the 'TTAA' sequence of the region between the two lacZ coding sequence fragments, allowing for the expression of a fully active β-Gal protein. This assay allowed rapid screening of large numbers of colonies and identified positive excision events (Fig. ##FIG##9##10##). A simple PCR of blue colonies confirmed that excision had occurred (Fig. ##FIG##10##11##). Subsequent sequencing of some of these blue colonies validated these findings.</p>", "<p>Our mutational analysis demonstrates that all members of the proposed triad, D268, D346, and D447, are required for efficient <italic>piggyBac </italic>catalyzed excision in a cellular environment. The additional amino acid targeted for mutational analysis, D450, has a primary requirement for a negative charge, since the asparagine replacement significantly inhibited excision, while a glutamate replacement yielded moderate excision, although not to the degree of the wild-type transposase.</p>", "<p>Even though the trends remained the same, a difference in overall excision efficiency between donor plasmids was also demonstrated. The pBKOα plasmid donor element was able to facilitate some level of excision for all mutant transposases except D447N (Fig. ##FIG##11##12##). In contrast, despite the larger number of colonies screened, pCR2.1-<italic>piggyBac</italic>{SV40} excision failed to yield events for D268E, D268N, D346E, and D447N (Fig. ##FIG##12##13##). When precise excision was catalyzed, all frequencies were less than that of the pBKOα counterpart when the same helper plasmid was utilized (Table ##TAB##1##2##). Incomplete digestion of the helper plasmid in the REN screen excision assay prior to plating (see: methods) may have been a contributing factor, leading to artifact colonies which would inflate the actual number of excised colonies. However, excision efficiency may be influenced by other factors, such as donor fragment size or the physical properties of the DNA at the excision sites. The size of the excision fragments of the two donor plasmids vary considerably: 6218 bp for pBKOα and 825 bp for pCR2.1-<italic>piggyBac</italic>{SV40}.</p>", "<title>Western blot</title>", "<p>A western blot was performed to ensure that full length <italic>piggyBac </italic>transposase was being produced from the expression vectors. This was done to verify that any mutant expression vectors unable to drive excision activity were a result of the mutations in the transposase and not for a lack of expression through faulty vectors. All mutant vectors expressed equivalent amounts of protein of approximately 68 kDa to which a polyclonal <italic>piggyBac </italic>antibody was able to bind. All lanes probed positive for actin, used as a loading control (Fig. ##FIG##13##14##).</p>" ]

[ "<title>Discussion</title>", "<p>Sarkar et al. suggested the presence of a 'DDD' motif for <italic>piggyBac</italic>, without empirical evidence of the association of the motif with mobility. Their proposal was based on two weak matches returned when two <italic>piggyBac </italic>related proteins, but not <italic>piggyBac </italic>itself, were used as a query in an NCBI Conserved Domain Search. These query hits were for the Pfam domain pfam01609 [##REF##12955498##48##]. The conserved D268 and D346 were thus matched to the bacterial <italic>IS</italic>4/5 transposase family DDE motif based on their degree of conservation in the transposase core and the presence of a glutamate immediately following D268, and an asparagine following D346. No reason for choosing D447 was cited, but both D447 and D450 are part of a highly conserved motif discussed below.</p>", "<p>Bigot and colleagues [##REF##8890745##54##] used a similar approach of transposase alignments to propose the existence of a 'DDE' motif in <italic>hAT </italic>elements, with the second aspartate replaced by a serine in <italic>Ac</italic>, <italic>hobo</italic>, and <italic>Hermes</italic>. They aligned members of the <italic>Tc1-mariner </italic>superfamily with members of the <italic>hAT </italic>family and identified conserved and similar residues common between both groups. The 'DSE' speculation has since been empirically disproven [##REF##12426102##55##]. However, of this 'DSE' triad, both D402 and E572 (with respect to <italic>Hermes</italic>) were essential for transposition while alteration of S535 to either an alanine or an aspartate had no statistically significant effect on transposition efficiency. This, at least, demonstrated the necessity for D402 and E572, but did not prove if either residue was part of an essential triad.</p>", "<p>Starting at the N-terminus of <italic>piggyBac </italic>there are four acidic amino acids: D32, D38, E45, and D49 that are present in most of the aligned proteins (Fig. ##FIG##0##1##). While charges are conserved at these positions, the residues themselves do not seem to have any requirement as to whether they are an aspartate or a glutamate. Interestingly, this interchangeability is particularly variable at these positions, even within closely related proteins, such as the <italic>piggyBac </italic>related proteins in three different species of <italic>Xenopus</italic>, and among the human <italic>piggyBac </italic>derived proteins (PGBD). Examination of <italic>piggyBac </italic>related transposons in <italic>Xenopus </italic>identified three elements, Uribo-1, Uribo-2, and Kobuta. Xtr-Uribo2_PCR_Iv1b proved to be a functional mobile element complete with transposase able to catalyze movement in GP293 cells [##REF##17934208##49##]. Kobuta, however, lacks excision activity. Xtr-Uribo2_PCR_Iv1b possesses a glutamate at <italic>piggyBac</italic>'s D32 and does not have a match for E45, even though other inactive <italic>Xenopus </italic>putative transposases, Uribo-1 and Kobuta, do have matches for E45. Additionally, these N-terminal acidic residues are spaced so closely together that they are unlikely to be the DDD/DDE triad in our opinion. Interestingly, both Uribo proteins contained analogs to D268, D346, and D447, while the inactive Kobuta protein contained only D346 as a rule with two divergent Kobuta examples also having the D268 residue. All <italic>Xenopus </italic>proteins also harbor the highly conserved D450 residue.</p>", "<p>Distinct clusters of conserved amino acids are present through the rest of the <italic>piggyBac </italic>family starting at P131 (Fig. ##FIG##1##2##). The fact that the first constellation of conservation begins with a proline is worth noting, as proline is known to disrupt the periodic structure of α-helices and β-sheets, often demarcating the protein from one functional domain to the next [##REF##8692877##56##]. Together with the adjacent region of conservation, we speculate that the area just downstream of P131 is most likely a functional domain in the transposase. A conserved domain search returns an extremely weak (e = .44) match to pfam02388, <italic>Staphylococcus </italic>proteins involved in formation of the peptidoglycan layer, a coincidence in our opinion.</p>", "<p>The <italic>piggyBac </italic>family analog to K246 is also a highly conserved proline, but as this amino acid is not present in <italic>piggyBac </italic>it is not required for a functional transposase (Fig. ##FIG##2##3##). However, P261, while less conserved than the K246 proline analogs, is present in both <italic>piggyBac </italic>and Uribo-2. It also lays just N-terminal of the very well conserved residues D268, the first member of the 'DDD' triad, and E269.</p>", "<p>The next cluster of conserved amino acids includes D346, the second member of the proposed 'DDD' triad (Fig. ##FIG##3##4##). Also in this region lies the only residue in the alignment that is absolutely conserved is G369 (Fig. ##FIG##4##5##). This glycine is the start of a nearly universally conserved motif among <italic>piggyBac </italic>related proteins: 'GTVRxNKRxIP.' While R372 is limited to arginine, the other two basic amino acids, K375 and R376, seem to be conserved only in charge, as some proteins use either arginine or lysine at these positions. When a basic amino acid occupies sites analogous to both position 375 and 376 in a protein, it is always one of each and never the same residue, except for <italic>Strongylocentrotus purpuratus </italic>which utilizes arginines in both locations. I378 is also another residue conserved only in properties, in this case hydrophobicity. Methionine, leucine, and isoleucine each are employed at this site with no clear pattern as to which is used outside of immediately related members. Finally, P379 does not seem to indicate the start of any highly conserved clusters, but it does lie at the end of a conserved cluster starting at approximately E331, possibly ending a functional domain in <italic>piggyBac</italic>. Of note, this motif is not present in its entirety in the functional transposase, Uribo-2. However, the analogous sequence of Uribo-2 'GTINRNRKxLP' does preserve similar features.</p>", "<p>The next highly conserved proline, P433, is located only a short distance from P379, just upstream of the third proposed aspartate, D447, and another highly conserved aspartate at D450 (Fig. ##FIG##4##5##). This proline delineates the start of one of the most highly conserved motifs we found in our alignment: 'PxxxxxxYxxxxGGVDxxD' which contains both D447 and D450. This motif is present in both <italic>piggyBac </italic>and Uribo-2 as well as most other members of our analysis. Among members where this motif is loosely present, G444 is replaced by an alanine in the silkworm Yabusame proteins, and G445 is replaced with an alanine in the human PGBD-4. P433 could mark the start of another required functional domain in <italic>piggyBac</italic>, and for this reason we decided to mutate both D447 and D450. In the more divergent proteins, mouse PGBD-5, human PGBD-5, human PGBD-1, <italic>Anopheles gambiae </italic>PGDB protein <ext-link ext-link-type=\"gen\" xlink:href=\"XP_312615\">XP_312615</ext-link>, and <italic>Ajellomyces capsulatus </italic>predicted protein <ext-link ext-link-type=\"gen\" xlink:href=\"XP_001599370\">XP_001599370</ext-link>, this motif is not fully present.</p>", "<p>The C-terminus of most <italic>piggyBac </italic>related proteins contains a cysteine-rich motif: C559, C562, C574, C577, and C582 (Fig. ##FIG##6##7##). The spacing between these residues is somewhat conserved even though the intervening residues are not. In <italic>piggyBac</italic>, this region is also a novel match for a RING-finger motif [##UREF##7##52##], a type of Zinc-finger which has been implicated in protein-protein interactions [##REF##9923704##53##]. The high degree of conservation in this region suggests a selective pressure for the presence and spacing of these cysteines. Recently, Mitra and colleagues [##UREF##5##34##] have suggested this Zinc-finger could in fact be a PHD finger, implicated in heterochromatin interactions. The ability of their purified transposase to function in an <italic>in vitro </italic>environment on free, unwound DNA despite the removal of this C-terminal domain is consistent with this hypothesis. The occurrence of a basic charged residue at R569 is also a commonality.</p>", "<p>In <italic>piggyBac</italic>, we have demonstrated that this area contains a functional NLS (aa 551–571) (in press). In fact, this region is so rich with basic amino acids, that 4 PSORTII [##REF##10087920##57##] predicted NLS matches exist in this short region: 2 monopartite at positions 551 and 563, and 2 bipartite signals at positions 554 and 555, respectively. Interestingly, this NLS cluster is not present in the functional Uribo-2 transposase, however a PSORT analysis of Uribo-2 shows it harbors a NLS matching a monopartite pattern beginning at P276, with respect to the Uribo-2 sequence.</p>", "<p>The excision assays reveal that substitution of D268, D346, D447, or D450 with either an asparagine or a glutamate impairs the function of the transposase from the donor plasmid pCR2.1-<italic>piggyBac</italic>{SV40}. In contrast, while the substitution D450E significantly impaired excision from pCR2.1-<italic>piggyBac</italic>{SV40}, it did not appear to have a statistically significant effect with regards to pBKOα. The reasons for this apparent difference reflect level of error inherent in the protocols between the two assays. For the REN colony screen, a randomly chosen representative cross section is cultured and digested from the colonies available. This method is prone to a larger amount of error as fewer colonies are screened for excision events. However, the blue/white colony screen permits the analysis of all the colonies on a plate for excision events. This provides a much larger population of donor plasmids to be analyzed and reduces the standard error.</p>", "<p>These four residues mutated in our study are far from the only conserved acidic amino acids in the <italic>piggyBac </italic>family alignment: the short cluster at the amino terminus previously discussed, as well as D141, E175, D249, and D300 are all conserved to a degree, and may be involved in transposition. Each of the mutations tested severely reduced or completely shut down excision activity of the transposase. Previous studies of acidic amino acids in <italic>Hermes </italic>support the idea that essential amino acids are not limited to just the three members of a proposed triad, as alterations to D180, D248, D402, and E572 in the <italic>Hermes </italic>transposase all affect transpositional activity [##REF##12426102##55##,##REF##15616554##58##].</p>", "<p>Here, we test only the excision step of the entire transposition reaction in a cell culture system. There are other possibilities that cannot be ruled out by our data, including the necessity of these residues in forming a functional secondary structure of the transposase. We cannot say for certain which specific parts of the excision process these mutations hinder. It is entirely possible that they are required for DNA binding or possibly the recruitment of auxiliary host factors. However, the reports of Mitra <italic>et al. </italic>[##UREF##5##34##] examining <italic>piggyBac </italic>in function an <italic>in vitro </italic>system suggests that the transposase alone may carry out all steps of transposition without any additional requirement for host factors. Substitution of D268, D346, and D447 with alanine does not inhibit specific binding of the transposase to the terminal repeats of <italic>piggyBac </italic>[##UREF##5##34##], but each of these mutations abrogates all steps of transposition, including 3' OH nicking and hairpin formation – both integral steps for excision. Furthermore, unlike wild type <italic>piggyBac</italic>, these mutants are defective for target joining when synapsed with an artificial excision fragment. Testing these mutants in a yeast system also demonstrated they were functionally defective [##UREF##5##34##]. The lack of catalytic activity in our D268, D346, and D447 mutant assays confirms the relevance of the observation of Mitra <italic>et al. </italic>to <italic>piggyBac </italic>movement in insect cell systems.</p>", "<p>In contrast, Mitra <italic>et al. </italic>demonstrate that D450A is still catalytically active in an <italic>in vitro </italic>environment, while our results show a definite interfering effect. One explanation for this discrepancy is that D450 is likely not a part of the metal interaction motif, but may be involved in the proper folding of the protein with limited tolerances for certain amino acids. Certainly, our findings support that D450 is the least critical of the four aspartates we tested, but is still necessary to a degree.</p>", "<p>Just because an amino acid is acidic and required for transposition does not automatically make it a member of a divalent metal interaction motif, nor does particular mutant interfere with all steps of transposition. An example of this can be found in a mutational study of the V(D)J recombination initiator, RAG1. In this experiment, a great number of acidic amino acids were mutated, some of which impaired cleavage activity. One of these mutations, E811Q, was deficient for DNA binding activity, a loss-of-function that could indirectly lead to decreased cleavage activity. This study also defined two classes of mutants: class I which retained a measure of cleavage activity, and class II which yielded no detectable cleavage products, even though they retained DNA binding activity [##REF##10601032##42##]. It is possible that alteration of D450 in <italic>piggyBac </italic>may be analogous to such a class I mutant.</p>", "<p>Another example of a mutant transposase deficient for specific steps of transposition would be the D248A mutant of <italic>Hermes</italic>, which was deficient for DSB activity. Upon further investigation, this mutant appeared to only be deficient in the first 5' nicking step of excision. When supplied with a pre-nicked substrate, it was able to facilitate hairpin formation and a measure of target joining in the presence of Mn²⁺, the second step of DSB and the final step of transposition, respectively [##REF##15616554##58##]. These examples illustrate that a number of steps exist in which a mutant could interfere with transposition, thereby decreasing the formation of the end product.</p>", "<p>Iron-induced hydroxyl radical protein cleavage is one direct test for metal binding activity [##REF##9214642##59##]. This assay takes advantage of the ability of Fe²⁺, in the presence of ascorbate or H₂O₂, to generate hydroxyl radicals. If the protein in question has the ability to bind Fe²⁺, then hydroxyl radicals will be generated at the sites where the ion is located. These radicals subsequently cleave the peptide backbone of the protein which bound the Fe²⁺, yielding cleavage products with sizes consistent with the location of the metal binding pockets. Regarding recombinases, this approach was used to narrow down the location of the metal binding residues of RAG1 prior to the generation of site-specific mutants [##REF##10601033##43##].</p>", "<p>Another common test for metal interaction is the replacement of either the aspartate or the glutamate with a cysteine [##REF##10373361##60##]. This test is based on the ability of glutamate and aspartate metal ligand residues to supply a carboxyl group for metal interaction. These amino acids use the oxygen on their R-chain as the interacting atom via O-Mg²⁺or O-Mn²⁺formation. However, interactions with Mn²⁺, but not Mg²⁺, are also able to occur using a cysteine via a S-Mn²⁺bond [##REF##6334536##61##]. Such an interaction can be analogous to the metal binding activities of glutamate and aspartate. For example, substitutions D180C, D248A, and D248C in <italic>Hermes </italic>all showed the ability to catalyze hairpin formation of substrate DNA in the presence of Mn²⁺during the excision step of transposition, but only D180C and D248A were able to complete the joining of the transpososome to target DNA. E572A and E572C left <italic>Hermes </italic>unable to facilitate any step of the transposition reaction [##REF##15616554##58##].</p>", "<p>Finally, much work has been done with X-ray crystallography on integrases, resolvases, and transposases at different stages of catalysis, including multimers, free floating proteins, and enzymes complexed with their target DNA. Direct resolution of these structures has been invaluable to the understanding of structure-function relationships. Indeed, the various studies have found structural similarities in the active sites of the recombinase family and nucleases, including the DDD/DDE metal binding motif for both one and two metal binding proteins [##REF##7628011##62##, ####REF##9177177##63##, ##REF##9311978##64##, ##REF##15102449##65##, ##REF##7628012##66##, ##REF##9735293##67##, ##REF##10884228##68##, ##REF##7563093##69####7563093##69##]. In light of what we and others have found [##UREF##5##34##] it would not be surprising to find <italic>piggyBac </italic>shared many features common to the recombinase family.</p>" ]

[ "<title>Conclusion</title>", "<p>The <italic>piggyBac </italic>family alignment revealed a number of interesting features in the transposase. Regions of high conservation in the catalytic core were sometimes demarcated by proline residues, possibility separating functional domains. Furthermore, we found four conserved acidic residues at the N-terminus of the transposase, and four more throughout the rest of the transposase. A cysteine-rich region with somewhat conserved spacing exists at the C-terminus and is a novel match for the RING finger protein-interaction motif. Our data indicate which of the four tested residues are essential for transposase-mediated excision from a donor plasmid in <italic>Drosophila </italic>cultured cells. Our donor plasmids yielded similar results, however a charge-preserving substitution from aspartate to glutamate was at least moderately tolerated at positions D450. The existence of an acidic charge was necessary at all four positions tested for both of our donor plasmids with a specific requirement for an aspartate at D268, D346, and D447. We conclude that the four amino acids tested are indeed vital for efficient excision of the <italic>piggyBac </italic>element from a donor plasmid in cell culture.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The <italic>piggyBac </italic>mobile element is quickly gaining popularity as a tool for the transgenesis of many eukaryotic organisms. By studying the transposase which catalyzes the movement of <italic>piggyBac</italic>, we may be able to modify this vector system to make it a more effective transgenesis tool. In a previous publication, Sarkar A, Sim C, Hong YS, Hogan JR, Fraser MJ, Robertson HM, and Collins FH have proposed the presence of the widespread 'DDE/DDD' motif for <italic>piggyBac </italic>at amino acid positions D268, D346, and D447.</p>", "<title>Results</title>", "<p>This study utilizes directed mutagenesis and plasmid-based mobility assays to assess the importance of these residues as the catalytic core of the <italic>piggyBac </italic>transposase. We have functionally analyzed individual point-mutations with respect to charge and physical size in all three proposed residues of the 'DDD' motif as well as another nearby, highly conserved aspartate at D450. All of our mutations had a significant effect on excision frequency in S2 cell cultures. We have also aligned the <italic>piggyBac </italic>transposase to other close family members, both functional and non-functional, in an attempt to identify the most highly conserved regions and position a number of interesting features.</p>", "<title>Conclusion</title>", "<p>We found all the designated DDD aspartates reside in clusters of amino acids that conserved among <italic>piggyBac </italic>family transposase members. Our results indicate that all four aspartates are necessary, to one degree or another, for excision to occur in a cellular environment, but D450 seems to have a tolerance for a glutamate substitution. All mutants tested significantly decreased excision frequency in cell cultures when compared with the wild-type transposase.</p>" ]

[ "<title>Authors' contributions</title>", "<p>JHK created the donor plasmids used in the blue/white colony screen, performed all aspects of the blue/white screen, performed the sequence alignment, BoxShade processing and alignment analysis, and prepared the manuscript. CAS performed the western blot and prepared parts of the manuscript dealing with the western blot. TSF performed all aspects of the REN colony screen. MJF conceived of the study and provided guidance.</p>" ]

[ "<title>Acknowledgements</title>", "<p>Many thanks to Meggan Keith for her help with the western blot. This research was funded by NIH grant RO1 AI48561 to Malcolm J. Fraser Jr.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 1–63 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 64–160 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 161–260 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 261–351 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks. The aspartate residues mutated in this study are highlighted in yellow.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 352–451 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks. The aspartate residues mutated in this study are highlighted in yellow.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 452–558 are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks.</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>Alignment of <italic>piggyBac</italic>-related proteins</bold>. A BoxShade server alignment of the proteins listed in table 1. Residues aligning with <italic>piggyBac </italic>position 559 through the c-terminus are shown. Only two <italic>piggyBac </italic>family proteins have been shown to catalyze transposition, these are indicated by bold face type and asterisks.</p></caption></fig>", "<fig position=\"float\" id=\"F8\"><label>Figure 8</label><caption><p><bold>Diagram of <italic>piggyBac </italic>ORF and genotypes used in this study</bold>. A diagrammatic representation of the <italic>piggyBac </italic>transposase mutant genotypes used in this study. The entire <italic>piggyBac </italic>ORF is displayed with the aspartates noted with their corresponding residue number. 4 × NLS represents 4 PSORT predicted nuclear localization patterns as described in discussion.</p></caption></fig>", "<fig position=\"float\" id=\"F9\"><label>Figure 9</label><caption><p><bold>Schematic of the REN colony screen</bold>. (A) The donor plasmid pBKOα is co-transfected with one of the <italic>piggyBac </italic>expression plasmids (fig. 8), transformed into <italic>E. coli </italic>and plated. (B) Precise excision of the <italic>piggyBac </italic>cassette removes the lacZ open reading frame. Digestion with <italic>Bgl</italic>II removes any excess <italic>piggyBac </italic>expression plasmids and donor plasmids which have not undergone excision. Excision events are scored as white colonies. Plating a portion of undigested plasmids and scoring blue colonies yields the total number of potential donor plasmids.</p></caption></fig>", "<fig position=\"float\" id=\"F10\"><label>Figure 10</label><caption><p><bold>Schematic of the blue/white colony excision assay</bold>. (A) The donor plasmid pCR2.1-<italic>piggyBac</italic>{SV40} is co-transfected with one of the <italic>piggyBac </italic>expression plasmids (fig. 8) transformed into <italic>E. coli </italic>and plated. (B) Precise excision of the <italic>piggyBac</italic>{SV40} cassette restores the original lacZ open reading frame at the original 'TTAA' insertion site. By plating on kanamycin media containing IPTG and X-gal, only <italic>E. coli </italic>containing donor plasmids will develop into colonies. Colonies which are blue represent excision events, while the number of blue and white colonies represents the total number of potential donor plasmids.</p></caption></fig>", "<fig position=\"float\" id=\"F11\"><label>Figure 11</label><caption><p><bold>PCR analysis of donor plasmid sizes from the blue/white colony screen</bold>. PCR of 10 white (negative, top row) colonies and 10 blue (positive, bottom row) colonies, randomly chosen, from the blue/white colony screen is shown on a .9% TAE agarose gel stained with ethidium bromide. The amplicon crosses the entire donor fragment. Expected band size for the pre-excision plasmid is 1027 bp and 202 bp for the post-excision donor plasmid amplicon.</p></caption></fig>", "<fig position=\"float\" id=\"F12\"><label>Figure 12</label><caption><p><bold>Relative frequency of excision obtained with the REN colony screen</bold>. Positive control, wild-type <italic>piggyBac</italic>, is set to 100. Data are expressed as a mean of three replicates +/- standard error bars. ANOVA test was performed using GraphPad Prism 3.0 software. Means were considered statistically significant when p-values less than 0.05 were obtained with the Dunnett's post-test. Statistical significance of difference with regards to positive control is indicated on all data figures as asterisks above bars. (p &lt; 0.05)</p></caption></fig>", "<fig position=\"float\" id=\"F13\"><label>Figure 13</label><caption><p><bold>Relative frequency of excision obtained with the Blue/White colony screen</bold>. Positive control, wild-type <italic>piggyBac</italic>, is set to 100. Data are expressed as a mean of three replicates +/- standard error bars. ANOVA test was performed using GraphPad Prism 3.0 software. Means were considered statistically significant when p-values less than 0.05 were obtained with the Dunnett's post-test. Statistical significance of difference with regards to positive control is indicated on all data figures as asterisks above bars. (p &lt; 0.05)</p></caption></fig>", "<fig position=\"float\" id=\"F14\"><label>Figure 14</label><caption><p><bold>Western blot of <italic>piggyBac</italic> mutant transposases</bold>. A western blot was performed on each <italic>piggyBac</italic> mutant with 125 μg total cell lysate per lane. The top row was probed with anti-<italic>piggyBac </italic>antibody and indicates the presence of the <italic>piggyBac </italic>transposase at 68 kDa in each mutant, the positive control, phsp-pBac, and a lack of transposase in the negative control. The bottom row was probed for actin, a 43 kDa protein, using anti-actin I-19 and shows equal loading in all lanes.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Proteins used in the alignment</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Accession</bold></td><td align=\"left\"><bold>Taxon</bold></td><td align=\"left\"><bold>Protein Name</bold></td></tr></thead><tbody><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"J04364\">J04364</ext-link></td><td align=\"left\">Trichoplusia ni</td><td align=\"left\">piggyBac</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"AAM76341\">AAM76341</ext-link></td><td align=\"left\">Daphnia pulicara</td><td align=\"left\">Pokey 6.6 kb</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"AAM76342\">AAM76342</ext-link></td><td align=\"left\"><italic>Daphnia pulicara</italic></td><td align=\"left\">Pokey 5 kb</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"ABS18391\">ABS18391</ext-link></td><td align=\"left\"><italic>Helicoverpa armigera</italic></td><td align=\"left\">transposase</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAD07480\">BAD07480</ext-link></td><td align=\"left\"><italic>Bombyx mori</italic></td><td align=\"left\">Yabusame-w</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAD11135\">BAD11135</ext-link></td><td align=\"left\"><italic>Bombyx mori</italic></td><td align=\"left\">Yabusame-1</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAD11136\">BAD11136</ext-link></td><td align=\"left\"><italic>Bombyx mori</italic></td><td align=\"left\">Yabusame-2</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAF82017\">BAF82017</ext-link></td><td align=\"left\"><italic>Xenopus laevis</italic></td><td align=\"left\">Kobuta</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAF82019\">BAF82019</ext-link></td><td align=\"left\"><italic>Xenopus tropicalis</italic></td><td align=\"left\">Uribo-1</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAF82020\">BAF82020</ext-link></td><td align=\"left\"><italic>Xenopus laevis</italic></td><td align=\"left\">Uribo-1</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAF82021\">BAF82021</ext-link></td><td align=\"left\"><italic>Xenopus borealis</italic></td><td align=\"left\">Uribo-1</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"BAF82022\">BAF82022</ext-link></td><td align=\"left\"><italic>Xenopus tropicalis</italic></td><td align=\"left\">Uribo-2</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CAF99963\">CAF99963</ext-link></td><td align=\"left\"><italic>Tetraodon nigroviridis</italic></td><td align=\"left\">Unnamed Product</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"CAI18712\">CAI18712</ext-link></td><td align=\"left\"><italic>Homo sapiens</italic></td><td align=\"left\">PGBD-2</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"NP_689808\">NP_689808</ext-link></td><td align=\"left\"><italic>Homo sapiens</italic></td><td align=\"left\">PGBD-4</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"NP_741958\">NP_741958</ext-link></td><td align=\"left\"><italic>Mus musculus</italic></td><td align=\"left\">PGBD-5</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"Q8N328\">Q8N328</ext-link></td><td align=\"left\"><italic>Homo sapiens</italic></td><td align=\"left\">PGBD-3</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"Q8N414\">Q8N414</ext-link></td><td align=\"left\"><italic>Homo sapiens</italic></td><td align=\"left\">PGBD-5</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"Q96JS3\">Q96JS3</ext-link></td><td align=\"left\"><italic>Homo sapiens</italic></td><td align=\"left\">PGBD-1</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_001030237\">XP_001030237</ext-link></td><td align=\"left\"><italic>Tetrahymena thermophila</italic></td><td align=\"left\">Predicted protein</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_001541487\">XP_001541487</ext-link></td><td align=\"left\"><italic>Ajellomyces capsulatus</italic></td><td align=\"left\">Predicted protein</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_001599370\">XP_001599370</ext-link></td><td align=\"left\"><italic>Nasonia vitripennis</italic></td><td align=\"left\">Predicted protein</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_312615\">XP_312615</ext-link></td><td align=\"left\"><italic>Anopheles Gambiae</italic></td><td align=\"left\">PGBD</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_590785\">XP_590785</ext-link></td><td align=\"left\"><italic>Bos taurus</italic></td><td align=\"left\">Predicted protein</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_699416\">XP_699416</ext-link></td><td align=\"left\"><italic>Danio rero</italic></td><td align=\"left\">Predicted protein</td></tr><tr><td align=\"left\"><ext-link ext-link-type=\"gen\" xlink:href=\"XP_797885\">XP_797885</ext-link></td><td align=\"left\"><italic>Strongylocentrotus purpuratus</italic></td><td align=\"left\">Predicted protein</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Excision frequencies for donor plasmids</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\">Blue-White</td><td align=\"center\" colspan=\"2\">REN Screen</td></tr><tr><td/><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\">Mutant</td><td align=\"right\">Excision Frequency</td><td align=\"right\">+/- SE</td><td align=\"right\">Excision Frequency</td><td align=\"right\">+/- SE</td></tr></thead><tbody><tr><td align=\"left\">D268E</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td><td align=\"right\">9.96E-03</td><td align=\"right\">3.73E-03</td></tr><tr><td align=\"left\">D268N</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td><td align=\"right\">8.03E-05</td><td align=\"right\">4.73E-05</td></tr><tr><td align=\"left\">D346E</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td><td align=\"right\">8.97E-05</td><td align=\"right\">4.90E-05</td></tr><tr><td align=\"left\">D346N</td><td align=\"right\">2.97E-05</td><td align=\"right\">1.49E-05</td><td align=\"right\">3.62E-04</td><td align=\"right\">2.02E-04</td></tr><tr><td align=\"left\">D447E</td><td align=\"right\">4.44E-05</td><td align=\"right\">8.54E-06</td><td align=\"right\">2.40E-04</td><td align=\"right\">1.84E-04</td></tr><tr><td align=\"left\">D447N</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td><td align=\"right\">3.99E-04</td><td align=\"right\">2.93E-04</td></tr><tr><td align=\"left\">D450E</td><td align=\"right\">8.80E-04</td><td align=\"right\">1.36E-04</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td></tr><tr><td align=\"left\">D450N</td><td align=\"right\">1.38E-05</td><td align=\"right\">1.38E-05</td><td align=\"right\">1.25E-03</td><td align=\"right\">0.00E+00</td></tr><tr><td align=\"left\">+ctrl</td><td align=\"right\">1.40E-02</td><td align=\"right\">2.12E-03</td><td align=\"right\">3.15E-03</td><td align=\"right\">8.86E-04</td></tr><tr><td align=\"left\">-ctrl</td><td align=\"right\">0.00E+00</td><td align=\"right\">0.00E+00</td><td align=\"right\">00E+00</td><td align=\"right\">0.00E+00</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>GenBank accession number, taxon, common name, and protein name of the proteins used in the ClustalW alignment.</p></table-wrap-foot>", "<table-wrap-foot><p>Values obtained for the frequency of excision using the two different donor plasmids with each of the mutant transposases. These numbers are normalized to a positive control frequency of 100%.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2199-9-73-1\"/>", "<graphic xlink:href=\"1471-2199-9-73-2\"/>", "<graphic xlink:href=\"1471-2199-9-73-3\"/>", "<graphic xlink:href=\"1471-2199-9-73-4\"/>", "<graphic xlink:href=\"1471-2199-9-73-5\"/>", "<graphic xlink:href=\"1471-2199-9-73-6\"/>", "<graphic xlink:href=\"1471-2199-9-73-7\"/>", "<graphic xlink:href=\"1471-2199-9-73-8\"/>", "<graphic xlink:href=\"1471-2199-9-73-9\"/>", "<graphic xlink:href=\"1471-2199-9-73-10\"/>", "<graphic xlink:href=\"1471-2199-9-73-11\"/>", "<graphic xlink:href=\"1471-2199-9-73-12\"/>", "<graphic xlink:href=\"1471-2199-9-73-13\"/>", "<graphic xlink:href=\"1471-2199-9-73-14\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Previous epidemiologic and clinical evidence indicate that a poor cardiorespiratory fitness is a major risk factor for life-style related diseases (LSRD) such as obesity, hypertension, hypercholesterolaemia, arteriosclerosis and diabetes [##REF##8403528##1##, ####REF##14514602##2##, ##REF##11187415##3##, ##REF##10068380##4####10068380##4##]. Moreover, low cardiorespiratory fitness has been found to be a predictor of cardiovascular disease (CVD) mortality, and all-cause mortality [##REF##8667564##5##, ####REF##10546694##6##, ##REF##11893790##7##, ##REF##11268224##8####11268224##8##]. Thus, it is essential to maintain a high level of cardiorespiratory fitness to prevent LSRD.</p>", "<p>Cardiovascular fitness is usually evaluated as the maximal oxygen uptake per body mass (<italic>V</italic>o₂max, mL·kg^-1·min^-1). The Japanese Ministry of Health Labour and Welfare in 2006 proposed <italic>V</italic>o₂max reference values for each age group to prevent LSRD [##UREF##0##9##]. These <italic>V</italic>o₂max reference values were determined by the \"Committee for the Determination of the Recommended Exercise Allowance and Exercise Guide\" established in August 2005, and were referenced in the \"Exercise and Physical Activity Reference Quantity for Health Promotion 2006 (EPAR2006)\". Originally, the \"Recommended Quantity of Exercise for Health Promotion (1989)\" had been formulated to mainly target the prevention of coronary artery disease. With the passage of more than 15 years following the establishment of this standard, the morbidity pattern of people has worsened and LSRD have increased in prevalence. In order to face this situation, the EPAR2006 was made based on the latest scientific evidence, and was designed to maintain and promote the health of people and prevent LSRD by improving their capacity for physical activity and exercise. These <italic>V</italic>o₂max reference values proposed in the EPAR2006 were determined by experts through the systematic review of literature regarding the relationship between <italic>V</italic>o₂max and LSRD such as obesity, hypertension, hypercholesterolemia, diabetes, cerebrovascular disease, CVD mortality and all-cause mortality.</p>", "<p>It is well known that <italic>V</italic>o₂max decreases with age [##REF##13794892##10##, ####REF##1141670##11##, ##REF##7153117##12##, ##REF##8002510##13##, ##REF##8832543##14##, ##REF##9390967##15##, ##REF##11509497##16##, ##REF##11584034##17##, ##REF##3493922##18##, ##REF##3182484##19##, ##REF##15047671##20####15047671##20##]. It has been suggested that the age-related decline in <italic>V</italic>o₂max is a consequence of attenuation of central and peripheral functions such as stroke volume, heart rate max (HR_max), peripheral O₂extraction, and lean body mass (LBM) or muscle mass [##REF##3182484##19##,##REF##2708223##21##, ####REF##7327965##22##, ##REF##4008419##23##, ##REF##9134886##24##, ##REF##16497840##25####16497840##25##]. Among these determinants, reductions in HR_maxand LBM or muscle mass have been suggested to be primary factors [##REF##11581561##26##,##REF##12974656##27##]. While many studies on cardiovascular fitness have focused on cardiac measurements, it should be emphasized that muscle mass is one of the critical determinants of <italic>V</italic>o₂max [##REF##8002510##13##,##REF##8832543##14##,##REF##3182484##19##,##REF##9134886##24##,##REF##11581561##26##,##REF##15778898##28##, ####REF##7898326##29##, ##REF##17115179##30####17115179##30##] since the amount of tissue available to extract oxygen during maximal exercise, i.e., muscle, can directly contribute to the value of <italic>V</italic>o₂max. For example, Sanada et al. reported the MRI-measured lower body skeletal muscle mass was closely associated to the absolute <italic>V</italic>o₂max during running [##REF##15778898##28##,##REF##17115179##30##]. Additionally, the age-related decrement in <italic>V</italic>o₂max can be related to the age-associated muscle loss [##REF##9134886##24##,##REF##3182484##19##]. Further, it is important to notice that LBM or muscle mass can be maintained to some degree by exercise training, while such training cannot prevent age-related declines in HR_max, [##REF##11581561##26##,##REF##12974656##27##].</p>", "<p>Therefore, we hypothesized that a certain level of muscle mass required to maintain sufficient cardiovascular fitness is present and that it could be a limiting factor of age-related <italic>V</italic>o₂max attenuation. Based on this hypothesis, it is advantageous to Japanese women's health to propose such muscle mass required to maintain sufficient <italic>V</italic>o₂max. Thus, the purpose of this study was to determine a required value of muscle mass to maintain the <italic>V</italic>o₂max reference value determined by the Japanese Ministry of Health Labour and Welfare in 2006 (Ministry of Health, Labour and Welfare of Japan 2006).</p>" ]

[ "<title>Methods</title>", "<title>Subjects</title>", "<p>A group of 403 Japanese women aged 20 to 69 years were randomly allocated to either a validation group (V-group, n = 201) or a cross-validation group (CV-group, n = 202). The subjects were recruited from the community around the National Institute of Health and Nutrition. All subjects were active and free of overt CVD assessed using a medical history questionnaire. All assessments were conducted at the National Institute of Health and Nutrition between February 2004 and October 2006. The study was approved by the Ethics Committee of the National Institute of Health and Nutrition, and written consent was obtained from all participants.</p>", "<title>Percentage of muscle mass</title>", "<p>The lean soft tissue mass of legs and arms were measured with a whole-body Dual Energy X-ray Absorptiomettry (DXA) scanner (Hologic QDR-4500, Hologic INC., Waltham, MA, USA). The body regions were delineated according to specific anatomical landmarks using manual DXA analysis software (version11.2.3). The appendicular lean soft tissue mass was calculated as a sum of the lean soft tissue mass of the legs and the arms. The lean soft tissue mass of extremities assessed using DXA was assumed to represent appendicular skeletal muscle mass along with a small and relatively constant amount of skin and underlying connective tissues. The percentage of muscle mass (%MM) was calculated as follows;</p>", "<p></p>", "<title><italic>V</italic>o_2max</title>", "<p>We assessed peak oxygen uptake (<italic>Vo</italic>_{2<italic>peak</italic>}: mL·kg^-1·min^-1) instead of <italic>Vo</italic>_{2<italic>max </italic>}as an index of cardiorespiratory fitness, which is defined as the highest level of oxygen uptake that is determined by the protocol of a graded exercise load. The <italic>Vo</italic>_{2<italic>peak </italic>}was measured using the incremental cycle exercise. An initial work intensity of 30 W or 60 W was selected for each patient based on the patient's fitness level. The work intensity was increased thereafter by a step of 15 W/min, until the subject was not able to maintain the required pedaling frequency of 60 rpm. The heart rate and rating of perceived exertion (RPE) were monitored throughout the exercise. The O₂consumption and the minute ventilation were monitored during each 1-min exercise stage (two 30 sec samplings for each stage), after RPE reached 18. The expired air was collected using Douglas bags. Expired O₂and CO₂gas concentrations were measured using a mass spectrometer (ARCO-1000A, ARCO SYSTEM, Chiba, Japan), and gas volume was measured using a dry gas meter (DC-5C Shinagawa Seiki, Tokyo, Japan). If the subject became exhausted and was not able to keep the pedaling frequency at 60 rpm, it was decided that the maximum effort had been achieved and the test was terminated. The highest value of <italic>Vo</italic>₂during the exercise test was designated as <italic>Vo</italic>_{2<italic>peak</italic>}. Note that the oxygen uptake obtained in this procedure is referred to as <italic>Vo</italic>_{2<italic>peak</italic>}, to discriminate this from <italic>Vo</italic>_{2<italic>max </italic>}in the strict definition. However, we equate the obtained <italic>Vo</italic>_{2<italic>peak </italic>}to <italic>Vo</italic>_{2<italic>max </italic>}in the present study since the <italic>Vo</italic>_{2<italic>max </italic>}reference value was determined using both <italic>Vo</italic>_{2<italic>max </italic>}and <italic>Vo</italic>_{2<italic>peak </italic>}as mentioned in the next section.</p>", "<title><italic>Vo</italic>_2maxkreference values</title>", "<p>The Japanese Ministry of Health Labour and Welfare proposed <italic>V</italic>o₂max reference values to prevent life-style related illness for women [##UREF##0##9##]. The <italic>Vo</italic>_{2<italic>max </italic>}reference values are provided for each age group. The procedure to determine <italic>Vo</italic>_{2<italic>max </italic>}reference values was described in the EPARQ2006 [##UREF##0##9##]. In brief, these <italic>Vo</italic>_{2<italic>max </italic>}reference values were determined by experts through a systematic review of literature. The target age was 6 years and older. The target LSRD were obesity, hypertension, hyperlipemia, diabetes mellitus, cerebrovascular disorders, death due to circulatory diseases, osteoporosis, ADL and total mortality. By means of this systematic review, the threshold values of the <italic>Vo</italic>_{2<italic>max </italic>}or <italic>Vo</italic>_{2<italic>peak </italic>}at which the morbidity of LSRD statistically increases in each age group were collected from the literature. The average values of these threshold values for each age group were then calculated and designated as the <italic>Vo</italic>_{2<italic>max </italic>}reference values for preventing LSRD. The identified <italic>Vo</italic>_{2<italic>max </italic>}reference values (mL·kg^-1·min^-1) were 33 (20–29 yr), 32 (30–39 yr), 31 (40–49 yr), 29 (50–59 yr), and 28 (60–69 yr).</p>", "<title>Analyses</title>", "<p>First, a single regression analysis was used to test the correlation between age and <italic>V</italic>o₂max, and between %MM and <italic>V</italic>o₂max in V-group. Then, a multiple regression analysis was performed using <italic>V</italic>o₂max as a dependent variable, and age and %MM as the independent variables. This analysis was based on the hypothesis that <italic>V</italic>o₂max can be accounted for by age and %MM. In this hypothesis, we assumed that the age factor included <italic>V</italic>o₂max determinant factors related to aging except for muscle mass, such as HR_max, maximal stroke volume, and peripheral O₂extraction [##REF##2708223##21##, ####REF##7327965##22##, ##REF##4008419##23####4008419##23##,##REF##16497840##25##,##REF##12974656##27##]. The validity of the prediction by the obtained regression equation was tested by applying the obtained regression equation to the CV-group. After the equation was cross-validated, the data from the two groups were pooled together to obtain the final prediction equation and in the subsequent analysis.</p>", "<p>The purpose of the final prediction equation was to obtain the required %MM to maintain the reference <italic>V</italic>o₂max value in each age group. Thus, the required %MM for each subject was recalculated by assigning the <italic>V</italic>o₂max reference values and age in the final prediction equation. If the difference of the required %MM among the age groups was very small, the mean value of the required %MM was calculated to be used in the following analysis. To test the validity of the required %MM, the correlation between the sufficiency of <italic>V</italic>o₂max, i.e., individual's <italic>V</italic>o₂max as the percentage of the <italic>V</italic>o₂max reference values (% <italic>V</italic>o₂max reference values), and the sufficiency of the required %MM, i.e., individual's %MM as the percentage of the required %MM (%required-%MM), were tested.</p>", "<p>All data are reported as means ± standard deviations (SD). <italic>P </italic>&lt; 0.05 was used as a level of significance for all comparisons.</p>" ]

[ "<title>Results</title>", "<title>Physiological characteristics</title>", "<p>The physiological characteristics for each group are shown in Table ##TAB##0##1##. There were no significant physiological differences between V-group and CV-group.</p>", "<title>Relationship between age and Vo₂max in V-group</title>", "<p><italic>V</italic>o₂max in V-group was from 16.4 to 56.9 ml.kg^-1min^-1(mean 33.5 ± 7.9) (Table ##TAB##0##1##). As expected, a strong negative linear correlation was found between <italic>V</italic>o₂max and age (Figure ##FIG##0##1##). The decrement was 2.58 ml.kg^-1min^-1per decade. The <italic>V</italic>o₂max reference values for each age group in the EPAR2006 were superimposed in Figure ##FIG##0##1##. With increasing age, the proportion of subjects with <italic>V</italic>o₂max values below the reference <italic>V</italic>o₂max values increased.</p>", "<title>Relationship between Vo₂max and %MM in V-group</title>", "<p>%MM in V-group was from 18.7 to 37.3% (mean 30.3 ± 3.2%) (Table ##TAB##0##1##). There was also a strong correlation between <italic>V</italic>o₂max and %MM, while the correlation was positive (Figure ##FIG##1##2##).</p>", "<title>Multiple-regression analysis in V-group</title>", "<p>Multiple regression analysis in V-group revealed that age (R²= 0.286) and %MM (R²= 0.540) were significant (p &lt; 0.0001) contributors to the prediction of the measured <italic>V</italic>o₂max. The multiple regression equation obtained in the V-group was the following: <italic>V</italic>o₂max = -0.135 × Age + 1.315 × %MM -0.799. In this equation, R²and SEE were 0.522 and 5.4 mL·kg^-1·min^-1, respectively.</p>", "<title>Cross-validation of the multiple regression equation</title>", "<p>The multiple regression equation derived from the V-group was used to predict <italic>V</italic>o₂max in the CV-group. Figure ##FIG##2##3## shows the residual plot. There was not statistically significant correlation between the predicted <italic>V</italic>o₂max and residual error (p &gt; 0.05). Thus, the residual plot indicates that there was no bias in the prediction of <italic>V</italic>o₂max of the CV-group using the multiple regression obtained in the V-group.</p>", "<title>Final prediction equation</title>", "<p>Data from the two groups were pooled to generate the final equations:</p>", "<p></p>", "<p>In the final equation, analysis revealed that age (R²= 0.282) and %MM (R²= 0.570) were significant (p &lt; 0.0001) independent contributors to the prediction of the measured <italic>V</italic>o₂max. Figure ##FIG##3##4## shows the residual plot of the multiple-regression. There was no statistically significant correlation between the predicted <italic>V</italic>o₂max and residual error (p &gt; 0.05). Thus, the residual plot indicates that there was no bias in the prediction of <italic>V</italic>o₂max.</p>", "<title>Estimation of the required %MM</title>", "<p>The equation (1) was rearranged to predict required %MM as follow;</p>", "<p></p>", "<p>The required %MM was calculated by assigning the <italic>V</italic>o₂max reference values, and age in the equation (2). The calculated required %MM was shown in Table ##TAB##1##2##. The mean value and standard deviation of required %MM was 28.5 ± 0.35%. Figure ##FIG##4##5## shows the relationship between the measured %MM and age with the required %MM superimposed on the plot. The older people tended to have a %MM lower than the required. With increasing age, the proportion of subjects with %MM below the required %MM increased.</p>", "<title>The validity of the required %MM</title>", "<p>Figure ##FIG##5##6## shows the relationship between %<italic>V</italic>o₂max reference values and %required-%MM. The %<italic>V</italic>o₂max reference values positively correlated with %required-%MM (r = 0.651, p &lt; 0.05).</p>" ]

[ "<title>Discussion</title>", "<p>The primary finding of the present study is that appendicular muscle mass of 28.5% of body weight is needed to maintain the <italic>V</italic>o₂max reference values determined by the Japanese Ministry of Health Labour and Welfare in Japanese women. By use of the multiple-regression analysis, the regression equation of <italic>V</italic>o₂max from age and %MM was obtained in the V-group at first. Then the validity of the regression equation was confirmed in the CV-group (Figure ##FIG##2##3##). The required %MM to maintain the <italic>V</italic>o₂max reference values was obtained using the final regression equation using the data of V- and CV-groups (equation (2)) and the <italic>V</italic>o₂max reference values for each age group (Table ##TAB##1##2##). There was strong correlation between percentages of the required %MM and <italic>V</italic>o₂max reference values (Figure ##FIG##5##6##).</p>", "<title>Required muscle mass</title>", "<p>We propose the required %MM in Japanese women as a reference value of muscle mass for the usage of maintaining the reference value of <italic>V</italic>o₂max proposed by the Ministry of Health Labour and Welfare of Japan. Interestingly, the calculated required %MM was not different among age groups (Table ##TAB##1##2##). Thus, we proposed the averaged required muscle mass (28.5%) as the general value for all age groups. A large portion of the subjects (68%) satisfied the required muscle mass, while with increasing age, the proportion of subjects with %MM below the required %MM increased (Figure ##FIG##4##5##). This tendency was similar to <italic>V</italic>o₂max, i.e., with increasing age, the proportion of subjects with <italic>V</italic>o₂max values below the reference <italic>V</italic>o₂max values increased (Figure ##FIG##0##1##). Additionally, there was strong positive relation between percentages of <italic>V</italic>o₂max reference values and required %MM (Figure ##FIG##5##6##). The results indicate that subjects with total muscle mass lower than 100% of the required %MM also tended to have lower <italic>V</italic>o₂max when compared to levels of <italic>V</italic>o₂max reference values. Thus, our result suggests that one of the reasons for insufficient <italic>V</italic>o₂max may be insufficient %MM. Women who have %MM less than the required %MM are encouraged to increase their %MM above the required %MM to achieve the <italic>V</italic>o₂max reference values. The required %MM can be used as an additional parameter for preventing LSRD together with the <italic>V</italic>o₂max reference values. The required %MM obtained in this study is practical and appropriate for most Japanese women, because it is slightly less than the average %MM of the total number of subjects. Thus, the value is an achievable goal for most of Japanese women. Although strength training is not typically included in exercise programs targeting prevention of the age-related decline in <italic>V</italic>o₂max or to increase <italic>V</italic>o₂max, it would be advisable to recommend some form of strength training as well as aerobic training especially for individuals who do not achieve the required %MM.</p>", "<p>Several prior studies demonstrated the significance of fat free mass, muscle mass, and/or muscle function to morbidity and mortality, although there are few researches targeting women [##REF##11896498##31##, ####REF##10702748##32##, ##REF##12036820##33####12036820##33##]. The Japanese Ministry of Health Labour and Welfare also has admitted the importance of muscle mass and muscle function to prevent LSRD and/or mortality in EPAR2006. However practical target values have not been offered in the statement due to the lack of evidences compared to <italic>V</italic>o₂max. In this present study we determined the target value of muscle mass through the <italic>V</italic>o₂max reference values, which already has strong evidences. Although we have not confirmed the direct relation between muscle mass and LSRD morbidity and/or mortality, we believe Japanese women could aim to achieve the required %MM as one of targets for their health. Whether an increase of skeletal muscle mass would result in an improvement of exercise capacity and or reduce morbidity and mortality needs to be confirmed by future studies.</p>", "<p>It should note that some individuals may have a large muscle mass, yet be at a high mortality risk. For example, it is well known that central obesity is one of risk factor of LSRD morbidity. Thus, it is important to remember that muscle mass is not the only important parameter but also, other risk factor should be monitored and considered together.</p>", "<title>Prediction of Vo2max from age and muscle mass</title>", "<p>The residuals of the multiple regression might be due to the approximation that all age-related determinant factors were included in age in the multiple regression. In the present model, we hypothesized that determinants such as HR_max, maximal stroke volume, and peripheral O₂extraction were age-related, and therefore their effects were included in the factor of age. It was suggested that HR_max[##REF##8832543##14##,##REF##7327965##22##,##REF##11581561##26##,##REF##7898326##29##,##REF##10331888##34##, ####REF##4770349##35##, ##REF##3558232##36##, ##REF##2262469##37##, ##REF##8847316##38##, ##REF##12015340##39####12015340##39##] and peripheral O₂extraction [##REF##2708223##21##,##REF##10331888##34##] do decline with age, and are not influenced by exercise training. However, although maximum stroke volume was also suggested to decline with age in sedentary individuals [##REF##4008419##23##], it was suggested that age-related decline of maximum stroke volume was prevented by exercise [##REF##2708223##21##,##REF##10331888##34##]. Thus, the simplification must be the error factor, and it is likely in future to improve the multiple regression equations using these age-related <italic>V</italic>o₂max determinants, and to improve the estimation of the required MMI.</p>", "<p>We studied only a statistical relationship between <italic>V</italic>o₂max and muscle mass. Therefore, the results do not necessarily suggest a cause-effect relationship. It is possible that muscle mass and <italic>V</italic>o₂max are physiologically unrelated but indirectly correlated, i.e., people with a high <italic>V</italic>o₂max may be more physically active and perform activities that increase muscle mass. However, muscle mass is highly likely physiologically important determinant of <italic>V</italic>o₂max because the amount of tissue available to extract oxygen during maximal exercise directly contribute to the value of <italic>V</italic>o₂max.</p>", "<title>Study limitations</title>", "<p>The current study has limitations that require caution when interpreting and generalizing the findings reported herein. This study included only the cross-sectional design, and it did not investigate the relationship between the required %MM and the morbidity of LSRD or mortality by using a prospective design. Thus, it has not been clarified how the required %MM reflects these risks in this present study. Further investigation is required to validate the required %MM through a prospective study with the morbidity and/or mortality as an endpoint. Additionally, the potential difference between methods using %MM or absolute muscle mass (kg) as the indicator of health should be also investigated. Another limitation of this study is the results of this study are applicable to only Japanese women. The decided %MM in this study may not be able be applicable to men and/or other racial group since they may have different characteristics of the relationship between muscle mass and <italic>V</italic>o₂max.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, the present study proposed the required muscle mass (28.5% per body weight) in Japanese women to maintain the <italic>V</italic>o₂max reference values determined by the Japanese Ministry of Health Labour and Welfare. This required muscle mass can be used as one of the reference parameters of fitness level in Japanese women.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Since it is essential to maintain a high level of cardiorespiratory fitness to prevent life-style related disease, the Ministry of Health, Labour and Welfare of Japan in 2006 proposed to determine the maximal oxygen uptake (<italic>V</italic>o₂max: mL·kg^-1·min^-1) reference values to prevent life-style related diseases (LSRD). Since muscle mass is one of the determinant factors of <italic>V</italic>o₂max, it could be used as the reference parameter for preventing LSRD. The aim of this study was to determine and quantify the muscle mass required to maintain the <italic>V</italic>o₂max reference values in Japanese women.</p>", "<title>Methods</title>", "<p>A total of 403 Japanese women aged 20–69 years were randomly allocated to either a validation or a cross-validation group. In the validation group, a multiple regression equation, which used a set of age and the percentage of muscle mass (%MM, percentage of appendicular lean soft tissue mass to body weight), as independent variables, was derived to estimate the <italic>V</italic>o₂max. After the equation was cross-validated, data from the two groups were pooled together to establish the final equation. The required %MM for each subject was recalculated by substituting the <italic>V</italic>o₂max reference values and her age in the final equation.</p>", "<title>Results</title>", "<p>The mean value of required %MM was identified as (28.5 ± 0.35%). Thus, the present study proposed the required muscle mass (28.5% per body weight) in Japanese women to maintain the <italic>V</italic>o₂max reference values determined by the Japanese Ministry of Health Labour and Welfare.</p>", "<title>Conclusion</title>", "<p>The estimated required %MM (28.5% per body weight) can be used as one of the reference parameters of fitness level in Japanese women.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>MM performed analysis and data interpretation as well as drafted and revised the manuscript. KM participated in the conception of this study, interpretation of the analysis and critically reviewed this manuscript, and provided comment as Statistical expertise. HK, YG, KY, MT, TO, CU and SK performed data analysis and interpretation, and provided comment and review of the manuscript. MH and IT designed the project, assisted with data interpretation and provided comment and revisions for the manuscript. MM designed the project, participated in the conception of this study, interpretation of the analysis and critically reviewed this manuscript. All authors read and give final approval of the final manuscript for publication.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2458/8/291/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Ms. Andrea Brown for her assistance with the manuscript preparation. This study was supported by the Health and Labour Sciences Research Grants of I. Tabata for the research on exercise and physical activity guidelines, awarded from the Ministry of Health, Labour and Welfare, Japan, the Health and Labour Sciences Research Grants of M. Miyachi, awarded from the Ministry of Health, Labour and Welfare, Japan, and Japan and Research Resident Fellowship of M. Miyatani awarded from Japan Foundation for Aging and Health.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>The relationship between age and <italic>V</italic>o₂max in the V-group</bold>. The <italic>V</italic>o₂max reference values by the Japanease Ministry of Health Labour and Welfare were shown for reference.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Relationship between percentage of muscle mass (%MM) and <italic>V</italic>o₂max in the V-group.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Relationship between estimated <italic>V</italic>o₂max by the multiple regression equation and the residuals for the CV-group.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p>Relationship between estimated <italic>V</italic>o₂max by the multiple regression equation and the residuals for both the V-group and the CV-group.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>The relationship between age and the percentage of muscle mass (%MM) in the V-group and the CV-group</bold>. Required %MM is shown for reference.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>The relationship between the sufficiency of <italic>V</italic>o₂max (%<italic>V</italic>o₂max reference values) and the sufficiency of the required %MM (% required %MM) in both the V-group and the CV-group</bold>. Solid line: regression line, dashed line: lines of 100% of Required %MM and 100% of <italic>V</italic>o₂max reference values.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Characteristics of validation and cross-validation group</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">V-group</td><td align=\"center\">CV-group</td></tr></thead><tbody><tr><td align=\"left\"><italic>n</italic></td><td align=\"center\">202</td><td align=\"center\">201</td></tr><tr><td align=\"left\">Age (yr)</td><td align=\"center\">41.4 ± 16.7</td><td align=\"center\">41.6 ± 16.9</td></tr><tr><td align=\"left\">Height (cm)</td><td align=\"center\">158.5 ± 6.4</td><td align=\"center\">157.9 ± 6.1</td></tr><tr><td align=\"left\">Body weight (kg)</td><td align=\"center\">54.4 ± 7.4</td><td align=\"center\">53.9 ± 7.3</td></tr><tr><td align=\"left\">Body mass index (kg/m²)</td><td align=\"center\">21.6 ± 2.7</td><td align=\"center\">21.7 ± 2.9</td></tr><tr><td align=\"left\">Appendicular muscle mass (kg)</td><td align=\"center\">16.4 ± 2.4</td><td align=\"center\">16.1 ± 2.3</td></tr><tr><td align=\"left\">% MMI (%)</td><td align=\"center\">30.3 ± 3.2</td><td align=\"center\">30.0 ± 3.4</td></tr><tr><td align=\"left\">Vo₂max (ml·kg^-1·min^-1)</td><td align=\"center\">33.5 ± 7.9</td><td align=\"center\">32.7 ± 7.7</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Required %MM for <italic>V</italic>o₂max reference values of each age group</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Age group</td><td align=\"center\">20 Y</td><td align=\"center\">30 Y</td><td align=\"center\">40 Y</td><td align=\"center\">50 Y</td><td align=\"center\">60 Y</td><td align=\"center\">Total</td></tr></thead><tbody><tr><td align=\"left\"><italic>n</italic></td><td align=\"center\">143</td><td align=\"center\">48</td><td align=\"center\">55</td><td align=\"center\">73</td><td align=\"center\">84</td><td align=\"center\">403</td></tr><tr><td align=\"left\">Required MMI (%)</td><td align=\"center\">28.3 ± 0.26</td><td align=\"center\">28.6 ± 0.29</td><td align=\"center\">28.9 ± 0.27</td><td align=\"center\">28.4 ± 0.25</td><td align=\"center\">28.6 ± 0.30</td><td align=\"center\">28.5 ± 0.35</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula>%MM (%) = (Appendicular lean soft tissue mass)/Body weight × 100.</disp-formula>", "<disp-formula id=\"bmcM1\"><label>(1)</label><italic>V</italic>o₂max = -0.131 × Age + 1.344 × %MM - 2.035.</disp-formula>", "<disp-formula id=\"bmcM2\"><label>(2)</label>%MM = (0.131 × Age + 2.035 + <italic>V</italic>o₂max)/1.344.</disp-formula>" ]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>mean ± SD, V-group, Validation group; CV-group, Cross-validation group; %MM, percentage of muscle mass</p></table-wrap-foot>", "<table-wrap-foot><p>Mean ± SD; %MMI, percentage of muscle mass</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2458-8-291-1\"/>", "<graphic xlink:href=\"1471-2458-8-291-2\"/>", "<graphic xlink:href=\"1471-2458-8-291-3\"/>", "<graphic xlink:href=\"1471-2458-8-291-4\"/>", "<graphic xlink:href=\"1471-2458-8-291-5\"/>", "<graphic xlink:href=\"1471-2458-8-291-6\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Chronic mesenteric ischaemia is an important cause of abdominal pain, especially in older patients with risk factors for vascular disease [##REF##10784596##1##]. Percutaneous angioplasty and stenting have recently been shown to be effective and safe alternatives to surgical revascularization and are increasingly used in high-risk patients with chronic mesenteric ischaemia [##REF##18295100##2##].</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>Chronic mesenteric ischaemia is an important cause of abdominal pain, especially in older patients with risk factors for vascular disease. Until recently, surgical revascularization procedures such as endarterectomy and aorto-coeliac or aorto-mesenteric bypass grafting were the only available treatment options for patients with chronic mesenteric ischaemia [##REF##10784596##1##]. However, reported rates of perioperative major complications (15% to 33%) and mortality (up to 17%) are high, influenced by a high prevalence of significant patient comorbidities [##REF##18295100##2##, ####REF##11137925##3##, ##REF##18281908##4####18281908##4##]. Percutaneous angioplasty and stenting have been shown to be effective and safe alternatives to surgical revascularization in high-risk patients with chronic intestinal ischaemia [##REF##18295100##2##,##REF##16614146##5##]. This is the first reported case of splenic infarction complicating otherwise successful coeliac artery stenting, presumably as a consequence of distal embolization of disrupted calcific plaque, with this complication occurring on a background of nonocclusive splenic arterial calcification and representing a novel cause of abdominal pain post-procedure.</p>" ]

[ "<title>Conclusion</title>", "<p>While coeliac artery stenting may be an effective procedure for the relief of chronic intestinal ischaemia, the possibility of complications related to distal embolism of disrupted calcific plaque should be considered, leading in this particular instance to splenic infarction.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Chronic mesenteric ischaemia is an important cause of abdominal pain, especially in older patients with risk factors for vascular disease. Until recently, surgical revascularization procedures such as endarterectomy and aorto-coeliac or aorto-mesenteric bypass grafting were the only available treatment options for patients with chronic mesenteric ischaemia. Percutaneous angioplasty and stenting have recently been shown to be effective and safe alternatives to surgical revascularization in high-risk patients with chronic mesenteric ischaemia.</p>", "<title>Case Presentation</title>", "<p>We report an 84-year-old woman with symptoms of chronic mesenteric ischaemia, including post-prandial abdominal pain and weight loss. Investigations demonstrated calcific stenoses at the origins of the celiac, superior mesenteric and inferior mesenteric arteries, along with nonocclusive calcification in the mid-splenic artery. Coeliac artery angioplasty and stenting was performed, resulting in excellent arterial dilatation at the stenotic point and distal filling of the coeliac and superior mesenteric arteries and their branches. Within hours of successful stenting of the coeliac artery, the patient developed severe left upper quadrant pain. Progress imaging demonstrated splenic infarction, likely as a result of calcific emboli dislodged from the calcified plaque at the origin of the celiac artery at the time of angioplasty and stenting. The left upper quadrant pain resolved after 8 days and the patient remains asymptomatic 2 years post-procedure.</p>", "<title>Conclusion</title>", "<p>This is the first reported case of splenic infarction complicating otherwise successful coeliac artery stenting, presumably as a consequence of distal embolization of disrupted calcific plaque. This complication, occurring on a background of non-occlusive splenic arterial calcification, represents a novel cause of abdominal pain post-procedure.</p>" ]

[ "<title>Case presentation</title>", "<p>An 84-year-old-woman with hypertension, hypercholesterolaemia and type 2 diabetes presented with symptoms of post-prandial abdominal pain and weight loss in excess of 8 kg, from 63.5 to 55 kg, over the previous 6 months. Physical examination revealed evidence of peripheral and cerebrovascular disease, with poor peripheral pulses and bruits audible over both carotid arteries. No abdominal bruits or other signs, such as abdominal tenderness, palpable masses or enlarged viscera, were evident. Faecal occult blood testing performed on three occasions was negative. Precordial examination was unremarkable. The full blood count and differential were normal. The serum albumin level was 29 g/l (normal 34 to 45 g/l). Liver biochemistry was otherwise within normal limits. The prothrombin time was similarly normal. A computed tomography (CT) scan of the abdomen showed calcified plaque in the abdominal aorta, along with nonocclusive calcification in the mid-splenic artery (Figure ##FIG##0##1a##). No abnormalities of the hollow or solid viscera were evident. Doppler studies revealed increased velocity at the origins of the coeliac, superior mesenteric and inferior mesenteric arteries consistent with significant ostial stenoses. A CT angiogram with special views of the coeliac, superior mesenteric and inferior mesenteric arteries demonstrated tight, short-segment stenoses at the origins of each of these arteries, with calcified plaque at the origins. Nonocclusive calcification in the mid-splenic artery was evident, as before. An electrocardiogram confirmed sinus rhythm. Echocardiography demonstrated no abnormality.</p>", "<p>A diagnosis of chronic mesenteric ischaemia was made and coeliac artery stenting was performed 72 hours later, using a right brachial approach. The intention was to later stent the superior mesenteric artery as well, should flow in this artery arising from collaterals from a revascularized coeliac artery not be evident. The coeliac artery was catheterized selectively using a 6 Fr catheter, and an 8 × 26 mm balloon-mounted stent (Biotronik, Berlin, Germany) was deployed, resulting in excellent arterial dilatation at the stenotic point and distal filling of the coeliac and superior mesenteric arteries and their branches. Within several hours of successful stenting of the coeliac artery, the patient developed severe left upper quadrant pain requiring narcotic analgesia. A repeat CT scan of the abdomen performed 18 hours post-procedure revealed two wedge-shaped areas of low density within the periphery of the spleen indicative of splenic infarcts, likely as a result of calcific emboli dislodged from the calcified plaque at the origin of the coeliac artery at the time of angioplasty and stenting (Figure ##FIG##0##1b##). The vascular stent was sited within the proximal coeliac trunk. The coeliac artery distal to the stent and the superior mesenteric artery each opacified with no obvious filling defects, the latter as a result of filling via collaterals arising from the coeliac artery, demonstrating successful restoration of mesenteric blood flow and obviating the need for additional stenting of the superior mesenteric artery. There was no evidence of arterial embolism elsewhere. The patient had remained in sinus rhythm and there were no signs of infective endocarditis. The left upper quadrant pain resolved after 8 days. The splenic infarcts were no longer evident on progress CT scan performed 3 months later. The patient has experienced no further symptoms of mesenteric ischaemia now 2 years post-procedure, with a progress Doppler study demonstrating ongoing stent patency.</p>", "<title>Abbreviations</title>", "<p>CT: Computed tomography.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>Both authors contributed to the patient care and the drafting of this case report.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patient for publication of this case report and any images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>CT scans of the abdomen</bold>. (a) CT scan of the abdomen performed prior to percutaneous transluminal stenting of the coeliac artery, demonstrating calcified plaque in the abdominal aorta (long arrow) and mid-splenic artery (short arrow). The spleen is normal (arrowhead). (b) A progress CT scan performed 18 hours post-procedure demonstrating two wedge-shaped splenic infarcts, one of which is depicted on this view by the arrowhead. Splenic artery calcification is evident not only as before but also more distally (short arrows), in keeping with embolism of calcified plaque during coeliac artery stenting. The coeliac artery stent is pictured protruding into the abdominal aorta (long arrow).</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1752-1947-2-261-1\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Diffuse idiopathic hyperostosis was first described in 1950 by Forestier and Rotes-Querol [##UREF##0##1##]. It is characterised by excessive ligamentous calcification and ossification at spinal and extraspinal locations. When the cervical spine is involved large osteophytes may form, causing symptoms of dysphagia. We describe the case of an 88-year-old man with dysphagia and weight loss secondary to diffuse idiopathic skeletal hyperostosis (DISH).</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>DISH is a common but overlooked condition seen in the elderly. It is characterised by new bone formation into axial and peripheral enthesial regions. The prevalence of DISH has been reported to be 10% in patients over the age of 70 (see [##REF##1153976##2##]). The aetiology of DISH has not been defined but there are associations with diabetes, obesity [##REF##935390##3##], hypercholesterolaemia and gout. DISH most commonly affects the thoracic spine although cervical involvement is found in 76% of those affected [##REF##1129458##4##]. Dysphagia related to DISH affecting the cervical spine has a reported prevalence of 28% [##REF##341323##5##]. Dysphagia caused by DISH may be due to several factors: direct mechanical compression of the oesophagus by large anterior osteophytes; smaller osteophytes located at sites of oesophageal fixation such as at the level of the cricoid cartilage; inflammation of the peri-oesophageal soft tissue in contact with overlying osteophytes; or oesophageal spasm caused by painful osteophytes [##REF##3496409##6##].</p>", "<p>The diagnosis of DISH is radiological. Plain radiographs of the cervical spine typically show flowing calcification and ossification along the anterior surface of at least four contiguous vertebrae. Large anterior osteophytes are commonly found between C4 and C7 [##REF##12430101##7##]. Computed tomography is another useful imaging modality in the diagnosis of DISH as the size and shape of the osteophytes are shown in relation to the oesophagus and other important structures. Barium swallow or video fluoroscopy will confirm oesophageal compression and obstruction in relation to large anterior osteophytes. Endoscopy in these patients carries a risk of perforation but may be necessary to exclude other intrinsic causes of dysphagia such as oesophageal strictures, oesophagitis, oesophageal webs, motility disorders, tumours and candidiasis [##REF##12027318##8##]. Other clinical manifestations associated with cervical DISH are hoarseness, stridor, aspiration pneumonia, myelopathy, thoracic outlet syndrome and sleep apnoea [##REF##12430101##7##]. Treatment is divided between conservative and surgical. Conservative management includes modification of diet, non-steroidal inflammatory medications, corticosteroids and muscle relaxants [##REF##7299268##9##,##REF##3873932##10##]. In severe cases surgical management may be the only option and involves osteophytectomy. The surgical approach may be anterolateral, posterolateral or transpharyngeal when C2 to C4 vertebrae are involved. Complications include laryngeal nerve damage, stroke, Horner's syndrome and cervical instability [##REF##16803720##11##].</p>" ]

[ "<title>Conclusion</title>", "<p>Dysphagia is a common presentation seen in older people. The diagnosis of DISH involving the cervical spine often goes unrecognised as a cause of dysphagia despite its prevalence in the elderly population. Diagnosis is established with plain cervical radiographs and barium swallow especially when endoscopy has excluded an intrinsic cause for dysphagia.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Dysphagia is a common presentation in older people. Diffuse idiopathic skeletal hyperostosis affecting the cervical spine is an uncommon cause of dysphagia and may be overlooked.</p>", "<title>Case presentation</title>", "<p>We present the case of an 88-year-old man with dysphagia and weight loss. Initial investigation with upper gastrointestinal endoscopy was inconclusive. A diagnosis of diffuse idiopathic skeletal hyperostosis as a cause for dysphagia was eventually made using video fluoroscopy. This showed a bony prominence impeding swallow at the level of C3. The patient was unfit for surgical management so a percutaneous endoscopic gastrostomy tube was inserted for feeding.</p>", "<title>Conclusion</title>", "<p>The diagnosis of diffuse idiopathic skeletal hyperostosis involving the cervical spine often goes unrecognised as a cause of dysphagia despite its prevalence in the elderly population. Diagnosis is made using cervical radiographs, barium swallow and computed tomography. There is a risk of perforation with endoscopy in patients who have cervical diffuse idiopathic skeletal hyperostosis. Conservative management includes non-steroidal anti-inflammatory medications and a modified diet. Surgery may be considered in certain patients where conservative management fails.</p>" ]

[ "<title>Case presentation</title>", "<p>An 88-year-old man presented with a 6-month history of dysphagia for solid foods and significant weight loss. He denied any symptoms of odynophagia. He denied any hoarseness of the voice, neck pain or breathlessness. There was no change in bowel habit or blood in the stools. His calorific intake was solely dependent on protein supplement drinks. His previous medical history was of type 2 diabetes, hypercholesterolaemia, hypertension, atrial fibrillation and glaucoma.</p>", "<p>On examination he was cachetic and pale. His weight was 54 kg. The rest of his physical examination was unremarkable. His full blood count showed a normocytic anaemia (10.3 g/dl) with a normal ferritin level. Liver function was normal apart from an albumin of 28 g/l. Erythrocyte sedimentation rate and thyroid stimulating hormone were normal. An endoscopy was performed to exclude an intrinsic cause for the patient's symptoms. This showed chronic atrophic gastritis but no cause for the dysphagia. Video fluoroscopy was performed which showed a bony prominence impeding swallow at the level of C3. A lateral cervical spine radiograph showed anterior osteophyte formation, most marked at the C3/C4 vertebrae and consistent with DISH (Figure ##FIG##0##1##).</p>", "<p>He was commenced on nasogastric feeding, as there was evidence of aspiration on video fluoroscopy. He was referred to the spinal surgeons but they did not feel surgery was appropriate due to the patient's frail condition and comorbidities. A percutaneous endoscopic gastrostomy tube was placed 3 weeks later. The patient died 6 weeks after admission, from complications secondary to an unrelated septic arthritis of the shoulder.</p>", "<title>Abbreviations</title>", "<p>DISH: Diffuse idiopathic skeletal hyperostosis.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>The authors were involved in the writing of the manuscript or patient clinical care. All authors read and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent could not be obtained in this case since the patient's next-of-kin were untraceable. We believe this case report contains a worthwhile clinical lesson which could not be as effectively made in any other way. We expect the patient's next-of-kin not to object to the publication since every effort has been made so the patient remains anonymous.</p>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Lateral radiograph of the cervical spine showing anterior osteophyte formation most marked at the C3/C4 vertebrae and calcification of the anterior longitudinal ligaments.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1752-1947-2-287-1\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>A hydatid cyst is a parasitosis caused by the larval form of <italic>Echinococcus granulosus </italic>or rarely <italic>Echinococcus alveolaris</italic>. The main hosts for <italic>E</italic>. <italic>granulosus </italic>are predators such as dogs, wolves, and foxes, while intermediate hosts include sheep, goats, and cattle. Humans are a coincidental intermediate host. The disease is more frequent in the Middle East, Central Europe, Australia, and South America, where the intermediate hosts are common. The organs affected most often are the liver (70%) and lungs (10–15%). Other locations are extremely rare [##UREF##0##1##]. Primary subcutaneous hydatid cyst is very rare and the incidence is unknown. In this report, we present two cases of primary hydatid cysts located subcutaneously: one in the medial thigh and one in the hand.</p>" ]

[]

[]

[ "<title>Discussion</title>", "<p>Here we report two cases of primary subcutaneous hydatid cysts both treated surgically. In a large series, the distribution of hydatid cysts outside the liver and lungs was reported as 9% of cases [##REF##9465756##2##]. Chevalier <italic>et al</italic>. reported that the incidence of subcutaneous hydatid cysts was 2%, but some of the patients had hydatid cysts in other organs too [##REF##8079861##3##]. Subcutaneous hydatid cyst may be secondary or primary. In secondary cysts, there is a primary location of hydatid disease like liver, lung, or spleen that is operated or not operated. Reports of primary subcutaneous hydatid cysts are very rare [##REF##11289668##4##, ####REF##11216615##5##, ##REF##10405477##6####10405477##6##], and we were unable to find a case of a palmar hydatid cyst in a literature review. In our cases, the hydatid cysts were located subcutaneously, the patients had not undergone previous surgery for hydatid cysts, and no hydatid cysts were found in other organs. Therefore, our patients were diagnosed as having primary subcutaneous hydatid cysts.</p>", "<p>The mechanism of primary subcutaneous localization is unclear. After being ingested orally, under the action of gastric and intestinal enzymes, the oncosphere is released; it penetrates the intestinal wall, joins the portal system and reaches the liver. If the eggs attach to the liver, an hepatic hydatid cyst takes shape. Parasite eggs can pass to the systemic circulation and cause disease in other end organs. Larvae must pass through two filters (liver and lung) to form a solitary hydatid cyst, but that is very difficult. It is very possible that systemic dissemination via the lymphatic route accounts for cases with solitary cysts in uncommon sites [##REF##11289668##4##]. Direct spread from adjacent sites may be another mechanism of infection provided a microrupture has occurred [##REF##18203655##7##].</p>", "<p>Diagnosing hydatid cysts is very difficult in patients living outside the endemic regions. Because exposure to the contents of the cyst can cause problems such as anaphylactic reaction and local recurrence, making the diagnosis pre-operatively is important. The diagnosis of a palmar hydatid cyst was not considered in our second patient pre-operatively since the mass was very small and this localization is very rare. When the cyst contents were seen during excision, the possibility of a hydatid cyst was then considered. No anaphylactic reaction developed in either patient.</p>", "<p>The radiological findings of a thick cyst wall, calcification, daughter cysts, and a germinative membrane separate from the cyst wall are findings specific to hydatid cysts [##UREF##1##8##]. Our first case was diagnosed according to the appearance of the mass on superficial US and CT.</p>", "<p>Serology is a useful tool for the diagnosis. The indirect hemagglutination (IHA) test is positive in more than 80% of liver hydatid cysts. However, false negative IHA results can be higher in other located hydatid cyst. In those cases, more specific serologic tests are mandatory. A positive indirect hemagglutination test for hydatid cysts is significant, although negative test results do not indicate the absence of the disease, as in our patients. Therefore, the most important diagnostic tool is the awareness of the physician, particularly for the unusual presentation of the disease.</p>", "<p>The best treatment option is total surgical excision without opening the cyst. If the cyst cannot be excised without opening, the fluid contents should be removed, the laminated membrane should be totally excised, and the cyst pouch should be irrigated with protoscolicidal solutions [##REF##2245554##9##]. Subcutaneous located cysts are more prone to rupture since they have not been diagnosed pre-operatively. We performed total cyst excision in both cases and irrigated the surgical areas with protoscolicidal agents. Identifying postoperative recurrence of the cyst in endemic regions is very difficult because the probability of formation of a new cyst is high. However, since our patients were still free of disease in the third postoperative year, any subsequent hydatid cyst formation may be considered to be a new infestation.</p>" ]

[ "<title>Conclusion</title>", "<p>Hydatid cyst should be considered in the differential diagnosis of subcutaneous cysts in regions where hydatid cysts are endemic. Total excision of the cyst with an intact wall is the best treatment.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Introduction</title>", "<p>Hydatid cyst disease is common in some regions of the world and is usually located in the liver and lungs. This report presents two cases of primary hydatid cysts located subcutaneously: one in the medial thigh and one in the left palm between the index and middle fingers.</p>", "<title>Case presentations</title>", "<p>A 64-year-old male farmer visited our hospital because a swelling on the right medial thigh had grown during the last year. Superficial ultrasound and computed tomography revealed a lesion resembling a hydatid cyst. A germinative membrane was encountered during surgical excision. Pathological examination was compatible with a hydatid cyst. The second case involved a 67-year-old male farmer who complained of a swelling that had grown in his left palm in the last year. The preliminary diagnosis was a lipoma. However, a hydatid cyst was diagnosed during surgical excision and after the pathological examination. The patient did not have a history of hydatid cyst disease and hydatid cysts were not detected in other organs. There has been no disease recurrence after following both patients for 3 years.</p>", "<title>Conclusion</title>", "<p>A hydatid cyst should be considered in the differential diagnosis of subcutaneous cystic lesions in regions where hydatid cysts are endemic, and should be excised totally, with an intact wall, to avoid recurrence.</p>" ]

[ "<title>Case presentations</title>", "<p>A 64-year-old male farmer visited our clinic because of a swelling on the medial thigh that had grown during the last year. On physical examination, a mobile, painless, fluctuant, 8 × 9 cm mass was palpated. The overlying skin was normal. The only abnormality in the pre-operative laboratory examination was an increased erythrocyte sedimentation rate (ESR 60 mm/hour). The patient had no history of surgery for a hydatid cyst in another organ. Ultrasound (US) and computed tomography (CT) showed a lesion resembling a hydatid cyst (Fig. ##FIG##0##1##). During surgical exploration under spinal anesthesia, the skin and subcutaneous layers were incised and the cyst was reached. Hypertonic saline (3% NaCl) was injected into the cyst and after waiting for 10 min, the cyst was completely excised. A germinative membrane was seen during excision (Fig. ##FIG##1##2##). We thought that the cyst was fertile as it contained daughter cysts. The surgical site was irrigated with 40% povidone iodine (Betadine^®) and hypertonic saline. The subcutaneous layers and skin were closed in the standard manner.</p>", "<p>Histopathological examination revealed a hydatid cyst, but no additional hydatid cysts were observed on US or CT of the abdomen and thorax; the indirect hemagglutination test for hydatid cysts was negative. The patient was started on albendazole for 3 months (15 mg/kg/day). No findings associated with local or systemic hydatid cysts were detected during a 3-year follow-up period.</p>", "<p>The other case involved a 67-year-old male farmer who complained of a subcutaneous swelling inside the left palm between the index and middle fingers. Physical examination revealed a subcutaneous immobile 2 × 3 cm mass on the palmar side of the left hand between the thumb and index fingers. Surgical excision was planned with a pre-operative diagnosis of lipoma. A hydatid cyst was considered when a germinative membrane was seen during excision under local anesthesia (Fig. ##FIG##2##3##). We also thought that the cyst was fertile as it contained daughter cysts as in the previous patient. The cyst space was irrigated with 40% povidone iodine (Betadine^®) and hypertonic saline. Total cyst excision and primary closure were performed, and histopathological examination revealed a hydatid cyst. The only abnormality in the pre-operative laboratory examination was an increased ESR (60 mm/hour). The patient had no history of surgery for a hydatid cyst in another organ, and no additional cysts were observed on US and CT of the abdomen and thorax. The indirect hemagglutination test for hydatid cysts was negative, and the patient was placed on albendazole for 3 months (15 mg/kg/day). No findings associated with local or systemic hydatid cysts were detected during a 3-year follow-up period.</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>AD is the consultant surgeon who drafted the article and performed the operations. BU assisted in performing the surgery, took the pictures and helped revise the article. CK helped in acquisition of data and technical support. VK performed the literature search and helped in revision. All authors read, appraised and approved the final manuscript.</p>", "<title>Consent</title>", "<p>Written informed consent was obtained from the patients before publication of this case series and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.</p>" ]

[]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Subcutaneous hydatid cyst in the right medial thigh, displacing the muscles laterally.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Subcutaneous hydatid cyst in the right medial thigh.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p>Germinative membrane of cyst localized in the palmar site of the hand.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1752-1947-2-273-1\"/>", "<graphic xlink:href=\"1752-1947-2-273-2\"/>", "<graphic xlink:href=\"1752-1947-2-273-3\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>We previously used mitochondrial DNA analyses to describe the history of population expansion and divergence of the bananaquit (<italic>Coereba flaveola</italic>), the most abundant and widely distributed songbird in the West Indies, which also occurs in the humid tropics of continental America [##UREF##0##1##, ####REF##11711673##2##, ##UREF##1##3####1##3##]. The geographic distribution and relationship of mtDNA RFLP haplotypes suggested that populations of this species were periodically invasive, and then quiescent. Here we increase our sample of populations and genes to dissect more finely the population history of bananaquits.</p>", "<p>The bananaquit is a small nectivorous and frugivorous emberizine bird (order Passeriformes) that is an abundant resident throughout the West Indies, except for Cuba [##UREF##2##4##, ####UREF##3##5##, ##UREF##4##6####4##6##]. On the continent, it is widely distributed from southern Mexico through much of South America. Geographic variation in plumage coloration led to the recognition of 41 subspecies throughout the range of the bananaquit [##UREF##5##7##], but mtDNA RFLP analysis failed to support many of these distinctions [##UREF##1##3##]. The mtDNA analyses also revealed levels of genetic divergence between some populations within the range of genetic differences observed between species [##UREF##6##8##,##UREF##7##9##].</p>", "<p>Building on our earlier studies of the bananaquit [##UREF##0##1##, ####REF##11711673##2##, ##UREF##1##3####1##3##], we have now included representatives of more populations from the West Indies and the continent, expanded our nucleotide sample of the mitochondrial genome of each individual to 3744 base pairs, and have added at least 2049 base pairs representing three nuclear gene regions. Our phylogenetic analysis is rooted by the addition of five individuals of three species of emberizid finches representing three genera.</p>", "<p>Our principal objectives were to determine the ancestral area of <italic>C. flaveola</italic>, to infer the number and directions of colonization events within the West Indies and between the islands and the continent, and to assess the power of nuclear versus mitochondrial genes to inform analyses of colonization history and subsequent population dynamics. Our phylogenetic results locate the geographic ancestral area of the bananaquit in the region of the Greater Antilles and Bahamas, and strongly support the hypothesis that continental bananaquits were derived from West Indian ancestors. In addition, comparisons of mitochondrial and nuclear gene genealogies exposed a complex and dynamic history of bananaquits in the Greater and Lesser Antilles that would have remained masked without recourse to both maternal and biparental genealogical markers.</p>" ]

[ "<title>Methods</title>", "<title>Sampling</title>", "<p>We obtained tissue or blood samples from one to three <italic>C. flaveola </italic>individuals from 16 islands within the West Indies (Antigua, Bahamas, Barbados, Barbuda, British Virgin Islands, Cayman Islands, Dominica, Dominican Republic, Grenada, Guadeloupe, Jamaica, Martinique, Montserrat, Puerto Rico, Saint Lucia and Saint Vincent) and seven countries in Middle and South America (Belize, Bolivia, Mexico, Panama, Peru, Trinidad and Venezuela) (Figure ##FIG##0##1##). No voucher specimens were collected in the West Indies because identification of species is not an issue. The sampling locations cover the entire distribution of bananaquits within the West Indies, and are broadly representative of the geographic range of the species in Central and South America. Bananaquits occur only accidentally in Cuba and Florida [##UREF##27##42##]. To root the bananaquit phylogeny, we used the following outgroups: two individuals of <italic>Tiaris olivacea </italic>(from Puerto Rico, PRTOL and the Cayman Islands, CYTOL), two <italic>Loxigilla portoricensis </italic>(Puerto Rico, PRLPO1, PRLPO2), and one <italic>Melanospiza richardsoni </italic>(Saint Lucia, SLMRI), which are recognized as close relatives of <italic>C. Flaveola </italic>[##REF##12144023##10##]. Altogether, our sampling included 49 individuals. Additional file ##SUPPL##0##1## presents details for sample localities. Blood and tissue collection was non-destructive as described in Seutin et al. [##UREF##1##3##]. On Grenada and St. Vincent, we sampled bananaquits of the typical yellow form as well as the melanistic form [##REF##11369199##43##, ####UREF##28##44##, ##UREF##29##45####29##45##].</p>", "<title>DNA extraction and sequencing</title>", "<p>Total cellular DNA was extracted from most samples using the CTAB extraction procedure described in [##UREF##1##3##]. The following six mitochondrial genes were amplified: ATP synthase 8, ATP synthase 6 (ATPase 8, ATPase 6, 852 bp); cytochrome b (cyt b, 717 bp), cytochrome oxidase (COI, 651 bp), Nadh dehydrogenase 2 (ND2, 1023 bp), Nadh dehydrogenase 6 (ND6, 501 bp). In addition, we amplified three nuclear genes: the recombination activating gene-1 (RAG-1, 1009 bp [##REF##9089097##46##]), the fifth intron of the beta fibrinogen gene (Bfib5, 545 bp [##UREF##30##47##]), and the chromo-helicase-DNA-binding protein, which is sex-linked (CHDZ, 495 bp [##REF##12859633##48##]). In total, we sequenced 3744 nucleotides of mitochondrial genes and 2049 nucleotides of nuclear genes. Negative controls were included in all PCR amplifications to confirm the absence of contaminants. Amplification of PCR products was verified by visualization on 1.5% TBE agarose gels stained with ethidium bromide. PCR products were then cut from 1.5% TAE agarose gels and left to incubate for two hours at 46°C in presence of gelase.</p>", "<p>Sequencing reactions were conducted with the gel purified products and BigDye chemistry (Applied Biosystems, Foster City, CA, USA), and cleaned using Sephadex G50 purification columns (Sigma). Sequencing reaction products were run on an ABIPrism 3130xl automated sequencer (Applied Biosystems). DNA sequence fragments were edited and aligned using Sequencher software version 4.5.</p>", "<p>We cloned samples in which nuclear sequences exhibited more than one heterozygous nucleotide site (double peaks of approximately the same height present on both strands) or double peaks extending through a portion of the entire sequence due to allele length variants. Cloning was accomplished using the Promega cloning kit (pGEM-T Easy Vector System II). Ligated plasmids were used to transform <italic>Escherichia coli </italic>competent cells (JM109) selected for inserts by growth on LB plates with IPTG and X-Gal (5'-3'). Positive colonies were grown overnight in LB and up to eight colonies were isolated in 50 μL of purified water. PCR, cycle sequencing, and purifications were then performed as previously described. For some individuals we sequenced one colony per clone and used the resulting sequence to deduce the sequence of the second allele from the original sequence based on the PCR amplification of genomic DNA. Where the original sequence was not interpretable, we sequenced between three and six colonies per clone to obtain clean sequences for both alleles. Cloning errors were identified by comparing multiple sequences and their consensus, and the error rate was estimated by dividing the number of cloning errors by the number of nucleotides sequenced.</p>", "<p>Our preliminary data indicated discordant nuclear and mitochondrial trees for Dominican Republic bananaquits (see results), which warranted increased sampling of individuals and genes. Accordingly, we sequenced the mitochondrial ATPase and nuclear BFib5 genes for eight additional birds from diverse locations across the Dominican Republic (additional file ##SUPPL##0##1##)</p>", "<title>Phylogenetic analyses</title>", "<p>Nucleotide composition, nucleotide bias, percentage of variable sites and parsimony informative sites for both mitochondrial and nuclear genes were analyzed using PAUP* and Sequencher 6.1 [##UREF##31##49##]. We assessed saturation in the mitochondrial dataset by plotting the transition/transversion ratio against uncorrected genetic distance for the combined mitochondrial dataset.</p>", "<p>Phylogenetic analyses for each mitochondrial gene independently, for each nuclear gene independently, and for combined datasets followed verification of the homogeneity of gene regions in combination. Congruence among tree topologies generated using the six mitochondrial genes combined or among the three nuclear genes combined was tested with the partition homogeneity test in PAUP*, with 1000 heuristic replications [##UREF##32##50##,##UREF##33##51##]. In turn, we used three approaches to infer relationships among bananaquits. Maximum parsimony (MP) analysis was performed using heuristic searches with TBR branch swapping and support for interior nodes was assessed using a bootstrap approach (1000 replicates). Maximum likelihood (ML) analyses used MrModelTest v2.2 [##UREF##34##52##] to select the best-fit nucleotide substitution model for the data. Bayesian phylogenetic analyses were conducted using MrBayes v.3.0b4 [##REF##11524383##53##]. We estimated posterior probability distributions by allowing six incrementally heated Markov chains to proceed for two millions generations, with samples taken every 1000 generations. The Markov chain of interest was considered to have converged when stationarity was reached, which we determined by plotting the posterior probability values of nodes against generation time in a cumulative fashion. Burn-in samples were discarded from the two separate analyses, and the remaining samples were combined to create a consensus phylogeny and to estimate posterior probability values and branch lengths.</p>", "<p>After fixing the topology of the consensus Bayesian tree, we implemented a |²test of log-likelihood ratios to compare the difference in support between trees with and without a molecular clock enforced [##UREF##35##54##] so that we could evaluate the constancy of nucleotide substitution rate within the combined mitochondrial gene dataset. We analyzed the nucleotide substitution rate only for bananaquit lineages and did not include the outgroups.</p>", "<p>We failed to reject the null hypothesis of rate constancy in our data. It was not possible to obtain a robust calibration for the application of the molecular clock, first because passerines are poorly represented in the fossil record, and are difficult to identify to species when they do occur, and secondly because calibration information such as radiometric ages of heterochronous sequences or inferred ages of lineage splitting events [##UREF##8##13##] are not available for the studied species. However, our aim was to provide an approximation (not precise dating) for times of lineage splitting. Therefore, we used a broad range of linear substitution rates of 1.5–3% My^-1reported for bird studies [##UREF##8##13##,##UREF##36##55##]. To estimate divergence times, we considered the net average genetic distance between pairs of clades and its standard deviation, using a Tamura-Nei model calculated using MEGA software, version 3.1 [##REF##15260895##56##] and divided the mean genetic distance by 1.5–3%.</p>", "<p>We employed the ancestral area method from Bremer [##UREF##24##39##] to infer the direction and sequence of island and mainland colonization of <italic>C. flaveola </italic>in the West Indies. This is a cladistic method based only on the topology of the tree, which is used to infer a gain-loss ratio for each branch of a simplified area cladogram. The cladistic analysis was based on the topology of the Bayesian tree for the combined mitochondrial dataset.</p>", "<p>We used the software NETWORK 4.111 [##REF##10331250##57##] to estimate gene genealogies for each of the nuclear genes and for the combined set of nuclear genes, and to construct unrooted minimum spanning networks. A partition homogeneity test in PAUP*, with 1000 heuristic replications, was used to test for incongruence among tree topologies generated using the seven nuclear genes.</p>" ]

[ "<title>Results</title>", "<title>Sequencing, nucleotide composition and saturation</title>", "<p>We obtained clean sequences for all 43 <italic>C. flaveola </italic>distributed within the West Indies and South-central America (Figure ##FIG##0##1##) and for six outgroup samples, with a few exceptions, for six mitochondrial genes and three nuclear genes (see additional file ##SUPPL##0##1##). All sequences were submitted to Genbank (accession numbers from <ext-link ext-link-type=\"gen\" xlink:href=\"EF567429\">EF567429</ext-link> to <ext-link ext-link-type=\"gen\" xlink:href=\"EF567954\">EF567954</ext-link>; additional file ##SUPPL##0##1##).</p>", "<p>Cloning was performed on nine samples for BFib5, 10 samples for Rag1, and two samples for CHDZ. Cloning error rate was estimated to be about 0.1% and cloning errors were eliminated from cloned alleles.</p>", "<p>Several properties of the data were examined to ascertain the utility of the genes for phylogenetic analysis (additional file ##SUPPL##1##2##). None of the mitochondrial genes exhibited stop codons when translated into amino acids. A test of homogeneity indicated that sequences had similar base frequencies across taxa (p values for all genes were above 0.99; data not shown). As expected, mtDNA sequences showed an anti-guanine bias, except for ND6, which showed an anti-cytosine bias and is the only one of the six genes encoded by the L strand; all other protein-coding mitochondrial genes are encoded by the H strand.</p>", "<p>The majority of variable sites in the mitochondrial datasets were third-position substitutions, as expected for protein-coding genes. The mitochondrial sequence dataset included more variation than the nuclear dataset, with a mean percentage of variable sites ranging from 4.8 to 6.2 for mitochondrial genes compared to 0.3 (RAG1, a protein coding region) to 1.8 for nuclear genes.</p>", "<p>We calculated the relative substitution rate between mitochondrial and nuclear data by dividing the net average mitochondrial distance and the net average nuclear distance between the Bahamas individuals and the rest of the <italic>C. flaveola </italic>phylogeny. The mean substitution rate was approximately 16 times slower for nuclear genes than for mitochondrial genes.</p>", "<p>Plots of the transition/transversion ratio against uncorrected distances indicated that nucleotide substitution in the mitochondrial genome was not saturated (data not shown). All plots were linear whether plotted by position or by gene. Thus, all nucleotides were employed in the ensuing phylogenetic analyses of <italic>C. flaveola</italic>.</p>", "<title>Phylogenetic analyses: outgroups</title>", "<p>The closest relatives to <italic>C. flaveola </italic>[##REF##12144023##10##] chosen here as outgroups to root our phylogenies (i.e. <italic>Tiaris olivacea, Loxigilla portoricensis </italic>and <italic>Melanospiza richardsoni</italic>) were divergent by at least 11.2% from a mitochondrial perspective and at least 2% from a nuclear perspective.</p>", "<title>Phylogenetic analyses: congruence among tree topologies using different approaches and different genes</title>", "<p>Phylogenetic trees generated using the three approaches – MP, ML and Bayesian – were congruent for both mitochondrial and nuclear datasets. We also failed to reject homogeneity of phylogenetic trees based on each mitochondrial gene region independently (p = 0.3) or each nuclear gene region independently (p = 0.07). Therefore, for the subsequent phylogenetic analyses, we combined all six mitochondrial genes for the mitochondrial dataset and all three nuclear genes for the nuclear dataset. Concatenation of the different genes for nuclear data can be problematic as independent sorting of alleles in different parts of the genome and stochasticity of lineage sorting may lead to erroneous species trees [##REF##15792224##11##,##REF##17392434##12##]. However, our results should be unaffected by this issue because the nuclear and mitochondrial trees are congruent, with the exception of the mtDNA of Hispaniolan birds (Figures ##FIG##1##2## and ##FIG##2##3##). The GTR+I+G model of evolution was selected using the AIC criterion in Mr ModelTest for both the mitochondrial and the nuclear datasets.</p>", "<title>Phylogenetic analysis using mtDNA</title>", "<p>When describing the phylogeographic results, we use the following area name codes: LA = Lesser Antilles; PR = Puerto Rico; GA = Greater Antilles; SCA = South and Central America; BH/QR = Bahamas/Quintana Roo; DR = Dominican Republic (island of Hispaniola); JA/CY = Jamaica/Cayman Islands). A consensus phylogenetic tree based on a Bayesian analysis combining all six mitochondrial genes identified four major mitochondrial clades representing BH and QR, GA (except PR), LA (including PR), and SCA (Figure ##FIG##1##2##). Relationships were strongly supported with marginal posterior probability values ≥ 0.99 for all 15 major nodes.</p>", "<p>The continental (SCA) clade of bananaquits was sister to the PR and LA clades, which were imbedded within the GA (excluding PR) clades. This topology indicates derivation of the continental clade of bananaquits from within the GA. Within the PR/LA clade, sequences from PR had a sister relationship to the rest of the clade, and bananaquits on Grenada and Saint Vincent form a distinct phylogenetic group sister to populations in the northern LA. Within the SCA clade, samples from Central America (Panama and Belize) were grouped and distinct from samples from South America. Within South America, two groups were distinguished: birds from Trinidad and Venezuela and birds from Peru and Bolivia. A sample from Mexico (Biological Station of Los Tuxlas, Veracruz) sequenced with ND2 (M. Miller, pers. comm.) fell within the Central America group (data not shown) when added to our mitochondrial data.</p>", "<title>Phylogenetic analysis using nuclear DNA</title>", "<p>Bayesian analysis combining all three nuclear genes (Figure ##FIG##2##3##) distinguished four clades: (1) BH, (2) JA and CY, (3) DR together with isolated haplotypes from Montserrat, Barbados, Saint Lucia and PR, and (4) PR, LA and SCA. All three genes showed the affiliation of continental haplotypes with PR/LA haplotypes and the distinctiveness of DR and JA/CY haplotypes. Nevertheless each gene shows a specific pattern. For example, BFib5, the most variable gene, unites the four DR and seven LA/PR haplotypes, a group that is separated from the other sequences by five nucleotide changes. CHDZ, the least variable gene, separates with only one nucleotide change the JA/CY samples on one side and DR samples on the other side from the rest of the phylogeny (Figure ##FIG##3##4##).</p>", "<title>Mitochondrial versus nuclear phylogenetic analyses</title>", "<p>In comparison with the mitochondrial tree, the tree based on nuclear data resolved the more recent divergences poorly. For example, the nuclear data grouped the continental samples with those from the LA. Nonetheless, the nuclear phylogeny was consistent with the mitochondrial tree in the basal branching pattern for <italic>C. flaveola </italic>within the West Indies. The distinctiveness of DR birds in the nuclear tree was surprising given their relative proximity to JA/CY birds in the mitochondrial tree. Because the discrepancy between mitochondrial and nuclear data suggests a distinctive phylogenetic history for the DR population, we sequenced eight additional DR individuals with both mitochondrial (ATPase) and nuclear (BFib5) genes. Those additional sequences confirmed that DR birds grouped with CY and JA birds from a mitochondrial perspective and formed a separate clade from the other populations from a nuclear perspective (data not shown).</p>", "<title>Estimates of population splitting times</title>", "<p>The likelihood-ratio test based on the six mitochondrial genes failed to reject the null hypothesis of rate constancy (-ln<italic>L </italic>= 9243.85 enforced tree and 9217.02 non enforced tree, χ²= 53.66, df = 40, p = 0.073). Therefore, to estimate divergence times, we used linear mtDNA substitution rates of 1.5 and 3% Ma^-1, which span the range of most calibrations (see \"Methods\" for justification [##UREF##8##13##,##UREF##9##14##]).</p>", "<p>The average genetic distance between BH/QR birds and all other populations was 0.0562 ± 0.0037, placing the ingroup root between 1.75 and 3.99 Mya. The average divergence between the GA and LA/PR/SCA groups was 0.0529 ± 0.0038, indicating that the split between those two clades occurred at approximately the same time, i.e., 1.75 to 3.99 Mya. The divergence between the LA/PR clade and the SCA clade was 0.0234 ± 0.0025, implying a split about 0.69 to 1.72 Mya. Finally, PR diverged from the LA approximately 0.34–0.93 Mya.</p>" ]

[ "<title>Discussion</title>", "<p>In this paper, we have described phylogeographic relationships of bananaquit populations to determine the history of colonization within the Caribbean Basin. Additional analyses using coalescent models to infer population parameters require a different sampling regime (i.e., more individuals per population and more nuclear genes) and will be reported separately (Bellemain et al. unpublished).</p>", "<p>We provide a well-resolved phylogeny of the bananaquit in the West Indies, based on multiple genes. Aspects of the bananaquit phylogeny highlight points of general interest that are not commonly appreciated for birds. First, we infer that populations sampled in the Greater Antilles and Bahamas were the source of mainland colonization for <italic>C. flaveola</italic>, which is the reverse of the usual continent-to-island direction of colonization. Second, our study demonstrated the dynamic nature of the bananaquit distribution, resulting from several phases of overlapping expansions, especially through the Lesser Antilles. Third, a discrepancy between mitochondrial and nuclear haplotypes among bananaquits on Hispaniola (Dominican Republic samples) suggested the recent replacement of the mitochondrial genome by introgression from Jamaica.</p>", "<title>Mitochondrial versus nuclear data: relative coalescence time, sorting of ancestral polymorphism and inferences concerning phylogenetic history</title>", "<p>DNA sequences of mitochondrial genes provide a single estimate of a species phylogeny based on one linkage group [##REF##15012752##15##]. In our analysis of bananaquit phylogeny, we adopted a multi-gene approach based on three nuclear genes as well as DNA sequences for six mitochondrial genes. The more rapid coalescence of mtDNA represents an advantage as it is more likely to resolve nodes with short internode distances, and the probability of incomplete lineage sorting is reduced compared to nuclear DNA [##UREF##10##16##,##UREF##11##17##]. However, an evolutionary reconstruction based on multiple independent genes increases confidence that the true species tree has been recovered, and improves phylogenetic resolution by averaging out potentially misleading effects of ancestral polymorphisms [##UREF##10##16##,##REF##16490279##18##,##REF##14574403##19##]. Furthermore, analytical problems resulting from the stochastic nature of lineage sorting and nucleotide substitution are reduced with an increased sample of genes and nucleotides. Our aim, here, was to explore the evolutionary history of the bananaquit populations within the West Indies from the vantage points offered by the different genes independently and collectively, considering their different mutation and substitution rates, coalescence times, modes of inheritance and effective population sizes.</p>", "<p>We obtained a well-resolved phylogeny of <italic>C. flaveola </italic>based on analysis of the six mitochondrial genes. The substitution rate of bananaquit mtDNA was high relative to the observed rate of lineage splitting, as evidenced by abundant synapomorphies and complete lineage sorting (reciprocal monophyly) of the major clades. The data exhibited no saturation and approximated clock-like nucleotide substitution. Thus, we are confident that the tree presented in Figure ##FIG##1##2## represents a strongly supported hypothesis of matrilineal relationship.</p>", "<p>In contrast, nuclear genes demonstrated considerably lower resolution regarding the phylogenetic relationships of bananaquit populations. The substitution rate of the nuclear genes was, on average, 16 times slower than the mitochondrial genes, and thus closely related clades strongly supported by the mitochondrial data (e.g., north central LA sister to Grenada/St. Vincent, and JA/CY sister to DR) were not distinguished by the nuclear data. Nonetheless, the allelic divergence at nuclear loci and the relative frequency of nuclear alleles across populations (Figure ##FIG##3##4##) clearly identifies the genetic distinctiveness of the bananaquit clades we have named \"Bahamas\", \"Jamaica\" and \"Puerto Rico\", and lends strong support to the hypothesis that these clades separated early in the diversification of <italic>Coereba</italic>.</p>", "<p>The slow nuclear sorting rate relative to population diversification resulted in many examples of incomplete lineage sorting compared to the mitochondrial perspective. Alternatively, the nuclear data could be interpreted as revealing abundant gene flow mediated by male bananaquits, biparental gene flow followed by localized episodes of selective sweeps acting on the mitochondrial genome, or drift associated with reduction in female population size. We suspect incomplete lineage sorting because deep in the bananaquit phylogeny both the nuclear and mitochondrial data consistently identify the same clades, with the single exception that individuals on Hispaniola (DR) have mitochondrial DNA closely related to JA/CY bananaquits, whereas the nuclear markers are allied with those on PR and the north central LA.</p>", "<title>Phylogenetic history of the Dominican Republic population on Hispaniola revealed by the discrepancy between nuclear and mitochondrial data</title>", "<p>Nuclear markers separate DR from JA/CY birds, whereas those populations are grouped in the same clade from a mitochondrial perspective. This surprising result was confirmed by sequencing eight additional samples from this population for nuclear (BFib5) and mitochondrial (ATPase) genes (data not shown). Recent introgression of JA/CY mitochondrial haplotypes into the DR population is the most likely explanation of conflicting positions of the DR samples in the nuclear and mitochondrial trees (Figures ##FIG##1##2## and ##FIG##2##3##). Although JA/CY mtDNA completely replaced the local DR mtDNA, we found no evidence of introgression in the nuclear genome. The challenge is to understand the complete introgression of the JA mitotype against a predominately DR nuclear background.</p>", "<p>Mitochondrial genomes are particularly susceptible to introgression, although this phenomenon is not clearly understood (see [##REF##15012752##15##] for a review). The ca. four-fold smaller effective population size of the mtDNA genome compared to the nuclear genome implies a higher probability for introgression by mtDNA. However, this outcome would be relatively unlikely if the number of JA immigrants was small relative to the population of resident DR bananaquits. Of course, if immigration from JA coincided with a population crash of Hispaniolan bananaquits, the likelihood of stochastic fixation of the JA mtDNA clade would have increased accordingly.</p>", "<p>Alternatively, mitochondrial introgression could have been favoured by selection, while the nuclear genomes of the two populations were incompatible. This type of selection-driven introgression has been demonstrated in <italic>Drosophila </italic>from mtDNA microinjection studies [##REF##2507929##20##] and more recently in wild goats from a molecular phylogenetic study [##UREF##12##21##]. The authors of the latter study suggested that proto-<italic>Hemitragus </italic>mtDNA could have invaded the ancestral population of <italic>Capra </italic>because the former were better adapted to high altitudes. However, we cannot imagine differences in the selective environments of basal bananaquit populations that might have led to the selective advantage of the JA mitochondrion, considering that the major islands of the Greater Antilles have a similar range of environments.</p>", "<p>A third hypothesis is that sexual selection could account for the observation, much in the same manner as hypothesized for <italic>Dendroica occidentalis </italic>warblers along the west coast and islands of British Colombia [##REF##11308096##22##]. In this case, hybrid JA/DR males would have a mating disadvantage, slowing the introgression of nuclear genes relative to the mitochrondrial genomes passed on only by the females. Each backcross generation would dilute the contribution of JA nuclear alleles, while JA mitotypes might become fixed by chance. However, unless the JA mitochondrion experienced a selective advantage, this scenario is likely only in the case of greatly reduced DR populations.</p>", "<p>Other biological processes that can create topological incongruence between gene trees include lineage sorting, paralogy, and lateral gene transfer [##REF##12116420##23##]. These alternatives can easily be discounted in the case of DR bananaquits.</p>", "<p>First, because several independent nuclear gene sequences support the complete divergence of the nuclear genomes of JA/CY and DR birds, the combination of DR nuclear and JA/CY mitochondrial genomes is not likely the result of incomplete lineage sorting of an ancestral polymorphism in nuclear alleles. Although scenarios implying gene duplications and gene deletions could be inferred for one nuclear gene only, it is highly unlikely that the same scenario may have occurred independently and identically in the three unlinked nuclear genes (RAG-1, Bfib5 and CHDZ). Indeed, the absence of substantial divergence between JA/CY and DR mitochondrial genomes indicates recent derivation. Second, phylogenetic trees using paralogous sequences may be misinterpreted if one assumes that the nuclear sequences are orthologous. Orthologous genes derive from the same locus whereas paralogous genes derive from different loci that originated by gene duplication [##UREF##13##24##]. However, reconstructing an erroneous gene tree based on paralogy or gene duplication/deletion is highly improbable because it would imply one multiple-gene or genome-wide duplication event at the root of the tree, a panmictic DR/JA/CY population until recently (necessary to explain the similar mitochondrial genomes), and several recent nuclear gene deletions. Finally, lateral gene transfer other than by hybridization/introgression can happen when an organism incorporates genetic material from another distantly related organism, and this can create topological incongruence between gene trees. However, animals seem to be largely unaffected by this phenomenon [##REF##15761667##25##] and it has never been reported for birds.</p>", "<title>The evolutionary history of bananaquits</title>", "<p>The mitochondrial phylogeny pictured in Figure ##FIG##1##2## confirms the phylogeographic structure of bananaquits revealed by the earlier RFLP analysis [##UREF##1##3##]. Regional mtDNA haplotype clades displayed levels of sequence divergence typically in excess of 2%, with the largest distances exceeding 5% (e.g., BH versus other populations). The nuclear DNA data confirm the mtDNA-based hypothesis of early divergence amongst bananaquit populations today revealed by three highly differentiated regional assemblages: BH, JA/CY, and PR/LA/SCA.</p>", "<p>Bananaquit lineages representing the BH, JA and PR were probably isolated soon after the initial geographic spread of the group in the GA. Subsequent expansions from the BH and JA were geographically restricted. Bananaquits from the BH probably spread to the Yucatán Peninsula of Mexico early in the history of that clade based on the mtDNA sequence of a single bird collected from QR (note that bananaquits from the coast of Veracruz group with other Central American birds, and that the species does not occur elsewhere on the Yucatán Peninsula, except for islands off the coast of Quintana Roo [##UREF##14##26##]. The sister relationship of this QR individual and the BH sample could place the root of the bananaquit phylogeny on the continent, independently of the widespread and more recent SCA clade. A more likely interpretation is that the QR individual represents relict population of a separate invasion from the Greater Antilles now restricted primarily to Cozumel Island. This raises the intriguing possibility that it is a relict of a former divergent population of bananaquits on Cuba, which would have been a likely source of colonization from the GA to QR. It seems unlikely that bananaquits never existed on Cuba. Their current status has been defined as \"possible permanent resident\" on cays off the northern coast of Cuba (Ciego de Ávila and Camagüey Provinces) and on the island itself at Gibara (Holguín Province), but breeding has not been established [##UREF##15##27##]. To summarize, bananaquits from coastal Yucatan deserve additional study, but data in hand suggest that the matriline allied to the BH is narrowly restricted in comparison to the predominant mtDNA haplotype clade in Middle America.</p>", "<p>The lineage of bananaquits found today on JA/CY is also narrowly distributed from a joint nuclear and mtDNA perspective. Given the predominance of the JA/CY matriline in the DR, however, it is clear that at least female bananaquits have moved between the islands relatively recently. Thus, migration or range expansion of the JA clade group has been recent in comparison to that of the BH mtDNA haplotype clade.</p>", "<p>Nuclear and mitochondrial data indicate that most of the contemporary distribution of bananaquits results from the spread of birds whose descendents are now found in PR, LA and SCA. The geographic expansion of this clade is relatively recent in comparison to the original diversification of bananaquits, and the first split of this expanding lineage (PR clade) separated island from continental birds. Subsequent diversification on the mainland led to reciprocally monophyletic mtDNA haplotype clades, one predominant in South America and the other in Middle America. In the islands, PR populations became isolated from LA populations, and then bananaquits in the north central LA became separated from the populations on Grenada and St. Vincent.</p>", "<p>The pattern of evolutionary quiescence followed by geographic expansion is also repeated in the mtDNA record of bananaquits in the LA. This history was clearly revealed in our earlier research [##UREF##1##3##] based on a mtDNA RFLP analysis of a larger sample of birds per island, and demonstrated that bananaquits had recently expanded their distribution through the northern islands in the chain. However, we did not anticipate the northward expansion of the north-central Lesser Antilles bananaquit clade all the way to the British Virgin Islands. It is particularly noteworthy that bananaquits crossed the Anegada Gap, which serves as a significant biogeographic divide in the West Indies, to colonize islands that would have been connected to PR, or nearly so, during Pleistocene low sea level stands. This seems improbable if the British Virgin Islands had been occupied by the Puerto Rican population of bananaquits, and suggests that a catastrophic event might have caused the extirpation of populations in the northern LA and the British Virgin Islands. The alternative scenario of north-central LA bananaquits displacing PR like birds in the British Virgin Islands as a result of competitive superiority is lessened by the evident failure of this lineage to invade Puerto Rico. Our sampling in PR included coastal areas on the eastern end of the island close to the Virgin Islands.</p>", "<p>At the other extreme of the LA, Grenada and Saint Vincent have maintained their evolutionary separation from islands to the north, but no significant separation from one another as measured genetically or morphologically. Both islands harbor melanistic forms of the bananaquit, as well as shared mtDNA haplotypes, that are not found on islands to the north. The evolutionary connection between Grenada and St. Vincent might reflect their separation by a shallow bank of islands (the Grenadines) that would have connected the islands during Pleistocene low sea level stands [##UREF##16##28##]. This is not the case for other islands in the LA, which are mostly (excluding St. Kitts-Nevis and Antigua-Barbuda) separated one from the other by deep-water channels.</p>", "<title>Phylogenetic support for taxonomic distinctions among subspecies</title>", "<p>Our molecular systematic appraisal of bananaquits permits us to assess phylogenetic support for taxonomic distinctions among the many named subspecies. Two subspecies groups were recognized by Paynter [##UREF##5##7##]: <italic>bahamensis </italic>(from the Bahamas) and <italic>flaveola </italic>(representing all other populations), but most populations in the West Indies have received specific or subspecific epithets at some time in the past, Bond [##UREF##17##29##] recognizing 16 subspecies. Our data confirm the genetic distinctiveness of the <italic>bahamensis </italic>birds; however, the <italic>flaveola </italic>group encompasses mtDNA haplotype clades that are nearly as divergent as <italic>flaveola </italic>and <italic>bahamensis </italic>groups. For example the JA/CY/DR clade is approximately 5% diverged in mitochondrial sequence from the remainder of the populations recognized as the <italic>flaveola </italic>subspecies by Paynter [##UREF##5##7##]. Additionally, subspecies such as <italic>portoricensis </italic>on Puerto Rico represent distinct evolutionary lineages. However, more often than not closely related or identical mtDNA haplotypes encompass several subspecies. For instance, the northern LA mtDNA haplotype clade includes four subspecies (<italic>sancti-thomae</italic>, <italic>bartholemica, martinicana</italic>, and <italic>dominicana</italic>), the two Panama bananaquits comprise different subspecies (<italic>columbiana </italic>and <italic>aterrina</italic>), and birds from Bolivia and Peru belong to three different subspecies (<italic>intermedia</italic>, <italic>dispar </italic>and <italic>alleni</italic>). Although finer genetic distinctions consistent with morphological differences between populations may exist, this study adds evidence that presently recognized bird subspecies often do not represent historically and phylogenetically equivalent evolutionary lineages (e.g., [##UREF##18##30##]).</p>", "<title>Revision of earlier phylogenetic and biogeographic history of the bananaquit</title>", "<p>Our analysis also allows us to review the phylogenetic and biogeographic history of the lineage. Bond [##UREF##19##31##] interpreted the distribution of <italic>C. flaveola </italic>in the West Indies as resulting from two invasions, one from South America spreading north through the LA and west to JA, and the other from Central America spreading north and east to the BH. Our initial mitochondrial RFLP-based survey of bananaquits [##UREF##1##3##] indicated a different, more complex history. However lacking samples from bananaquit populations on Dominican Republic and the Bahamas, as well as a suitable outgroup, we could not satisfactorily address Bond's [##UREF##19##31##] hypothesis of a continental origin for the species [##UREF##1##3##]. Results reported here confirm and extend the earlier molecular phylogenetic analyses.</p>", "<p>The sister-group relationship between SCA bananaquit populations rejects Bond's hypothesis, which predicted that the two continental regions should be most closely related to the island populations founded from South and Central America, respectively.</p>", "<title>Islands as the ancestral area of the bananaquit and \"reverse colonisation\" of the continent</title>", "<p>Because species diversity on islands decreases with distance from continental source areas [##UREF##20##32##,##UREF##21##33##], biologists have assumed that colonization of islands or archipelagos is a one-way process, and that \"reverse colonization\" to the mainland against a diversity gradient rarely, if ever, occurs. Our study confirms previous indications that island species also can colonize continental areas. Although the depauperate biotas of remote islands and archipelagos have little chance of recolonizing continental landmasses, near islands, such as the West Indies, have larger biotas with fewer impediments to dispersal, considerably improving the probability of back migration, or onward migration. Colonization from the islands to the mainland has similarly been reported within the West Indies for several bird species (e.g. <italic>Icterus </italic>orioles, [##UREF##22##34##]; <italic>Myiarchus </italic>tyrant-flycatchers [##REF##15019615##35##]; possibly <italic>Amazona </italic>parrots, [##UREF##23##36##]). Island to mainland colonization has also been demonstrated in monarch flycatchers from the Solomon Islands to New Guinea/Australia [##REF##16281034##37##] (see [##REF##18584910##38##] for a review).</p>", "<p>In the case of the bananaquit, we have provided both mitochondrial and nuclear evidence that permits strong inference that birds from the islands have colonized the mainland. The nesting of the South American to Panama samples within the West Indian clades and the deep paraphyly of bananaquits from the BH and JA clade with respect to all other bananaquits, including all mainland birds (except the single QR individual), represent the strongest lines of evidence that the ancestral node of the extant lineages is most parsimoniously placed in the Greater Antilles. Furthermore, ancestral area analysis (data not shown) based on the Bremer method [##UREF##24##39##] clearly excludes the continent as the ancestral area of <italic>Coereba</italic>. Finally, near outgroups for the bananaquit are principally emberizid finches from the West Indies [##REF##12144023##10##]. We cannot place the origin (stem lineage) of the species itself, but this issue is not relevant to the present study.</p>", "<p>To conclude, islands, including the West Indies, might be significant sources of biodiversity for continents, and we emphasize the importance of considering reverse colonisation for interpreting biogeographic patterns.</p>", "<title>Diversification and range expansion of Coereba flaveola in the West Indies: alternative scenarios</title>", "<p>Alternative scenarios of diversification and range expansion, from the Greater Antilles/Bahamas, can explain the phylogenetic patterns observed in both the mitochondrial and nuclear gene trees. They differ mainly in whether the continent was invaded directly from the Greater Antilles or through the Lesser Antilles.</p>", "<p>In the simplest scenario, bananaquits expanded from the GA to independently colonize the LA (through PR) and the continent (directly from the GA) approximately 1.7 to 4 Mya, through an Eastern route. Considering the affinity of South American genotypes to those on PR rather than DR or JA, a Western route can be excluded. This scenario is consistent from a mitochondrial point of view. It does not exclude the possibility that several phases of expansion might have occurred within the LA (including a recent one that would have homogenized the gene pool across the northern Antilles). However, direct colonization of South America from GA seems unlikely for several reasons. First, bananaquits, which do not flock and are not strong fliers, would have difficulty making a long over-water flight. Second, virtually all colonization events in the West Indies occur in stepping-stone fashion from one island to the next, rather than over long distances [##REF##11711673##2##,##UREF##25##40##]. Third, remnants of the nuclear genome of the South American birds in PR and LA (Figure ##FIG##2##3##) favour dispersal through the islands rather than directly from the GA.</p>", "<p>We envision colonization from GA to SCA through LA as occurring in the following way (Figure ##FIG##4##5##). First, bananaquits spread from the DR to PR and through the LA approximately 1.7 to 4 Mya. Evidence of this expansion is seen in the clade of haplotypes in the nuclear phylogeny recovered from DR, PR, and LA. This expansion did not reach the continent of South America.</p>", "<p>A second expansion would have occurred from PR through the LA to SCA about 0.7 to 1.7 Mya, as seen in the phylogenetic link between SCA, PR, and LA populations, exclusive of other GA populations, particularly DR (Figure ##FIG##1##2##). This is also corroborated by the fact that the combined nuclear genes (Figure ##FIG##3##4##) show the affiliation of continental haplotypes with LA and PR haplotypes, to the exclusion of DR haplotypes. It is also possible that the DR/PR/LA and PR/LA/SCA clades represent the same expansion, followed by lineage sorting.</p>", "<p>A third, more recent expansion from PR through the LA, but not to the continent, is indicated by the shared mitochondrial haplotypes of those two populations about 0.34 to 0.93 Mya. After the first and second expansions, PR birds would have had sufficient time to diverge from DR and continental populations from a mitochondrial perspective, but incompletely from a nuclear perspective. This would explain why the LA clade does not include DR mitochondrial sequences but does retain remnants of the DR nuclear genome.</p>" ]

[ "<title>Conclusion</title>", "<p>Analysis of genetic diversity in the bananaquit shows that the different rates of nuclear and mitochondrial genome processes, and incongruities between nuclear and mitochondrial phylogenies, can be used to dissect the often complex phylogeographic history of populations. We emphasize the importance of including multiple genes with distinct evolutionary histories. Our study is the first, to our knowledge, to demonstrate such biogeographic complexity for a single species. First, we demonstrated that the ancestral node of the extant bananaquit lineages is most parsimoniously placed in the Greater Antilles, indicating that islands, including the West Indies, might be significant sources of biodiversity for continents. We suggest that the \"reverse colonisation\" phenomenon deserves more systematic attention in phylogenetic analyses, and assessing its significance is of prime importance in studies of biogeography and ecology. Second, several phases of colonization and mixing among islands occurred before the bananaquit populations became isolated long enough to develop reciprocal monophyly in mtDNA. Third, the mixed nuclear and mitochondrial genomes in the Dominican Republic and the remnants of old Dominican Republic nuclear lineages in the Lesser Antilles suggest that expanding bananaquit populations mix with resident populations during expansion phases. Thus, genetic compatibility is maintained over periods exceeding three million years and perhaps much more, despite morphological and song differentiation. This does not exclude the possibility that expansions can follow extinctions of local populations or that colonists can competitively exclude local populations, as suggested by non-overlapping distributions of recently expanded mtDNA lineages in several species of Lesser Antillean birds [##UREF##26##41##].</p>" ]

[ "<title>Background</title>", "<p>The bananaquit (<italic>Coereba flaveola</italic>) is a small nectivorous and frugivorous emberizine bird (order Passeriformes) that is an abundant resident throughout the Caribbean region. We used multi-gene analyses to investigate the evolutionary history of this species throughout its distribution in the West Indies and in South and Middle America. We sequenced six mitochondrial genes (3744 base pairs) and three nuclear genes (2049 base pairs) for forty-four bananaquits and three outgroup species. We infer the ancestral area of the present-day bananaquit populations, report on the species' phylogenetic, biogeographic and evolutionary history, and propose scenarios for its diversification and range expansion.</p>", "<title>Results</title>", "<p>Phylogenetic concordance between mitochondrial and nuclear genes at the base of the bananaquit phylogeny supported a West Indian origin for continental populations. Multi-gene analysis showing genetic remnants of successive colonization events in the Lesser Antilles reinforced earlier research demonstrating that bananaquits alternate periods of invasiveness and colonization with biogeographic quiescence. Although nuclear genes provided insufficient information at the tips of the tree to further evaluate relationships of closely allied but strongly supported mitochondrial DNA clades, the discrepancy between mitochondrial and nuclear data in the population of Dominican Republic suggested that the mitochondrial genome was recently acquired by introgression from Jamaica.</p>", "<title>Conclusion</title>", "<p>This study represents one of the most complete phylogeographic analyses of its kind and reveals three patterns that are not commonly appreciated in birds: (1) island to mainland colonization, (2) multiple expansion phases, and (3) mitochondrial genome replacement. The detail revealed by this analysis will guide evolutionary analyses of populations in archipelagos such as the West Indies, which include islands varying in size, age, and geological history. Our results suggest that multi-gene phylogenies will permit improved comparative analysis of the evolutionary histories of different lineages in the same geographical setting, which provide replicated \"natural experiments\" for testing evolutionary hypotheses.</p>" ]

[ "<title>Authors' contributions</title>", "<p>EvB carried out the molecular genetic studies, participated in the sequence alignment and phylogentic analyses and drafted the manuscript. ElB and RER conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>This work was conducted at the Smithsonian Tropical Research Institute, Panama. Eva Bellemain was supported by the Smithsonian Institution James Bond Restricted Endowment. Research by E Bermingham and RER on West Indian birds has been supported by the National Geographic Society, the National Science Foundation, and the Smithsonian Institution. We are very grateful to L. Garcia, M. Gonzalez and C. Vergara for technical support in the laboratory, to A. J. Crawford for comments on an earlier draft of this manuscript and to O. Sanjur for advice. We also thank A. T Peterson and an anonymous reviewer for helpful comments on an earlier version of the manuscript.</p>" ]

[ "<fig id=\"F1\" position=\"float\"><label>Figure 1</label><caption><p><bold>Geographic representation of the sample localities of the <italic>Coereba flaveola </italic>specimens analyzed</bold>. Locality codes are the same as in additional file ##SUPPL##0##1##.</p></caption></fig>", "<fig id=\"F2\" position=\"float\"><label>Figure 2</label><caption><p><bold><italic>Coereba flaveola </italic>phylogenetic relationships based on the combined mitochondrial dataset (ATPase 8/6, cyt b, BCO1, ND2 and ND6 genes) inferred from a Bayesian analysis and rooted using three outgroup species (<italic>Tiaris olivacea</italic>, <italic>Loxigilla portoricensis </italic>and <italic>Melanospiza richardsoni</italic>)</bold>. Values above the major branches represent the number of substitutions per site, estimated as the mean value of the branch in all samples of the Markov chain where the branch appears. Values below each major branch represent posterior probability values. Sample names are composed of a locality code (same as in additional file ##SUPPL##0##1##) and a sample number.</p></caption></fig>", "<fig id=\"F3\" position=\"float\"><label>Figure 3</label><caption><p><bold><italic>Coereba flaveola </italic>phylogenetic relationships based on the combined nuclear Bfib5, Rag1 and CHDZ genes, inferred from a Bayesian analysis and rooted using three outgroup species (<italic>Tiaris olivacea</italic>, <italic>Loxigilla portoricensis </italic>and <italic>Melanospiza richardosoni</italic>)</bold>. Letters following each sample name (a or b) represent the two haplotypes for each sample.</p></caption></fig>", "<fig id=\"F4\" position=\"float\"><label>Figure 4</label><caption><p><bold>Haplotype networks for the three nuclear genes (Bfib5, Rag1 and CHDZ) and the combined genes for <italic>Coereba flaveola</italic></bold>. Branch lengths are proportional to the number of mutations and the size of each node is proportional to haplotype frequency. Each of the clades defined from the mitochondrial or nuclear consensus trees (Figures 2 and 3) is given a specific color.</p></caption></fig>", "<fig id=\"F5\" position=\"float\"><label>Figure 5</label><caption><p><bold>Phylogeny of <italic>Coereba flaveola </italic>surimposed on the geography of the Caribbean region</bold>. The geographic patterns of the different mitochondrial and nuclear lineages allow resolving the complex phylogenetic history of the species.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Table 1. Blood and tissue samples used in this study with sampling locations, geographical coordinates and Genbank accession numbers for each sequenced gene. For nuclear genes, each accession numbers corresponds to an allele sequence. NA stands for \"none available\" (a clean sequence could not be obtained), NS for \"not sequenced\", numbers beginning with a \" A\" refer to previously published sequences.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Table 2. Molecular characterization of the mitochondrial and nuclear genes in <italic>Coereba flaveola</italic>.</p></caption></supplementary-material>" ]

[]

[ "<graphic xlink:href=\"1471-2148-8-240-1\"/>", "<graphic xlink:href=\"1471-2148-8-240-2\"/>", "<graphic xlink:href=\"1471-2148-8-240-3\"/>", "<graphic xlink:href=\"1471-2148-8-240-4\"/>", "<graphic xlink:href=\"1471-2148-8-240-5\"/>" ]

[ "<media xlink:href=\"1471-2148-8-240-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2148-8-240-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>TEs are widely distributed in eukaryotes, representing 50% of the human genome [##REF##11237011##1##], 15% of the Drosophila genome, and up to 70% in <italic>Zea mays </italic>[##UREF##0##2##]. Because of their capacity of transposition they are able to invade the genome and promote insertional mutations and chromosomal rearrangements. Recurrent mobility allows them to persist in spite of their harmful effects in the host [##REF##16888345##3##]. Most of the proposed models in population dynamic studies [##UREF##1##4##, ####REF##2559652##5##, ##REF##1334899##6##, ##REF##1334900##7##, ##REF##15466430##8####15466430##8##] suggest that TEs are able to invade the genome if their transposition rate is enough to balance out opposing forces as excision and selection against deleterious insertions and chromosomal arrangements. Yet, these models, often too general, do not consider that each element behaves depending on both its own characteristics and the history of the population to which it belongs. This challenge to standard reasoning is most relevant in colonizing populations [##REF##11486506##9##]. Several authors have suggested that bursts of transposition could be induced in colonization by the foreign, often stressful, environment faced by the founders of colonizing populations [##REF##12082134##10##,##REF##9391219##11##]. Moreover, colonizing populations are subjected to well documented founder, drift effects [##UREF##2##12##]. Both processes generate population instabilities that may incorporate new variables to the interpretation of TE occupancy profiles in colonizing populations. These considerations qualify the study of TEs in colonization as of prime interest to understanding their invasive dynamics and putative evolutionary role in populations.</p>", "<p>Colonization effects on TEs were studied in Drosophila species [##REF##11486506##9##,##REF##9391219##11##,##REF##12572617##13##] showing that this process plays an important role in the TE chromosomal distribution. In particular studies in colonizing populations of <italic>D. buzzatii </italic>showed a TE bimodal distribution with sites either highly occupied, in a few cases, or showing low insertion occupancy, in most cases. Molecular studies of TE copies from high and low occupied sites [##REF##17151248##14##] strongly indicated that the most reliable explanation of the observed bimodal distribution is that a founder effect followed by genetic drift occurred during the colonization process. These results notwithstanding, valid for <italic>D. buzzatii</italic>, cannot be generalized to other colonizing Drosophila species, with different genomic characteristics, and subjected to different environmental pressures.</p>", "<p><italic>D. subobscura</italic>, a Paleartic species belonging to the obscura group [##UREF##3##15##] and characterized by a rich inversion polymorphism [##UREF##4##16##], has colonized North and South America almost 30 years ago [##UREF##5##17##,##REF##16593967##18##]. It was found for the first time in Puerto Montt (Chile) in 1978 [##UREF##6##19##] and later near Port Townsend in Washington (USA) in 1982 [##UREF##7##20##]. Thereafter this species showed a rapid spread and adaptation to the new colonized environment in form of latitudinal clines for chromosomal polymorphism and body size that paralleled the Paleartic clines [##UREF##5##17##,##REF##16593967##18##,##UREF##8##21##]. Main after-colonization population effects were the presence of allelic lethal genes in different populations [##UREF##9##22##], the low genetic variability of mtDNA [##REF##16578796##23##,##REF##2299979##24##] and the reduction of microsatellite allele numbers [##REF##11319257##25##] compared to original founder populations. These are expected outcomes of the founder drift effect of colonization. However nothing is known of the impact of colonization on the TE chromosomal distribution in this species.</p>", "<p>Here we present the study of the distribution of two TEs, <italic>gypsy </italic>and <italic>bilbo</italic>, in original and colonizing populations of <italic>D. subobscura</italic>. Results show that TE frequency distribution differ between original and colonizing populations in a way that colonization, chromosomal inversion polymorphism and particular characteristics inherent to each element can provide a sufficient likely explanation. In this paper we particularly emphasize the importance of population structure and history to explain TE distribution in natural populations.</p>" ]

[ "<title>Methods</title>", "<title>Drosophila strains</title>", "<p>The control strain <italic>chcu </italic>carries the recessive markers cherry eyes and curled wings and is homokaryotypic for chromosomal arrangements A_st, J_st, U_st, E_stand O₃₊₄. It is kept by mass-culturing to maintain its viability. <italic>In situ </italic>hybridization for insertions of <italic>bilbo </italic>and <italic>gypsy </italic>displayed high stability over generations in 19C, 46A, 46C, 73A, 81D, 84A, 96A for <italic>bilbo </italic>and in 7C and 52A for <italic>gypsy</italic>.</p>", "<p>The original population was sampled in Spring 2005 in Bordils (42.30°N, Girona, Spain). The colonizing populations were sampled in Spring 2004 in Davis (38.33°N, California, USA) and Bellingham (48.45°N, Washington, USA), and in Spring 2005 in Maipú (36.52°S, Argentina).</p>", "<title>Mating system (prior to \"<italic>in situ</italic>\" hybridization)</title>", "<p>Individual males of natural populations were crossed with virgin females of the control line <italic>chcu</italic>. Insertion profiles were analyzed in F₁female larval progeny to include the X chromosome. The TE insertion profile of each male was deduced by subtracting the TE insertion profile of the control line from that of the F1 larva.</p>", "<title><italic>In situ </italic>hybridization and DNA probes</title>", "<p>Polytene chromosome [##UREF##4##16##] squashes from salivary glands of third-instar larvae, prepared as described in [##REF##2185305##79##], were hybridized with digoxigenin labelled probes of <italic>bilbo </italic>and <italic>gypsy</italic>. The probes consisted of PCR fragments (2.6 and 2.8 kb long) which included the reverse transcriptase region. Prehybridization solutions and posthybridization washes were done following a protocol by Roche [##UREF##23##80##]. PCR reactions were carried out in a final volume of 25 μl, including 1× activity buffer (Ecogen), 1.6 mM MgCl₂, 0.2 mM of each dNTP (Roche), 0.4 μM primer (Roche), 10–20 ng of genomic template DNA, and 0.04 units per μl of Taq polymerase (Ecotaq from Ecogen). Amplifications were run in a MJ Research Inc. thermocycler programmed as follows: 5 min preliminary denaturation at 94°, 30 cycles of 45 s at 94° (denaturation), 45 s at specific PCR annealing temperatures, 1.5 min at 72° (extension) and a final extension for 10 min at 72°. PCR products were gel purified with a Geneclean kit (BIO 101) and labelled using the random primer method. After hybridization signal development was done using an anti-digoxigenin antibody conjugated with alkaline phosphatase (Roche).</p>", "<p><italic>In situ </italic>hybridization is the more suitable method used in localization of TEs on chromosomal arms. However, the power of resolution of this technique allow us neither discriminate between closely neighbouring sites, nor between elements that diverge below 10%.</p>", "<title>Statistical analyses</title>", "<p>Statistical analyses were performed excluding centromeric and pericentromeric TEs insertions. The statistical software SPSS version 14.0 was used for most of the statistical data analyses.</p>", "<p>In cases of multiple testing, corrections were achieved measuring the significance of False Discovery Rates [##UREF##24##81##] through q values. To get the q-value we used the software QVALUE [##UREF##25##82##] on the p values obtained from the multiple test. When this test could not be applied, Bonferroni's correction was performed [##UREF##26##83##].</p>" ]

[ "<title>Results</title>", "<title>Chromosomal distribution of <italic>bilbo </italic>and <italic>gypsy</italic></title>", "<p>We analyzed the distribution of <italic>bilbo </italic>and <italic>gypsy </italic>in polytene chromosomes of <italic>D. subobscura</italic>. Fig. ##FIG##0##1## shows two examples of chromosomal distribution: <italic>bilbo </italic>in chromosome O and <italic>gypsy </italic>in chromosome U. A different distribution pattern is observed, in general, when we compare colonizing and original populations. Colonizing populations present insertion frequencies of <italic>bilbo </italic>and <italic>gypsy </italic>higher than those of the original population. In general the same distribution pattern is observed for the rest of chromosomes. Ten sites (7A, 16A, 20A, 45C, 58D, 74D 82A, 83C, 85A, 89C) show a <italic>bilbo </italic>insertion polymorphism greater than 32% in at least one colonizing population. <italic>Gypsy </italic>insertion frequencies are lower than those of <italic>bilbo </italic>with an occupancy of more than 10% in eight chromosomal sites (39D, 41C, 43D, 49D, 52D, 63C, 71B, 74D). Differences in occupancy profiles between original and colonizing populations are represented in Table ##TAB##0##1## that shows the distribution of the number of times that each site is occupied in the studied sample. Thus, in <italic>bilbo </italic>the occupancy frequency ranges from 1 to 51 times in colonizing populations and only from 1 to 19 in the original population. Although <italic>gypsy </italic>shows a low occupancy profile compared to <italic>bilbo </italic>(colonizing populations range: 1–15; original population range: 1–5), the occupancy rate of both TEs in colonizing populations is greater than in the original population. The highest <italic>bilbo </italic>insertion frequencies are observed, in decreasing order, in Bellingham, Maipú and Davis. In the original population of Bordils, the highest insertion frequency corresponds to one site observed 16 times.</p>", "<p>Table ##TAB##1##2## lists the means and variances of copy number for <italic>bilbo </italic>and <italic>gypsy </italic>per chromosome and haploid genome. The mean copy number of both TEs for the whole genome (HG) is always higher in colonizer populations than in the original one. The <italic>bilbo </italic>mean copy number differs greatly among chromosomes ranging from 2.58 copies in chromosome O from Bellingham to 0.55 in chromosome J from Davis. In fact chromosome J hosts the lowest number of <italic>bilbo </italic>in all populations. A different scenario is found for <italic>gypsy </italic>in which the A (X) chromosome contains the lowest number of insertions, in colonizer and original populations alike. However, among the autosomes J is the least occupied in all populations. Deviation from Poisson distribution was tested by chi-square goodness of fit tests (for details, see additional files ##SUPPL##0##1## and ##SUPPL##1##2##) pooling adjacent classes with low expected numbers. In colonizing populations <italic>bilbo </italic>distribution in each chromosome fits a Poisson distribution. <italic>Gypsy </italic>deviates from a Poisson distribution in E chromosome from Davis and Bellingham and in U chromosome from Maipú. When the whole genome is considered both TEs follow a Poisson distribution in the original population and deviate in all colonizing ones, except for <italic>bilbo </italic>in Bellingham and gypsy in Maipú. For this element the general trend in colonizing populations is a lower than expected number of genomes with a single copy and an excess of genomes with three or more copies (see Table ##TAB##0##1##). An alternative test was performed using dispersion coefficients (DC), which measure the ratio between the variance (V_n) and the mean (m) (DC = V_n/m, see table ##TAB##1##2##). DC of 1 indicates that TE distribution is Poisson, and DC &gt; 1 or DC &lt; 1 indicates contagious or repulsive distributions, respectively. When the haploid genome is considered, there is a general tendency towards DCs &gt; 1 for both elements in all populations except for <italic>gypsy </italic>in Maipú (these results are due to the greater effect of some chromosomes in the final result of the test).</p>", "<p>Because in some cases TE sites seem to be distributed in a contagious way (DC &gt; 1), linkage disequilibrium was computed for each pair of sites by way of 2 × 2 contingency tables [##REF##2558961##26##]. Linkage disequilibrium between TE sites could be responsible of the non-random distribution detected in some cases. The observed distribution of correlation coefficients between all paired sites was compared to the expected distribution in absence of linkage disequilibrium using Fisher's hypergeometric formula [##UREF##10##27##]. Figure ##FIG##1##2## depicts, as an example, the correlation coefficient distributions (pooled in intervals of 0.1) of <italic>bilbo </italic>in chromome E from Bordils and in chromosome O from Maipú; and of <italic>gypsy </italic>in chromosome E from Davis and Bellingham. Tests were significant in most cases where a deviation from Poisson distribution was observed. Moreover we also found significant results in some cases where departures from Poisson distribution were not detected (e.g <italic>bilbo </italic>on chromosome O of Maipú). The general trend is a defect of class (-0.09–0.00) and an excess of some positive correlation classes. This indicates that some sites tend to stay together, as indicated by a DC &gt; 1. This tendency was observed in all cases where deviations from Poisson distribution were observed, except for <italic>gypsy </italic>in chromosome U from Maipú where there is an overabundance in class (-0.09–0.00) and the DC is lower than 1.</p>", "<title>Copy number comparisons among chromosomes</title>", "<p>Montgomery et al [##REF##3032743##28##] proposed that selection against TE insertions would lead to a lower number of TE copies in chromosome X than in autosomes due to the stronger deleterious effect of recessive insertional mutations in the X chromosome of hemizygous males. In order to test this hypothesis we compared the copy number in the A (X) chromosome with that in autosomes. To estimate the expected number of insertions we multiply the relative proportion of chromatin of each chromosome by the number of total insertions in the population. The relative proportion of chromatin is that reported by Stumm-Zollinger and Goldschmidt [##UREF##11##29##] corrected by eliminating the dot chromosome, not included in our analyses. If TEs are randomly distributed, we expect a TE copy number per chromosome proportional to the amount of chromatin.</p>", "<p>Observed and expected proportions were compared by a G test [##UREF##12##30##] among all chromosomes (G_a), between the A (X) chromosome and autosomes (G_b), and among autosomes (G_c), as indicated in Table ##TAB##2##3##. G_bvalues were significant for <italic>gypsy </italic>in all populations, and for <italic>bilbo </italic>only in Maipú and Bordils. Because some differences may be due to high insertion sites, additional analyses were done after eliminating these sites. After elimination the significance was maintained for <italic>gypsy </italic>in all populations except in Maipú, and removed for <italic>bilbo</italic>. In general <italic>gypsy </italic>shows a low copy number in the A (X) chromosome compared to autosomes. However, this is not the rule for <italic>bilbo </italic>where Maipú and Bordils show a high copy number in A (X). Interestingly, those populations that display <italic>gypsy </italic>copy number differences between A (X) and autosomes, show also significant differences among autosomes (G_c), specially in colonizer populations where chromosomes E and O show a higher copy number than expected.</p>", "<p>In general, copy number tend to be higher for <italic>bilbo </italic>in chromosome O and for <italic>gypsy </italic>in chromosome U in all colonizing populations, (except <italic>bilbo </italic>in Maipú), whereas in the original population the E chromosome hosts the highest proportion of <italic>gypsy </italic>and <italic>bilbo</italic>. In order to determine if chromosomal differences have the same tendency in colonizing populations, heterogeneity (H) tests were performed for comparisons among chromosomes, between A (X) and autosomes and among autosomes. Table ##TAB##2##3## shows that all cases were heterogeneous for both TEs. However when Maipú is excluded from the analyses and high insertion frequency sites are eliminated, Bellingham and Davis become homogeneous for <italic>bilbo </italic>(data not shown).</p>", "<title>Correlation studies between high frequency sites and chromosomal arrangements</title>", "<p>All five pairs of acrocentric chromosomes of <italic>D. subobscura </italic>are polymorphic for inversions. Frequencies of chromosomal arrangements show clinal variation correlated with latitude in Paleartic populations [##REF##14503625##31##,##UREF##13##32##] and clines that follow the same latitudinal gradient evolved in recent colonizing populations in both hemispheres of the Americas [##UREF##5##17##,##REF##16593967##18##]. These parallel observations across continents provided a natural experiment that supports the adaptative role of the chromosomal inversion polymorphism.</p>", "<p>Frequencies of chromosomal arrangements in the analyzed populations of this work are summarized in Table ##TAB##3##4##. Each arrangement is conventionally designed by the letter of the chromosome in which it occurs, followed by a combination of digits that identify the set of inversions included in it [##UREF##4##16##]. Arrangement frequencies are of the same order of magnitude as those previously reported, including the North-South latitudinal variation of most arrangements [##UREF##8##21##,##REF##14503625##31##,##UREF##13##32##]. However it is interesting to note that Maipú presents a higher O_Stfrequency than expected according to its latitude.</p>", "<p>Some authors consider recombination as the main factor determining the chromosomal distribution of TEs [##REF##12032249##33##,##REF##11875027##34##], but see [##REF##11875027##34##]. The model of ectopic exchange, predicts a negative correlation between recombination rate and TE copy number if ectopic exchange is reduced in parallel with regular meiotic recombination rate [##REF##8878672##35##,##REF##2854088##36##]. Under this model, TEs are expected to be more abundant in regions of low recombination as inversions or inversion break-points. In these regions the probability of induction of deleterious rearrangements produced by unequal recombination between TEs, is low because most of the time inversions will be found in heterozygous state (recombination is suppressed inside). Experimental evidences [##REF##10411506##37##, ####UREF##14##38##, ##REF##9770505##39####9770505##39##] suggest that TEs are responsible of chromosomal inversions in natural populations of Diptera and are particularly abundant inside and near inversion break-points [##REF##1334899##6##,##REF##1334900##7##,##REF##8088526##40##].</p>", "<p>In order to know whether an association between high insertion sites and arrangements exist, we computed the product-moment correlation coefficient (r) for high-frequency sites (Table ##TAB##4##5##). We observed two <italic>bilbo </italic>sites of particular interest (67A and 89C) that show the highest correlation coefficients. The 67A site is located inside the breakpoint of arrangement E₁₂and is significantly associated with E_1+2+9+12in Davis (r = 0.64) and Maipú (r = 0.85). The 89C site is located near the break-point of O₈arrangement and is significantly correlated with arrangement O₃₊₄₊₈in Davis (r = 0.58) and Bellingham (r = 0.34), and only marginally (r = 0.26) in Maipú. Other instances of significant associations are not so easily explained because sites are external to inversion breakpoints. Thus, highly occupied 74D <italic>bilbo </italic>site is located outside of chromosomal inversions, yet, it is also significantly associated with E_1+2+9+12in Davis (r = 0,33) and Maipú (r = 0,24). This site is also highly occupied by <italic>gypsy </italic>but in this case associations are not significant. In other cases we observe associations of sites inside highly frequent inversions where the crossing-over is not reduced. This is the case of 11B <italic>bilbo </italic>site, for example, negatively associated to A₂arrangement in all populations except Bellingham but located inside it.</p>" ]

[ "<title>Discussion</title>", "<title><italic>Bilbo </italic>and <italic>gypsy </italic>distributions are different in original and colonizer populations</title>", "<p>Results show a clear differential TE distribution in original and colonizing populations. While in the original population most sites have low insertion frequencies, colonizing populations present some highly occupied sites, with frequencies higher than 50% for <italic>bilbo </italic>and close to 20% for <italic>gypsy</italic>. Interestingly, most of them are common to all populations. Mean copy number of both elements is higher in colonizing populations than in the original one due to the presence of these highly occupied sites.</p>", "<p>Low occupied sites would represent insertions occurred after colonization and/or copies from the original population whose frequency is decreasing in colonizing populations. An argument in favour of the former hypothesis is the existence of unique sites that would correspond to new transpositions (i.e. site 48D of gypsy), while the latter hypothesis explains the existence of low-occupancy original sites common to different populations (i.e. site 41A of gypsy or 85B of bilbo).</p>", "<p>High insertion frequency sites are most likely due to a founder event during the colonization process (the founder hypothesis), as previously reported in other Drosophila species [##REF##11486506##9##,##REF##9391219##11##,##REF##12572617##13##]. In <italic>D. buzzatii </italic>this hypothesis was also verified by molecular studies showing identical <italic>Osvaldo </italic>retrotransposon structures and flanking genomic sequences in high insertion frequency sites from different colonizing populations [##REF##17151248##14##].</p>", "<p>In this study two lines of evidence support the founder hypothesis. First, the two studied TEs belong to different subclasses, yet they show a similar population behaviour. Second, most highly occupied sites are located in colonizing population chromosomes, although some exceptions occur for <italic>bilbo </italic>whose insertion frequency exceeds 10% in 9 sites in the original population of Bordils. All these sites correspond also to high insertion sites in colonizing populations, except 90C site and 21A, which are, respectively, free of insertions or occupied at low frequency in America.</p>", "<p>The presence of high frequency sites in the original population could be a consequence of the transposition mechanism of <italic>bilbo</italic>, a LINE element. It has been shown that LINE elements (L1) make 5' truncated copies during their transposition mechanism indicating that 5' sequences are not absolutely necessary to insertion [##REF##17023124##41##, ####REF##2550903##42##, ##REF##2445384##43####2445384##43##]. In fact, the majority of the L1 copies present in mammalian genomes are 5' truncated with a length of not more than 1 kb [##REF##11237011##1##,##REF##12368240##44##]. We can think that selection against truncated, \"dead-on-arrival\" (DOA) copies should be weak because they are not transcribed, potentially immobile and shorter than full copies. Thus, deleted copies could persist in some genomic regions without being completely eliminated by natural selection. In fact, some Drosophila TE families (most of them LINE like elements) seem to be only marginally affected by purifying selection, reaching high insertion frequencies in euchromatin [##REF##12716993##45##].</p>", "<p>On the other hand, some of <italic>bilbo </italic>high frequency sites from Bordils could be explained by the dragging effect from the rich inversion polymorphism of <italic>D. subobscura</italic>. For example the 67A site located in the break-point of E₁₂arrangement presents highly significant correlations with this arrangement in 2 out of 3 colonizing populations. In Bordils, this correlation is not significant because of the lower frequency of this arrangement in this population. Arrangements of chromosome E cover approximately 75% of its length and it is not rare to find this kind of associations. In this chromosome another high insertion frequency site (74D) shows association with the same E_1+2+9+12chromosomal arrangement. This site corresponds to a heterochromatic telomeric site where it is not rare to find an accumulation of TE insertions. In fact <italic>gypsy </italic>is inserted also in this chromosomal site at occupation rates that range from 1.3 to 11.4%. Accumulation of TEs in heterochromatin is well documented in <italic>D. melanogaster </italic>where a significant excess of insertions were reported in heterochromatin, dot and Y chromosomes alike [##REF##15219154##46##, ####REF##7664614##47##, ##REF##8078581##48##, ##REF##12654931##49####12654931##49##].</p>", "<p>Seasonal fluctuations in population frequency of chromosomal rearrangements can modify recombination rates and associations between arrangements and genes. In <italic>D. subobscura </italic>no seasonal fluctuations were reported in some works [##REF##5584166##50##,##UREF##15##51##], but fluctuations and seasonal changes of associations between chromosomal inversions and allozymes were reported in others, specially in the O chromosome from original populations [##REF##17246183##52##,##REF##12778553##53##]. In the present case, we observe no associations between insertions and specific chromosomal arrangements in the original population, but we do detect this kind of associations in colonizing populations (where fluctuations were not studied). However, changes in associations between chromosomal arrangements and chromosomal sites do not follow a definite trend. As an example, the U_STarrangement, whose frequency has increased in all colonizing populations, shows a positive association to 43B and 45C sites but a negative one to 53A site in Maipu. This is a rather odd outcome since increase of rearrangement frequency is always expected to break down associations due to an increase of recombination rate. So, the likely explanation would be that fluctuations do not affect associations or at least not in the same way for every studied rearrangement polymorphism.</p>", "<p>On the other hand, we favor the general idea that the positive correlation between arrangements and TE copies is not due to an inversion effect but, most probably, to the founder event [##UREF##6##19##,##REF##11319257##25##,##REF##7995925##54##,##UREF##16##55##]. This could explain why arrangement E_1+2+9+12and the 74D site, which is located outside of the inversion, show a positive association and also why an excess of classes including positive correlation coefficients between chromosomal sites was observed in some chromosomes like E. Genetic estimates suggest that the number of founders ranged from 10 to 150 [##REF##11319257##25##,##UREF##17##56##]. If some founders carried together this site and this arrangement, both will appear together in all populations because they are identical by descent. The founder hypothesis is favored by the fact that all correlations between sites and arrangements are significant only in colonizing populations. In the original population in spite of having correlation coefficients of 0.57 (in 57D) and 0.56 (in 83C) with E₁₊₂₊₉and O₃₊₄₊₇respectively, these are not significant. In fact, these two arrangements are currently decreasing in frequency in the Mediterranean populations and perhaps these combinations descend also from a few individuals. All these considerations suggest that most of the associations detected are due to a founder effect.</p>", "<p>The general rule, as reported in <italic>D. melanogaster </italic>[##REF##12716993##45##,##REF##1334919##57##], is that TEs are spread and have low insertion frequencies in euchromatin. In some cases, however, accumulations of TEs in some chromosomal sites have been reported, as in the 42B [##REF##2548982##58##], 87C [##UREF##18##59##] and 38 [##UREF##19##60##] regions, of <italic>D. melanogaster</italic>, and the 85D region of <italic>D. subobscura </italic>[##REF##2612293##61##,##UREF##20##62##], and even fixation has occurred, as in the 42C site in natural populations of <italic>D. simulans </italic>[##REF##8642613##63##]. Preferential insertion sites (hotspots) have been suggested for some Drosophila elements [##UREF##21##64##, ####REF##6266759##65##, ##REF##2832692##66####2832692##66##] and we cannot completely discard the possibility of an activation of transposition to specific hotspots during the colonization process. This hypothesis could be verified if a process affecting equally the two TEs studied occurred, as shown in <italic>D. melanogaster</italic>. In this species some proteins are involved in RNA-silencing mechanisms for retrotransposable elements repression [##REF##17277359##67##, ####REF##17135323##68##, ##REF##16809489##69####16809489##69##]. We cannot discard the existence of a similar mechanism in <italic>D. subobscura </italic>that was de-repressed as a consequence of the colonization process contributing simultaneously to an increase of transposition of different transposable elements.</p>", "<title>Factors affecting TEs distribution in <italic>D. subobscura</italic></title>", "<p>In Drosophila, TEs seem to be maintained in populations as the result of a balance between transposition and opposing forces that reduce their copy number. In this way selection can act either directly against deleterious insertions or indirectly against deleterious chromosomal rearrangements produced by ectopic recombination between TEs [##UREF##1##4##,##REF##2559652##5##,##REF##2854088##36##,##REF##17246144##70##]. In this work a test of selection against deleterious insertions was done by comparing copy numbers between X and autosomes, selection being more effective in the former than in the latter.</p>", "<p>For <italic>gypsy </italic>we observe a clear tendency to follow a selection model, except in Maipú. This result is in concordance with that observed in a natural population of <italic>D. melanogaster </italic>with this element [##REF##8082837##71##]. For <italic>bilbo </italic>the data do not fit a selection model against deleterious insertions; even in those cases where the test is significant, a higher copy number on A (X), compared to autosomes, is observed. A possible explanation of this result is that <italic>bilbo </italic>could have a differential transposition rate between X and autosomes. Some examples of transposition restricted to female or male <italic>D. melanogaster </italic>germ line have been reported [##UREF##22##72##,##REF##9230904##73##] and they should be taken into account when X and autosomes are compared. On the other hand, the discrepancies observed between the two elements may be accounted for by the different factors that control copy numbers in each of these elements. In <italic>D. melanogaster gypsy </italic>is a retrovirus [##REF##8108403##74##] submitted probably to a strong selection effect, its transposition depending on the presence of permissive alleles most likely segregating in natural populations. In <italic>D. subobscura </italic>this retrotransposon seems to be non infectious because current available copies have an apparently inactive <italic>env </italic>region [##REF##8600460##75##], but this does not discard the putative presence of alleles that control its transposition. On the other hand <italic>bilbo </italic>is a LINE element and could be submitted to a soft selection pressure due to its DOA transposition mechanism. Most of the copies are probably deleted and its deleterious capability by transposition is diminished. The model of selection against deleterious insertions has been questioned by some authors [##REF##3032743##28##,##REF##8078581##48##] because neither all ETs nor all populations had a lower insertion frequency on X chromosomes compared to autosomes. However in a later work [##REF##9440269##76##], where the authors reanalyze the data including more results from other species, selection against insertions is considered as the major mechanism of TE copy number control. On the other hand, values of selection coefficients against deleterious mutations could not be comparable to mutations associated to TE insertions. Moreover, deleterious effects of TEs can be species specific and populations may also sometimes suffer TE mobilizations that mask selection effects on TE distribution.</p>", "<p>In this work each element presents a different behavior probably due to their distinct transposition mechanisms. Moreover we should not forget that elements which are stable in some genome conditions could be unstable in others. Recently mobilized TEs and/or colonization events, in populations, could lead to a differential copy distribution between chromosomes, rendering the selection undetected. This could be the case of Maipú, a new colonizing Argentinian population, which shows a distribution pattern for <italic>gypsy </italic>and <italic>bilbo </italic>quite different from the other colonizing populations. In particular, some high insertion frequency sites are more represented, or even exclusive, in this population. It is possible that Maipú was established through a bottleneck of founder flies from Chile as a consequence of a secondary colonization. In this case, we cannot discard the existence of new transposition events in founders induced by the new environmental conditions encountered as previously proposed by other authors [##REF##12082134##10##,##REF##9391219##11##]. If this colonization occurred recently, as indicated by collecting records, selection has not had enough time to act, explaining the discrepancies in this population when comparing A (X) and autosome copy numbers in Table ##TAB##2##3## or when this population is included in heterogeneity tests. In addition if TEs are not at equilibrium, departures from random distribution across chromosomes could reflect the insertion pattern rather than the effect of natural selection.</p>", "<p>Another model proposed to explain the TE dynamics is the selection against deleterious arrangements produced by ectopic recombination between TEs. In <italic>D. subobscura </italic>accurate measures of recombination rate are not available and it is not possible to calculate a correlation between TE copies and recombination rates. This species has a rich inversion polymorphism in all chromosomes and recombination is reduced in heterokaryotypes. Under this model we expect accumulation of TEs in inverted segments, and in inversion break points or near them. In some cases arrangements include overlapping inverted fragments, often reaching frequencies higher than the standard arrangements, but in other cases, of low frequency arrangements, TE copy number is too low to allow statistical tests. Also recombination between non-overlapping inversions or inversion complexes may also be prevented [##REF##9652229##77##].</p>", "<p>We looked for accumulations of <italic>bilbo </italic>and <italic>gypsy </italic>in breakpoints of inversions but only one high insertion frequency <italic>bilbo </italic>site, 67A, coincides with an inversion breakpoint (E_1+2+9+12). In another case the 89C high frequency site of <italic>bilbo </italic>is located near the inversion O₈and shows a significant correlation with O₃₊₄₊₈arrangement. This is in concordance with several unsuccessful attempts to localize <italic>in situ </italic>hybridization middle repeated sequences in <italic>D. subobscura </italic>inversions breakpoints [##REF##2612293##61##,##REF##7705632##78##]. These data notwithstanding, we cannot discard that other elements may be responsible of chromosomal inversion induction as reported in other Drosophila species [##REF##10411506##37##,##UREF##14##38##].</p>" ]

[ "<title>Conclusion</title>", "<p>We conclude that the differential distribution of <italic>bilbo </italic>and <italic>gypsy </italic>between original and colonizing <italic>D. subobscura </italic>populations, is mainly due to a founder effect occurred during the colonization process of this species. We have shown that both founder effect and inversion polymorphism contribute notably to an excess of positive correlations between site pairs. Moreover the two transposable elements show a different pattern of distribution in populations that might be due to their differences in transposition and copy number regulatory mechanisms. This paper is also an attempt to emphasize the importance of population structure and history to explain the TE chromosomal distribution. We highlight the fact that comparisons in TE copy number between X and autosomes have to be interpreted cautiously. Sometimes TEs mobilizations can mask the effect of selection on TE distribution.</p>" ]

[ "<title>Background</title>", "<p>Transposable elements (TEs) constitute a substantial amount of all eukaryotic genomes. They induce an important proportion of deleterious mutations by insertion into genes or gene regulatory regions. However, their mutational capabilities are not always adverse but can contribute to the genetic diversity and evolution of organisms. Knowledge of their distribution and activity in the genomes of populations under different environmental and demographic regimes, is important to understand their role in species evolution. In this work we study the chromosomal distribution of two TEs, <italic>gypsy </italic>and <italic>bilbo</italic>, in original and colonizing populations of <italic>Drosophila subobscura </italic>to reveal the putative effect of colonization on their insertion profile.</p>", "<title>Results</title>", "<p>Chromosomal frequency distribution of two TEs in one original and three colonizing populations of <italic>D. subobscura</italic>, is different. Whereas the original population shows a low insertion frequency in most TE sites, colonizing populations have a mixture of high (frequency ≥ 10%) and low insertion sites for both TEs. Most highly occupied sites are coincident among colonizing populations and some of them are correlated to chromosomal arrangements. Comparisons of TE copy number between the X chromosome and autosomes show that <italic>gypsy </italic>occupancy seems to be controlled by negative selection, but <italic>bilbo </italic>one does not.</p>", "<title>Conclusion</title>", "<p>These results are in accordance that TEs in <italic>Drosophila subobscura </italic>colonizing populations are submitted to a founder effect followed by genetic drift as a consequence of colonization. This would explain the high insertion frequencies of <italic>bilbo </italic>and <italic>gypsy </italic>in coincident sites of colonizing populations. High occupancy sites would represent insertion events prior to colonization. Sites of low frequency would be insertions that occurred after colonization and/or copies from the original population whose frequency is decreasing in colonizing populations. This work is a pioneer attempt to explain the chromosomal distribution of TEs in a colonizing species with high inversion polymorphism to reveal the putative effect of arrangements in TE insertion profiles. In general no associations between arrangements and TE have been found, except in a few cases where the association is very strong. Alternatively, founder drift effects, seem to play a leading role in TE genome distribution in colonizing populations.</p>" ]

[ "<title>Authors' contributions</title>", "<p>MPGG participated in the design, the chromosomal slides, some statistical analyses and the writing of the manuscript. BECS collected the Bordils population, performed most of the technical work, the reading of slides and some statistical analyses. JB collected Davis and Bellingham populations, supervised all arrangement readings and performed the data set analyses. LS collected the Bordils population, contributed to the design and thoroughly revised the manuscript AF participated in the design, directed the project, coordinated the data analyses, contributed to the writing of the manuscript and collected the Maipú and Bordils populations. All authors read and approved the final manuscript</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>This work was funded by projects BOS2003-05904-C02-01 and CGL2006-13423-C02-01/02 from the Ministerio de Educación y Ciencia, Spain, and project 2005SGR 00995 from Generalitat de Catalunya, Spain to the Grup de Biología Evolutiva (Principal Investigator: AF); and a doctoral fellowship from UAB to BECS. We acknowledge technical help by Montse Peiró and field assistance by Dr. E. Hasson, Dr. P. Fernández-Iriarte, Dr. F. García-Franco and D. Vela.</p>" ]

[ "<fig id=\"F1\" position=\"float\"><label>Figure 1</label><caption><p><bold>Distribution of bilbo and gypsy in chromosomes O and U, respectively, from colonizing (DA: Davis, BE: Bellingham, MA: Maipú) and original populations (BO: Bordils) of D. subobscura</bold>. Number of haploid genomes analyzed are given in parenthesis.</p></caption></fig>", "<fig id=\"F2\" position=\"float\"><label>Figure 2</label><caption><p><bold>Observed and expected frequency distributions of correlation coefficients between all pairs of sites in natural populations: A) </bold><italic>bilbo </italic>in chromosome E from Bordils and O from Maipú. <bold>B)</bold><italic>gypsy </italic>in chromosome E from Davis and Bellingham.</p></caption></fig>" ]

[ "<table-wrap id=\"T1\" position=\"float\"><label>Table 1</label><caption><p>Occupancy profiles of euchromatic sites in original and colonizing populations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">TE</th><th align=\"center\">Populations</th><th align=\"center\" colspan=\"18\">Occupancy profiles</th></tr></thead><tbody><tr><td/><td/><td/><td align=\"center\"><bold>1</bold></td><td align=\"center\"><bold>2</bold></td><td align=\"center\"><bold>3</bold></td><td align=\"center\"><bold>4</bold></td><td align=\"center\"><bold>5</bold></td><td align=\"center\"><bold>6</bold></td><td align=\"center\"><bold>7</bold></td><td align=\"center\"><bold>8</bold></td><td align=\"center\"><bold>9</bold></td><td align=\"center\"><bold>10</bold></td><td align=\"center\"><bold>11</bold></td><td align=\"center\"><bold>12</bold></td><td align=\"center\"><bold>13</bold></td><td align=\"center\"><bold>14</bold></td><td align=\"center\"><bold>15</bold></td><td align=\"center\"><bold>16</bold></td><td align=\"center\"><bold>17–51</bold></td></tr><tr><td colspan=\"20\"><hr/></td></tr><tr><td align=\"left\"><bold>bilbo</bold></td><td align=\"center\"><bold>Colonizing</bold></td><td align=\"left\">DA</td><td align=\"center\">7</td><td align=\"center\">6</td><td align=\"center\">9</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">7</td><td align=\"center\">0</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">5</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">7</td></tr><tr><td/><td/><td align=\"left\">BE</td><td align=\"center\">3</td><td align=\"center\">5</td><td align=\"center\">3</td><td align=\"center\">2</td><td align=\"center\">4</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">10</td></tr><tr><td/><td/><td align=\"left\">MA</td><td align=\"center\">8</td><td align=\"center\">8</td><td align=\"center\">4</td><td align=\"center\">7</td><td align=\"center\">4</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">5</td><td align=\"center\">2</td><td align=\"center\">3</td><td align=\"center\">2</td><td align=\"center\">3</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">12</td></tr><tr><td/><td align=\"center\"><bold>Original</bold></td><td align=\"left\">BO</td><td align=\"center\">32</td><td align=\"center\">19</td><td align=\"center\">21</td><td align=\"center\">11</td><td align=\"center\">6</td><td align=\"center\">2</td><td align=\"center\">5</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">3</td><td align=\"center\">1</td><td align=\"center\">1</td></tr><tr><td colspan=\"20\"><hr/></td></tr><tr><td align=\"left\"><bold>gypsy</bold></td><td align=\"center\"><bold>Colonizing</bold></td><td align=\"left\">DA</td><td align=\"center\">8</td><td align=\"center\">4</td><td align=\"center\">4</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">0</td><td/><td/></tr><tr><td/><td/><td align=\"left\">BE</td><td align=\"center\">11</td><td align=\"center\">5</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td><td/><td/></tr><tr><td/><td/><td align=\"left\">MA</td><td align=\"center\">9</td><td align=\"center\">10</td><td align=\"center\">6</td><td align=\"center\">3</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td/><td/></tr><tr><td/><td align=\"center\"><bold>Original</bold></td><td align=\"left\">BO</td><td align=\"center\">10</td><td align=\"center\">12</td><td align=\"center\">5</td><td align=\"center\">2</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">0</td><td/><td/></tr></tbody></table></table-wrap>", "<table-wrap id=\"T2\" position=\"float\"><label>Table 2</label><caption><p>Tests of the Poisson distribution of <italic>bilbo </italic>and <italic>gypsy </italic>per chromosome and haploid genome.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th/><th align=\"center\" colspan=\"10\">Populations</th></tr><tr><th/><th/><th colspan=\"10\"><hr/></th></tr><tr><th/><th/><th align=\"center\" colspan=\"5\">DA (76)</th><th align=\"center\" colspan=\"5\">BE (88)</th></tr><tr><th/><th/><th colspan=\"10\"><hr/></th></tr><tr><th align=\"left\">TE</th><th align=\"center\">Ch.</th><th align=\"left\">m</th><th align=\"center\">V_n</th><th align=\"center\">DC</th><th align=\"center\"><bold>χ</bold>²</th><th align=\"center\">df</th><th align=\"left\">m</th><th align=\"center\">V_n</th><th align=\"center\">DC</th><th align=\"left\"><bold>χ</bold>²</th><th align=\"left\">df</th></tr></thead><tbody><tr><td/><td align=\"center\"><bold>A</bold></td><td align=\"left\">0.84</td><td align=\"center\">0.72</td><td align=\"center\">0.86</td><td align=\"center\">0.61</td><td align=\"center\">2</td><td align=\"left\">1.07</td><td align=\"center\">0.77</td><td align=\"center\">0.73</td><td align=\"left\">2.68</td><td align=\"left\">2</td></tr><tr><td/><td align=\"center\"><bold>J</bold></td><td align=\"left\">0.55</td><td align=\"center\">0.49</td><td align=\"center\">0.89</td><td align=\"center\">0.11</td><td align=\"center\">1</td><td align=\"left\">0.76</td><td align=\"center\">0.67</td><td align=\"center\">0.88</td><td align=\"left\">1.61</td><td align=\"left\">2</td></tr><tr><td/><td align=\"center\"><bold>U</bold></td><td align=\"left\">1.01</td><td align=\"center\">0.87</td><td align=\"center\">0.86</td><td align=\"center\">5.74</td><td align=\"center\">3</td><td align=\"left\">1.11</td><td align=\"center\">1.00</td><td align=\"center\">0.90</td><td align=\"left\">1.46</td><td align=\"left\">3</td></tr><tr><td/><td align=\"center\"><bold>E</bold></td><td align=\"left\">1.38</td><td align=\"center\">1.73</td><td align=\"center\">1.25</td><td align=\"center\">4.70</td><td align=\"center\">4</td><td align=\"left\">0.82</td><td align=\"center\">0.84</td><td align=\"center\">1.03</td><td align=\"left\">0.69</td><td align=\"left\">3</td></tr><tr><td/><td align=\"center\"><bold>O</bold></td><td align=\"left\">1.71</td><td align=\"center\">1.67</td><td align=\"center\">0.98</td><td align=\"center\">3.47</td><td align=\"center\">5</td><td align=\"left\">2.58</td><td align=\"center\">1.80</td><td align=\"center\">0.70</td><td align=\"left\">7.06</td><td align=\"left\">4</td></tr><tr><td align=\"left\"><bold>bilbo</bold></td><td align=\"center\"><bold>HG</bold></td><td align=\"left\">5.50</td><td align=\"center\">9.40</td><td align=\"center\">1.71**</td><td align=\"center\">32.56**</td><td align=\"center\">11</td><td align=\"left\">6.34</td><td align=\"center\">7.79</td><td align=\"center\">1.23</td><td align=\"left\">18.61</td><td align=\"left\">11</td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td/><td align=\"center\" colspan=\"5\"><bold>MA (81)</bold></td><td align=\"center\" colspan=\"5\"><bold>BO (81)</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td/><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"center\"><bold>χ</bold>²</td><td align=\"center\"><bold>df</bold></td><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"left\"><bold>χ</bold>²</td><td align=\"left\"><bold>df</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>A</bold></td><td align=\"left\">1.75</td><td align=\"center\">1.69</td><td align=\"center\">0.96</td><td align=\"center\">1.54</td><td align=\"center\">5</td><td align=\"left\">1.06</td><td align=\"center\">0.71</td><td align=\"center\">0.67</td><td align=\"left\">8.11</td><td align=\"left\">2</td></tr><tr><td/><td align=\"center\"><bold>J</bold></td><td align=\"left\">0.91</td><td align=\"center\">0.93</td><td align=\"center\">1.02</td><td align=\"center\">0.25</td><td align=\"center\">3</td><td align=\"left\">0.75</td><td align=\"center\">0.81</td><td align=\"center\">1.08</td><td align=\"left\">13.65*</td><td align=\"left\">4</td></tr><tr><td/><td align=\"center\"><bold>U</bold></td><td align=\"left\">1.54</td><td align=\"center\">1.28</td><td align=\"center\">0.83</td><td align=\"center\">4.15</td><td align=\"center\">4</td><td align=\"left\">0.84</td><td align=\"center\">0.69</td><td align=\"center\">0.82</td><td align=\"left\">1.14</td><td align=\"left\">2</td></tr><tr><td/><td align=\"center\"><bold>E</bold></td><td align=\"left\">1.80</td><td align=\"center\">1.66</td><td align=\"center\">0.92</td><td align=\"center\">1.70</td><td align=\"center\">4</td><td align=\"left\">1.09</td><td align=\"center\">1.70</td><td align=\"center\">1.57**</td><td align=\"left\">29.79**</td><td align=\"left\">5</td></tr><tr><td/><td align=\"center\"><bold>O</bold></td><td align=\"left\">1.79</td><td align=\"center\">1.99</td><td align=\"center\">1.11</td><td align=\"center\">6.53</td><td align=\"center\">5</td><td align=\"left\">0.96</td><td align=\"center\">1.28</td><td align=\"center\">1.34</td><td align=\"left\">9.58</td><td align=\"left\">3</td></tr><tr><td/><td align=\"center\"><bold>HG</bold></td><td align=\"left\">7.80</td><td align=\"center\">19.51</td><td align=\"center\">2.50**</td><td align=\"center\">254.34**</td><td align=\"center\">18</td><td align=\"left\">4.70</td><td align=\"center\">5.76</td><td align=\"center\">1.22</td><td align=\"left\">11.88</td><td align=\"left\">10</td></tr><tr><td colspan=\"12\"><hr/></td></tr><tr><td/><td/><td align=\"center\" colspan=\"5\"><bold>DA (70)</bold></td><td align=\"center\" colspan=\"5\"><bold>BE (84)</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td/><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"center\"><bold>χ</bold>²</td><td align=\"center\"><bold>df</bold></td><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"left\"><bold>χ</bold>²</td><td align=\"left\"><bold>df</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>A</bold></td><td align=\"left\">0</td><td align=\"center\">0</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"left\">0.02</td><td align=\"center\">0.02</td><td align=\"center\">1.00</td><td align=\"left\">-</td><td align=\"left\">-</td></tr><tr><td/><td align=\"center\"><bold>J</bold></td><td align=\"left\">0</td><td align=\"center\">0</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"left\">0.02</td><td align=\"center\">0.02</td><td align=\"center\">1.00</td><td align=\"left\">-</td><td align=\"left\">-</td></tr><tr><td/><td align=\"center\"><bold>U</bold></td><td align=\"left\">0.98</td><td align=\"center\">1.26</td><td align=\"center\">1.28</td><td align=\"center\">5.53</td><td align=\"center\">3</td><td align=\"left\">0.43</td><td align=\"center\">0.49</td><td align=\"center\">1.14</td><td align=\"left\">1.76</td><td align=\"left\">3</td></tr><tr><td/><td align=\"center\"><bold>E</bold></td><td align=\"left\">0.58</td><td align=\"center\">0.97</td><td align=\"center\">1.66**</td><td align=\"center\">44.10**</td><td align=\"center\">4</td><td align=\"left\">0.33</td><td align=\"center\">0.56</td><td align=\"center\">1.69**</td><td align=\"left\">38.10</td><td align=\"left\">3</td></tr><tr><td/><td align=\"center\"><bold>O</bold></td><td align=\"left\">0.04</td><td align=\"center\">0.04</td><td align=\"center\">0.97</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"left\">0.09</td><td align=\"center\">0.11</td><td align=\"center\">1.17</td><td align=\"left\">1.38</td><td align=\"left\">1</td></tr><tr><td align=\"left\"><bold>gypsy</bold></td><td align=\"center\"><bold>HG</bold></td><td align=\"left\">1.61</td><td align=\"center\">2.44</td><td align=\"center\">1.51*</td><td align=\"center\">14.89</td><td align=\"center\">5</td><td align=\"left\">0.90</td><td align=\"center\">1.60</td><td align=\"center\">1.77**</td><td align=\"left\">33.18**</td><td align=\"left\">4</td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td/><td align=\"center\" colspan=\"5\"><bold>MA (80)</bold></td><td align=\"center\" colspan=\"5\"><bold>BO (80)</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td/><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"center\"><bold>χ</bold>²</td><td align=\"center\"><bold>df</bold></td><td align=\"left\"><bold>m</bold></td><td align=\"center\"><bold>V_n</bold></td><td align=\"center\"><bold>DC</bold></td><td align=\"left\"><bold>χ</bold>²</td><td align=\"left\"><bold>df</bold></td></tr><tr><td/><td/><td colspan=\"10\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>A</bold></td><td align=\"left\">0.12</td><td align=\"center\">0.16</td><td align=\"center\">1.29</td><td align=\"center\">4.46</td><td align=\"center\">1</td><td align=\"left\">0.02</td><td align=\"center\">0.02</td><td align=\"center\">1.00</td><td align=\"left\">-</td><td align=\"left\">-</td></tr><tr><td/><td align=\"center\"><bold>J</bold></td><td align=\"left\">0.14</td><td align=\"center\">0.12</td><td align=\"center\">0.87</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"left\">0.10</td><td align=\"center\">0.12</td><td align=\"center\">1.16</td><td align=\"left\">1.26</td><td align=\"left\">1</td></tr><tr><td/><td align=\"center\"><bold>U</bold></td><td align=\"left\">0.42</td><td align=\"center\">0.27</td><td align=\"center\">0.64</td><td align=\"center\">8.49*</td><td align=\"center\">1</td><td align=\"left\">0.11</td><td align=\"center\">0.10</td><td align=\"center\">0.90</td><td align=\"left\">-</td><td align=\"left\">-</td></tr><tr><td/><td align=\"center\"><bold>E</bold></td><td align=\"left\">0.39</td><td align=\"center\">0.32</td><td align=\"center\">0.82</td><td align=\"center\">1.43</td><td align=\"center\">1</td><td align=\"left\">0.30</td><td align=\"center\">0.34</td><td align=\"center\">1.13</td><td align=\"left\">2.27</td><td align=\"left\">1</td></tr><tr><td/><td align=\"center\"><bold>O</bold></td><td align=\"left\">0.27</td><td align=\"center\">0.28</td><td align=\"center\">1.01</td><td align=\"center\">0.12</td><td align=\"center\">1</td><td align=\"left\">0.24</td><td align=\"center\">0.23</td><td align=\"center\">0.99</td><td align=\"left\">0.00</td><td align=\"left\">1</td></tr><tr><td/><td align=\"center\"><bold>HG</bold></td><td align=\"left\">1.35</td><td align=\"center\">1.27</td><td align=\"center\">0.94</td><td align=\"center\">11.48</td><td align=\"center\">4</td><td align=\"left\">0.77</td><td align=\"center\">0.88</td><td align=\"center\">1.14</td><td align=\"left\">3.44</td><td align=\"left\">2</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"T3\" position=\"float\"><label>Table 3</label><caption><p>Comparison of the proportion of <italic>gypsy </italic>and <italic>bilbo </italic>sites among chromosomes, autosomes and between chromosome A and autosomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"center\">TE</th><th/><th align=\"center\" colspan=\"4\">gypsy</th><th align=\"center\" colspan=\"4\">bilbo</th></tr><tr><th colspan=\"6\"><hr/></th><th colspan=\"4\"><hr/></th></tr><tr><th align=\"center\">Ch.</th><th align=\"center\">P. chromat</th><th align=\"left\">DA</th><th align=\"left\">BE</th><th align=\"left\">MA</th><th align=\"left\">BO</th><th align=\"left\">DA</th><th align=\"left\">BE</th><th align=\"left\">MA</th><th align=\"left\">BO</th></tr></thead><tbody><tr><td align=\"center\"><bold>A(X)</bold></td><td align=\"center\">0.16</td><td align=\"left\">0.00</td><td align=\"left\">0.03</td><td align=\"left\">0.09</td><td align=\"left\">0.03</td><td align=\"left\">0.15</td><td align=\"left\">0.17</td><td align=\"left\">0.22</td><td align=\"left\">0.23</td></tr><tr><td align=\"center\"><bold>J</bold></td><td align=\"center\">0.20</td><td align=\"left\">0.01</td><td align=\"left\">0.03</td><td align=\"left\">0.10</td><td align=\"left\">0.13</td><td align=\"left\">0.10</td><td align=\"left\">0.12</td><td align=\"left\">0.12</td><td align=\"left\">0.16</td></tr><tr><td align=\"center\"><bold>U</bold></td><td align=\"center\">0.19</td><td align=\"left\">0.61</td><td align=\"left\">0.48</td><td align=\"left\">0.31</td><td align=\"left\">0.14</td><td align=\"left\">0.18</td><td align=\"left\">0.17</td><td align=\"left\">0.20</td><td align=\"left\">0.18</td></tr><tr><td align=\"center\"><bold>E</bold></td><td align=\"center\">0.20</td><td align=\"left\">0.36</td><td align=\"left\">0.37</td><td align=\"left\">0.29</td><td align=\"left\">0.39</td><td align=\"left\">0.25</td><td align=\"left\">0.13</td><td align=\"left\">0.23</td><td align=\"left\">0.23</td></tr><tr><td align=\"center\"><bold>O</bold></td><td align=\"center\">0.25</td><td align=\"left\">0.03</td><td align=\"left\">0.10</td><td align=\"left\">0.20</td><td align=\"left\">0.31</td><td align=\"left\">0.31</td><td align=\"left\">0.40</td><td align=\"left\">0.23</td><td align=\"left\">0.20</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>Df</bold></td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\"><bold>Ga</bold></td><td align=\"center\">4</td><td align=\"left\">197.23** (115.82**)</td><td align=\"left\">71.18** (61.31**)</td><td align=\"left\">22.26** (5.08)</td><td align=\"left\">21.40** (21.40**)</td><td align=\"left\">36.98** (0.08)</td><td align=\"left\">87.16** (16.98**)</td><td align=\"left\">41.82** (4.80)</td><td align=\"left\">15.67 (8.66)</td></tr><tr><td align=\"center\"><bold>Gb</bold></td><td align=\"center\">1</td><td align=\"left\">40.48** (26.15**)</td><td align=\"left\">15.24** (17.20**)</td><td align=\"left\">4.63* (1.14)</td><td align=\"left\">11.06**</td><td align=\"left\">0.36 (4.8)</td><td align=\"left\">0.08 (3.47)</td><td align=\"left\">15.56** (2.9)</td><td align=\"left\">9.69** (0.52)</td></tr><tr><td align=\"center\"><bold>Gc</bold></td><td align=\"center\">3</td><td align=\"left\">156.75** (89.66**)</td><td align=\"left\">55.93** (44.11**)</td><td align=\"left\">17.63** 3.94</td><td align=\"left\">10.34*</td><td align=\"left\">36.61** (3.47)</td><td align=\"left\">87.08** (13.50*)</td><td align=\"left\">26.26** (1.87)</td><td align=\"left\">5.97 (8.10*)</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\"><bold>Ga</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">Total</td><td align=\"center\">12</td><td align=\"center\" colspan=\"4\">290.67**(182.21**)</td><td align=\"center\" colspan=\"4\">165.96**(30.06**)</td></tr><tr><td align=\"center\">Pooled</td><td align=\"center\">4</td><td align=\"center\" colspan=\"4\">230.15*(110.30**)</td><td align=\"center\" colspan=\"4\">102.01**(1.8)</td></tr><tr><td align=\"center\">H</td><td align=\"center\">8</td><td align=\"center\" colspan=\"4\">60.52**(71.90**)</td><td align=\"center\" colspan=\"4\">63.95**(28.23**)</td></tr><tr><td align=\"center\"><bold>Gb</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">Total</td><td align=\"center\">3</td><td align=\"center\" colspan=\"4\">60.36**(44.50**)</td><td align=\"center\" colspan=\"4\">16.00**(11.20**)</td></tr><tr><td align=\"center\">Pooled</td><td align=\"center\">1</td><td align=\"center\" colspan=\"4\">44.97**(23.78**)</td><td align=\"center\" colspan=\"4\">5.77*(1.09)</td></tr><tr><td align=\"center\">H</td><td align=\"center\">2</td><td align=\"center\" colspan=\"4\">15.38**(20.71**)</td><td align=\"center\" colspan=\"4\">10.24*(10.10*)</td></tr><tr><td align=\"center\"><bold>Gc</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">Total</td><td align=\"center\">9</td><td align=\"center\" colspan=\"4\">230.32**(137.71**)</td><td align=\"center\" colspan=\"4\">149.95**(18.85)</td></tr><tr><td align=\"center\">Pooled</td><td align=\"center\">3</td><td align=\"center\" colspan=\"4\">185.18**(86.52**)</td><td align=\"center\" colspan=\"4\">96.25**(0.72)</td></tr><tr><td align=\"center\">H</td><td align=\"center\">6</td><td align=\"center\" colspan=\"4\">45.13**(51.19**)</td><td align=\"center\" colspan=\"4\">53.71**(18.12*)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"T4\" position=\"float\"><label>Table 4</label><caption><p>Frequencies of chromosomal arrangements in natural populations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Arrangements</th><th align=\"center\" colspan=\"4\">Populations</th></tr><tr><th colspan=\"1\"><hr/></th><th colspan=\"4\"><hr/></th></tr><tr><th/><th align=\"center\">DA</th><th align=\"center\">BE</th><th align=\"center\">MA</th><th align=\"center\">BO</th></tr></thead><tbody><tr><td align=\"left\"><bold>Ast</bold></td><td align=\"center\">0.57</td><td align=\"center\">0.67</td><td align=\"center\">0.55</td><td align=\"center\">0.53</td></tr><tr><td align=\"left\"><bold>A1</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.17</td></tr><tr><td align=\"left\"><bold>A2</bold></td><td align=\"center\">0.43</td><td align=\"center\">0.33</td><td align=\"center\">0.45</td><td align=\"center\">0.30</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Jst</bold></td><td align=\"center\">0.41</td><td align=\"center\">0.45</td><td align=\"center\">0.26</td><td align=\"center\">0.40</td></tr><tr><td align=\"left\"><bold>J1</bold></td><td align=\"center\">0.59</td><td align=\"center\">0.55</td><td align=\"center\">0.74</td><td align=\"center\">0.60</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Ust</bold></td><td align=\"center\">0.32</td><td align=\"center\">0.42</td><td align=\"center\">0.50</td><td align=\"center\">0.17</td></tr><tr><td align=\"left\"><bold>U1</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.03</td></tr><tr><td align=\"left\"><bold>U1+2</bold></td><td align=\"center\">0.39</td><td align=\"center\">0.40</td><td align=\"center\">0.20</td><td align=\"center\">0.72</td></tr><tr><td align=\"left\"><bold>U1+2+8</bold></td><td align=\"center\">0.29</td><td align=\"center\">0.18</td><td align=\"center\">0.30</td><td align=\"center\">0.07</td></tr><tr><td align=\"left\"><bold>U1+2+3</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.01</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Est</bold></td><td align=\"center\">0.54</td><td align=\"center\">0.74</td><td align=\"center\">0.59</td><td align=\"center\">0.53</td></tr><tr><td align=\"left\"><bold>E8</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.01</td></tr><tr><td align=\"left\"><bold>E1+2</bold></td><td align=\"center\">0.07</td><td align=\"center\">0.05</td><td align=\"center\">-</td><td align=\"center\">0.30</td></tr><tr><td align=\"left\"><bold>E1+2+9</bold></td><td align=\"center\">0.12</td><td align=\"center\">0.01</td><td align=\"center\">0.08</td><td align=\"center\">0.03</td></tr><tr><td align=\"left\"><bold>E1+2+9+12</bold></td><td align=\"center\">0.05</td><td align=\"center\">0.15</td><td align=\"center\">0.23</td><td align=\"center\">0.12</td></tr><tr><td align=\"left\"><bold>E1+2+9+3</bold></td><td align=\"center\">0.22</td><td align=\"center\">0.05</td><td align=\"center\">0.10</td><td align=\"center\">0.01</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Ost</bold></td><td align=\"center\">0.08</td><td align=\"center\">0.23</td><td align=\"center\">0.22</td><td align=\"center\">0.22</td></tr><tr><td align=\"left\"><bold>O2</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.01</td></tr><tr><td align=\"left\"><bold>O5</bold></td><td align=\"center\">0.01</td><td align=\"center\">0.14</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"left\"><bold>O7</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.01</td><td align=\"center\">0.04</td></tr><tr><td align=\"left\"><bold>O3+4</bold></td><td align=\"center\">0.20</td><td align=\"center\">0.11</td><td align=\"center\">0.30</td><td align=\"center\">0.32</td></tr><tr><td align=\"left\"><bold>O3+4+7</bold></td><td align=\"center\">0.17</td><td align=\"center\">0.01</td><td align=\"center\">0.21</td><td align=\"center\">0.04</td></tr><tr><td align=\"left\"><bold>O3+4+2</bold></td><td align=\"center\">0.34</td><td align=\"center\">0.19</td><td align=\"center\">0.22</td><td align=\"center\">0.06</td></tr><tr><td align=\"left\"><bold>O3+4+8</bold></td><td align=\"center\">0.20</td><td align=\"center\">0.32</td><td align=\"center\">0.04</td><td align=\"center\">0.30</td></tr><tr><td align=\"left\"><bold>O3+4+23+2</bold></td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.01</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"T5\" position=\"float\"><label>Table 5</label><caption><p>Correlation coefficients between chromosomal arrangements and high insertion frequency (HF) sites</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th/><th align=\"center\" colspan=\"8\">Populations</th></tr><tr><th/><th/><th colspan=\"8\"><hr/></th></tr><tr><th/><th/><th align=\"center\" colspan=\"2\">DA</th><th align=\"center\" colspan=\"2\">BE</th><th align=\"center\" colspan=\"2\">MA</th><th align=\"center\" colspan=\"2\">BO</th></tr></thead><tbody><tr><td align=\"center\"><bold>HF sites of bilbo</bold></td><td align=\"center\"><bold>Arrang.</bold></td><td align=\"center\"><bold>r</bold></td><td align=\"center\"><bold>q-value</bold></td><td align=\"center\"><bold>r</bold></td><td align=\"left\"><bold>q-value</bold></td><td align=\"center\"><bold>r</bold></td><td align=\"center\"><bold>q-value</bold></td><td align=\"center\"><bold>r</bold></td><td align=\"center\"><bold>q-value</bold></td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">11B</td><td align=\"center\">A2</td><td align=\"center\">-0.13</td><td align=\"center\">(0.42)</td><td align=\"center\">0.35**</td><td align=\"left\">(10^-7)</td><td align=\"center\">0.28*</td><td align=\"center\">0.02</td><td align=\"center\">-0.07</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">20A</td><td align=\"center\">J1</td><td align=\"center\">0.24</td><td align=\"center\">(0.11)</td><td align=\"center\">-</td><td align=\"left\">-</td><td align=\"center\">-0.06</td><td align=\"center\">(0.39)</td><td align=\"center\">-0.04</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">43B</td><td align=\"center\">Ust</td><td align=\"center\">-0.08</td><td align=\"center\">(0.46)</td><td align=\"center\">0.04</td><td align=\"left\">0.44</td><td align=\"center\">0.23*</td><td align=\"center\">(0.04)</td><td align=\"center\">0.24</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">45C</td><td align=\"center\">Ust</td><td align=\"center\">0.11</td><td align=\"center\">(0.56)</td><td align=\"center\">0.20</td><td align=\"left\">(0.08)</td><td align=\"center\">0.40**</td><td align=\"center\">(3.10^-7)</td><td align=\"center\">0.05</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">U1+2</td><td align=\"center\">-0.13</td><td align=\"center\">(0.59)</td><td align=\"center\">0.22*</td><td align=\"left\">(0.04)</td><td align=\"center\">-0.19</td><td align=\"center\">0.08</td><td align=\"center\">0.02</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">45D</td><td align=\"center\">Ust</td><td align=\"center\">0.15</td><td align=\"center\">(0.42)</td><td align=\"center\">0.49**</td><td align=\"left\">(3.10^-7)</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td/><td align=\"center\">U1+2</td><td align=\"center\">-0.02</td><td align=\"center\">(0.86)</td><td align=\"center\">-0.34**</td><td align=\"left\">(2.10^-3)</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"center\">53A</td><td align=\"center\">Ust</td><td align=\"center\">-0.20</td><td align=\"center\">(0.15)</td><td align=\"center\">-0.35**</td><td align=\"left\">(3.10^-7)</td><td align=\"center\">-0.22*</td><td align=\"center\">(0.04)</td><td align=\"center\">-0.05</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">U1+2</td><td align=\"center\">0.26</td><td align=\"center\">(0.11)</td><td align=\"center\">0.05</td><td align=\"left\">0.44</td><td align=\"center\">0.18</td><td align=\"center\">(0.08)</td><td align=\"center\">0.07</td><td align=\"center\">(0.99)</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">57D</td><td align=\"center\">E1+2+9</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">0.25</td><td align=\"left\">(0.12)</td><td align=\"center\">-0.10</td><td align=\"center\">(0.44)</td><td align=\"center\">0.57</td><td align=\"center\">(0.41)</td></tr><tr><td/><td align=\"center\">E1+2+9+3</td><td align=\"center\">-0.06</td><td align=\"center\">(0.72)</td><td align=\"center\">0.17</td><td align=\"left\">(0.15)</td><td align=\"center\">0.28*</td><td align=\"center\">(0.04)</td><td align=\"center\">-0.02</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">59C</td><td align=\"center\">Est</td><td align=\"center\">0.36**</td><td align=\"center\">(5.10^-3)</td><td align=\"center\">-</td><td align=\"left\">-</td><td align=\"center\">-</td><td align=\"center\">-</td><td align=\"center\">-0.02</td><td align=\"center\">(0.80)</td></tr><tr><td align=\"center\">67A</td><td align=\"center\">Est</td><td align=\"center\">-0.15</td><td align=\"center\">(0.42)</td><td align=\"center\">-0.25*</td><td align=\"left\">(0.04)</td><td align=\"center\">-0.69**</td><td align=\"center\">(4.10^-8)</td><td align=\"center\">-0.03</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">E1+2+9+12</td><td align=\"center\">0.64**</td><td align=\"center\">(1.10^-4)</td><td align=\"center\">-</td><td align=\"left\">-</td><td align=\"center\">0.85**</td><td align=\"center\">(4.10^-8)</td><td align=\"center\">0.22</td><td align=\"center\">(0.51)</td></tr><tr><td align=\"center\">74D</td><td align=\"center\">E1+2+9+12</td><td align=\"center\">0.33*</td><td align=\"center\">(0.04)</td><td align=\"center\">-</td><td align=\"left\">-</td><td align=\"center\">0.24*</td><td align=\"center\">(0.04)</td><td align=\"center\">0.13</td><td align=\"center\">(0.99)</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\">82A</td><td align=\"center\">Ost</td><td align=\"center\">0.12</td><td align=\"center\">(0.63)</td><td align=\"center\">-0.10</td><td align=\"left\">(0.28)</td><td align=\"center\">0.29*</td><td align=\"center\">(0.02)</td><td align=\"center\">-0.16</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">83C</td><td align=\"center\">O3+4+7</td><td align=\"center\">0.00</td><td align=\"center\">(0.72)</td><td align=\"center\">0.09</td><td align=\"left\">(0.08)</td><td align=\"center\">-0.14</td><td align=\"center\">(0.17)</td><td align=\"center\">0.56</td><td align=\"center\">(0.11)</td></tr><tr><td align=\"center\">85A</td><td align=\"center\">O3+4</td><td align=\"center\">-0.14</td><td align=\"center\">(0.46)</td><td align=\"center\">0.27*</td><td align=\"left\">(0.02)</td><td align=\"center\">0.10</td><td align=\"center\">(0.17)</td><td align=\"center\">0.03</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">O3+4+7</td><td align=\"center\">-0.17</td><td align=\"center\">(0.41)</td><td align=\"center\">0.08</td><td align=\"left\">0.53</td><td align=\"center\">-0.24*</td><td align=\"center\">(0.04)</td><td align=\"center\">-0.04</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">89C</td><td align=\"center\">O3+4</td><td align=\"center\">-0.16</td><td align=\"center\">0.42</td><td align=\"center\">-0.25*</td><td align=\"left\">(0.03)</td><td align=\"center\">-0.21</td><td align=\"center\">(0.06)</td><td align=\"center\">-0.09</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">O3+4+2</td><td align=\"center\">-0.36**</td><td align=\"center\">(5.10^-3)</td><td align=\"center\">-0.31**</td><td align=\"left\">(7.10^-3)</td><td align=\"center\">0.09</td><td align=\"center\">(0.22)</td><td align=\"center\">0.07</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">O3+4+8</td><td align=\"center\">0.58**</td><td align=\"center\">(1.10^-4)</td><td align=\"center\">0.34**</td><td align=\"left\">(4.10^-3)</td><td align=\"center\">0.26</td><td align=\"center\">(0.05)</td><td align=\"center\">0.02</td><td align=\"center\">(0.99)</td></tr><tr><td align=\"center\">91B</td><td align=\"center\">Ost</td><td align=\"center\">0.28</td><td align=\"center\">(0.16)</td><td align=\"center\">0.02</td><td align=\"left\">(0.12)</td><td align=\"center\">0.32*</td><td align=\"center\">(0.03)</td><td align=\"center\">-0.06</td><td align=\"center\">(0.99)</td></tr><tr><td/><td align=\"center\">O5</td><td align=\"center\">-0.03</td><td align=\"center\">(0.86)</td><td align=\"center\">0.28*</td><td align=\"left\">(0.02)</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td><td align=\"center\">--</td></tr><tr><td align=\"center\">98D</td><td align=\"center\">O3+4+2</td><td align=\"center\">0.05</td><td align=\"center\">(0.72</td><td align=\"center\">0.12</td><td align=\"left\">(0.18)</td><td align=\"center\">0.32*</td><td align=\"center\">(0.03)</td><td align=\"center\">0.29</td><td align=\"center\">(0.66)</td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\"><bold>HF sites of gypsy</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">41C</td><td align=\"center\">U1+2</td><td align=\"center\">0.35*</td><td/><td align=\"center\">0.52**</td><td/><td align=\"center\">0.25*</td><td/><td align=\"center\">--</td><td/></tr><tr><td align=\"center\">52D</td><td align=\"center\">U1+2</td><td align=\"center\">0.32*</td><td/><td align=\"center\">0.28*</td><td/><td align=\"center\">-0.12</td><td/><td align=\"center\">--</td><td/></tr><tr><td align=\"center\">63C</td><td align=\"center\">Est</td><td align=\"center\">--</td><td/><td align=\"center\">--</td><td/><td align=\"center\">-0.46**</td><td/><td align=\"center\">--</td><td/></tr><tr><td/><td align=\"center\">E1+2+9+12</td><td align=\"center\">--</td><td/><td align=\"center\">--</td><td/><td align=\"center\">0.45**</td><td/><td align=\"center\">--</td><td/></tr><tr><td align=\"center\">74D</td><td align=\"center\">E1+2+9+3</td><td align=\"center\">0.31</td><td/><td align=\"center\">-0.09</td><td/><td align=\"center\">0.34</td><td/><td align=\"center\">-0.04</td><td/></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p><bold>Poisson distribution: raw data of bilbo copy number per chromosome and population, P values and chi tests</bold>. A table of detailed tests of Poisson distribution of bilbo per chromosome and haploid genome.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p><bold>Poisson distribution: raw data of gypsy copy number per chromosome and population, P values and chi tests</bold>. A table of detailed tests of Poisson distribution of gypsy per chromosome and haploid genome.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>Population origin: Davis (DA), Bellingham (BE), Maipú (MA), Bordils (BO).</p><p>Occupancy profile: number of times that each site is occupied in populations.</p></table-wrap-foot>", "<table-wrap-foot><p>TE: Transposable elements; Ch: chromosome; HG: haploid genome; m: mean copy number; V_n: variance of copy number; Numbers of haploid genomes are in parenthesis; DC: dispersion coefficient (V_n/m); *P &lt; 0.05; **P &lt; 0.01. Bonferroni's correction was applied. See Table 1 for population origin</p></table-wrap-foot>", "<table-wrap-foot><p>P. chromat: Proportion of chromatin. Ga: Comparison of the proportion of TEs among chromosomes. Gb: Comparison of the proportion of TEs between chromosome A (X) and autosomes. Gc: Comparison of the proportion of TEs among autosomes; H: Heterogeneity test between colonizing populations; Df: Degrees of freedom; Pooled: Only colonizing populations; *P &lt; 0.05; **P &lt; 0.001. Bonferroni's correction was applied. Test values excluding high insertion frequency sites are in parenthesis.</p></table-wrap-foot>", "<table-wrap-foot><p>-: Arrangement absent</p></table-wrap-foot>", "<table-wrap-foot><p>Only high insertion sites showing correlation coefficient values either significant or higher than 0.20 at least in one population, are considered. Arrang: arrangement; r: Correlation coefficient; -: indicates cases where correlations cannot be computed because of low ETs copy number; --: indicates the lack of a site or an inversion in the population). See Table 1 for population origin. *P &lt; 0.05; **P &lt; 0.01. Q-value and Bonferroni corrections were applied to <italic>bilbo </italic>and <italic>gypsy </italic>respectively</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2148-8-234-1\"/>", "<graphic xlink:href=\"1471-2148-8-234-2\"/>" ]

[ "<media xlink:href=\"1471-2148-8-234-S1.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2148-8-234-S2.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Transposable elements (TEs) are mobile repetitive DNA that have been found in virtually all eukaryotic genomes investigated so far [##REF##9582191##1##, ####REF##11731497##2##, ##REF##17984973##3####17984973##3##]. LTR retrotransposons are class I TEs that transpose in a \"copy and paste\" mode via RNA intermediates. Typical structural characters of a LTR retrotransposon include: 1) two highly similar LTR sequences from several hundred to several thousand bp; 2) 4–6 bp target site duplication (TSD) at its 5' and 3' ends; 3) primer binding site (PBS) downstream of 5' LTR and polypurine tract (PPT) upstream of 3' LTR; 4) protein-coding domains of enzymes important to retrotransposition, e.g. Capsid protein (GAG), Aspartic Proteinase (AP), Reverse Transcriptase (RT), Integrase (IN), and RNase H (RH). Sometimes Envelope protein (ENV) may occur as well [##REF##12584121##4##]. In the plant kingdom, LTR elements present a significant fraction of many genomes and even make predominant components of large genomes [##REF##2870519##5##, ####REF##11591643##6##, ##REF##12372141##7####12372141##7##]. The amplification and deletion of these elements is considered to be an important mechanism underlying the remarkable genome size variation in plants [##REF##8864112##8##, ####REF##11439119##9##, ##REF##16954538##10##, ##REF##16963705##11####16963705##11##]. Moreover, LTR retrotransposons affect genome organization, gene regulation [##REF##9929394##12##,##REF##12885961##13##], novel gene origination [##REF##16914031##14##,##REF##16829590##15##] and other genetic functions. In summary, the dynamics of LTR retrotransposons are thought to be an important source of genome evolution.</p>", "<p><italic>Medicago truncatula </italic>is a model plant of the Fabaceae, the third largest angiosperm family. Because of their vital role in agriculture and environment [##REF##12644639##16##,##REF##17003129##17##], legumes have provoked great interests. The identification and study of LTR elements is one of the basic and indispensable step to understand biology and evolution of this family. The sequencing of <italic>Mt </italic>opens an unprecedented opportunity to carry out a thorough study of it at the molecular level. Genomic data so far released have made it possible to explore many important facts of the <italic>Mt </italic>genome, specifically, the characteristics of LTR elements and their interactions with the host organism.</p>", "<p>In comparison with the Gramineae, the knowledge of LTR retrotransposons in the Fabaceae is relatively limited [##REF##16093661##18##,##REF##17996080##19##]. To date, a few <italic>Mt </italic>LTR families, e.g. MEGY and Ogre have been well documented [##REF##14750527##20##, ####REF##15668770##21##, ##REF##17052864##22####17052864##22##] and some families have been deposited in Repbase [##UREF##0##23##] and TIGR Plant Repeat Databases [##UREF##1##24##]. However, little research has been focused on the comprehensive identification and description of LTR retrotransposons based on high-throughput <italic>Mt </italic>genomic sequences.</p>", "<p>Here we report the result of the computer-based analysis of LTR retrotransposons in 233 Mb <italic>Mt </italic>BAC sequences. At least 85 LTR families were found. We analyzed their phylogenetic relationship and structural patterns, with emphasis on several important families. We investigated the amplification-deletion pattern of these LTR elements and found that the removal of LTR elements in <italic>Mt </italic>has been more rapid than in rice, and more than 10 Mb of LTR retrotransposon sequences have been lost. The present work in about 41% of the whole-genome provides the LTR retrotransposon landscape in <italic>Medicago truncatula</italic>.</p>" ]

[ "<title>Methods</title>", "<title>Genomic sequences, LTR element databases and tRNA database</title>", "<p>The <italic>Mt </italic>genomic data were composed of 1826 BACs, about 233 Mb in length. The data were downloaded from <italic>Medicago truncatula </italic>Sequencing Resources website (Version 1.0. Released on July, 2006) [##UREF##3##38##].</p>", "<p>A database of known legume LTR retrotransposons was constructed by extracting legume elements from literatures [##REF##15668770##21##,##REF##15777633##29##, ####REF##18031571##30##, ##REF##17895280##31####17895280##31##], Repbase [##UREF##0##23##] and TIGR Plant Repeat Databases [##UREF##1##24##]. This database was used to discriminate previously reported families from novel ones discovered in this research. A <italic>Mt </italic>tRNA database was also built by scanning the genome with tRNAscan-SE [##REF##9023104##39##]. It was used to detect PBS of LTR elements by LTR_FINDER, our newly developed <italic>ab initio </italic>tool for the prediction of full-length LTR retrotransposons [##REF##17485477##25##].</p>", "<title>Mining LTR retrotransposons in <italic>Medicago truncatula </italic>genome</title>", "<p>We first identified candidates of full-length element with LTR_FINDER, then annotated other copies related to them in the genome by homology search and the elimination of pseudo-copies. At last, only the candidates that had multiple copies were kept as LTR retrotransposons for further analysis.</p>", "<p>The initial LTR_FINDER scan retrieved more than 600 candidates. They were then subjected to the following steps to validate copies.</p>", "<p>1. Selected reliable LTR copies of candidates (Rset). The <italic>Mt </italic>genome was searched against each LTR candidate and all the matches longer than 100 bp were taken as the basic set of copies related to that candidate. This basic set were partitioned into two sets: Part I and Part II. Part I (called Rset) consisted of matches that covered both the LTR region and internal domain to a certain length (Figure ##FIG##3##4##), which, obviously, was a subset of all copies because it excluded severely truncated ones. Part II consisted of other matches. Since this set might contain pseudo-copies generated by unrelated sequences, it is processed by the following two steps to eliminate pseudo-copies.</p>", "<p>2. Detected unrelated sequences derived from other LTR elements and eliminated their pseudo-copies. The internal domain of each candidate was searched against all the candidates to find whether it contained other LTR retrotransposons. The subregions derived from other candidates were recorded as unrelated sequences. Accordingly, the matches generated by such subregions were eliminated from Part II.</p>", "<p>3. Detected unrelated sequences derived from other TEs and eliminated their pseudo-copies. When an unrelated sequence was derived from an abundant TE, it would have many matches in the genome. Therefore, if the subregions of the internal domain had significantly high number of matches, the possibility that they were unrelated sequences was high (Figure ##FIG##3##4##). We used a sliding window to find such subregions:</p>", "<p>(a) A window of size w (say 100 bp) moved from 5' to 3' along the internal domain and stopped at the first position that at least k (say 20) hits were found in it. Here a hit was a member of Part II that covered at least 80% of the window.</p>", "<p>(b) The window extended 1 bp and was checked if it still had k (or more) hits. The extension continued until less than k hits were in the window, then the current window was marked and this completed a search cycle. the next cycle started from the next position to the 3' end of the window. The search continued until the window reached the 3' end of the internal domain.</p>", "<p>(c) All of the marked windows were checked to filter those that obviously overlapped with TE proteins. Subsequently, the remaining windows were connected if the distances between them were less than a threshold (say 10 bp). At last, the regions covered by such windows were taken as unrelated sequences and their corresponding matches were eliminated from Part II (Figure ##FIG##3##4##).</p>", "<p>Although this simple greedy algorithm might fail to deal with a few complicated situations, it identified most of the pseudo-copies efficiently.</p>", "<p>4. Obtained copies of candidates. Rset and the remaining copies in Part II were combined to obtain the copies of the candidates. If one locus in the genome matched several candidates, it was assigned to the best matched one. At last, a full-length candidate was taken as a LTR element if it had several hits covering at least 80% of it. Such hits are called strong hits or strong-hit copies. After the above validation, a total of 526 full-length elements and their 16565 related copies were selected. To be reliable, the above validation excluded the matches that were shorter than 100 bp. This might skip some severely truncated copies and thus brought some underestimation of DNA loss and the contribution of LTR retrotransposons to the genome.</p>", "<p>Subsequently, full-length elements were categorized into families by their sequence similarity [##REF##17984973##3##], and the copies of each family were obtained by combining all the copies of its full-length members. The annotation process identified unrelated TE sequences in elements and discarded pseudo-copies, thus estimated the contribution of LTR elements to the genome more accurately.</p>", "<title>TE domain identification</title>", "<p>LTR_FINDER tried to detect ORFs of RT, IN and RH in the full-length elements by calling PS_SCAN [##REF##17485477##25##,##REF##15130850##40##]. Besides this, we scanned them (e-value: 10^-6) with the hmmsearch program in the HMMER package [##UREF##4##41##] to locate positions of important domains. The profiles were downloaded directly from Pfam (V22.0) [##REF##16381856##42##]. According to the suggestion of [##REF##17407597##26##], TE domains were represented by the following profiles: RT by PF00078, PF07727 and PF05380; IN by PF00665, PF00552 and PF02022; PRO by PF00026 and PF00077; RH by PF00075; GAG by PF03732 and PF00098; and ENV by PF03078. We note that the scan process may skip some domains if they are highly divergent among different retrotransposon families or not built in Pfam profiles.</p>", "<title>Phylogenetic and statistical analysis</title>", "<p>The phylogenetic tree and multiple alignments were constructed by CLUSTALW [##REF##7984417##43##]. The tree was edited with MEGA4 [##REF##17488738##44##]. Statistical analyses were performed by R [##UREF##5##45##]. Following the suggestion of [##REF##17101966##37##], 1.3 × 10^-8/<italic>site</italic>/<italic>yr </italic>was used as the average substitution rate of <italic>Mt </italic>LTR elements to obtain the insertion date of elements.</p>" ]

[ "<title>Results and Discussion</title>", "<title>Estimation of copy-number of LTR elements</title>", "<p>The development of <italic>ab initio </italic>algorithms [##REF##12584121##4##,##REF##17485477##25##,##REF##17407597##26##] has greatly promoted the identification and analysis of LTR elements in large-scale genomic data. With predicted full-length elements at hand, a widely adopted method to find their related copies is to perform homology search against the host genome. However, subregions of full-length elements may be generated through insertion of other TEs, e.g. nested elements are caused by the insertion of LTR elements one into another [##REF##8864112##8##,##REF##11439119##9##]. In this report, we call these subregions unrelated sequences. Based only on the recognition of structural characters, <italic>ab initio </italic>prediction is not capable to provide information on such sequences. If an element contains unrelated sequences derived from highly abundant TEs, taking the direct matches as its copies will greatly overestimate its copy-number and exaggerate its contribution to the host genome. Therefore, we developed an algorithm (see Methods) to discriminate unrelated sequences and discard the matches generated by them (pseudo-copies). Using this method we obtained a more accurate estimation of the number of <italic>Mt </italic>LTR copies.</p>", "<title>Overview of LTR retrotransposons</title>", "<p>This survey identified 526 full-length LTR elements in 232996 Kb <italic>Mt </italic>BAC sequences [see Additional file ##SUPPL##0##1##]. The following validation process detected more than 16000 copies, corresponding to 22470 Kb sequences, about 9.6% of all the sequences scanned. If this value is kept in the unreleased genomic sequences, the percentage of the LTR retrotransposons in <italic>Mt </italic>is lower than that in rice (17%–22%) [##REF##12372141##7##,##REF##15240870##27##], yet still remarkably higher than that in <italic>Arabidopsis thaliana </italic>(1–2%) [##REF##10952195##28##]. The length of the full-length elements is within the ranges of 364 bp to 18.7 Kb and that of the LTRs is 126 bp to 3.5 Kb [see Additional file ##SUPPL##1##2##]. Most of the elements showed canonical TG-CA boxes and 4–6 bp TSDs.</p>", "<p>In this report, We define the LTR family by DNA sequence similarity, following the suggestion of Wicker et al. [##REF##17984973##3##]: two elements belong to the same family if they share 80% (or more) sequence identity in at least 80% of their coding region or internal domain, or within their LTR, or in both. A novel family is discovered when the following standards are met: 1) None of the members in the family belong to the same family with known legume LTR retrotransposons. 2) Besides a full-length member, the family has at least one strong hit (also called strong-hit copies. See Methods).</p>", "<p>The 526 full-length elements and their related copies thus were classified into 85 families, of which 64 were identified for the first time. The information of these families is listed in Table ##TAB##0##1##. LTR families are denoted as MtrXX (XX are digits) and the last two columns of Table ##TAB##0##1## list the number of full-length and strong-hit copies because these two values provide multi-copy supports for a family. The following sections sometimes mention the total copy-number of a family and the length of its sequences. Such values, however, are estimated by all copies of that family, including full-length, strong-hit and other truncated ones.</p>", "<p>Phylogenetic analysis classified 74 families as Copia or Gypsy superfamily (Figure ##FIG##0##1##) and the rest 11, though quite abundant in genome, could not be categorized as either superfamily by their protein-coding domain organization or sequence similarity. We found that half of the 11 families had long ORFs in their internal domain and some ORFs showed a certain degree of homology with known TE proteins. These families were categorized into TRIMs or LARDs group (TRIMs-LARDs) by their length [##REF##17984973##3##].</p>", "<title>Protein domain organization and phylogenetic relationships within LTR families</title>", "<p>We analyzed protein-domain organization of the 85 families (see Methods) and found 9 patterns (Table ##TAB##1##2## and [see Additional file ##SUPPL##2##3##]). HMMER detected the canonical Copia and Gypsy domain structures, i.e. 5'-GAG-IN-RT-3' and 5'-GAG-RT-IN-3', in 35 and 14 families, respectively. Although it failed to detect the GAG proteins in 21 families, they could still be categorized by the order of their RT and IN in the POL. Mtr3, Mtr5 and Mtr62 had RT but not IN, and they were assigned to either superfamilies by sequence similarity of RT domain (The reason of this assignment is explained in next paragraph): Mtr3 and Mtr5 were categorized as Copia superfamily while Mtr62 as Gypsy superfamily. At last, we obtained 56 Copia-like and 18 Gypsy-like families. Using a RT of Bel-Pao element (BEL-1-I_NVp from Repbase) as outgroup, we constructed the NJ phylogenetic tree of the 74 families based on their RT similarity (Figure ##FIG##0##1##). The tree branched into two clades and this split was well supported (bootstrap value: 100%). In the tree, the superfamily label of each external node was given according to the order of domains. It is worth noting that the two clades consist of neither more nor less than members of two superfamilies, respectively. In other words, the categorization of superfamily based on RT similarity concurs with that based on domain organization. This means that RT similarity is enough to categorize LTR elements at the level of superfamily. In Figure ##FIG##0##1##, Mtr3, Mtr5, and Mtr62 are also drawn with others, but the tree topology do not change if they are deleted. These results support their earlier categorization by RT similarity.</p>", "<p>To reveal the phylogenetic relationships within the superfamilies, we collected from literatures RT domains of 158 reference elements representing known Eukaryotic LTR lineages [##REF##15668770##21##,##REF##15777633##29##, ####REF##18031571##30##, ##REF##17895280##31####17895280##31##] and combined these data with our 74 families to construct trees [see Additional file ##SUPPL##3##4##]. We found that the Copia-like families belonged to 10 clades. MTC-1, a new lineage composed of Mtr5, Mtr49 and Mtr55, was recognized with middle support (Bootstrap value: 62%). The Gypsy-like families belonged to 4 well defined lineages (Figure ##FIG##0##1##).</p>", "<title>PBS pattern of LTR elements</title>", "<p>We investigated TSD, PPT and PBS patterns of LTR elements. Although the TSDs and PPTs did not show significant sequence preference, we found clear tRNA usage bias through the PBS strings. The validation of a PBS sequence was to find the string which was located immediately downstream of the 5' LTR and a reverse complement to the 3' ends of a tRNA [##REF##17556529##32##]. By the criterion of matching at least 14 bp, the PBSs were detected in 80 families, including all members in Copia and Gypsy superfamilies and 6 other families. We found that tRNAs corresponding to His, Phe, Tyr, Ser and Cys were never used as primer of reverse transcription and the majority of the rest 15 actually detected tRNA types occurred with low frequency. By contrast, the most-detected 4 types were used by nearly 3/4 families. Moreover, tRNA_{<italic>Met </italic>}occurred in about 60% of the 80 families and was the most frequently used type in both superfamilies and TRIMs-LARDs. tRNA_{<italic>Arg </italic>}was the second important primer in Gypsy superfamily and was only used by this group (Table ##TAB##2##3## and [see Additional file ##SUPPL##2##3##]).</p>", "<title>Copia superfamily</title>", "<p>The present research discovered 64 novel families, including 38 Copia-like, 15 Gypsy-like and 11 other ones. We describe each group in the following three sections, with emphasis on some important families.</p>", "<p>The total copy-number of the 56 Copia-like families reached 4816 and their sequences had a total length of 7164 Kb, about 3% of all genomic sequences investigated. Full-length elements varied in length from 3 to 12.7 Kb, with an average of 5.9 Kb. The longest family Mtr2/COPIA4, which had more than 130 copies, was one of the most abundant Copia-like families. We detected 3 long ORFs in its internal domain. From 5' to 3', the first two ORFs encoded canonical GAG-POL proteins. The third ORF, located less than 1 Kb downstream of the POL region, encoded a protein longer than 790AA. Although the homology search against Uniprot [##UREF##2##33##] did not return significant match to this ORF, it showed quite high conservation among the family members (Figure ##FIG##1##2b##). Moreover, we found that a 258 bp subregion in this ORF matched the putative ENV protein of the <italic>Glycine max </italic>putative endogenous retrovirus SIRE1-8 with low significance (similarity: 22%, e-value: 0.003). These results indicated that this ORF probably encoded a protein related to putative plant ENV.</p>", "<p>Besides Mtr2, there were 6 Copia-like families longer than 10 Kb and all of them had the GAG, IN and RT domains. Mtr1 was the most abundant Copia-like family and the second largest in all the 85 families. It had 69 full-length members, more than 800 copies and its sequences reached more than 2.5 Mb in length, about 36% of the total length of the Copia-like copies. The percentage was 6.6 times as high as that of the second largest Copia-like family Mtr2, whose sequences were 392 Kb in length. The PBS of Mtr1 bounded tRNA_{<italic>Met </italic>}and the length of its full-length members and LTRs were about 12 and 1.3 Kb, respectively. Outside <italic>Mt</italic>, the best match of its RT domain in Uniprot was from <italic>V. vinifera </italic>(Accession: A5BWH6). Similar to Mtr2, a third long ORF was also detected in its internal domain (Figure ##FIG##1##2a##). However, this ORF, matching a putative uncharacterized <italic>Mt </italic>protein (Q2HU06), was less conservative among the family members. The length of the LTRs of Copia-like families fell within the range of 126 bp to 2 Kb, with an average of 506 bp. LTRs could be roughly categorized into 4 zones: 100–500 bp, 600–850 bp, 1.2–1.45 Kb and &gt;1.5 Kb. The number of families in these zones was 39, 8, 6 and 3, respectively [see Additional file ##SUPPL##1##2##]. We found that long elements tended to have long LTRs. In fact, almost all LTRs longer than 1 Kb were from elements longer than 10 Kb. Mtr3 and Mtr18 were exceptions. The length of the LTR of Mtr3 reached 1.28 Kb yet that of the full length was only 6 Kb. As one of the most abundant Copia-like retrotransposon, Mtr3 had 292 Kb sequences in the genome, It was a typical non-autonomous family since no &gt;500 bp ORF could be detected in its internal domain and its RT degenerated to a fragment of 40AA.</p>", "<p>There were 11 Copia-like families whose LTRs and full-length sequences were shorter than 200 bp and 5 Kb, respectively. 6 of them have been deposited in Repbase. Mtr30/MTCOPIA2 and Mtr32/COP3 were quite active in the genome and their copies corresponded to more than 200 and 109 Kb sequences, respectively. Despite short LTRs, we detected 5'-IN-RT-3' domains in all of them and GAG proteins in 7.</p>", "<title>Gypsy superfamily</title>", "<p>The 18 Gypsy-like families corresponded to 11652 Kb sequences and constituted 5% of all genomic data. This group had a full length of 5.1 to 18.7 Kb, with an average of 9.8 Kb. Their LTRs were from 313 to 3.5 Kb in length, with an average of 1.5 Kb. Compared with Copia-like LTR retrotransposons, Gypsy-like elements were longer in general: the great majority of Gypsy-like families had a full length &gt; 6 Kb and LTR &gt;500 bp, while the full length and the LTR of most Copia-like families were &lt; 6 Kb and 500bp, respectively [see Additional file ##SUPPL##1##2##]. The total copy-number in this superfamily was 7434, about 1.5 times more than Copia superfamily (4816). Despite fewer members, Gypsy superfamily contributed more to the <italic>Mt </italic>genome than Copia superfamily because of longer length and more active amplification in the past.</p>", "<p>Mtr57 and Mtr59 were Ogre families [##REF##14750527##20##,##REF##17052864##22##] and Mtr57/Ogre1 was the largest in all the 85 families. Our survey detected its 114 full-length members and more than 1000 copies in total. The length of its sequences reached 4.2 Mb. Mtr70 was closely related to Mtr57 in the phylogenetic tree, and was the second longest in all the families (The longest one is Mtr57/Ogre1). These two families used tRNA_{<italic>Arg </italic>}as primer and their internal domain encoded 5'-GAG-RT-RH-IN-3' proteins. We detected an ORF of 1527 bp located upstream of the GAG and an intron in the POL. Such phylogenetic and structural features well support that Mtr70 is a novel Ogre family. Mtr58 was the second largest family in the Gypsy group and the third largest in all the families. It had more than 600 copies in total and corresponded to 1.4 Mb sequences, about 1/3 of Mtr57/Ogre1. Its full length were about 8.8 Kb and the LTRs were 2.1 Kb in length. Its internal domain encoded 5'-GAG-PRO-RT-RH-IN-3' proteins (Figure ##FIG##1##2f##) and its PBS matched tRNA_{<italic>Met </italic>}well. Phylogenetically, this family belonged to the Tekay clade.</p>", "<p>Mtr67, Mtr60 and Mtr64 were the other 3 families longer than &gt;10 Kb. Similar to Copia superfamily, it was found that, when the full-length of an element was &gt;10 Kb, the LTR was correspondingly &gt;1 Kb. The only exceptional family Mtr67 had a LTR of 720 bp. Besides normal 5'-GAG-RT-RH-IN-3' domains, this family had 5 additional &gt;500 bp ORFs downstream of the POL. They were all located in the complementary chain and had no match in Uniport. However, these ORFs were quite conservative among the family members (Figure ##FIG##1##2g##). We estimated that these ORFs were derived from other sources and later captured by Mtr67. The short LTR reflected short original length of this family. Mtr60 belonged to the Athila clade (Figure ##FIG##0##1##). Its PBS bound tRNA_{<italic>Asp </italic>}and its protein-coding domains organized as 5'-GAG-RT-IN-3'. Downstream of the POL, there were two &gt;500 bp ORFs encoding uncharacterized proteins (best match in Uniprot: A2Q2P5 and A2Q2P6). Mtr64, the sister branch of Mtr60, also had an extra ORF downstream of the POL. Its best match in Uniprot was from <italic>Garden asparagus </italic>(Q2AA44) and it shared weak similarity with the first extra ORF in Mtr60 (Similarity: 24%, e-value: 2e-06). Known elements of the Athila clade were putative plant endogenous retroviruses, thus the possibility that the extra ORFs in Mtr60 and Mtr64 encoded the putative ENVs was strong, although they did not share significant similarity with the putative ENVs of known Athila elements.</p>", "<p>Mtr65 and Mtr74 were from the CRM clade, while Mtr72/GYPSHAN and Mtr73 were from Renia. Families of these two clades were relatively inactive in <italic>Mt</italic>: each had a copy-number &lt;50 and corresponded to &lt;80 Kb sequences. Even so, they all showed multiple domains in their internal domain [see Additional file ##SUPPL##2##3##].</p>", "<title>TRIMs and LARDs</title>", "<p>Because their internal domain lacked strong homology to any known TE proteins, the 11 families were required to have at least 5 strong hits in the genome. The total sequences of them were 3654 Kb in length, about 1.6% of all data. According to the suggestion of [##REF##17984973##3##], the 5 families that had a length less than 4 Kb were classified as TRIMs and the other 6 as LARDs.</p>", "<p>We detected ORFs longer than 700 bp in 4 families: Mtr80 had 2 such ORFs. One shared weak similarity with a GAG protein in rice (Q7XRT, 35%, 4 × 10^-92) and the other with a putative transposon protein in <italic>A. thaliana </italic>(Q9XH30, 27%, 2 × 10^-8). Although HMMER failed to detect (e-value: 10^-6) RT and IN domains in 4 of the 5 full-length members, previous analyses suggested that Mtr80/MEGY belonged to a distinct clade called env-class [##REF##15668770##21##]. Mtr78, Mtr82 and Mtr76 each had only one ORF &gt;700 bp. The best Uniprot match of the ORF in Mtr78 was again Q9XH30 (24%, 2 × 10^-9), while that of the ORF in Mtr82 was an uncharacterized protein from grape (AB5PC1, 46%, 3 × 10^-57). The ORF in Mtr76 was highly similar to that in Mtr82 (80.1%) and a subregion in this ORF was reported as a GAG by HMMER (Figure ##FIG##1##2h##).</p>", "<p>Mtr81 is the longest family in the 11. Although its internal domain was long, most members in this family rarely contained long ORFs. Searching the internal domain against Uniprot with BLASTX retrieved a 438 bp region homologous to some RT proteins and the best well-studied match was from the maize (<italic>Zea mays</italic>) Opie element (Q8H7T1, 60%, 1 × 10^-48). The high similarity with Opie strongly supported that this ORF did encode a RT domain. However, it could not be detected by HMMER and this indicated that this RT might be not built in current RT profiles. Phylogenetic analysis further revealed that it belonged to neither Copia nor Gypsy superfamily but was close to the outgroup [see Additional file ##SUPPL##4##5##]. Further investigation is needed to fully resolve its position.</p>", "<p>The last family that shared homology with known TE proteins was Mtr85. It had a ~321 bp ORF encoding a fragment of RH (A4PUT7, similarity: 91%, e-value: 1 × 10^-49). Each of the other 5 families had more than 10 strong hits and quite large copy-number in the genome. Mtr75 was the shortest family, of which the full-length members and the LTRs were only 364 and 130 bp in length, respectively. Instead of typical 5'-TG-3', 5' ends of its LTRs were 5'-TA-3'. Despite highly degenerated internal domain, this family had 9 full-length members and 74 strong hits. Mtr77, Mtr83 and Mtr84 were LARDs. Similar to Mtr75, Mtr77 was an abundant non-autonomous family with highly degenerated internal domain (about 200 bp).</p>", "<title>Structure of LTR retrotransposons in <italic>Mt</italic></title>", "<p>We studied the structure of the LTR families and Figure ##FIG##1##2## displays the structures of 8 highly abundant ones, five of which have been described above. The structure of Ogre elements is not shown because it has been reported previously [##REF##17052864##22##]. Here we just point out that the LTR regions of most families tend to be less conservative among the family members in comparison with TE proteins, as well as many long ORFs. This result well supports that LTRs are the most rapidly evolving regions in LTR retrotransposons [##REF##17984973##3##,##REF##15003117##34##].</p>", "<title>Insertion-deletion of LTR retrotransposons in <italic>Mt</italic></title>", "<p>Mtr1, Mtr2, Mtr6, Mtr10, Mtr57-59 and Mtr76 each had more than 10 full-length members. The total number of these full-length copies was 296, making up 56.3% of all the full-length elements identified. Their total copies constituted 45.3% of the LTR retrotransposon sequences.</p>", "<p>Paleontology analysis on the 296 elements revealed that they were quite young: all were inserted within the last 2 MY and 90% within 0.4 MY. Compared with others, the active period of Mtr6 (10 full-length copies) and Mtr76 (17 full-length copies) was relatively long [see Additional file ##SUPPL##5##6##]. Recent researches have argued that truncated LTR elements were mainly caused by unequal homologous or illegitimate recombination within genome and the result of recombination was the deletion of genomic sequences [##REF##15240870##27##,##REF##17556529##32##,##REF##12097344##35##,##REF##17617907##36##]. We estimated the deletion of LTR copies in <italic>Mt </italic>genome from two aspects: 1) the deletion of full-length structure and 2) the number of DNA loss. The deletion of a full-length structure means that mutation and recombination remove so many structural characters of a full-length element that it can not be recognized any more. Assuming that repetitive sequences are removed at a constant rate, the survival time of full-length structure obeys an exponential distribution and therefore the half-life is an index to estimate the speed of removal. With this method, [##REF##17556529##32##] estimated that the half-life of the full-length elements in rice was about 0.79 MY.</p>", "<p>We calculated the insertion date of all the 526 full-length elements and found that 90% of them inserted within the last 0.52 MY (Figure ##FIG##2##3a##). Fitting of the distribution to the exponential function obtained <italic>α </italic>= -2.71, which corresponded to a half-life <italic>τ </italic>= 0.26 MY (Figure ##FIG##2##3b##). The bootstrap revealed that the half-life varied between 0.24 to 0.3 MY. To compare the speed of removal in legume and grass, we calculated the half-life for 705 full-length elements in the two sequenced rice genomes (<italic>Oryza sativa indica ssp</italic>. and <italic>japonica ssp</italic>.). Elements in rice and <italic>Mt </italic>were predicted under the same parameters (Hao Wang, unpublished data). As can be seen from Figure ##FIG##2##3c## and ##FIG##2##3d##, our data supported that the half-life of full-length structure in rice was ~0.4 MY, a lesser value than the estimation of [##REF##17556529##32##] but still greater than that in <italic>Mt</italic>. Furthermore, statistical testing revealed that the insertion dates in the two species were from different distributions (Kolmogorov-Smirnov test, P-Value: 3.4 × 10^-14). If the mean substitution rates of LTR elements in <italic>Mt </italic>and grass are approximately the same [##REF##17101966##37##], the above results support that the full-length structures have been deleted more rapid in <italic>Mt </italic>than in rice. If the deletions have been occurred randomly in genome, the results further indicate that the removal of LTR elements in <italic>Mt </italic>has been more rapid than in rice.</p>", "<p>The total number of the strong hits was only 6% of all detected copies, but their size reached 42%. This indicated that LTR elements in <italic>Mt </italic>were highly fragmented and these truncated copies, great in number, might be generated by the removal of genomic DNA. If the truncated LTR copies were real vestiges of paralogous copies of families and if they had similar lengthes to the representative copies at the time of insertion, the difference of the length of truncated and representative copies provided the amount of deleted DNA since their insertion [##REF##17617907##36##]. The estimation of the upper and lower limits of DNA loss could be as follows: we used the copies of Rset (see Methods) to estimate the lower limit. The data revealed that 5.5 Mb sequences have been deleted. Since Rset only consisted of not-so-severely truncated copies, it caused an underestimate of DNA loss. In contrast, we used all the truncated copies to estimate the upper limit and this gave more than 46 Mb of DNA has been removed. Since only 40% of the genome was analyzed here, we estimated that more than 10 Mb of LTR retrotransposon sequences have been deleted from the <italic>Mt </italic>genome.</p>" ]

[ "<title>Results and Discussion</title>", "<title>Estimation of copy-number of LTR elements</title>", "<p>The development of <italic>ab initio </italic>algorithms [##REF##12584121##4##,##REF##17485477##25##,##REF##17407597##26##] has greatly promoted the identification and analysis of LTR elements in large-scale genomic data. With predicted full-length elements at hand, a widely adopted method to find their related copies is to perform homology search against the host genome. However, subregions of full-length elements may be generated through insertion of other TEs, e.g. nested elements are caused by the insertion of LTR elements one into another [##REF##8864112##8##,##REF##11439119##9##]. In this report, we call these subregions unrelated sequences. Based only on the recognition of structural characters, <italic>ab initio </italic>prediction is not capable to provide information on such sequences. If an element contains unrelated sequences derived from highly abundant TEs, taking the direct matches as its copies will greatly overestimate its copy-number and exaggerate its contribution to the host genome. Therefore, we developed an algorithm (see Methods) to discriminate unrelated sequences and discard the matches generated by them (pseudo-copies). Using this method we obtained a more accurate estimation of the number of <italic>Mt </italic>LTR copies.</p>", "<title>Overview of LTR retrotransposons</title>", "<p>This survey identified 526 full-length LTR elements in 232996 Kb <italic>Mt </italic>BAC sequences [see Additional file ##SUPPL##0##1##]. The following validation process detected more than 16000 copies, corresponding to 22470 Kb sequences, about 9.6% of all the sequences scanned. If this value is kept in the unreleased genomic sequences, the percentage of the LTR retrotransposons in <italic>Mt </italic>is lower than that in rice (17%–22%) [##REF##12372141##7##,##REF##15240870##27##], yet still remarkably higher than that in <italic>Arabidopsis thaliana </italic>(1–2%) [##REF##10952195##28##]. The length of the full-length elements is within the ranges of 364 bp to 18.7 Kb and that of the LTRs is 126 bp to 3.5 Kb [see Additional file ##SUPPL##1##2##]. Most of the elements showed canonical TG-CA boxes and 4–6 bp TSDs.</p>", "<p>In this report, We define the LTR family by DNA sequence similarity, following the suggestion of Wicker et al. [##REF##17984973##3##]: two elements belong to the same family if they share 80% (or more) sequence identity in at least 80% of their coding region or internal domain, or within their LTR, or in both. A novel family is discovered when the following standards are met: 1) None of the members in the family belong to the same family with known legume LTR retrotransposons. 2) Besides a full-length member, the family has at least one strong hit (also called strong-hit copies. See Methods).</p>", "<p>The 526 full-length elements and their related copies thus were classified into 85 families, of which 64 were identified for the first time. The information of these families is listed in Table ##TAB##0##1##. LTR families are denoted as MtrXX (XX are digits) and the last two columns of Table ##TAB##0##1## list the number of full-length and strong-hit copies because these two values provide multi-copy supports for a family. The following sections sometimes mention the total copy-number of a family and the length of its sequences. Such values, however, are estimated by all copies of that family, including full-length, strong-hit and other truncated ones.</p>", "<p>Phylogenetic analysis classified 74 families as Copia or Gypsy superfamily (Figure ##FIG##0##1##) and the rest 11, though quite abundant in genome, could not be categorized as either superfamily by their protein-coding domain organization or sequence similarity. We found that half of the 11 families had long ORFs in their internal domain and some ORFs showed a certain degree of homology with known TE proteins. These families were categorized into TRIMs or LARDs group (TRIMs-LARDs) by their length [##REF##17984973##3##].</p>", "<title>Protein domain organization and phylogenetic relationships within LTR families</title>", "<p>We analyzed protein-domain organization of the 85 families (see Methods) and found 9 patterns (Table ##TAB##1##2## and [see Additional file ##SUPPL##2##3##]). HMMER detected the canonical Copia and Gypsy domain structures, i.e. 5'-GAG-IN-RT-3' and 5'-GAG-RT-IN-3', in 35 and 14 families, respectively. Although it failed to detect the GAG proteins in 21 families, they could still be categorized by the order of their RT and IN in the POL. Mtr3, Mtr5 and Mtr62 had RT but not IN, and they were assigned to either superfamilies by sequence similarity of RT domain (The reason of this assignment is explained in next paragraph): Mtr3 and Mtr5 were categorized as Copia superfamily while Mtr62 as Gypsy superfamily. At last, we obtained 56 Copia-like and 18 Gypsy-like families. Using a RT of Bel-Pao element (BEL-1-I_NVp from Repbase) as outgroup, we constructed the NJ phylogenetic tree of the 74 families based on their RT similarity (Figure ##FIG##0##1##). The tree branched into two clades and this split was well supported (bootstrap value: 100%). In the tree, the superfamily label of each external node was given according to the order of domains. It is worth noting that the two clades consist of neither more nor less than members of two superfamilies, respectively. In other words, the categorization of superfamily based on RT similarity concurs with that based on domain organization. This means that RT similarity is enough to categorize LTR elements at the level of superfamily. In Figure ##FIG##0##1##, Mtr3, Mtr5, and Mtr62 are also drawn with others, but the tree topology do not change if they are deleted. These results support their earlier categorization by RT similarity.</p>", "<p>To reveal the phylogenetic relationships within the superfamilies, we collected from literatures RT domains of 158 reference elements representing known Eukaryotic LTR lineages [##REF##15668770##21##,##REF##15777633##29##, ####REF##18031571##30##, ##REF##17895280##31####17895280##31##] and combined these data with our 74 families to construct trees [see Additional file ##SUPPL##3##4##]. We found that the Copia-like families belonged to 10 clades. MTC-1, a new lineage composed of Mtr5, Mtr49 and Mtr55, was recognized with middle support (Bootstrap value: 62%). The Gypsy-like families belonged to 4 well defined lineages (Figure ##FIG##0##1##).</p>", "<title>PBS pattern of LTR elements</title>", "<p>We investigated TSD, PPT and PBS patterns of LTR elements. Although the TSDs and PPTs did not show significant sequence preference, we found clear tRNA usage bias through the PBS strings. The validation of a PBS sequence was to find the string which was located immediately downstream of the 5' LTR and a reverse complement to the 3' ends of a tRNA [##REF##17556529##32##]. By the criterion of matching at least 14 bp, the PBSs were detected in 80 families, including all members in Copia and Gypsy superfamilies and 6 other families. We found that tRNAs corresponding to His, Phe, Tyr, Ser and Cys were never used as primer of reverse transcription and the majority of the rest 15 actually detected tRNA types occurred with low frequency. By contrast, the most-detected 4 types were used by nearly 3/4 families. Moreover, tRNA_{<italic>Met </italic>}occurred in about 60% of the 80 families and was the most frequently used type in both superfamilies and TRIMs-LARDs. tRNA_{<italic>Arg </italic>}was the second important primer in Gypsy superfamily and was only used by this group (Table ##TAB##2##3## and [see Additional file ##SUPPL##2##3##]).</p>", "<title>Copia superfamily</title>", "<p>The present research discovered 64 novel families, including 38 Copia-like, 15 Gypsy-like and 11 other ones. We describe each group in the following three sections, with emphasis on some important families.</p>", "<p>The total copy-number of the 56 Copia-like families reached 4816 and their sequences had a total length of 7164 Kb, about 3% of all genomic sequences investigated. Full-length elements varied in length from 3 to 12.7 Kb, with an average of 5.9 Kb. The longest family Mtr2/COPIA4, which had more than 130 copies, was one of the most abundant Copia-like families. We detected 3 long ORFs in its internal domain. From 5' to 3', the first two ORFs encoded canonical GAG-POL proteins. The third ORF, located less than 1 Kb downstream of the POL region, encoded a protein longer than 790AA. Although the homology search against Uniprot [##UREF##2##33##] did not return significant match to this ORF, it showed quite high conservation among the family members (Figure ##FIG##1##2b##). Moreover, we found that a 258 bp subregion in this ORF matched the putative ENV protein of the <italic>Glycine max </italic>putative endogenous retrovirus SIRE1-8 with low significance (similarity: 22%, e-value: 0.003). These results indicated that this ORF probably encoded a protein related to putative plant ENV.</p>", "<p>Besides Mtr2, there were 6 Copia-like families longer than 10 Kb and all of them had the GAG, IN and RT domains. Mtr1 was the most abundant Copia-like family and the second largest in all the 85 families. It had 69 full-length members, more than 800 copies and its sequences reached more than 2.5 Mb in length, about 36% of the total length of the Copia-like copies. The percentage was 6.6 times as high as that of the second largest Copia-like family Mtr2, whose sequences were 392 Kb in length. The PBS of Mtr1 bounded tRNA_{<italic>Met </italic>}and the length of its full-length members and LTRs were about 12 and 1.3 Kb, respectively. Outside <italic>Mt</italic>, the best match of its RT domain in Uniprot was from <italic>V. vinifera </italic>(Accession: A5BWH6). Similar to Mtr2, a third long ORF was also detected in its internal domain (Figure ##FIG##1##2a##). However, this ORF, matching a putative uncharacterized <italic>Mt </italic>protein (Q2HU06), was less conservative among the family members. The length of the LTRs of Copia-like families fell within the range of 126 bp to 2 Kb, with an average of 506 bp. LTRs could be roughly categorized into 4 zones: 100–500 bp, 600–850 bp, 1.2–1.45 Kb and &gt;1.5 Kb. The number of families in these zones was 39, 8, 6 and 3, respectively [see Additional file ##SUPPL##1##2##]. We found that long elements tended to have long LTRs. In fact, almost all LTRs longer than 1 Kb were from elements longer than 10 Kb. Mtr3 and Mtr18 were exceptions. The length of the LTR of Mtr3 reached 1.28 Kb yet that of the full length was only 6 Kb. As one of the most abundant Copia-like retrotransposon, Mtr3 had 292 Kb sequences in the genome, It was a typical non-autonomous family since no &gt;500 bp ORF could be detected in its internal domain and its RT degenerated to a fragment of 40AA.</p>", "<p>There were 11 Copia-like families whose LTRs and full-length sequences were shorter than 200 bp and 5 Kb, respectively. 6 of them have been deposited in Repbase. Mtr30/MTCOPIA2 and Mtr32/COP3 were quite active in the genome and their copies corresponded to more than 200 and 109 Kb sequences, respectively. Despite short LTRs, we detected 5'-IN-RT-3' domains in all of them and GAG proteins in 7.</p>", "<title>Gypsy superfamily</title>", "<p>The 18 Gypsy-like families corresponded to 11652 Kb sequences and constituted 5% of all genomic data. This group had a full length of 5.1 to 18.7 Kb, with an average of 9.8 Kb. Their LTRs were from 313 to 3.5 Kb in length, with an average of 1.5 Kb. Compared with Copia-like LTR retrotransposons, Gypsy-like elements were longer in general: the great majority of Gypsy-like families had a full length &gt; 6 Kb and LTR &gt;500 bp, while the full length and the LTR of most Copia-like families were &lt; 6 Kb and 500bp, respectively [see Additional file ##SUPPL##1##2##]. The total copy-number in this superfamily was 7434, about 1.5 times more than Copia superfamily (4816). Despite fewer members, Gypsy superfamily contributed more to the <italic>Mt </italic>genome than Copia superfamily because of longer length and more active amplification in the past.</p>", "<p>Mtr57 and Mtr59 were Ogre families [##REF##14750527##20##,##REF##17052864##22##] and Mtr57/Ogre1 was the largest in all the 85 families. Our survey detected its 114 full-length members and more than 1000 copies in total. The length of its sequences reached 4.2 Mb. Mtr70 was closely related to Mtr57 in the phylogenetic tree, and was the second longest in all the families (The longest one is Mtr57/Ogre1). These two families used tRNA_{<italic>Arg </italic>}as primer and their internal domain encoded 5'-GAG-RT-RH-IN-3' proteins. We detected an ORF of 1527 bp located upstream of the GAG and an intron in the POL. Such phylogenetic and structural features well support that Mtr70 is a novel Ogre family. Mtr58 was the second largest family in the Gypsy group and the third largest in all the families. It had more than 600 copies in total and corresponded to 1.4 Mb sequences, about 1/3 of Mtr57/Ogre1. Its full length were about 8.8 Kb and the LTRs were 2.1 Kb in length. Its internal domain encoded 5'-GAG-PRO-RT-RH-IN-3' proteins (Figure ##FIG##1##2f##) and its PBS matched tRNA_{<italic>Met </italic>}well. Phylogenetically, this family belonged to the Tekay clade.</p>", "<p>Mtr67, Mtr60 and Mtr64 were the other 3 families longer than &gt;10 Kb. Similar to Copia superfamily, it was found that, when the full-length of an element was &gt;10 Kb, the LTR was correspondingly &gt;1 Kb. The only exceptional family Mtr67 had a LTR of 720 bp. Besides normal 5'-GAG-RT-RH-IN-3' domains, this family had 5 additional &gt;500 bp ORFs downstream of the POL. They were all located in the complementary chain and had no match in Uniport. However, these ORFs were quite conservative among the family members (Figure ##FIG##1##2g##). We estimated that these ORFs were derived from other sources and later captured by Mtr67. The short LTR reflected short original length of this family. Mtr60 belonged to the Athila clade (Figure ##FIG##0##1##). Its PBS bound tRNA_{<italic>Asp </italic>}and its protein-coding domains organized as 5'-GAG-RT-IN-3'. Downstream of the POL, there were two &gt;500 bp ORFs encoding uncharacterized proteins (best match in Uniprot: A2Q2P5 and A2Q2P6). Mtr64, the sister branch of Mtr60, also had an extra ORF downstream of the POL. Its best match in Uniprot was from <italic>Garden asparagus </italic>(Q2AA44) and it shared weak similarity with the first extra ORF in Mtr60 (Similarity: 24%, e-value: 2e-06). Known elements of the Athila clade were putative plant endogenous retroviruses, thus the possibility that the extra ORFs in Mtr60 and Mtr64 encoded the putative ENVs was strong, although they did not share significant similarity with the putative ENVs of known Athila elements.</p>", "<p>Mtr65 and Mtr74 were from the CRM clade, while Mtr72/GYPSHAN and Mtr73 were from Renia. Families of these two clades were relatively inactive in <italic>Mt</italic>: each had a copy-number &lt;50 and corresponded to &lt;80 Kb sequences. Even so, they all showed multiple domains in their internal domain [see Additional file ##SUPPL##2##3##].</p>", "<title>TRIMs and LARDs</title>", "<p>Because their internal domain lacked strong homology to any known TE proteins, the 11 families were required to have at least 5 strong hits in the genome. The total sequences of them were 3654 Kb in length, about 1.6% of all data. According to the suggestion of [##REF##17984973##3##], the 5 families that had a length less than 4 Kb were classified as TRIMs and the other 6 as LARDs.</p>", "<p>We detected ORFs longer than 700 bp in 4 families: Mtr80 had 2 such ORFs. One shared weak similarity with a GAG protein in rice (Q7XRT, 35%, 4 × 10^-92) and the other with a putative transposon protein in <italic>A. thaliana </italic>(Q9XH30, 27%, 2 × 10^-8). Although HMMER failed to detect (e-value: 10^-6) RT and IN domains in 4 of the 5 full-length members, previous analyses suggested that Mtr80/MEGY belonged to a distinct clade called env-class [##REF##15668770##21##]. Mtr78, Mtr82 and Mtr76 each had only one ORF &gt;700 bp. The best Uniprot match of the ORF in Mtr78 was again Q9XH30 (24%, 2 × 10^-9), while that of the ORF in Mtr82 was an uncharacterized protein from grape (AB5PC1, 46%, 3 × 10^-57). The ORF in Mtr76 was highly similar to that in Mtr82 (80.1%) and a subregion in this ORF was reported as a GAG by HMMER (Figure ##FIG##1##2h##).</p>", "<p>Mtr81 is the longest family in the 11. Although its internal domain was long, most members in this family rarely contained long ORFs. Searching the internal domain against Uniprot with BLASTX retrieved a 438 bp region homologous to some RT proteins and the best well-studied match was from the maize (<italic>Zea mays</italic>) Opie element (Q8H7T1, 60%, 1 × 10^-48). The high similarity with Opie strongly supported that this ORF did encode a RT domain. However, it could not be detected by HMMER and this indicated that this RT might be not built in current RT profiles. Phylogenetic analysis further revealed that it belonged to neither Copia nor Gypsy superfamily but was close to the outgroup [see Additional file ##SUPPL##4##5##]. Further investigation is needed to fully resolve its position.</p>", "<p>The last family that shared homology with known TE proteins was Mtr85. It had a ~321 bp ORF encoding a fragment of RH (A4PUT7, similarity: 91%, e-value: 1 × 10^-49). Each of the other 5 families had more than 10 strong hits and quite large copy-number in the genome. Mtr75 was the shortest family, of which the full-length members and the LTRs were only 364 and 130 bp in length, respectively. Instead of typical 5'-TG-3', 5' ends of its LTRs were 5'-TA-3'. Despite highly degenerated internal domain, this family had 9 full-length members and 74 strong hits. Mtr77, Mtr83 and Mtr84 were LARDs. Similar to Mtr75, Mtr77 was an abundant non-autonomous family with highly degenerated internal domain (about 200 bp).</p>", "<title>Structure of LTR retrotransposons in <italic>Mt</italic></title>", "<p>We studied the structure of the LTR families and Figure ##FIG##1##2## displays the structures of 8 highly abundant ones, five of which have been described above. The structure of Ogre elements is not shown because it has been reported previously [##REF##17052864##22##]. Here we just point out that the LTR regions of most families tend to be less conservative among the family members in comparison with TE proteins, as well as many long ORFs. This result well supports that LTRs are the most rapidly evolving regions in LTR retrotransposons [##REF##17984973##3##,##REF##15003117##34##].</p>", "<title>Insertion-deletion of LTR retrotransposons in <italic>Mt</italic></title>", "<p>Mtr1, Mtr2, Mtr6, Mtr10, Mtr57-59 and Mtr76 each had more than 10 full-length members. The total number of these full-length copies was 296, making up 56.3% of all the full-length elements identified. Their total copies constituted 45.3% of the LTR retrotransposon sequences.</p>", "<p>Paleontology analysis on the 296 elements revealed that they were quite young: all were inserted within the last 2 MY and 90% within 0.4 MY. Compared with others, the active period of Mtr6 (10 full-length copies) and Mtr76 (17 full-length copies) was relatively long [see Additional file ##SUPPL##5##6##]. Recent researches have argued that truncated LTR elements were mainly caused by unequal homologous or illegitimate recombination within genome and the result of recombination was the deletion of genomic sequences [##REF##15240870##27##,##REF##17556529##32##,##REF##12097344##35##,##REF##17617907##36##]. We estimated the deletion of LTR copies in <italic>Mt </italic>genome from two aspects: 1) the deletion of full-length structure and 2) the number of DNA loss. The deletion of a full-length structure means that mutation and recombination remove so many structural characters of a full-length element that it can not be recognized any more. Assuming that repetitive sequences are removed at a constant rate, the survival time of full-length structure obeys an exponential distribution and therefore the half-life is an index to estimate the speed of removal. With this method, [##REF##17556529##32##] estimated that the half-life of the full-length elements in rice was about 0.79 MY.</p>", "<p>We calculated the insertion date of all the 526 full-length elements and found that 90% of them inserted within the last 0.52 MY (Figure ##FIG##2##3a##). Fitting of the distribution to the exponential function obtained <italic>α </italic>= -2.71, which corresponded to a half-life <italic>τ </italic>= 0.26 MY (Figure ##FIG##2##3b##). The bootstrap revealed that the half-life varied between 0.24 to 0.3 MY. To compare the speed of removal in legume and grass, we calculated the half-life for 705 full-length elements in the two sequenced rice genomes (<italic>Oryza sativa indica ssp</italic>. and <italic>japonica ssp</italic>.). Elements in rice and <italic>Mt </italic>were predicted under the same parameters (Hao Wang, unpublished data). As can be seen from Figure ##FIG##2##3c## and ##FIG##2##3d##, our data supported that the half-life of full-length structure in rice was ~0.4 MY, a lesser value than the estimation of [##REF##17556529##32##] but still greater than that in <italic>Mt</italic>. Furthermore, statistical testing revealed that the insertion dates in the two species were from different distributions (Kolmogorov-Smirnov test, P-Value: 3.4 × 10^-14). If the mean substitution rates of LTR elements in <italic>Mt </italic>and grass are approximately the same [##REF##17101966##37##], the above results support that the full-length structures have been deleted more rapid in <italic>Mt </italic>than in rice. If the deletions have been occurred randomly in genome, the results further indicate that the removal of LTR elements in <italic>Mt </italic>has been more rapid than in rice.</p>", "<p>The total number of the strong hits was only 6% of all detected copies, but their size reached 42%. This indicated that LTR elements in <italic>Mt </italic>were highly fragmented and these truncated copies, great in number, might be generated by the removal of genomic DNA. If the truncated LTR copies were real vestiges of paralogous copies of families and if they had similar lengthes to the representative copies at the time of insertion, the difference of the length of truncated and representative copies provided the amount of deleted DNA since their insertion [##REF##17617907##36##]. The estimation of the upper and lower limits of DNA loss could be as follows: we used the copies of Rset (see Methods) to estimate the lower limit. The data revealed that 5.5 Mb sequences have been deleted. Since Rset only consisted of not-so-severely truncated copies, it caused an underestimate of DNA loss. In contrast, we used all the truncated copies to estimate the upper limit and this gave more than 46 Mb of DNA has been removed. Since only 40% of the genome was analyzed here, we estimated that more than 10 Mb of LTR retrotransposon sequences have been deleted from the <italic>Mt </italic>genome.</p>" ]

[ "<title>Conclusion</title>", "<p>We have systematically identified and described LTR retrotransposons in nearly half of the <italic>Medicago truncatula </italic>genome, investigated their classification, structure, evolutionary dynamics and impact on the evolution of the host genome. The present work has provided a LTR retrotransposon landscape for this model legume. The sequencing of other species such as <italic>Lotus japonicus </italic>and <italic>Glycine max </italic>will provide great opportunity to study comparatively the evolutionary dynamics of LTR families in two or more legume organisms and further explore the interactions between these elements and their host genomes.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Long terminal repeat retrotransposons (LTR elements) are ubiquitous Eukaryotic TEs that transpose through RNA intermediates. Accounting for significant proportion of many plant genomes, LTR elements have been well established as one of the major forces underlying the evolution of plant genome size, structure and function. The accessibility of more than 40% of genomic sequences of the model legume <italic>Medicago truncatula </italic>(<italic>Mt</italic>) has made the comprehensive study of its LTR elements possible.</p>", "<title>Results</title>", "<p>We use a newly developed tool LTR_FINDER to identify LTR retrotransposons in the <italic>Mt </italic>genome and detect 526 full-length elements as well as a great number of copies related to them. These elements constitute about 9.6% of currently available genomic sequences. They are classified into 85 families of which 64 are reported for the first time. The majority of the LTR retrotransposons belong to either Copia or Gypsy superfamily and the others are categorized as TRIMs or LARDs by their length. We find that the copy-number of Copia-like families is 3 times more than that of Gypsy-like ones but the latter contribute more to the genome. The analysis of PBS and protein-coding domain structure of the LTR families reveals that they tend to use only 4–5 types of tRNAs and many families have quite conservative ORFs besides known TE domains. For several important families, we describe in detail their abundance, conservation, insertion time and structure. We investigate the amplification-deletion pattern of the elements and find that the detectable full-length elements are relatively young and most of them were inserted within the last 0.52 MY. We also estimate that more than ten million bp of the <italic>Mt </italic>genomic sequences have been removed by the deletion of LTR elements and the removal of the full-length structures in <italic>Mt </italic>has been more rapid than in rice.</p>", "<title>Conclusion</title>", "<p>This report is the first comprehensive description and analysis of LTR retrotransposons in the <italic>Mt </italic>genome. Many important novel LTR families were discovered and their evolution is elucidated. Our results may outline the LTR retrotransposon landscape of the model legume.</p>" ]

[ "<title>Authors' contributions</title>", "<p>HW designed and carried out the LTR retrotransposon studies, participated in the design of LTR retrotransposon mining program and drafted the manuscript. J-SL participated in the design of the program of LTR copy validation. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>The authors thank Professor Bai-Lin Hao for valuable comments and suggestions on the manuscript. This work is supported by Shanghai Leading Academic Discipline Project (Project Number: B111).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>RT phylogenetic tree of 74 LTR families</bold>. A Bel-Pao type RT (BEL-1-I_NVp from Repbase) is used as outgroup. The 74 families are grouped into Copia or Gypsy superfamily. In the tree, each family is described by its name and a superfamily label. The superfamily label is given according to the order of domains in the POL. RT similarity and domain organization give consistent categorization. Mtr3, Mtr5 and Mtr62 lack other domains except RT, so they are categorized directly though RT similarity and are marked by the lowercase initials of the superfamilies. The 14 clades, to which the 74 families belong, are shown in the figure. The placement of Mtr3 and Mtr39 is unresolved and they are marked by grey dots [see Additional file ##SUPPL##3##4##].</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Structure of LTR families</bold>. Each sub-figure gives the structure of a family. the X-axis displays coordinates of nucleotides and the Y-axis displays average similarities among the full-length members of that family (calculated using the PLOTCON program in the EMBOSS package [##REF##10827456##46##]). Grey stripes show the positions of the LTR and the domains detected. We display ORFs that are &gt;500 bp in length. The arrow under a ORF label represents the length of that ORF. In Mtr67, the ORFs are found in both chains and their orientation is indicated by the arrows above the ORF labels. Sudden collapse of similarity (e.g. 1.8–2 Kb of Mtr8 and 2–3.5 Kb of Mtr10) is caused by the insertion or deletion events in one or two family members.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Half-life of full-length LTR retrotransposons in <italic>Mt </italic>and rice</bold>. 526 <italic>Mt </italic>and 705 rice full-length elements are analyzed. Each bin represents 0.1 MY. Vertical bars under the histogram represent insertion events. a) The distribution of the insertion date of <italic>Mt </italic>elements. Fitting of this distribution to a exponential curve indicates that the insertions in the recent 0.1 MY have been significantly active. b) Fitting the dates to the exponential curve. The logarithm of the dates fits the straight line <italic>y </italic>= 0.52 - 2.71<italic>x </italic>well. Therefore the rate of the exponential curve is <italic>α </italic>= -2.71, which corresponds to a half-life of 0.26 MY. c) and d) display the fitting in rice, which gives a half-life of 0.4 MY.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Homologous matches of an candidate</bold>. The lines represent matches generated by whole-genome homology search of a reference candidate. Some matches are made of several pieces (segments on the same horizontal line). All the matches are categorized into Part I and Part II. Part I (Rset) consists of the matches that cover both the LTR region and the internal domain. They are reliable copies of the reference candidate. Part II is further classified into pseudo-copies and \"copies in part II\". Pseudo-copies are the matches that correspond to unrelated sequences. Unrelated sequences (dark grey regions) are the subregions that have significantly high matches (grey stripes) or that match some LTR elements well (not showing here). At last, \"copies in part II\" and Rset are combined to obtain the total copies of the candidate.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Summary of the 85 <italic>Medicago truncatula </italic>LTR families</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Family</td><td align=\"left\">Pre-existing name</td><td align=\"left\">Super-family</td><td align=\"left\">BAC</td><td align=\"left\">Location(bp)</td><td align=\"left\">LTR size(bp)</td><td align=\"left\">Element size(bp)</td><td align=\"left\">FL</td><td align=\"left\">Strong hit</td></tr></thead><tbody><tr><td align=\"left\">Mtr1</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC150246.1</td><td align=\"left\">34464–46424</td><td align=\"left\">1309</td><td align=\"left\">11961</td><td align=\"left\">69</td><td align=\"left\">184</td></tr><tr><td align=\"left\">Mtr2</td><td align=\"center\">COPIA4</td><td align=\"center\">Copia</td><td align=\"left\">AC137553.45</td><td align=\"left\">99838–112535</td><td align=\"left\">2045</td><td align=\"left\">12698</td><td align=\"left\">11</td><td align=\"left\">29</td></tr><tr><td align=\"left\">Mtr3</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CR931729.2</td><td align=\"left\">71151–77207</td><td align=\"left\">1287</td><td align=\"left\">6057</td><td align=\"left\">5</td><td align=\"left\">22</td></tr><tr><td align=\"left\">Mtr4</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC157648.18</td><td align=\"left\">22659–28446</td><td align=\"left\">627</td><td align=\"left\">5788</td><td align=\"left\">9</td><td align=\"left\">15</td></tr><tr><td align=\"left\">Mtr5</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC146866.6</td><td align=\"left\">121051–127748</td><td align=\"left\">602</td><td align=\"left\">6698</td><td align=\"left\">8</td><td align=\"left\">14</td></tr><tr><td align=\"left\">Mtr6</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC151725.26</td><td align=\"left\">4572–10226</td><td align=\"left\">797</td><td align=\"left\">5655</td><td align=\"left\">10</td><td align=\"left\">14</td></tr><tr><td align=\"left\">Mtr7</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CT967304.4</td><td align=\"left\">59158–64899</td><td align=\"left\">639</td><td align=\"left\">5742</td><td align=\"left\">7</td><td align=\"left\">13</td></tr><tr><td align=\"left\">Mtr8</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC145027.17</td><td align=\"left\">30490–37188</td><td align=\"left\">676</td><td align=\"left\">6699</td><td align=\"left\">8</td><td align=\"left\">12</td></tr><tr><td align=\"left\">Mtr9</td><td align=\"center\">SHACOP3</td><td align=\"center\">Copia</td><td align=\"left\">AC159223.1</td><td align=\"left\">27730–32760</td><td align=\"left\">189</td><td align=\"left\">5031</td><td align=\"left\">6</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Mtr10</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC144482.11</td><td align=\"left\">104300–109315</td><td align=\"left\">436</td><td align=\"left\">5016</td><td align=\"left\">10</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Mtr11</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC165219.2</td><td align=\"left\">137152–141889</td><td align=\"left\">273</td><td align=\"left\">4738</td><td align=\"left\">7</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr12</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC149637.11</td><td align=\"left\">7608–18418</td><td align=\"left\">1344</td><td align=\"left\">10811</td><td align=\"left\">5</td><td align=\"left\">7</td></tr><tr><td align=\"left\">Mtr13</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC151956.5</td><td align=\"left\">65260–71649</td><td align=\"left\">203</td><td align=\"left\">6390</td><td align=\"left\">5</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mtr14</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC144538.23</td><td align=\"left\">111496–121985</td><td align=\"left\">1394</td><td align=\"left\">10490</td><td align=\"left\">5</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mtr15</td><td align=\"center\">COP20</td><td align=\"center\">Copia</td><td align=\"left\">AC121235.20</td><td align=\"left\">19414–24294</td><td align=\"left\">346</td><td align=\"left\">4881</td><td align=\"left\">5</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mtr16</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CR931743.1</td><td align=\"left\">32761–38060</td><td align=\"left\">574</td><td align=\"left\">5300</td><td align=\"left\">4</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mtr17</td><td align=\"center\">SHACOP12</td><td align=\"center\">Copia</td><td align=\"left\">AC148291.22</td><td align=\"left\">18569–23612</td><td align=\"left\">213</td><td align=\"left\">5044</td><td align=\"left\">5</td><td align=\"left\">5</td></tr><tr><td align=\"left\">Mtr18</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC124217.21</td><td align=\"left\">65448–73850</td><td align=\"left\">1419</td><td align=\"left\">8403</td><td align=\"left\">2</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr19</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC149492.14</td><td align=\"left\">60016–72184</td><td align=\"left\">1822</td><td align=\"left\">12169</td><td align=\"left\">2</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr20</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC145330.19</td><td align=\"left\">54872–60067</td><td align=\"left\">190</td><td align=\"left\">5196</td><td align=\"left\">3</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr21</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC144760.27</td><td align=\"left\">99316–104667</td><td align=\"left\">597</td><td align=\"left\">5352</td><td align=\"left\">4</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr22</td><td align=\"center\">COP10</td><td align=\"center\">Copia</td><td align=\"left\">AC144618.7</td><td align=\"left\">69511–74634</td><td align=\"left\">324</td><td align=\"left\">5124</td><td align=\"left\">4</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr23</td><td align=\"center\">COP6</td><td align=\"center\">Copia</td><td align=\"left\">AC125476.30</td><td align=\"left\">52976–57511</td><td align=\"left\">212</td><td align=\"left\">4536</td><td align=\"left\">2</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr24</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC148470.14</td><td align=\"left\">69233–73561</td><td align=\"left\">250</td><td align=\"left\">4329</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr25</td><td align=\"center\">SHACOP4</td><td align=\"center\">Copia</td><td align=\"left\">AC152964.13</td><td align=\"left\">48071–52925</td><td align=\"left\">276</td><td align=\"left\">4855</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr26</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CT573053.1</td><td align=\"left\">95022–106275</td><td align=\"left\">1608</td><td align=\"left\">11254</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr27</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC140916.17</td><td align=\"left\">54292–65468</td><td align=\"left\">1434</td><td align=\"left\">11177</td><td align=\"left\">1</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr28</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC174349.10</td><td align=\"left\">54241–58572</td><td align=\"left\">126</td><td align=\"left\">4332</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr29</td><td align=\"center\">COP12</td><td align=\"center\">Copia</td><td align=\"left\">AC165446.16</td><td align=\"left\">77640–82389</td><td align=\"left\">351</td><td align=\"left\">4750</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr30</td><td align=\"center\">MTCOPIA2</td><td align=\"center\">Copia</td><td align=\"left\">AC149471.1</td><td align=\"left\">84193–89268</td><td align=\"left\">186</td><td align=\"left\">5076</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr31</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CT573028.11</td><td align=\"left\">32334–34027</td><td align=\"left\">204</td><td align=\"left\">3059</td><td align=\"left\">1</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr32</td><td align=\"center\">COP3</td><td align=\"center\">Copia</td><td align=\"left\">AC138465.22</td><td align=\"left\">17893–22580</td><td align=\"left\">181</td><td align=\"left\">4688</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr33</td><td align=\"center\">MTCOPIA1</td><td align=\"center\">Copia</td><td align=\"left\">CT963078.3</td><td align=\"left\">62740–67719</td><td align=\"left\">269</td><td align=\"left\">4980</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr34</td><td align=\"center\">SHACOP11</td><td align=\"center\">Copia</td><td align=\"left\">AC154867.1</td><td align=\"left\">30673–35442</td><td align=\"left\">189</td><td align=\"left\">4770</td><td align=\"left\">1</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr35</td><td align=\"center\">SHACOP20</td><td align=\"center\">Copia</td><td align=\"left\">AC149038.2</td><td align=\"left\">47760–52995</td><td align=\"left\">263</td><td align=\"left\">5236</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr36</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC174295.7</td><td align=\"left\">36459–41224</td><td align=\"left\">171</td><td align=\"left\">4766</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr37</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC157979.11</td><td align=\"left\">69871–74887</td><td align=\"left\">249</td><td align=\"left\">5017</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr38</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC171778.15</td><td align=\"left\">79794–84281</td><td align=\"left\">222</td><td align=\"left\">4488</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr39</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC148470.14</td><td align=\"left\">54043–59356</td><td align=\"left\">861</td><td align=\"left\">5314</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr40</td><td align=\"center\">SHACOP9</td><td align=\"center\">Copia</td><td align=\"left\">AC175047.2</td><td align=\"left\">122584–127374</td><td align=\"left\">190</td><td align=\"left\">4791</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr41</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC174336.9</td><td align=\"left\">98223–102259</td><td align=\"left\">296</td><td align=\"left\">4704</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr42</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC157506.3</td><td align=\"left\">45694–50555</td><td align=\"left\">205</td><td align=\"left\">4862</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr43</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC175047.2</td><td align=\"left\">115144–119648</td><td align=\"left\">256</td><td align=\"left\">4505</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr44</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC183304.10</td><td align=\"left\">99523–104053</td><td align=\"left\">167</td><td align=\"left\">4531</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr45</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CR955009.1</td><td align=\"left\">105072–109675</td><td align=\"left\">306</td><td align=\"left\">4604</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr46</td><td align=\"center\">COP14</td><td align=\"center\">Copia</td><td align=\"left\">AC170583.6</td><td align=\"left\">12146–16446</td><td align=\"left\">171</td><td align=\"left\">4301</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr47</td><td align=\"center\">COP21</td><td align=\"center\">Copia</td><td align=\"left\">AC182817.5</td><td align=\"left\">43694–48680</td><td align=\"left\">290</td><td align=\"left\">4987</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr48</td><td align=\"center\">SHACOP21</td><td align=\"center\">Copia</td><td align=\"left\">AC161106.13</td><td align=\"left\">30630–35152</td><td align=\"left\">232</td><td align=\"left\">4523</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr49</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC158377.1</td><td align=\"left\">75346–80903</td><td align=\"left\">131</td><td align=\"left\">5558</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr50</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC175047.2</td><td align=\"left\">83093–87466</td><td align=\"left\">242</td><td align=\"left\">4374</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr51</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC123573.41</td><td align=\"left\">60243–65229</td><td align=\"left\">213</td><td align=\"left\">4987</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr52</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC135798.31</td><td align=\"left\">10206–15241</td><td align=\"left\">330</td><td align=\"left\">5036</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr53</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC137831.27</td><td align=\"left\">31862–36604</td><td align=\"left\">218</td><td align=\"left\">4782</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr54</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">CT963132.5</td><td align=\"left\">16390–21157</td><td align=\"left\">239</td><td align=\"left\">5030</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr55</td><td align=\"center\">-</td><td align=\"center\">Copia</td><td align=\"left\">AC149634.8</td><td align=\"left\">14602–17988</td><td align=\"left\">206</td><td align=\"left\">3387</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr56</td><td align=\"center\">SHACOP2</td><td align=\"center\">Copia</td><td align=\"left\">AC146909.23</td><td align=\"left\">66018–71021</td><td align=\"left\">274</td><td align=\"left\">5004</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr57</td><td align=\"center\">Ogre1A,B,C,D</td><td align=\"center\">Gypsy</td><td align=\"left\">AC144405.30</td><td align=\"left\">85771–104542</td><td align=\"left\">3529</td><td align=\"left\">18772</td><td align=\"left\">114</td><td align=\"left\">137</td></tr><tr><td align=\"left\">Mtr58</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC162162.23</td><td align=\"left\">96896–105667</td><td align=\"left\">2127</td><td align=\"left\">8772</td><td align=\"left\">34</td><td align=\"left\">69</td></tr><tr><td align=\"left\">Mtr59</td><td align=\"center\">Ogre2,3,4</td><td align=\"center\">Gypsy</td><td align=\"left\">AC138465.22</td><td align=\"left\">43789–60338</td><td align=\"left\">2435</td><td align=\"left\">16550</td><td align=\"left\">31</td><td align=\"left\">37</td></tr><tr><td align=\"left\">Mtr60</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC123573.41</td><td align=\"left\">34307–46826</td><td align=\"left\">1335</td><td align=\"left\">12520</td><td align=\"left\">2</td><td align=\"left\">26</td></tr><tr><td align=\"left\">Mtr61</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC147430.9</td><td align=\"left\">69500–78131</td><td align=\"left\">2072</td><td align=\"left\">8632</td><td align=\"left\">1</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr62</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC160097.27</td><td align=\"left\">42464–45517</td><td align=\"left\">2076</td><td align=\"left\">8661</td><td align=\"left\">1</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr63</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">CU024896.3</td><td align=\"left\">74551–82251</td><td align=\"left\">2222</td><td align=\"left\">7701</td><td align=\"left\">3</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mtr64</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC146759.29</td><td align=\"left\">74288–85435</td><td align=\"left\">1218</td><td align=\"left\">11148</td><td align=\"left\">4</td><td align=\"left\">5</td></tr><tr><td align=\"left\">Mtr65</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">CT963073.3</td><td align=\"left\">80019–85667</td><td align=\"left\">313</td><td align=\"left\">5649</td><td align=\"left\">4</td><td align=\"left\">5</td></tr><tr><td align=\"left\">Mtr66</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC150705.16</td><td align=\"left\">77136–84299</td><td align=\"left\">1943</td><td align=\"left\">7164</td><td align=\"left\">2</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr67</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC140773.20</td><td align=\"left\">23404–37605</td><td align=\"left\">721</td><td align=\"left\">14202</td><td align=\"left\">3</td><td align=\"left\">4</td></tr><tr><td align=\"left\">Mtr68</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC125481.23</td><td align=\"left\">24806–33987</td><td align=\"left\">330</td><td align=\"left\">9182</td><td align=\"left\">2</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr69</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC157375.2</td><td align=\"left\">85556–93073</td><td align=\"left\">2125</td><td align=\"left\">7518</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr70</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC144591.10</td><td align=\"left\">13089–29661</td><td align=\"left\">2370</td><td align=\"left\">16573</td><td align=\"left\">1</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Mtr71</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">CU024896.3</td><td align=\"left\">71754–86395</td><td align=\"left\">366</td><td align=\"left\">6936</td><td align=\"left\">1</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr72</td><td align=\"center\">GYPSHAN2</td><td align=\"center\">Gypsy</td><td align=\"left\">AC158209.13</td><td align=\"left\">42449–47637</td><td align=\"left\">409</td><td align=\"left\">5189</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr73</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">AC148657.1</td><td align=\"left\">69339–74484</td><td align=\"left\">394</td><td align=\"left\">5146</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr74</td><td align=\"center\">-</td><td align=\"center\">Gypsy</td><td align=\"left\">CU024896.3</td><td align=\"left\">86399–92950</td><td align=\"left\">819</td><td align=\"left\">6552</td><td align=\"left\">2</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Mtr75</td><td align=\"center\">-</td><td align=\"center\">TRIM</td><td align=\"left\">AC147537.35</td><td align=\"left\">119057–119409</td><td align=\"left\">130</td><td align=\"left\">364</td><td align=\"left\">9</td><td align=\"left\">74</td></tr><tr><td align=\"left\">Mtr76</td><td align=\"center\">-</td><td align=\"center\">TRIM</td><td align=\"left\">CR954194.1</td><td align=\"left\">12806–16125</td><td align=\"left\">652</td><td align=\"left\">3320</td><td align=\"left\">17</td><td align=\"left\">38</td></tr><tr><td align=\"left\">Mtr77</td><td align=\"center\">-</td><td align=\"center\">LARD</td><td align=\"left\">AC155884.2</td><td align=\"left\">39928–44595</td><td align=\"left\">2191</td><td align=\"left\">4668</td><td align=\"left\">5</td><td align=\"left\">26</td></tr><tr><td align=\"left\">Mtr78</td><td align=\"center\">-</td><td align=\"center\">LARD</td><td align=\"left\">CT030253.10</td><td align=\"left\">41580–46389</td><td align=\"left\">921</td><td align=\"left\">5497</td><td align=\"left\">3</td><td align=\"left\">26</td></tr><tr><td align=\"left\">Mtr79</td><td align=\"center\">-</td><td align=\"center\">TRIM</td><td align=\"left\">AC158173.13</td><td align=\"left\">32092–32698</td><td align=\"left\">190</td><td align=\"left\">607</td><td align=\"left\">5</td><td align=\"left\">25</td></tr><tr><td align=\"left\">Mtr80</td><td align=\"center\">-</td><td align=\"center\">env-class</td><td align=\"left\">AC146719.32</td><td align=\"left\">60449–68395</td><td align=\"left\">1239</td><td align=\"left\">7947</td><td align=\"left\">5</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Mtr81</td><td align=\"center\">-</td><td align=\"center\">LARD</td><td align=\"left\">CT025840.2</td><td align=\"left\">61376–73139</td><td align=\"left\">2414</td><td align=\"left\">11764</td><td align=\"left\">2</td><td align=\"left\">14</td></tr><tr><td align=\"left\">Mtr82</td><td align=\"center\">-</td><td align=\"center\">TRIM</td><td align=\"left\">CT009479.4</td><td align=\"left\">31485–34519</td><td align=\"left\">810</td><td align=\"left\">3035</td><td align=\"left\">7</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr83</td><td align=\"center\">-</td><td align=\"center\">LARD</td><td align=\"left\">AC140022.11</td><td align=\"left\">3262–11660</td><td align=\"left\">1440</td><td align=\"left\">8399</td><td align=\"left\">2</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr84</td><td align=\"center\">-</td><td align=\"center\">LARD</td><td align=\"left\">AC147201.16</td><td align=\"left\">18119–23949</td><td align=\"left\">259</td><td align=\"left\">5831</td><td align=\"left\">6</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Mtr85</td><td align=\"center\">-</td><td align=\"center\">TRIM</td><td align=\"left\">AC145219.16</td><td align=\"left\">111276–112148</td><td align=\"left\">249</td><td align=\"left\">873</td><td align=\"left\">1</td><td align=\"left\">6</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Domain organization of LTR families.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Superfamily</td><td align=\"center\">pattern^{<italic>a</italic>}</td><td align=\"center\">Number of families</td></tr></thead><tbody><tr><td align=\"center\">Copia</td><td align=\"center\">GAG-IN-RT</td><td align=\"center\">35</td></tr><tr><td/><td align=\"center\">IN-RT</td><td align=\"center\">19</td></tr><tr><td/><td align=\"center\">RT^{<italic>b</italic>}</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Gypsy</td><td align=\"center\">GAG-RT-IN</td><td align=\"center\">14</td></tr><tr><td/><td align=\"center\">RT-IN</td><td align=\"center\">3</td></tr><tr><td/><td align=\"center\">RT^{<italic>b</italic>}</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Other</td><td align=\"center\">GAG^{<italic>c</italic>}</td><td align=\"center\">3</td></tr><tr><td/><td align=\"center\">RT^{<italic>d</italic>}</td><td align=\"center\">1</td></tr><tr><td/><td align=\"center\">Other</td><td align=\"center\">7</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>tRNA usage of LTR families</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">tRNA type</td><td align=\"left\">Copia superfamily</td><td align=\"left\">Gypsy superfamily</td><td align=\"left\">Other</td><td align=\"left\">all</td></tr></thead><tbody><tr><td align=\"center\">Met</td><td align=\"center\">34</td><td align=\"center\">6</td><td align=\"center\">2</td><td align=\"center\">42</td></tr><tr><td align=\"center\">Lys</td><td align=\"center\">4</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">7</td></tr><tr><td align=\"center\">Leu</td><td align=\"center\">5</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">6</td></tr><tr><td align=\"center\">Arg</td><td align=\"center\">0</td><td align=\"center\">4</td><td align=\"center\">0</td><td align=\"center\">4</td></tr><tr><td align=\"center\">Ala</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">3</td></tr><tr><td align=\"center\">Glu</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">3</td></tr><tr><td align=\"center\">Val</td><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">3</td></tr><tr><td align=\"center\">Asn</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Ile</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Tyr</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Asp</td><td align=\"center\">0</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Gln</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Gly</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Pro</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Thr</td><td align=\"center\">1</td><td align=\"center\">0</td><td align=\"center\">0</td><td align=\"center\">1</td></tr><tr><td align=\"center\">SUM</td><td align=\"center\">56</td><td align=\"center\">18</td><td align=\"center\">6</td><td align=\"center\">80</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p><bold>Sequences of 526 full-length LTR elements identified in this study</bold>. this file contains the sequences of all full-length LTR elements identified in this study.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p><bold>Distribution of the length of Copia and Gypsy superfamilies</bold>. this file contains two figures showing the distributions of the full-length and LTR length of <italic>Mt </italic>elements.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p><bold>Domain structure and PBS usage of LTR families</bold>. this file provides the information to relate the LTR families with their protein domain structures and reverse transcription primer tRNAs.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p><bold>Phylogeny of Copia- and Gypsy-like LTR families</bold>. this file contains the phylogenetic analysis of Copia and Gypsy superfamilies.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p><bold>Phylogenetic position of Mtr81</bold>. the RT sequence of Mtr81 do not belongs to Copia or Gypsy superfamily. It is placed as a third branch the phylogenetic tree.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p><bold>Insertion dates of 8 abundant LTR families</bold>. this file contains a figure showing the distribution of the insertion time of 8 abundant LTR families.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>^{<italic>a </italic>}This table only shows the organization of GAG, IN and RT. See S3.1 for more information.</p><p>^{<italic>b </italic>}These elements are classified by RT similarity.</p><p>^{<italic>c </italic>}ORFs inside the three families share week similarity with some putative GAG proteins in UniProt.</p><p>^{<italic>d </italic>}This RT is from Mtr81 but can not be assigned to either superfamily.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2164-9-382-1\"/>", "<graphic xlink:href=\"1471-2164-9-382-2\"/>", "<graphic xlink:href=\"1471-2164-9-382-3\"/>", "<graphic xlink:href=\"1471-2164-9-382-4\"/>" ]

[ "<media xlink:href=\"1471-2164-9-382-S1.txt\" mimetype=\"text\" mime-subtype=\"plain\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-382-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-382-S3.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-382-S4.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-382-S5.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-382-S6.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Most common diseases have an etiology so complex that years of research have yielded scarce results towards the elucidation of their causes. Technology and methodology are improving quickly but results have been arriving slowly. Nonetheless, optimism is in the air, because large studies of many individuals and genetic markers seem to finally be revealing some of the genetic factors behind these common diseases [##REF##17495150##1##].</p>", "<p>The difficulty of elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Many factors, both genetic and environmental, each with possibly only a small effect, may be necessary for the expression of a particular disease phenotype. For example, most associations reported in the recent wave of genome-wide association studies of different common diseases exhibited small (1.1–1.4) to moderate (1.5–2) odds ratios [##REF##17554300##2##].</p>", "<p>These small effects may only be detectable by means of genetic association analysis in very large samples, or in smaller sub-samples in which, by sample selection, this effect is enlarged: a sub-sample where the allele frequency of a particular risk gene is increased; or a sub-sample where a combination of other alleles or environmental factors act to increase the observable effect of a particular gene [##REF##8346443##3##].</p>", "<p>Many genes may contribute to the expression of complex diseases. It is quite reasonable to expect that the effects of some of these genes do not sum up in a simple fashion. Epistasis generally refers to an interaction between the effects of genes at different loci, although the term has been used in different contexts by different disciplines [##REF##12351582##4##]. Some of these genetic effects may interact among them, such that the presence of two or more particular genes may increase the risk to a disease more than expected from their independent effects, the expectation being derived from a pre-defined model, such as additive or multiplicative. For example, the odds ratio for an epistatic effect of two genes may be larger, even much larger, than the combined effect (sum or product) of each of the two single genes [##REF##15793588##5##,##REF##12951571##6##]. Moreover, there are biological models of epistasis where genes only have epistatic effects [##REF##10899752##7##], such as a two-locus mutation masking a known phenotype. Some of these genetic effects may prove undetectable by current single-locus methodology [##REF##17605173##8##]. There have been some early attempts to search for epistatic effects [##REF##15793588##5##,##REF##17701901##9##, ####REF##11404819##10##, ##REF##17721534##11####17721534##11##], but there is currently a need for methods to study this important genetic phenomenon, perhaps key for complex diseases.</p>", "<p>A wealth of current research in molecular genetics has discovered millions of genetic markers which provide a good coverage of common genetic variation across the entire human genome [##REF##16255080##12##]. At the same time, advances in genotyping technology have greatly increased the quantity and quality of genotypes. Current genotyping platforms can generate millions of genotypes in short periods of time. These events have made possible the genetic association analysis of a trait across the entire genome.</p>", "<p>Although the arrival of genome-wide association testing is great news for the genetic dissection of complex traits, the large number of statistical tests involved raises the issue of statistical significance. For example, to maintain a Type I error of 5 percent when testing 100,000 markers for genetic association may require a test-statistic with a probability value of 5 × 10^-7, if a Bonferroni correction is applied. Nonetheless, many of these markers are correlated so this correction would be too strict, but in any case the required p-value would be very small.</p>", "<p>This problem of multiple testing is even more extreme for the test of epistasis. For example, for 100,000 markers, there are a total of 5 × 10⁺⁹two-locus combinations, which would require a Bonferroni-corrected p-value of 1 × 10^-11for a genome-wide significance level of 0.05, which again would be overly conservative due to the correlated nature of many of these tests. To achieve these significance levels it is necessary to study large samples and expect to find large epistatic effects.</p>", "<p>Replication of findings in independent samples is sought for growing confidence in statistical results. The lack of replication of association results may be due to different causes, some technical (low power due to small samples, bad quality of phenotypic or genotypic data, uncorrected noise or covariates) and some biological (heterogeneity of effects or population-specific risks). An approach to tackle the multiple testing issue is to divide the available sample into independent groups and to carry out the analysis in these independent groups to look for consistent results across the groups. Some true genetic effects will be missed due to lack of power (due to the reduced sample in each group) and to heterogeneity, but this approach may allow the identification of moderate/large-sized epistatic effects that are frequent and consistent.</p>", "<p>In this scenario, we have developed an analysis tool to search for genome-wide epistasis in a case-control design. Hypothesis Free Clinical Cloning (HFCC) is an standalone software which allows for single-locus genetic association testing, as well as epistasis testing for multi-locus combinations of markers. Due to the intense computational burden, it is programmed to take advantage of computer clusters by dividing the tasks into processes which can migrate to the available CPUs. We present here the method, as well as a genome-wide two-locus epistatic analysis performed on a real dataset of Parkinson's disease that illustrates the method. With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses.</p>" ]

[ "<title>Methods</title>", "<title>Input Data</title>", "<title>Sample</title>", "<p>The standard input to HFCC is a case-control sample with hundreds or thousands of individuals. Similarly to other association methods, it is convenient that cases and controls are matched for potentially important covariates like age, sex, ethnicity, geographical location, environmental factors, etc. Dichotomous phenotypes with a potential effect on the trait may be used as covariates in the analysis.</p>", "<p>If all cases have only one disease phenotype or trait, HFCC carries out a single-phenotype analysis. In the single-phenotype scenario, HFCC can analyze the full sample simultaneously for extra statistical power. In addition, we have developed a multi-group analysis strategy, explained in more detail in a later section, that allows the replication of consistent results, and it also aids the elimination of false positives results, a very attractive quality for genome-wide analysis of large number of genetic markers. For this single-phenotype multi-group analysis option, cases can be sub-divided into groups to allow for replication of consistent results across these groups. Controls can also be sub-divided into groups to eliminate spurious associations.</p>", "<p>Nonetheless, one of the strengths of HFCC is that it can analyze multiple phenotypes simultaneously. For this multiple-trait analysis, several groups of cases with different but related phenotypes are formed, each matched to its own control group. Indeed, the multi-group analysis strategy is especially convenient for the simultaneous analysis of several related diseases, or different symptoms of a syndrome, so that we can identify the genetic effects common to the different groups.</p>", "<title>Genotypes</title>", "<p>HFCC can currently analyze di-allelic markers such as single nucleotide polymorphisms (SNP), and it can also accommodate other dichotomous markers such as the presence or absence of a particular allele of a multi-allelic marker or of a haplotype. HFCC can analyze anything from small sets of candidate gene markers to genome-wide arrays of hundreds of thousands of markers.</p>", "<p>Markers can be filtered out before analysis if they have low call rate, low minor allele frequency, or if they fail a Hardy-Weinberg equilibrium test. Nonetheless, data analysis filters inherent in the software can eliminate, at least partly, these problematic markers.</p>", "<p>Currently, linkage disequilibrium (LD) among markers is ignored during the analysis, although it is useful for the validation and interpretation of results.</p>", "<title>Datasets</title>", "<p>To illustrate the method we used data from the SNP Resource at the NINDS Human Genetics Resource Center DNA and Cell Line Repository <ext-link ext-link-type=\"uri\" xlink:href=\"http://ccr.coriell.org/ninds/\"/>. The original genotyping was performed in the laboratory of Drs. Singleton and Hardy (NIA, LNG), Bethesda, MD USA [##REF##17052657##13##]. We have used data on 270 patients with Parkinson's disease and 271 normal control individuals who were genotyped for 396,591 SNPs in all 22 autosomal chromosomes using the Illumina Infinium I and Infinium II assays. Cases were all unrelated white individuals with idiopathic Parkinson's disease and age of onset between 55–84 years (except for 3 young-onset individuals). The control sample was composed of neurologically normal, unrelated, white individuals from the USA.</p>", "<p>To explore the power of HFCC we also analyzed a simulated dataset that was originally generated to evaluate the power of a different gene-gene interaction method [##REF##12548676##14##]. These case-control data were simulated under different genetic models, and different sources of noise (genotyping error, missing data, phenocopy and genetic heterogeneity). For each genetic model and noise condition, 100 datasets were generated. Each dataset contains 200 cases and 200 controls, with genotypes for 10 SNPs under HWE. An epistatic effect with no single-locus marginal effect was simulated for a pair of SNPs, and the remaining 8 SNPs were simulated under the null hypothesis of no genetic effect. For the genetic heterogeneity case, two epistatic effects (each due to a different pair of SNPs) were simulated. More detail of these simulated datasets can be found in the original publication [##REF##12548676##14##].</p>", "<title>HFCC Modelling</title>", "<title>Statistical tests</title>", "<title>Single-Locus Association tests</title>", "<p>HFCC can perform a single-locus genome-wide association scan. A di-allelic marker with alleles A and B, has 3 possible genotypes: AA, AB and BB. For each genetic marker, HFCC performs three statistical tests, comparing each genotype against the other two. For example, the frequency of the AA genotype is compared against the combined frequency of the AB-BB genotypes, in cases and controls. This could be considered a dominance model test for the B allele. Similarly, recessive (BB versus AA-AB) and heterozygote models (AB versus AA-BB) are also considered. The test for association between the established genotypic classes and the case-control groups can be a Wald test or a chi-squared test with one degree of freedom (df).</p>", "<title>Multi-Locus and Epistatic Association tests</title>", "<p>HFCC can also perform a multi-locus genome-wide association scan. For a two-locus scan, HFCC first forms all possible combinations of two markers from all available markers. For each two-marker combination (marker 1 with alleles A and B, and marker 2 with alleles C and D), there are 9 possible genotypic classes (AACC, AACD, AADD, ABCC, ...., BBDD), and a total of 512 fully penetrant disease models [##REF##10899752##7##]. For our purpose, this number of models can be reduced to 255, because some models are redundant or represent a model with no genetic effect. These 255 models include a variety of standard models (single-locus, double-recessive, double-heterozygote, etc.) as well as other rare models. The user can select to test all available models or a subset of them.</p>", "<p>As in the single-locus case, the statistical test involves comparing the frequency of two sets of genotypic classes in cases versus controls. The two sets of genotypic classes are defined by the model being tested. For example, in the case of the double-recessive model, the frequency of the BBDD genotypic class is compared against the combined frequency of all other genotypes (AACC through BBCD), in cases and controls, from which a Wald-test Z statistic, or a chi-squared statistic with one degree of freedom, can be obtained.</p>", "<p>Another analysis option is a more general multi-locus test [##REF##12951571##6##] which compares two chi-squared statistics with four degrees of freedom (one obtained for cases and the other one for controls). This test, although more general, may not be able to detect some disease models.</p>", "<p>For a three-locus scan, there are 27 possible genotypic classes, and the software is currently implemented to test the 27 simplest 3-locus genetic models, comparing the frequency of a genotypic class (ie, AACCEE) against the combined frequency of all other genotypes.</p>", "<title>Post-Hoc tests</title>", "<p>A variety of post-hoc statistical tests are included in the post-hoc analysis software, named Alambique. For single-locus analysis, it is possible to carry out Hardy-Weinberg equilibrium, heterozygous, homozygous, allele positivity (dominance), recessive, common odds ratio (Armitage's trend) [##REF##9423247##15##], and genotypic (2 degrees of freedom) tests.</p>", "<p>For the two-locus analysis, all 255 fully-penetrant models can be tested. Moreover, interaction indices can be estimated to determine to which extent an observed two-locus association deviates from an additive model [##REF##1391139##16##]. Finally, departures from a multiplicative model can be tested using a case-only chi-squared test [##REF##10069253##17##].</p>", "<p>These post-hoc analyses are useful to determine which genetic model explains better an observed association, and to measure the epistatic component of associated multi-locus combinations.</p>", "<title>Grouping</title>", "<title>Replication (Case versus control) groups</title>", "<p>The statistical tests for association of a trait with a marker are based on the differential frequency between cases and controls of a particular allelic or genotypic combination. Comparing the full sample of cases versus the full sample of controls is the most powerful approach to find statistically significant associations. Nonetheless, to evaluate genomewide association or epistasis we need to test a very large number of markers or marker combinations, which in turn can produce a large number of spurious results. Therefore, we need to improve the filtering of false-positive results, at the expense of increasing the false-negative findings.</p>", "<p>We have approached this multiple-testing issue by partitioning the available sample into multiple replication groups. Cases are selected randomly to be part of one and only one case group, and similarly for control individuals and control groups. Then, the statistical analysis is performed on each of the paired case-control groups, and results that are consistent across all replication groups are selected. This sample-splitting technique may prove less powerful to detect positive results in general, but provides a powerful tool to eliminate false positives, thereby highlighting potentially true effects that are consistent across samples. The number of groups into which the sample is partitioned can be chosen by the user depending on the study design, and the number of subjects and markers available for analysis.</p>", "<p>This multi-group strategy is one of the differentiating aspects between HFCC and conventional association methods, and it is particularly useful for the analysis of multiple related phenotypes. Case groups are directly defined by phenotypic criteria, and control groups are matched to each case group. This type of analysis can reveal genetic associations that are common to these phenotypes, revealing a common etiology for multiple symptoms of a disease, or for several related diseases [##REF##14962646##18##].</p>", "<title>Control filter (Control versus control) groups</title>", "<p>HFCC has developed an efficient noise filter, by applying the association tests to independent groups of controls. Positive results that arise from a comparison of two groups of controls must be spurious associations due to marker or sample characteristics. These spurious associations can be filtered out of the results from the case-control analysis, providing an efficient sample-specific background noise filter.</p>", "<title>Algorithm and program execution</title>", "<p>HFCC requires specific data and parameter files. The input data file is a simple-text matrix of integers in which rows represent genetic markers and columns represent individuals. Each integer represents the genotype for one individual at one marker, coded as 0 for missing, 1 for one homozygote, 2 for the heterozygote, and 3 for the other homozygote. These integers are entered sequentially, with no blank spaces or lines, to save space. There is one data matrix for each group of cases (F1.txt, F2.txt, etc.), controls (C1.txt, C2.txt, etc) and noise-filter controls (CF1.txt, CF2.txt, etc.), as can be seen in Figure ##FIG##0##1##. A parameter data file defines the type of analysis (single- or multi-locus; genetic model; test statistic), number of genetic markers, number of groups, sample size per group, statistical cut-off for significance, and other necessary parameters.</p>", "<p>The following algorithm describes HFCC analysis flow (Figure ##FIG##0##1##). Genetic markers are analyzed sequentially in the order in which they are entered in the data matrices. First, HFCC selects a marker variable (either a single-locus marker or a multi-locus combination of markers, depending on the type of analysis). Then, for the selected analysis model, it computes genotype frequencies and test statistics in each replication group, sequentially. If the test statistic is smaller than a pre-defined cut-off in any of the replication groups, the marker variable is dropped at that stage and no more computations are performed on this marker variable to save processing time. If the test statistic is larger than the cut-off in all replication groups, then the marker variable is written to the output file and also entered in the control noise filter. This noise reduction analysis computes frequencies and test statistics in each control filter (control versus control) group sequentially. If the test statistic is larger than a pre-defined cut-off in any of the filter groups, the marker variable is flagged for removal from the final output file. The marker can fail at any of the sequential group analyses (replication or control filter group comparisons), at which point that marker is dropped to save processing time. This procedure is repeated for all possible marker variables, writing to the output file all associations considered statistically significant. This output file contains the marker (or marker combination) and the genetic model for which it yielded a positive association (ie, for a two-locus combination: marker 1, genotypic class 1, marker 2, genotypic class 2).</p>", "<p>These selected marker variables can then be included in two sequential post-hoc analyses which aid in the interpretation of the results. The first post-hoc analysis yields odds ratios and chi-squared values for all selected marker variables. It also applies a direction filter, by selecting only those results which display the same direction of effect in all replication groups, and writes a new output file, which contains only those marker variables with a significant and consistent effect (same direction and same model) in all replication groups.</p>", "<p>The second post-hoc analysis (Alambique) identifies the best type of genetic model for each association selected in the first post-hoc analysis. For this reason, all replication groups are combined into a single group, that is, all cases in one case group and all controls in a control group. Alambique has its own noise elimination algorithm, denominated tracking filter. Many of the selected associations are due to what we call a tracking marker, a locus with a very large marginal effect. Many of these tracking markers are not in HWE and are filtered at this stage. In any case, having a large marginal effect makes a locus appear in many two-locus associations, because the large effect tracks other loci. Because our focus is on finding epistatic interactions, the many positive associations due to these tracking effects can be filtered out and analyzed independently. For the remaining marker variables, which have passed this tracking filter, there is one analysis option that groups the two-locus results into those with marginal effects for only one locus (conditional effect), or for both loci (simultaneous effect) or those without marginal effects (epistatic effect) [##REF##16776843##19##]. Some of the conditional and simultaneous results may still exhibit epistatic effects if the two-locus effect size deviates from an additive or multiplicative expectation, and these epistatic effects can also be flagged. A second analysis option tests all 255 fully-penetrant models in selected marker variables, to help choosing the model that best fit the data.</p>", "<p>Due to the extremely time-consuming and computer-intensive nature of these analyses, especially for genomewide multi-locus analysis, it will often be necessary to run HFCC under a small selection of genetic models, and then use Alambique to identify the best genetic model for the selected markers. The number and selection of genetic models to analyze will depend on the phenotype, the dataset, previous knowledge and computer resources available.</p>" ]

[ "<title>Results</title>", "<p>We have applied HFCC to both simulated and real datasets to illustrate the power and the functioning of the method.</p>", "<title>Simulated data analysis</title>", "<p>To evaluate the power of the method, we analyzed a simulated dataset published previously [##REF##12548676##14##]. Data were simulated under three types of two-locus epistasis models: Model 1 was a logical XOR model, a combination of exactly one heterozygous and one homozygous loci (i.e., for two markers with alleles A, B and C, D respectively, risk genotypes would be ABCC, ABDD, AACD and BBCD), similar to M170 [##REF##10899752##7##] but with variable penetrances; Model 2 involved the inheritance of exactly two, and only two, risk alleles (i.e., A and C) from any of two different loci (i.e., risk genotypes would be AADD, ABCD, and BBCC), such as M84 [##REF##10899752##7##]; Model 3 was a variable penetrance risk model with a protective double-heterozygote (i.e., protective genotype would be ABCD), similar to M16 [##REF##10899752##7##]. In addition, to make the simulated data more similar to real data, and therefore to evaluate the effect of noise in the detection of these epistatic effects, different sources of noise were modeled in the simulations. For each of the three types of genetic models described above, the data was simulated and analyzed under six types of noise: without noise, with 5% genotyping error (GE), with 5% missing data (MS), with 50% phenocopy (PC), with 50% genetic heterogeneity (GH), and with all sources of noise simultaneously. For more information on these simulated datasets please refer to the original publication [##REF##12548676##14##]. Power was defined as the proportion of times the correct model was detected out of each set of 100 simulations. For genetic heterogeneity the correct model was defined as detection of either one of the two epistatic loci simulated.</p>", "<p>To detect potential epistatic loci, we ran HFCC two-locus analysis with nine simple genetic models, the M1, M2 and M16 models [##REF##10899752##7##]. There are a total of 45 possible two-locus combinations that can be formed with the 10 simulated genetic markers. Due to this relatively small number of tests (relative to a genome-wide study), HFCC was performed with only one group of cases and controls, and a chi-square cut-off of 6.64 (approximately a p-value = 0.01 with 1 degree of freedom). Using only one case-control group allows also for direct comparison of HFCC's power to the power estimates published previously for this dataset. Results from the SNPs simulated under the null hypothesis reveal fewer Type I errors than expected, confirming that the method is not biased and perhaps conservative. This reduced number of false positives may reflect that some of the epistasis tests used were correlated, as well as a general lack of power to detect some epistatic effects, especially for rare genotypes.</p>", "<p>HFCC had excellent power (&gt;96%), with a Type I error of 0.01, to detect the simulated two-locus interactions under most genetic models and noise conditions, including genotyping error and missing data (See Table ##TAB##0##1##). Genetic heterogeneity reduced the power to 82% under model 3, and the presence of phenocopies had also a significant impact on power for models 1, and especially, 3. Finally, if all four sources of noise were acting simultaneously the power was reduced to 51% for model 1, 71% for model 2, and 34% to model 3.</p>", "<title>Parkinson's disease analysis</title>", "<p>To demonstrate the HFCC software in real data we analyzed the open-access Parkinson's dataset described in the Methods section. We included all 396,591 SNP markers. Many of them had low minor allele frequencies or failed Hardy-Weinberg equilibrium (HWE), but were included in order to test the data filters inherent in HFCC, which are meant to eliminate, at least partially, these problematic markers.</p>", "<p>The 270 cases and 271 controls were separated into groups, to illustrate HFCC multi-group analysis strategy. We created 3 replication groups of 90 cases each (groups F in Figure ##FIG##0##1##) and 3 groups of controls of approximately similar size (C in Figure ##FIG##0##1##; one group with 91 individuals and two groups of 90 individuals). Because of the lack of more control individuals, the noise filter control groups (CF in Figure ##FIG##0##1##) were selected respectively from each of the control groups, chosen so that the noise filter would not pair two identical control groups (ie, CF1 = C3; CF2 = C1; and CF3 = C2). Ideally, independent groups of C and CF controls would be used, so we expected that the noise filter in this experiment, in which the same groups of controls were used as C and CF, would not be as effective.</p>", "<p>To detect potential epistatic loci, we ran HFCC two-locus analysis with nine simple genetic models, the M1, M2 and M16 models [##REF##10899752##7##]. These nine genetic models were tested in all possible (78.6 × 10⁺⁹) two-locus marker combinations. In order to be considered a preliminary positive result, the chi-squared (1 df) cut-off value was set at 6.64, which yields a probability value of 0.01 for each replication group (p &lt; 10^-6over all three replication groups). Although this p-value may be considered low compared to the number of statistical tests performed, this is only a cut-off to select preliminary positive results, which are then filtered and subjected to post-hoc analysis to select the most promising results. We obtained a total of 418,535 preliminary two-locus associations at this p-value cut-off (Table ##TAB##1##2##). To evaluate the impact of the different noise filters (control, direction and tracking) we applied them selectively to these preliminary results.</p>", "<title>Noise filters (control, direction, tracking)</title>", "<title>Direction filter</title>", "<p>When the control filter is not used, the direction filter has a large impact on the number of results selected. Of the 418,535 preliminary associations, only 76.5 % (320,265) had effects in the same direction in all replication groups. These results can then be grouped into those with marginal effects in both loci (simultaneous), only one marginal effect (conditional), and no marginal effect (epistatic). A marginal effect was defined as a single-locus effect with a chi-squared (1 df) statistic larger than 3.84 (p-value &lt; .05). This liberal cut-off serves our goal of selecting as pure epistatic effects those marker combinations with no or small marginal effects. Under these criteria, 22.3% (71,332) of the results had simultaneous marginal effects, 77.7% (248,898) had conditional effects, and only 0.01% (35) had epistatic effects. At this point, out of the hundreds of thousands of preliminary results, only 35 two-locus associations without marginal effects remained, very likely to be epistatic interactions. The many thousand simultaneous and conditional results may also involve epistatic effects on top of the marginal effects, but the large number of them prevents a thorough post-hoc analysis.</p>", "<title>Direction and Tracking filters</title>", "<p>In order to distil further the post-direction-filter results we can apply the tracking filter. Many of these two-locus associations are due to what we have denominated tracking loci, that is, markers with large marginal effects, which therefore display significant two-locus effects with many other markers. Most of these tracking markers exhibit large association effects because they fail HWE, and they are filtered out at this stage. In this Parkinson dataset we detected 36 tracking markers, defined as those markers showing up in 270 or more two-locus associations (top 0.1% of post-direction-filter results). Most of these tracking markers (83.3%) failed HWE (p &lt; 0.001 in controls or &lt;0.0001 in cases), and others failed minor allele frequency (MAF&lt;0.1) or call rate (CR&lt;90%) criteria. Therefore, results involving these markers can be safely excluded.</p>", "<p>A few of these tracking markers represent the best single-locus association results which, due to their large marginal effects, also appear in a large number of two-locus association results. These large-single-locus-effect tracking markers need their own specific post-hoc analysis. Because of their large marginal effects, these markers are likely identifiable by single-locus analysis, but it is still noteworthy to discover if they have epistatic effects, and with which genes. However, it is hard to identify a significant epistatic interaction in the background of such a large marginal effect. Individual post-hoc analysis for each of these markers may identify the most likely multi-locus combination involving those marker.</p>", "<p>Interestingly, by filtering out the marker combinations involving the tracking markers, we can eliminate 91.8% of the previous positive results. Most of these results were conditional effects, involving the tracking locus (with a large single-locus effect) and a tracked locus (with no main effect, but tracked by the large effect in the other locus). The post-tracking-filter results include a total of 35 marker variables with epistatic effects, 6,706 with conditional effects, and 19,630 with simultaneous effects.</p>", "<title>Control, Direction and Tracking filters</title>", "<p>We can repeat this data filtering process, but this time starting by applying the control noise filter. The control filter was set to employ the same statistical cut-off (chi-squared = 6.64) used in the case-control comparisons. Association results above this cut-off value obtained in analysis of two control groups can be deemed problematic and excluded from further analysis. This control filter was able to eliminate 18.75% of the preliminary results, leaving a total of 340,043 associations (81.25%). Applying the direction filter to the post-control-filter results eliminates only a further 5.84% of preliminary results, yielding a total of 320,188 associations, almost exactly the same quantity as when the direction filter was used alone. Therefore, the control and direction filters seem to eliminate most of the same results, which reassures their correct functioning and also allow for different analysis strategies. On one hand, when enough control subjects are not available and consequently the control filter can not be used, these results suggest that the direction filter may work well alone. On the other hand, the direction filter may not be useful for some multiple-phenotype studies, expecting effects on different directions in different replication groups. Thus, in some scenarios, the control and tracking filters may provide enough noise elimination by themselves.</p>", "<p>When the tracking filter was applied to the results selected by the control and direction filters, we obtained 35 two-locus combinations with epistatic effects, 6,701 with conditional effects, and 19,611 with simultaneous effects. By applying three consecutive data filters (control, direction and tracking), we excluded almost 94% of the preliminary results. The remaining 6.3% of results are subsequently analyzed for departures of additive or multiplicative two-locus models, to estimate their potential for epistatic effects.</p>", "<title>Epistatic interaction indices</title>", "<p>HFCC analysis yielded 35 two-locus combinations with epistatic effects and no noticeable single-locus marginal effects, ten of which are displayed in Table ##TAB##2##3##. In addition, there are 26,312 conditional or simultaneous two-locus combinations, which may display interaction effects over and above the marginal effects. There are a variety of tests and indices to detect departures from additive or multiplicative models. For example, a case-only chi-squared test can detect two-locus interactions which deviate from a multiplicative model. For the present study, this case-only statistic was used to choose, among the conditional and simultaneous marker variables, those with the most significant interactions (Table ##TAB##2##3##). In addition, marker quality control criteria were checked to assure all markers in selected combinations passed a minimum requirement (HWE p-value &gt; 0.001 in controls and &gt;0.0001 in cases; MAF&gt;0.1; call rate&gt;90%).</p>", "<title>Validation analysis</title>", "<p>In order to validate to some extent these results, and without immediate access to a truly independent sample, we created 10 validation samples by randomly re-creating the case groups (F) from the full pool of cases (N = 270), and similarly for the control groups (C). In the described analysis of the Parkinson dataset, three replication groups were created randomly, to find consistent results across these groups. To examine the possible effect of this random group membership, the replication groups were re-created randomly and reanalysed in what we called validation experiments. These validation experiments are not permutation simulations to estimate the empirical significance level of parameter estimates, and are not a standard bootstrapping technique because they use sampling without replacement. The replication groups in each validation analysis were re-created under association (keeping cases as cases and controls as controls), and not under the null hypothesis of no association. These validation experiments are used to examine the consistency of results when the replication groups are re-created.</p>", "<p>The control noise filter was not employed for these validations analyses to save computing time, since it was found that for this dataset the direction and tracking filters alone were sufficiently efficient. Because we are using the same set of cases and controls in all the validation groups, a high degree of consistency of results across validations analyses would be expected a priori. Nonetheless, due to the small sample size of each group, the many requirements for the selection of marker variables, such as the consistency of strength and direction of result in three replication groups, and the subjective categorization (single-locus X²&gt; 3.84) of results into different types of effects (epistatic, conditional and simultaneous), a large variability in results across validation analyses is reasonable.</p>", "<p>The total number of preliminary results varies noticeably across validation groups (Table ##TAB##3##4##). This variability illustrates the randomness inherent in this type of analysis. The total number of two-locus combinations selected as simultaneous or conditional are much more consistent. Nonetheless, the number of epistatic effects is quite variable again, perhaps a consequence of the small number of marker combinations selected under this category.</p>", "<p>In addition to the variability in the number of results, it is important to note the general lack of consistent results across validation groups. The simultaneous effects were the most consistent type of result. One two-locus combination (rs7653784 rs499091) showed up in the original analysis and the 10 validation samples. Five other combinations with simultaneous effects were consistent in 10 out of the 11 samples, and 28 combinations were consistent in 9 samples. Of the conditional results, thirteen marker combinations were consistent in 8 samples. Perhaps because their effect is harder to replicate, only one epistatic marker combination was present in as much as 5 samples, while 2 combinations were present in 4 samples, and three combinations in three samples.</p>" ]

[ "<title>Discussion</title>", "<p>HFCC is a new computer software for exhaustive genome-wide analysis of multi-locus association effects in a case-control design. It carries out different types of statistical tests to assess a variety of genetic and epistatic models. HFCC differs from other association or multi-locus methods in that it can analyze simultaneously multiple samples or multiple phenotypes, and incorporates several complementary noise-signal filters, and also post-hoc analysis tools. To address the enormous computing task, it is elegantly designed to take advantage of the multiple CPUs available nowadays in computer servers or clusters.</p>", "<p>The goal of HFCC analysis is to find multi-locus marker combinations which are significantly associated with a phenotype, especially those displaying interaction effects which may not be detected in a single-locus analysis. By setting the type of genetic model, the number of subjects in each group, the number of replication groups, the statistical cut-offs for the different tests, and applying different noise elimination filters, HFCC can arrive at a selection of the most promising multi-locus combinations.</p>", "<p>Other multi-locus methods to detect gene-gene interactions exist. For example MDR [##REF##11404819##10##] is a method for exhaustive search of high-level multi-locus interactions, although it is extremely computationally intensive, and genome-wide searches for epistasis are prohibitive. More recently a promising Bayesian method (BEAM) has been suggested as a powerful alternative for detecting epistatic interactions, although it is not exhaustive and still requires further improvements to effectively handle the large SNP datasets commonly used in genome-wide studies [##REF##17721534##11##]. Other methods, like PLINK [##REF##17701901##9##] or others based on logistic regression [##REF##15793588##5##], can carry out genome-wide epistasis tests relatively quick, but are currently limited to two- or three-locus models, and only perform general tests of epistasis. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. Our analysis of a simulated dataset reveals that HFCC has good power, at least as good as or better than MDR [##REF##17654613##20##], to detect epistatic interactions, as long as they are relatively strong and common. In the most extreme simulation, with 5% genotyping error, 5% missing data, 50% phenocopies, and 50% genetic heterogeneity, HFCC still had 71% power to detect some types of epistasis, although the power for other types of epistasis was smaller (34–51%). We will need to carry out more extensive simulations to evaluate the power under different conditions and genetic models.</p>", "<p>For this illustrative application of the software we have also analyzed an open-access dataset of Parkinson's disease patients and unaffected controls. We would like to emphasize here the importance of these public datasets of real data to improve the quality of applied research, and also to foster the development of new methodology.</p>", "<p>One of the pecularities of HFCC is the possibility of dividing the case-control sample into replication groups, to detect only those effects that are consistent across samples. The number of replication case-control groups to be used depends on the available dataset (sample size and number of genetic markers). It is an important analysis parameter because the overall significance level is a function of the selected critical value for the test statistic and the number of replication groups. For the current analysis, the sample of cases was divided into three replication groups, and so were the controls. This strategy focuses on the detection of large and consistent effects, which are hopefully detectable with the available datasets. It is reasonable to expect that the joint effect of a combination of genes is larger and more penetrant than each of the single-locus effects, and therefore under some circumstances (i.e., not extremely heterogeneous or rare effect), these multi-locus effects can be identified. The detection of small, rare or heterogeneous effects may need larger samples and more complex models.</p>", "<p>HFCC allows for a variety of different genetic models and tests. Different models may be necessary to detect different types of effects, such as recessive, dominant or heterozygote effects. The best analysis strategy may depend on prior knowledge or hypothesis about the trait. An optimal strategy would apply a selected subset of models which would maximize the chances of detecting a hypothesized effect. For example, for this Parkinson's disease study, we have employed a subset of nine epistatic models which typically detects recessive effects.</p>", "<p>Another characteristic of HFCC analysis is the successive application of noise-signal filters. Control groups can be compared against each other to remove background noise associations. Direction of effect can be taken into account, so that only those results consistent in strength and direction across replication samples are selected. A final filter is able to remove those multi-locus results which are primarily due to quality-control failing markers (ie, in Hardy-Weinberg disequilibrium, low allele frequency or low call rate) or to large single-locus effects. The remaining multi-locus combinations can be categorized into epistatic, conditional and simultaneous effects, and interaction tests can be used to detect possible epistatic interactions over and above the marginal effects. The selected markers can then be included in a validation analysis in an independent sample. As an illustration, Table ##TAB##3##4## displays 30 two-locus combinations suggestive of displaying epistatic interactions influencing the development of Parkinson's disease. It is important to note that due to the small sample size used in this experiment, these results may not be reliable, and need re-analysis or confirmation in larger datasets. The number of combinations selected for a validation analysis depends on many factors, and tools are included to help perform this selection.</p>", "<p>The Parkinson's disease study reported here can illustrate several issues regarding the search for epistatic effects in large datasets. One of the most difficult tasks in large dataset analysis is selecting the most promising candidate results. The huge number of statistical tests performed requires a severe statistical cut-off, or a protocol of data filtering, to be able to select only the most promising results. For example, the two-locus analysis of a genome-wide association SNP dataset presented here reveals several hundred thousands two-locus marker combinations at a liberal significance level (i.e., p value &lt; 10^-6). Using a stringer significance level, such as a Bonferroni correction, may be overly conservative, sometimes potentially missing real effects. HFCC filters and post-hoc analyses help selecting the most promising two-locus interactions from a large set of preliminary findings. For example, all two-marker combinations in Table ##TAB##3##4## are consistently associated with Parkison's disease in three replication groups (overall two-locus X²(1 df) in the range 21–30), and they all also deviate from a multiplicative model (case-only X²(1 df) in the range 7–33) suggesting an epistatic interaction.</p>", "<p>The resampling validation analysis raises an important issue regarding the difficulty in replicating a result across different validation samples, a finding that may reflect the general lack of power to detect these types of effects, especially in the presence of heterogeneity. With the available sample size for this study we have approximately 80% power to detect large common effects (Odds ratio &gt; 3 in a genotype prevalence &gt; 25%) at a significance level of 0.01 per replication group. However, this small dataset is underpowered to find more moderate, and perhaps more realistic, effect sizes. The general lack of consistency suggested by our own sensitivity analysis may be a consequence of the small sample size analyzed. Fung et al. (2006) claimed that there is no common genetic variant that exerts a large genetic risk for late-onset Parkinson's disease in white North Americans. Multi-locus analysis may, however, reveal the existence of large complex (multi-locus) genetic effects.</p>", "<title>Analysis Guidelines</title>", "<p>HFCC provides a tool for the genome-wide study of epistasis. Its use may depend heavily on the researcher's goals and the data available. For this reason, it is hard to provide general guidelines on the optimal parameters for analysis, but HFCC's flexibility to accommodate to the specific needs of each study is a great asset.</p>", "<p>A key parameter is the number of replication groups. When the available sample size is fixed, dividing the sample into more replication groups decreases the power of the analysis, but also increases the confidence in the remaining results. For example, the two-locus analysis of the full Parkinson's dataset in one case-control group with a Type I error set at 10^-6yields a total of 784,506 preliminary positive results. The analysis of the same data splitted in three replication groups, each with alpha = 10^-2, yields only 418,535 results (53% of the single-group results).</p>", "<p>There is not an optimal number of replication groups. Researchers need to select this parameter as well as the significance level cut-off to fit their dataset and study design. For example, a study of three related diseases or phenotypes suggests the use of three replication groups. In the case of a single disease, the number of replication groups, the sample size in each group, and the statistical cut-off should be chosen depending on the nature of the study. A strict statistical correction may be necessary if the results are to be conclusive, while a more relaxed criterion may be used in a two-stage study where the goal of the preliminary analysis is to select a subset of markers for subsequent validation.</p>", "<p>HFCC's flexibility is also possible in the application of data filters. The results displayed in Table ##TAB##1##2## suggest that the control filter and the direction filter can eliminate most of the same noise results. The application of either or both of these filters can therefore depend on the study design. If a study has many control subjects and a limited number of cases, it can benefit from using the control filter. If a study has many affected individuals, then several replication groups and the direction filter can be used.</p>", "<p>There are also 255 possible two-marker genetic models that can be tested. Many of them are correlated, so it is probably not necessary to test them all. We suggest using a small subsample of models that cover the researcher's hypothesis. For example, for the Parkinson's analysis in this paper we tested nine simple genetic models. To identify subsamples of models that may optimize the chances of discovering epistatic effects of different nature would need a thorough simulation analysis that is beyond the scope of the current paper. Another analysis option is to use more general tests of epistasis, which are also implemented in the software.</p>", "<title>Statistical Issues</title>", "<p>The two-locus analysis of the full Parkinson's dataset as presented here comprises a total of 708 × 10⁹statistical tests. The two-locus analysis of these data in one case-control group with a Type I error set at 10^-6yields a total of 784,506 preliminary positive results, about 10% more of those expected by chance. This false positive inflation is probably due to the tracking markers (mainly QC-fail markers) as well as to the correlated nature of some of the statistical tests, and can be controlled by the use of replication groups, or by applying more stringent cut-offs if necessary.</p>", "<p>For the simulated dataset, analyzed with only one case-control group a significance level of 10^-2(chi-square 6.64), the Type I error was actually lower than expected (approximately around 0.006 on average). These results demonstrate that HFCC analysis is not only powerful but can also be conservative, preserving against Types I and II Errors. More thorough simulations to assess the impact of sample size, allele frequency, number of replication groups, and noise filter applications are needed in the future to understand these issues in detail.</p>", "<p>Applying strict multiple testing correction (Bonferroni) to the Parkison's disease analysis, we do not find any significant two-locus interactions. The reason for this may be the small sample size available in the Parkinson's dataset. But we can still select the most promising two-locus results for subsequent validation. The key issue is whether we are concerned with achieving an absolute level of statistical significance, which may not be properly defined in this setting given the complexity of the analysis suggested (multiple testing of correlated hypotheses, independent replication of results, data filtering steps), or selecting the most promising markers or marker combinations that pass a more or less stringent statistical criterion. In either case, the usefulness of HFCC for selecting marker combinations for later validation is doubtless.</p>", "<title>Computational Issues</title>", "<p>Multi-locus analysis is computationally intensive and is therefore limited by computing capabilities. HFCC is a relatively fast algorithm considering the huge number of computations it performs. The dataset analyzed in this study consists of 396,591 genetic markers, which results in 78.6 × 10⁹two-locus marker combinations. Nine genetic models were tested in the current study, resulting in a total of 708 × 10⁹statistical tests. Moreover, these tests may be carried out in as many as three case-control replication groups, and also in as many as three control-control noise-filter groups, so the computing task is staggering. HFCC is programmed to take advantage of computer resources by dividing the computing task into processes which can migrate to the available CPUs in a computer server or cluster. For the current analysis, we employed a computer cluster consisting of twelve 3.2 GHz CPUs, which was able to carry out the full genome-wide analysis in approximately 5 days.</p>", "<p>Another computational complication for multi-locus analysis is related to RAM memory. The data matrices need to be loaded onto memory to speed computations, and therefore a limitation exists for the analysis of very large datasets (millions of genetic markers or several thousands of subjects) where RAM memory is rapidly exhausted. This limitation, however, can be solved with parallel processing techniques (MPI like), such as dividing the data matrices into smaller subsets which are distributed around the computer network.</p>", "<p>HFCC can perform more complex multi-locus analysis (3-locus, 4-locus, etc.), but the number of computations grows exponentially with the number of interacting markers, and the analysis becomes dependent on computing resources and time limitations. Depending on these resources, genome-wide three- or four-locus analysis may require a two-stage strategy, where some markers are selected first by single-locus analysis, and then employed to guide the multi-locus testing [##REF##16776843##19##]. Our exhaustive two-locus genome-wide analysis of a Parkinson's disease dataset reveals that pure epistatic effects, as defined here, are rare (0.01% of the preliminary results). Therefore, a two-stage strategy for multi-locus analysis may be a more economical analysis with minimal information loss. This statement assumes that we had power to detect these epistatic effects, that more complex interactions behave as two-locus ones, and that Parkinson's disease is representative of other diseases. Our results suggest the use of a conditional two-stage strategy, where a liberal single-locus threshold is first used to select loci with marginal effects, and then these markers are used against the full panel for multi-locus analysis. This conclusion is similar to some previous suggestions [##REF##15793588##5##,##REF##16776843##19##] but not all [##REF##17002500##21##], confirming that a liberal single-locus cut-off (i.e., p &lt; .05) greatly reduces the computational task while minimizing the probability of discarding potential epistatic loci.</p>", "<p>It is also important to note that linkage disequilibrium (LD) is unaccounted for in our analyses. LD reflects an association among markers and therefore can affect the results of some tests. For example, it can produce a significant case-only chi-squared test. Nonetheless, HFCC's algorithm and analysis filters seem to prevent this bias. In the case where one marker is associated with several markers in LD, these results are detected in the last stage of marker selection.</p>" ]

[ "<title>Conclusion</title>", "<p>In summary, we propose that genome-wide multi-locus analysis is performed on available datasets of common diseases, because they can exploit the large genetic datasets and computing resources becoming available, to open a new phase of genetic analysis. The analysis of Parkinson's disease reported here represents the first exhaustive genome-wide epistasis search on a real dataset, effectively handling hundred of thousands of genetic markers, and demonstrating its feasibility. Due to the small sample size, however, these results are only illustrative and require re-analysis or confirmation in larger datasets. These multi-locus analyses would not substitute conventional single-locus analysis but add a new layer of genome-wide association studies, allowing the identification of new candidate markers for further validation. HFCC is a new genome-wide multi-locus software, which allows the user a high degree of control over analysis parameters, so that data analysis can be tailored to the specific needs of each project. HFCC can have a great impact on the discovery of the genetic causes of common diseases, especially to identify those multi-locus effects that may not be detectable using the available single-locus methods. The discovery of new genes affecting a disease may be useful as predictive tools or to find new therapeutic targets. HFCC has multiple applications, not only in the study of disease phenotypes, but also of other qualitative traits, and can be used in clinical trials or pharmacogenetics studies.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology.</p>", "<title>Results</title>", "<p>We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC) to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. HFCC has good power to detect multi-locus interactions simulated under a variety of genetic models and noise conditions. Most importantly, HFCC can accomplish exhaustive genome-wide epistasis search with large datasets as demonstrated with a 400,000 SNP set typed on a cohort of Parkinson's disease patients and controls.</p>", "<title>Conclusion</title>", "<p>With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses.</p>" ]

[ "<title>Availability and requirements</title>", "<p>HFCC is written in C and freely available for linux platforms from this Website: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.neocodex.com/en/hfcc.0.5.zip\"/></p>", "<title>List of abbreviations</title>", "<p>CPU: central processing unit; GE: genotyping error; GH: genotyping heterogeneity; HFCC: hypothesis free clinical cloning; HWE: Hardy-Weinberg equilibrium; LD: linkage disequilibrium; MS: missing data; PC: phenocopy; SNP: single nucleotide polymorphism; XOR: logical exclusive \"or\" statement.</p>", "<title>Authors' contributions</title>", "<p>JG, AG–P, and AR conceived and designed the experiments. JG, AG–P and AR analyzed the data. JG and AR wrote the paper. AR conceived the analysis tool. All authors helped develop the analysis tool. FB and AQ wrote the analysis tool. All authors read and approved the final manuscript.</p>", "<title>Competing Interests</title>", "<p>As a declaration of competing financial interest, authors in the paper are employees and/or shareholders in Neocodex. Neocodex owns a patent on the HFCC algorithm described in this paper (WO 2008010195 20080124).</p>" ]

[ "<title>Acknowledgements</title>", "<p>This study used data from the SNP Resource at the NINDS Human Genetics Resource Center DNA and Cell Line Repository <ext-link ext-link-type=\"uri\" xlink:href=\"http://ccr.coriell.org/ninds/\"/>. We thank the participants and the submitters for depositing samples at the repository. This work was supported in part by Agencia IDEA, Consejería de Innovación, Ciencia y Empresa (830882); Corporación Tecnológica de Andalucía (07/124); and Ministerio de Educación y Ciencia (PCT-A41502790-2006 and PCT-010000-2006-1).</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>HFCC data groups and algorithm</bold>. HFCC data groups are divided into cases (F), controls (C) and control filter (CF). The number of replication groups is experiment-specific and depends on the available dataset (sample size and number of genetic markers). The HFCC algorithm is defined by a particular analysis flow. For each marker variable (single-locus markers, two-locus marker combinations, etc. depending on the type of study), a sequential number of tests is performed. Case-controls comparisons are performed on each replication group, and control-control comparisons are carried out in each control filter group. If any of these tests is not beyond a statistical threshold, the marker variable is dropped, and the next marker variable is analyzed. Marker variables over the statistical threshold in all case-control tests, and below the threshold in all control-control tests, are selected.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Power Analysis.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"3\">Power (%)</td></tr><tr><td align=\"left\">Noise</td><td align=\"right\">Model 1</td><td align=\"right\">Model 2</td><td align=\"right\">Model 3</td></tr></thead><tbody><tr><td align=\"left\">None</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">99</td></tr><tr><td align=\"left\">GE</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">96</td></tr><tr><td align=\"left\">MS</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">97</td></tr><tr><td align=\"left\">PC</td><td align=\"right\">89</td><td align=\"right\">100</td><td align=\"right\">49</td></tr><tr><td align=\"left\">GH</td><td align=\"right\">100</td><td align=\"right\">100</td><td align=\"right\">82</td></tr><tr><td align=\"left\">GE+GH+PC+MS</td><td align=\"right\">51</td><td align=\"right\">71</td><td align=\"right\">34</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>HFCC analysis: Preliminary results and effect of noise filters.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Applied Filters</td><td align=\"center\">Unfiltered Results</td><td align=\"center\">After Control Filter</td><td align=\"center\">After Direction Filter</td><td align=\"center\">After Tracking Filter</td><td align=\"center\" colspan=\"3\">Selected two-locus SNP pairs</td></tr><tr><td/><td/><td/><td/><td/><td align=\"center\">Simultaneous</td><td align=\"center\">Conditional</td><td align=\"center\">Epistatic</td></tr></thead><tbody><tr><td align=\"left\">Method I</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> N</td><td align=\"center\">418,535</td><td align=\"center\">-</td><td align=\"center\">320,265</td><td align=\"center\">-</td><td align=\"center\">71,332</td><td align=\"center\">248,898</td><td align=\"center\">35</td></tr><tr><td align=\"left\"> %</td><td align=\"center\">100%</td><td align=\"center\">-</td><td align=\"center\">76.5%</td><td align=\"center\">-</td><td align=\"center\">17.0%</td><td align=\"center\">59.5%</td><td align=\"center\">0.01%</td></tr><tr><td align=\"left\">Method II</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> N</td><td align=\"center\">418,535</td><td align=\"center\">-</td><td align=\"center\">320,265</td><td align=\"center\">26,371</td><td align=\"center\">19,630</td><td align=\"center\">6,706</td><td align=\"center\">35</td></tr><tr><td align=\"left\"> %</td><td align=\"center\">100.0%</td><td align=\"center\">-</td><td align=\"center\">76.5%</td><td align=\"center\">6.3%</td><td align=\"center\">6.1%</td><td align=\"center\">2.1%</td><td align=\"center\">0.01%</td></tr><tr><td align=\"left\">Method III</td><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> N</td><td align=\"center\">418,535</td><td align=\"center\">340,043</td><td align=\"center\">320,188</td><td align=\"center\">26,347</td><td align=\"center\">19,611</td><td align=\"center\">6,701</td><td align=\"center\">35</td></tr><tr><td align=\"left\"> %</td><td align=\"center\">100.0%</td><td align=\"center\">81.2%</td><td align=\"center\">76.5%</td><td align=\"center\">6.3%</td><td align=\"center\">6.1%</td><td align=\"center\">2.1%</td><td align=\"center\">0.01%</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Selected Parkinson's disease two-locus combinations.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"right\">SNP1</td><td align=\"right\">SNP2</td><td align=\"right\">Effect</td><td align=\"right\">Genetic Model</td><td align=\"right\">Odds Ratio</td><td align=\"right\">2-locus X²</td><td align=\"right\">Case-only X²</td></tr></thead><tbody><tr><td align=\"right\">rs6542522</td><td align=\"right\">rs3923511</td><td align=\"right\">E</td><td align=\"right\">TC*GA</td><td align=\"right\">0.28</td><td align=\"right\">24.97</td><td align=\"right\">13.07</td></tr><tr><td align=\"right\">rs10799573</td><td align=\"right\">rs1341622</td><td align=\"right\">E</td><td align=\"right\">CC*CT</td><td align=\"right\">5.22</td><td align=\"right\">23.08</td><td align=\"right\">10.61</td></tr><tr><td align=\"right\">rs12520264</td><td align=\"right\">rs2992630</td><td align=\"right\">E</td><td align=\"right\">AG*GA</td><td align=\"right\">0.22</td><td align=\"right\">23.86</td><td align=\"right\">23.12</td></tr><tr><td align=\"right\">rs324454</td><td align=\"right\">rs12672177</td><td align=\"right\">E</td><td align=\"right\">GG*AG</td><td align=\"right\">0.21</td><td align=\"right\">24.31</td><td align=\"right\">11.55</td></tr><tr><td align=\"right\">rs6656554</td><td align=\"right\">rs3898966</td><td align=\"right\">E</td><td align=\"right\">GT*TC</td><td align=\"right\">3.83</td><td align=\"right\">23.44</td><td align=\"right\">22.34</td></tr><tr><td align=\"right\">rs7650598</td><td align=\"right\">rs12353255</td><td align=\"right\">E</td><td align=\"right\">AG*AG</td><td align=\"right\">3.99</td><td align=\"right\">23.94</td><td align=\"right\">9.40</td></tr><tr><td align=\"right\">rs2439525</td><td align=\"right\">rs1327918</td><td align=\"right\">E</td><td align=\"right\">TT*CC</td><td align=\"right\">2.39</td><td align=\"right\">22.04</td><td align=\"right\">7.13</td></tr><tr><td align=\"right\">rs10201616</td><td align=\"right\">rs4495512</td><td align=\"right\">E</td><td align=\"right\">CT*TT</td><td align=\"right\">5.04</td><td align=\"right\">24.08</td><td align=\"right\">8.63</td></tr><tr><td align=\"right\">rs11167062</td><td align=\"right\">rs1270919</td><td align=\"right\">E</td><td align=\"right\">TC*GT</td><td align=\"right\">0.20</td><td align=\"right\">21.83</td><td align=\"right\">20.65</td></tr><tr><td align=\"right\">rs2419117</td><td align=\"right\">rs10512174</td><td align=\"right\">E</td><td align=\"right\">GT*CC</td><td align=\"right\">5.55</td><td align=\"right\">23.33</td><td align=\"right\">9.33</td></tr><tr><td align=\"right\">rs1370699</td><td align=\"right\">rs1673130</td><td align=\"right\">C</td><td align=\"right\">CC*CC</td><td align=\"right\">0.35</td><td align=\"right\">25.50</td><td align=\"right\">30.15</td></tr><tr><td align=\"right\">rs1590957</td><td align=\"right\">rs8043401</td><td align=\"right\">C</td><td align=\"right\">TT*AG</td><td align=\"right\">0.32</td><td align=\"right\">24.17</td><td align=\"right\">28.18</td></tr><tr><td align=\"right\">rs1557615</td><td align=\"right\">rs2582597</td><td align=\"right\">C</td><td align=\"right\">TC*AG</td><td align=\"right\">0.35</td><td align=\"right\">21.76</td><td align=\"right\">26.38</td></tr><tr><td align=\"right\">rs11781101</td><td align=\"right\">rs4775501</td><td align=\"right\">C</td><td align=\"right\">CC*CC</td><td align=\"right\">0.22</td><td align=\"right\">23.99</td><td align=\"right\">25.69</td></tr><tr><td align=\"right\">rs1370699</td><td align=\"right\">rs7897163</td><td align=\"right\">C</td><td align=\"right\">CC*CC</td><td align=\"right\">0.34</td><td align=\"right\">30.65</td><td align=\"right\">25.68</td></tr><tr><td align=\"right\">rs13197142</td><td align=\"right\">rs2206699</td><td align=\"right\">C</td><td align=\"right\">GG*AA</td><td align=\"right\">2.33</td><td align=\"right\">21.85</td><td align=\"right\">25.16</td></tr><tr><td align=\"right\">rs732594</td><td align=\"right\">rs12373417</td><td align=\"right\">C</td><td align=\"right\">AA*GG</td><td align=\"right\">3.62</td><td align=\"right\">22.31</td><td align=\"right\">25.16</td></tr><tr><td align=\"right\">rs10498269</td><td align=\"right\">rs1551355</td><td align=\"right\">C</td><td align=\"right\">TC*CC</td><td align=\"right\">0.38</td><td align=\"right\">23.42</td><td align=\"right\">25.00</td></tr><tr><td align=\"right\">rs2555614</td><td align=\"right\">rs331617</td><td align=\"right\">C</td><td align=\"right\">AA*TT</td><td align=\"right\">0.35</td><td align=\"right\">24.15</td><td align=\"right\">24.22</td></tr><tr><td align=\"right\">rs3894377</td><td align=\"right\">rs10774863</td><td align=\"right\">C</td><td align=\"right\">AG*CT</td><td align=\"right\">0.31</td><td align=\"right\">25.47</td><td align=\"right\">23.84</td></tr><tr><td align=\"right\">rs4799327</td><td align=\"right\">rs2301661</td><td align=\"right\">S</td><td align=\"right\">AG*CC</td><td align=\"right\">4.32</td><td align=\"right\">20.65</td><td align=\"right\">33.62</td></tr><tr><td align=\"right\">rs2336865</td><td align=\"right\">rs7973385</td><td align=\"right\">S</td><td align=\"right\">GA*TC</td><td align=\"right\">3.22</td><td align=\"right\">30.71</td><td align=\"right\">27.77</td></tr><tr><td align=\"right\">rs6779648</td><td align=\"right\">rs270406</td><td align=\"right\">S</td><td align=\"right\">GG*AG</td><td align=\"right\">0.26</td><td align=\"right\">26.57</td><td align=\"right\">22.49</td></tr><tr><td align=\"right\">rs12599027</td><td align=\"right\">rs767055</td><td align=\"right\">S</td><td align=\"right\">TT*TT</td><td align=\"right\">0.23</td><td align=\"right\">26.23</td><td align=\"right\">24.34</td></tr><tr><td align=\"right\">rs3891371</td><td align=\"right\">rs4724620</td><td align=\"right\">S</td><td align=\"right\">AG*CC</td><td align=\"right\">0.29</td><td align=\"right\">35.76</td><td align=\"right\">23.92</td></tr><tr><td align=\"right\">rs2297518</td><td align=\"right\">rs660454</td><td align=\"right\">S</td><td align=\"right\">AG*TT</td><td align=\"right\">0.12</td><td align=\"right\">23.92</td><td align=\"right\">23.72</td></tr><tr><td align=\"right\">rs357968</td><td align=\"right\">rs1159145</td><td align=\"right\">S</td><td align=\"right\">AA*AA</td><td align=\"right\">0.26</td><td align=\"right\">30.29</td><td align=\"right\">23.47</td></tr><tr><td align=\"right\">rs1476097</td><td align=\"right\">rs5766305</td><td align=\"right\">S</td><td align=\"right\">TT*TT</td><td align=\"right\">0.37</td><td align=\"right\">23.93</td><td align=\"right\">23.19</td></tr><tr><td align=\"right\">rs2955005</td><td align=\"right\">rs2169793</td><td align=\"right\">S</td><td align=\"right\">GT*AG</td><td align=\"right\">3.29</td><td align=\"right\">25.74</td><td align=\"right\">22.76</td></tr><tr><td align=\"right\">rs2560790</td><td align=\"right\">rs9390939</td><td align=\"right\">S</td><td align=\"right\">AA*CA</td><td align=\"right\">0.32</td><td align=\"right\">23.35</td><td align=\"right\">22.62</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Validation analysis.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Sample</td><td align=\"right\">Preliminary Results</td><td align=\"right\">Simultaneous</td><td align=\"right\">Conditional</td><td align=\"right\">Epistatic</td></tr></thead><tbody><tr><td align=\"left\">Original</td><td align=\"right\">418,535</td><td align=\"right\">19,630</td><td align=\"right\">6,706</td><td align=\"right\">35</td></tr><tr><td align=\"left\">Validation 1</td><td align=\"right\">396,708</td><td align=\"right\">20,855</td><td align=\"right\">6,897</td><td align=\"right\">23</td></tr><tr><td align=\"left\">Validation 2</td><td align=\"right\">283,584</td><td align=\"right\">19,270</td><td align=\"right\">6,219</td><td align=\"right\">18</td></tr><tr><td align=\"left\">Validation 3</td><td align=\"right\">299,846</td><td align=\"right\">19,261</td><td align=\"right\">6,000</td><td align=\"right\">27</td></tr><tr><td align=\"left\">Validation 4</td><td align=\"right\">403,475</td><td align=\"right\">19,640</td><td align=\"right\">6,660</td><td align=\"right\">21</td></tr><tr><td align=\"left\">Validation 5</td><td align=\"right\">337,422</td><td align=\"right\">19,575</td><td align=\"right\">6,463</td><td align=\"right\">22</td></tr><tr><td align=\"left\">Validation 6</td><td align=\"right\">320,406</td><td align=\"right\">18,879</td><td align=\"right\">6,230</td><td align=\"right\">20</td></tr><tr><td align=\"left\">Validation 7</td><td align=\"right\">313,653</td><td align=\"right\">18,667</td><td align=\"right\">5,943</td><td align=\"right\">21</td></tr><tr><td align=\"left\">Validation 8</td><td align=\"right\">294,007</td><td align=\"right\">19,255</td><td align=\"right\">6,360</td><td align=\"right\">26</td></tr><tr><td align=\"left\">Validation 9</td><td align=\"right\">322,754</td><td align=\"right\">18,478</td><td align=\"right\">5,772</td><td align=\"right\">22</td></tr><tr><td align=\"left\">Validation 10</td><td align=\"right\">363,194</td><td align=\"right\">19,317</td><td align=\"right\">5,529</td><td align=\"right\">28</td></tr><tr><td align=\"left\">Average Count (St. Dev.)</td><td align=\"right\">341,235 (47,125)</td><td align=\"right\">19,348 (629)</td><td align=\"right\">6,253 (419)</td><td align=\"right\">24 (5)</td></tr><tr><td align=\"left\">Average %</td><td align=\"right\">100%</td><td align=\"right\">7.92%</td><td align=\"right\">2.56%</td><td align=\"right\">0.010%</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Power of HFCC to detect a two-locus interaction at an alpha level of 0.01 under 3 genetic epistasis models and different sources of noise: no noise (None), genotyping error (GE), missing data (MS), phenocopy (PC), genetic heterogeneity (GH), and all sources of noise simultenously (GE+GH+PC+MS). For the datasets with genetic heterogeneity, we reported the power to detect either of the two simulated two-locus effects. Model 1 is a heterozygote-homozygote risk (i.e., risk genotypes ABCC, ABDD, AACD and BBCD); Model 2 represents a \"2 and only 2\"-allele risk (i.e., A and C) from any of two loci (i.e., risk genotypes AADD, ABCD, and BBCC); Model 3 represents a protective double-heterozygote (i.e., protective genotype ABCD).</p></table-wrap-foot>", "<table-wrap-foot><p>Method I: Only Direction Filter applied.</p><p>Method II: Direction and Tracking filters applied.</p><p>Method III: All filters applied (Control, Direction, and Tracking filters sequentially in that order).</p><p>N: Number of selected two-locus SNP pairs.</p><p>%: Percentage of selected two-locus SNP pairs over the preliminary set (unfiltered HFCC results).</p><p>A total of 36 SNPs were identified as tracking SNPs in the two methods using tracking filter.</p></table-wrap-foot>", "<table-wrap-foot><p>A selection of two-locus marker combinations consistently and significantly associated to Parkinson's disease (p &lt; 10^-6) and displaying an epistatic (E) effect, or conditional (C) or simultaneous (S) effects with significant deviations of a multiplicative model. The genetic model tested is specified as SNP1 genotype * SNP2 genotype.</p></table-wrap-foot>", "<table-wrap-foot><p>Number of total preliminary results, and number of selected simultaneous, conditional and epistatic two-locus combinations in the original sample, and in ten random-placement validation samples. Average numbers (and standard deviations) for the 11 samples, and average percentage of each category, are included.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2164-9-360-1\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Asbestos is a family of naturally occurring silicate minerals that was once used extensively in a variety of building materials and industries and is still found in older structures. Exposure to certain forms of asbestos, such as crocidolite and amosite, have been shown to cause mesothelioma, asbestosis, fibrosis and carcinoma of the lungs, esophagus and stomach [##REF##8816862##2##, ####REF##2153315##3##, ##REF##9012357##4####9012357##4##]. Many developing countries continue to mine and use asbestos, presenting a continued risk to individuals.</p>", "<p>The biodurability and chemical reactivity of <italic>crocidolite </italic>asbestos, taken together, create a formidable carcinogen for the human lung to handle. Crocidolite can induce DNA strand breaks and base alterations. One expected response to this damage is apoptosis/cell death. But under certain conditions, cell replication can occur before the DNA damage is repaired, resulting in the formation of mutations. Events which promote survival of the cell with DNA damage and stimulate replication may lead to cancer. An unfortunate consequence of apoptosis is the stimulation of surrounding cells to replicate in an effort to repair the integrity of the damaged tissue. If the surrounding cells have experienced DNA damage, the result could be mutations, which may lead to cancer. What sets crocidolite apart from most other carcinogens is the persistent nature of the inhaled fibers, allowing for continued damage to surviving cells throughout the lifetime of the individual. Therefore, knowledge of the delicate balance between pathways that lead to proliferation or survival and those which lead to apoptosis or cell death are crucial for understanding the etiologies behind several asbestos-induced lung disorders and diseases.</p>", "<p>Much of the deleterious effects of asbestos can be attributed to the sustained synthesis of reactive oxygen species (ROS) which in turn results in DNA damage [##REF##1315628##5##, ####REF##8130850##6##, ##REF##8579364##7####8579364##7##] and oxidative stress within the cell. Iron associated with the fibers (up to 27% by weight in crocidolite) can participate in Fenton and Haber-Weiss chemistry and therefore plays an intimate role in ROS generation (reviewed by [##REF##10377212##8##]). Signals which reduce glutathione synthesis and increase efflux of reduced glutathione result in the reduction of intracellular glutathione concentrations [##REF##9400737##9##], thus, exacerbating the situation. At the crux of the decision to initiate apoptosis is a p53-dependent transcription response. Although the events upstream of p53 activation and the importance of p53 targets are not well characterized, the result of p53 activation is mitochondrial dysfunction leading to apoptosis [##REF##16357363##10##]. Apoptosis prevents continued proliferation of the damaged cell, but factors released from the damaged cell can also affect nearby cells causing inflammation and proliferation. In mapping the signal cascades which are activated/deactivated by asbestos, both human and non-human cell lines of epithelial and/or mesothelial cells, and rodent animal models have been useful. Studies have identified MAPkinase [##REF##17191120##11##, ####REF##16484683##12##, ##REF##12162423##13####12162423##13##], cytokines, Akt [##REF##17191120##11##,##REF##15897870##14##], PKC [##REF##17200189##15##], p53 [##REF##16357363##10##,##REF##14646501##16##] and NF-κB [##REF##16798876##17##,##REF##7667311##18##] signaling pathways as important players. Chromosomal translocations, promoter silencing, point mutations, deletions, and/or familial genetic susceptibility are also likely to contribute to a cell's inability to respond appropriately to the genotoxic insult of crocidolite [##REF##12085188##19##,##REF##16965949##20##]. The number and complexity of the signaling components identified thus far mirrors the idea that the asbestos response is not only related to the presence of iron and the production of ROS, but also involves receptor-mediated processes. An unavoidable caveat of trying to combine all the current experimental data lies in the inherent differences that exist between species and within cell lines, primary cells, and tumor specimens (reviewed in [##REF##15950812##21##]), and the involvement of neighboring tissue. The complexity of asbestos response and the multiple pathologies associated with the fiber would suggest the need for more systems biology approaches to the problem.</p>", "<p>This study was conducted to begin to elucidate how the A549 human lung epithelial cell transcriptome is altered when cells are exposed to crocidolite asbestos at 6 μg/cm². An experimental strategy was developed to ensure a statistically robust, comprehensive data set from which global observations and analyses of specific pathways could be made. This study extends a previous microarray experiment [##REF##17331233##22##] performed at 2 μg/cm²where replicates were not available. Using the more than 2,500 genes that were differentially regulated by crocidolite in A549 cells, we were able to: 1) Statistically classify the data set based on gene ontologies. This analysis revealed significant representation by transcriptional corepressor and repressor activities. Additionally, a significant unique representation by DNA modification ontologies within a less significant DNA repair/response ontology was found; 2) Identify specific novel genes that may play a role in experimentally observed asbestos-induced responses; and 3) Use a knowledge-based network approach to reveal a highly integrated series of networks related to cell death, cancer, cell cycle, cellular growth, proliferation, and gene expression. Network analysis identified several functional modules in which previously unidentified genes may play a central role in the response of cells to asbestos, including participation from an extensive extracellular set of growth factors and cytokines. Importantly, by combining genome-wide transcript changes and functional network analysis, we have documented a novel global view of the crocidolite-treated A549 transcriptome, which bears signatures of both proliferation/cell survival and apoptosis/cell death.</p>" ]

[ "<title>Methods</title>", "<title>Reagents and Antibodies</title>", "<p>Crocidolite was obtained from Dr. Richard Griesemer, NIEHS/NTP. The chemical formula for crocidolite is Na₂Fe^III₂(Fe^II, Mg)₃Si₈O₂₂(OH)₂. It has a mean length of 10 μm, a density of 3.2–3.3 g/cm³and contains 27% iron by weight [##UREF##2##69##]. A custom prepared Ham's F-12 cell culture medium free of iron salts and 0.5% trypsin with 0.2% EDTA were obtained from Invitrogen Inc. (Carlsbad, CA). Fetal bovine serum (FBS) was purchased from Hyclone (Logan, UT). Antibodies for Egr-1 (sc-189) and ATF3 (sc-188) were purchased from Santa Cruz Biotechnology (Santa Cruz, CA) and the antibody for β-actin was purchased from Sigma (St. Louis, MO). Anti-rabbit and anti-mouse enzyme-conjugated secondary antibodies were purchased from Jackson Immunoresearch Laboratories Inc. (West Grove, PA). Primers were purchased from IdtDNA (Coralville, IA). All remaining reagents were purchased in the highest purity possible.</p>", "<title>Cell Culture and Treatment</title>", "<p>A549 cells were purchased from American Type Culture Collection and grown in F12 medium without iron, with 10% FBS and 50 μg/mL gentamicin (BioWhittaker, Walkersville, MD). Cells were plated for treatments at a concentration of 20,000 cells/cm²and incubated 24 h before treatment. For all treatments, medium was removed and replaced with either fresh medium (for control samples) or medium containing the appropriate stimulus (treated samples). For crocidolite treatments, fibers were suspended in sodium bicarbonate at a concentration of 1 mg/mL and immediately diluted to a final concentration of 6 μg/cm²in complete medium. Sodium bicarbonate is used specifically to avoid iron mobilization in the media before the fibers can by endocytosed and maintains the pH [##REF##7979379##26##]. These are the exact same conditions and methodologies used previously in several other studies [##REF##9400737##9##,##REF##17191120##11##,##REF##16169567##25##, ####REF##7979379##26##, ##REF##9143343##27####9143343##27##].</p>", "<title>RNA Extraction and Use of DNA Microarrays</title>", "<p>mRNA was isolated from cells at passage 9 using TRIzol^®reagent from Invitrogen (Carlsbad, CA) following manufactures directions. This procedure yielded RNA of both high quantity and quality, as verified by both the A₂₆₀/A₂₈₀ratio (&gt; 1.8) and the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). The extracted RNA was processed by the Affymetrix core service at the Center for Integrated BioSystems, Utah State University (CIB-USU; Logan, UT). RNA was processed as per the manufacturer's instructions (Affymetrix Inc., Santa Clara, CA) for the first-strand cDNA synthesis and amplification, followed by cDNA synthesis and labeling. The cDNA was hybridized overnight to the HGU133-Plus2.0 Human Genome 2.0 genechips and post-hybridization washing, detection and data collection were performed as per manufacturer's instructions. Three biological replicates were performed. Each replicate consisted of a control plate and a crocidolite-treated plate. All experiments were done at passage 9.</p>", "<title>Statistical Analyses</title>", "<p>Using tools from the Bioconductor project [##REF##15461798##70##], the data were pre-processed using the RMA algorithm [##REF##12925520##71##], and a test for differential expression between control and treated (crocidolite-exposed) conditions was performed using the moderated t-statistic from the limma/eBayes approach [##REF##16646809##72##]. The raw p-values from this test were adjusted to control the false discovery rate [##UREF##0##34##] at 0.05. Dendrograms (Figure ##FIG##1##2##) were drawn by Hierarchical Clustering Explorer (HCE; <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.cs.umd.edu/hcil/hce/hce3.html\"/>) software version 3.0 to summarize RMA-normalized data after averaging across replicates. The cutoff value for minimum levels of gene expression was based on the whole genome expression profiles generated by HCE. The median cutoff value was set at the software-calculated median of gene expression and was colored black. The data were further subdivided into gene functional classes that had been annotated by the Human Genome Database. Each class was then clustered separately and the determined cutoff values were applied to generate colored expression maps for each individual class for ease of visualization. In addition, a global test [##REF##14693814##37##, ####REF##15657105##38##, ##UREF##1##39####1##39##] was used to identify gene ontologies of interest, where the expression levels of the genes in the ontology were statistically significant (p-value less than 0.05) for predicting the clinical outcome (crocidolite exposure). STRING analysis was performed at <ext-link ext-link-type=\"uri\" xlink:href=\"http://string.embl.de/\"/> using default parameters.</p>", "<title>Quantitative RT-PCR</title>", "<p>mRNA was isolated using TRIzol^®reagent from Invitrogen (Carlsbad, CA) following manufactures directions. DNase from the RNAqueous^®-4PCR kit (Ambion Inc., Austin, TX) was added to eliminate genomic DNA and removed following the manufacture protocol. cDNA was transcribed using SuperScript™ II Reverse Transcriptase (Invitrogen Inc., Carlsbad, CA). Specificity was confirmed by performing a melting curve on the final amplicons and running the amplicons on a 2% agarose gel. All qRT-PCR samples were also run on samples without reverse transcriptase to confirm the product was from mRNA, not DNA, and all of these samples showed no amplicon. Three different dilutions of cDNA were used to confirm that the samples were in the linear range.</p>", "<title>Western blot analysis</title>", "<p>Cells were harvested with trypsin and then lysed using RIPA buffer (0.15 M NaCl, 50 mM Tris, pH 7.2, 1% deoxycholate, 1% Triton X-100, 0.1% SDS) containing protease inhibitors (30 μL/mL aprotinin, 4 μg/mL leupeptin, 4 μg/mL soybean trypsin inhibitor, 0.1 mM PMSF and 1 μM benzamidine). After incubation on ice for 30 min, cells were centrifuged for 10 min at 8200 × <italic>g </italic>to remove cellular debris. Protein concentrations were determined using the Bradford method (Bio-Rad Laboratories, Hercules, CA). Cellular protein (50 μg) was analyzed using SDS-PAGE (10–15%) and transferred to polyvinyl difluoride (PVDF) membranes. Primary antibodies were diluted 1:200 in 5% dried milk in TTBS and incubated for 1 h at room temperature. Secondary antibodies were diluted 1:5000 and incubated for 1 h at room temperature. Blots were visualized using ECL Plus reagent from GE Healthcare Life Sciences (Piscataway, NJ).</p>", "<title>Pathway Analysis</title>", "<p>Data were analyzed through the use of Ingenuity Pathways (Ingenuity^®Systems, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ingenuity.com\"/>). The asbestos data set with gene identifiers and corresponding expression values was uploaded into the application. Each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base. A cutoff of p &lt; 0.01 was set to identify genes whose expression was significantly differentially regulated by ± 2-fold. These genes, called focus genes, were overlaid onto a global network developed from information contained in the Ingenuity Pathways Knowledge Base. Networks of these focus genes were then algorithmically generated based on their connectivity. Biological functions associated with these focus genes were identified using the Functional Analysis using the Ingenuity Pathways Knowledge Base. Fischer's exact test was used to calculate a p-value determining the probability that each biological function assigned to the data set was due to chance alone. Networks are graphical representations of the molecular relationships between genes/gene products. Genes or gene products are represented as nodes, and the biological relationship between two nodes is represented as an edge (line). All edges are supported by at least one reference from the literature, a textbook, or from canonical pathway information stored in the Ingenuity Pathways Knowledge Base.</p>" ]

[ "<title>Results and Discussion</title>", "<title>Experimental Design</title>", "<p>Given the difficulties in obtaining sufficient primary human lung epithelial cells to study the complex response to asbestos, many studies have instead employed the A549 human adenocarcinoma cell line. In doing so one must keep in mind that the transformed cell line may not be entirely applicable to normal human lung cells. However, all processes noted below are recapitulated in primary human lung epithelial cells, suggesting that A549 cells represent a valid model system. Importantly, use of a human cell line avoids the inherent differences that are seen between individual patients. Alveolar epithelial type II cells are key participants in inflammation, fibrogenesis, and carcinogenesis [##REF##8909230##23##] and have been described as the targets of asbestos-associated lung carcinomas [##REF##15374964##24##].</p>", "<p>The conditions used for obtaining the gene expression profile for crocidolite treated A549 cells were chosen to mimic conditions where a variety of biochemical observations have previously been made in our laboratories. Exposure of A549 cells to 6 μg/cm²crocidolite for 24 hours had previously been shown to result in the α_vβ₅integrin receptor-mediated endocytosis of asbestos fibers [##REF##16169567##25##], mobilization of iron from the fibers within the cell [##REF##7979379##26##], upregulation of ferritin protein to combat the iron overload [##REF##9143343##27##], production of reactive oxygen intermediates [##REF##14766669##28##], efflux of reduced glutathione [##REF##9400737##9##], DNA damage [##REF##8579364##7##], PARP cleavage and activation of initiator caspases [##REF##12540492##29##]. Thus, at 6 μg/cm²of crocidolite the microarray results could be related to an extensive body of biochemical information already available in A549 cells. In addition, this cell line has been used by other investigators for several studies to explore the mechanisms of DNA damage [##REF##7900829##30##], apoptosis [##REF##16357363##10##], and invasiveness [##REF##17616677##31##]. Use of the A549 human lung epithelial cell line complements studies done in mesothelial cells [##REF##12839939##32##] and by the less carcinogenic chrysotile in bronchial epithelial cells [##REF##11062161##33##]. Our goal was to extend our results beyond lists of genes and ontological classifications to discover new pathways based on functional interactions. Rather than diffusing statistical power by examining differences among multiple time points and asbestos concentrations, this experiment focused on the use of chemically defined crocidolite asbestos, a single concentration of crocidolite versus a control condition, and a single exposure time. This focus allowed for three replicates of mRNA from control and crocidolite-treated cells to be analyzed using the Affymetrix HGU133 Plus 2.0 GeneChip to provide the most comprehensive whole genome expression profile.</p>", "<title>Analysis of the Microarray Data</title>", "<p>Graphical checks of the gene expression data revealed a high-quality data set, with no spatial artifacts in the chip images, and a high degree of reproducibility within both the control and treated replicates (Additional File ##SUPPL##0##1##). Using tools described in the Methods Section and a false discovery rate [##UREF##0##34##] of 0.05, 2,546 genes with q-values (FDR-adjusted p-values) less than 0.05 were called statistically significant. These results are represented in a volcano plot (Figure ##FIG##0##1##).</p>", "<title>Crocidolite Induces Large Changes in the Transcriptome of A549 Human Lung Epithelial Cells</title>", "<p>Among the 54,120 probe sets on the GeneChip, 1808 were significantly up-regulated (492 of which were two-fold or greater), and 738 were significantly down-regulated (27 of which were two-fold or greater) when A549 cells were exposed to 6 μg/cm²crocidolite asbestos for 24 h. Of the probe-sets that changed two-fold or greater, 234 correspond to known genes for the up-regulated probe sets, and 16 of the down-regulated probe sets correspond to known genes (some genes were represented more than once on the chip). Genes that increased in expression five-fold or greater or decreased two-fold or greater and were associated with q-values less than 0.05 are shown in Table ##TAB##0##1##. A complete table of all significant genes can be found as Additional File ##SUPPL##1##2##. The observation that most of the expression changes are upregulated is contradictory to a previous microarray study in A549 cells [##REF##17331233##22##] which used a smaller dose of crocidolite (2 μg/cm²). A direct comparison of the two data sets was difficult due to differences in experimental design. Namely, replicates at a single time point were used in the current study versus single chips over a time course, and a lower crocidolite concentration, which is a likely cause for some differences. Cells exposed to asbestos may demonstrate a hierarchical oxidative stress response [##REF##14522998##35##]. Additionally, small amounts of asbestos have been shown to result in proliferation [##REF##15374964##24##]. This may be attributed to a transient response to an increase in iron, which is limiting in cells in culture. However, comparison of individual expression changes in our data set to other known experimental results (discussed below) demonstrated that our data set is consistent with the literature.</p>", "<p>Hierarchical clustering analysis (Figure ##FIG##1##2A##) of our data set showed that the majority of the up-regulated probe sets clustered together in four different hierarchical clusters. The down-regulated probe sets were mainly in one hierarchical cluster, but had several individual genes spread throughout the dendrogram. Within the four up-regulated clusters, 24 genes that were upregulated 5-fold could be mapped by functional String analysis shown in Fig ##FIG##1##2B##. Most of the gene products are connected; i.e., could be linked functionally by way of known molecular interactions. Three major pathways (MAPK, JNK/SAPK and cytokine-cytokine receptor interactions) are represented in the cluster. This result is consistent with what is currently known about the effect of asbestos in epithelial and mesothelial cells. When the down-regulated genes were functionally clustered, only two (<italic>fyr </italic>and <italic>uvo</italic>) out of 16 had a connection (data not shown).</p>", "<title>Validation of the Microarray Data</title>", "<p>Validation of the microarray data was confirmed by quantitative RT-PCR on four of the genes (<italic>Egr1</italic>, <italic>ATF3</italic>, c-<italic>Jun</italic>, and <italic>JunB</italic>) and was further corroborated with previously noted results from experiments using human cells/cell lines (Table ##TAB##1##2##). Quantitative RT-PCR also demonstrated that increases in Egr-1, ATF3, c-Jun, and JunB message occurred after 6 hours and continued to increase through 24 hours (data not shown). Increased mRNA expression from <italic>ATF3</italic>, c-<italic>Jun</italic>, and <italic>JunB </italic>was also observed by quantitative RT-PCR in primary human epithelial cells from small airways (SAEC) treated with crocidolite (data not shown). Increased protein expression in A549 cells exposed to crocidolite was observed for ATF3, c-Jun, and JunB (data not shown). Finally, previous results using asbestos-treated A549 cells have demonstrated increased mRNA and/or protein levels for <italic>IL8, TP53, HMOX1, CDKN1A, SOD2 </italic>and c-<italic>myc </italic>(see Table ##TAB##1##2## for additional references). The reproducibility of the microarray replicates, the significance level of the expression changes, and the validation by quantitative RT-PCR suggest that a highly useful and validated data set was obtained in this study. Furthermore, the large number of significant genes allowed us to perform a comprehensive analysis of the crocidolite-induced transcriptome in human lung epithelial cells.</p>", "<title>Specific Changes in the Crocidolite-Treated Transcriptome</title>", "<p>Although it is clearly established that asbestos induces DNA damage in both primary cells and cell culture lines, the literature illustrates that the molecular mechanism underlying this process and how the fate of the cell is dictated are multifaceted. Although ROS are intimately tied to the mechanism of asbestos-induced fibrosis and carcinogenesis, ROS alone do not offer a complete understanding of the asbestos response. In order to identify genes for which expression level changes are specific for crocidolite compared to oxidative stress, we compared our data set to expression changes that occur in A549 cells when exposed to hydrogen peroxide. In a previous study that documented changes in the A549 cell transcriptome, Cotgreave and co-workers [##REF##15019973##36##] showed that treatment of A549 cells with hydrogen peroxide results in DNA damage and apoptosis. Both hydrogen peroxide and crocidolite asbestos induced the upregulation of <italic>TNFRS10B, PPP1R15A, GADD34, CDKN1A, BTG2, DUSP1, DUSP5, DUSP14, SDC4, GDF15, IL8, ADM, FST, IER3, FOS, HMOX1, ATF3</italic>, and <italic>ZFP36</italic>. Therefore, expression changes in these genes may represent a response to an oxidative stress. Several unique genes that are differentially regulated in the crocidolite data set are noted in Table ##TAB##0##1## and include some genes which are associated with carcinogenesis such as <italic>STC1, IL6, FN1, BRE</italic>, and <italic>PTGS2</italic>. Differences between the hydrogen peroxide-treated and crocidolite-treated transcriptomes may be due to the additional iron released from fibers, present in cells treated with crocidolite, or reactive nitrogen species, changes in glutathione content and/or the involvement of processes initiated at the cell surface by the fiber. It will be very interesting to investigate if these apparent crocidolite-specific gene regulations play a role in crocidolite-induced cytobiological endpoints.</p>", "<title>Ontological Analysis of the Crocidolite-Treated Lung Transcriptome</title>", "<p>In order to identify themes in the global expression pattern of crocidolite-treated A549 cells, we used Gene Ontology (GO) classification. The differentially expressed genes (up-regulated/down-regulated ± 2-fold with p-values less than 0.2) were analyzed using Onto-Express <ext-link ext-link-type=\"uri\" xlink:href=\"http://vortex.cs.wayne.edu/\"/>. The Biological Process tree was expanded to the fourth tier in the hierarchy as a balance between specificity and coverage. Processes affected by crocidolite are shown in Figure ##FIG##2##3A##. Within the Cellular Metabolism classification, processes involved in transcription and phosphorus metabolism were highly represented. Expansion of Molecular Functions to the third tier revealed a large number of genes with functions related to transcription (over-represented in Protein binding (Figure ##FIG##2##3B##)). This observation was expanded upon by performing a global test [##REF##14693814##37##, ####REF##15657105##38##, ##UREF##1##39####1##39##] to identify specific gene ontologies related to transcription, where the expression levels of all the genes in the ontology give useful information for predicting the clinical outcome (or in this case, a cellular outcome of crocidolite exposure). Ontologies of particular interest related to transcription factor activity (GO:0003700) are summarized in Figure ##FIG##2##3C##, with nodes colored to correspond to global test p-values; the lighter nodes have lower p-values. To reduce visual clutter, only the last four digits of each ontology's identifier are reported in Figure ##FIG##2##3C##. The ontological analysis illustrates that transcriptional corepressor activity and repressor activity are highly represented in the data set. Overall the transcriptome of crocidolite-treated human lung epithelial (A549) cells is heavily populated by gene products associated with transcription.</p>", "<p>We also noted that DNA repair terms were not highly represented in the data set. Although this result was initially surprising, we noted that the transcriptome of A549 cells exposed to hydrogen peroxide, which also induces DNA damage, was also underrepresented in DNA repair terms [##REF##15019973##36##]. In order to gain a better understanding of how the transcriptome of crocidolite-treated A549 cells is reorganized in response to the resulting DNA damage, the results of the global test discussed above were also applied to ontologies related to DNA damage/repair. Although this analysis (see Additional File ##SUPPL##2##3##) confirms the overall observation that many of the processes related to DNA repair/damage are not highly represented, the analysis also highlights specific nodes in the GO tree related to DNA damage-induced phosphorylation (GO:6975), DNA dealkylation (GO:6307), DNA methylation (GO:6306), and DNA alkylation (GO:6305). In light of the several studies directed at linking promoter methylation status and carcinogenesis (reviewed in [##REF##16699174##40##]), it is interesting to point out that in as little as 24 hours of crocidolite exposure, the A549 transcriptome may be poised to affect the DNA methylation status that is associated with lung cancer pathogenesis.</p>", "<title>Identification of Novel, Putative Crocidolite-Related Genes</title>", "<p>Even though this study was initiated to understand the broad changes that occur in the lung transcriptome upon crocidolite exposure, we also sought to identify novel genes that had no previous association with crocidolite and to identify genes that may be downstream targets of well-known crocidolite-related players. Given the complex effects that asbestos has on the lung system, we expected that a systems biology approach may provide novel avenues to study. <italic>NR4A1</italic>, <italic>NR4A2</italic>, and <italic>NR4A3 </italic>belong to the steroid nuclear hormone receptor superfamily of immediate early genes that are induced by serum, growth factors and receptor engagement and are thus implicated in cell mitogenic responses. Although previously characterized as pro-survival, studies have also suggested an important role for these receptors in cell transformation and tumorigenicity via their anti-apoptotic and pro-apoptotic functions [##REF##16493583##41##]. Thus, depending on cellular context, these gene products may serve as switches in determining cell fate. All three members of this family show increased expression in our data set (Additional File ##SUPPL##1##2##) but have not previously been implicated in crocidolite-induced pulmonary toxicity.</p>", "<p>Modulation of apoptosis can also be affected by BRE (brain and reproductive organ-expressed protein), a stress-modulating protein also known as TNFRSF1A modulator. <italic>BRE </italic>expression was upregulated &gt;7-fold in crocidolite-treated A549 cells. Exogenous overexpression of BRE can attenuate intrinsic apoptosis and promote growth of the transfected Lewis lung carcinoma line in mice [##REF##15582573##42##] which is consistent with the recent finding that BRE protein is overexpressed in human hepatocellular carcinomas [##REF##17704801##43##]. Given the ability of BRE to interact with both Fas [##REF##15465831##44##] and the TNF receptor 1 [##REF##9737713##45##], and the observation that TNFα can attenuate asbestos cytotoxicity in mesothelial cells [##REF##16798876##17##], it will be very interesting to investigate possible roles of BRE in crocidolite-treated human lung cells. Also noteworthy is the upregulation of several \"early response\" NF-κB targets [##REF##16191192##46##] in our dataset (Additional File ##SUPPL##1##2##) including <italic>TNFAIP3, IL8, IL6, CXCL1, CXCL2, CXCL3, PTGS2</italic>, and <italic>PLAU</italic>. Activation of the NF-κB pathway is thought to play a critical role in cell survival in asbestos-treated cells [##REF##16798876##17##], but only a few of the downstream targets of NF-κB have been identified.</p>", "<p>The relationship between asbestos and calcium has received little attention in recent years, but the initial studies suggest that calcium may have an important role to play (reviewed in [##REF##12757757##47##]). Perhaps most compelling is the ability of the calcium-chelator Quin-2 to prevent crocidolite-induced DNA breaks [##REF##7526185##48##]. Additionally, several players in the asbestos response are regulated by calcium levels, e.g., protein kinase C [##REF##17200189##15##]. We were therefore interested in determining if the crocidolite-treated transcriptome demonstrated any clues regarding the regulation of calcium homeostasis. We observed that expression of <italic>MCTP1 </italic>and <italic>STC1 </italic>were both upregulated in our data set by 7.3- and 12.9-fold, respectively. MCTP1 is a transmembrane protein that binds calcium ions via C₂domains. Unique properties of this protein suggest that these proteins function in Ca²⁺signaling at the membrane [##REF##15528213##49##]. Stanniocalcin 1 (STC1) has long been studied as a regulator of both phosphate and calcium homeostasis in bony fish, but has recently received attention in mammalian systems. STC1 is a glycoprotein present in a variety of mammalian tissues where it can function as a regulator of gene expression and modulator of transendothelial cell migration [##REF##17032941##50##], and can also affect cellular metabolism by perturbing mitochondrial electron transport chain and mitochondrial calcium transport [##REF##17092635##51##]. STC1 affects calcium homeostasis in the heart [##REF##17457011##52##,##REF##12663264##53##] and the brain [##REF##10725397##54##]. Growing evidence also points to a correlation between STC1 expression and the development of human cancers [##REF##14503913##55##,##REF##17395153##56##]. Quantitative RT-PCR also demonstrated a 30.7 ± 5.1-fold increase in STC1 message in primary human SAEC exposed to crocidolite.</p>", "<p>Finally, in recent years a significant number of studies have been directed at understanding how the disruption of dynamic chromatin remodeling is linked to carcinogenesis. Mechanisms including the previously mentioned DNA methylation status and the use of histone modifications have led to the discovery of prognostic biomarkers [##REF##17906200##57##] and the use of HDAC inhibitors as cancer therapeutics [##REF##16088937##58##]. It is of little surprise then to find several differentially regulated genes in crocidolite-treated A549 cells that could participate in chromatin remodeling including the Jumonji domain histone demethylases <italic>JMJD1C</italic>, <italic>JMJD3 </italic>and <italic>JMJD1A</italic>, all of which showed increased expression (Supplementary Table 1). Other genes of interest are discussed below.</p>", "<title>Pathway Analysis Provides Unique View of Function-Based Networks in Crocidolite-Treated Cells</title>", "<p>In order to extract novel biological insight from the large number of genes upregulated/downregulated in our study, we employed a structured network knowledge-based approach to analyze genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ingenuity.com\"/>. Networks are generated not only based on functional interactions but also statistical likelihood. Genes/gene products are represented as nodes and are color-coded to represent fold-change in expression level. Interactions between nodes are designated as edges, or lines, and represent physical, transcriptional, and enzymatic interactions.</p>", "<title>Statistically Significant Function-based Networks and Pathways</title>", "<p>Using expression changes that were differentially regulated by ± 2-fold and having p values less than or equal to 0.01, Ingenuity Pathway^®Analysis demonstrated a highly complex set of 16 interconnected networks. These networks were related to cell death, cancer, cell cycle, cellular growth and proliferation, and gene expression. All networks had at least one gene in common and many had two genes in common, underscoring the interplay and complexity of the crocidolite response. The top scoring network (Figure ##FIG##3##4A##) was composed of genes related to cell death, organism survival and cancer, and highlighted <italic>MYC</italic>, <italic>PDGF BB</italic>, and <italic>EPAS1/HIF2 </italic>as prominent nodes. In particular, <italic>EPAS1 </italic>was a node for four genes whose expression levels changed 6-fold or greater. EPAS1 (endothelial PAS domain protein-1, or HIF2α) is one of the transcription factors which belong to the basic helix-loop-helix PAS family. It shares sequence similarity to HIF-1α and analogously to HIF-1α, regulates transcription of <italic>VEGF </italic>and is observed to be upregulated at both the message and protein levels in A549 cells as a result of hypoxia [##REF##11751212##59##]. Prognostic significance of increased levels of EPAS1 mRNA and/or protein has been observed in liver [##REF##17589895##60##] and colon [##REF##17717129##61##] cancers. Interestingly, EPAS1 -/- mice show impaired reactive oxygen species homeostasis [##REF##12750163##62##], which may be linked to the role of EPAS1 in maintaining mitochondrial homeostasis [##REF##17322295##63##], creating a hypothetical link between EPAS1 function and response to crocidolite.</p>", "<p>This first network (Figure ##FIG##3##4A##) is linked to the Nrf2-mediated oxidative stress pathway (one of the top scoring canonical pathways in our data set shown in Figure ##FIG##3##4B##) via the <italic>MAFF </italic>node. Cellular use of this canonical pathway has been linked to tumor cell survival by maintaining cellular redox homeostasis and protection against oxidative insult. Heterozygous Nrf2 (+/-) mice exposed to crocidolite fibers exhibit accelerated development of malignant mesotheliomas compared to wild-type littermates [##REF##16920675##64##]. Several of the known Nrf2 targets did not show significant changes in expression levels in our data set (data not shown). Although not all of the downstream targets of <italic>NRF2 </italic>were differentially upregulated upon exposure to crocidolite at 6 μg/cm², message levels for many of the Nrf2 targets were present in above average amounts on both the control and treated chips. Furthermore, data suggests that this pathway may be activated in a hierarchical fashion [##REF##14522998##35##], dependent on exposure. Selective activation of the Nrf2 pathway may contribute to carcinogenicity of the crocidolite fibers, while dysfunctional constitutive activation of Nrf2 [##REF##17020408##65##] has been observed in non-small-cell lung cancer.</p>", "<p>The topscoring network illustrates the interplay between processes involved in both cell survival/proliferation and cell death/apoptosis when A549 cells are exposed to crocidolite. Activation of the Nrf2 cytoprotective pathway in the transcriptome of crocidolite-treated A549 cells is imperfect. The observed selective Nrf2 target expression would define an environment that is rich in hydrogen peroxide and incapable of redox homeostasis.</p>", "<title>A Global View of the Functional Networks in A549 Cells in Response to Crocidolite</title>", "<p>Another approach to gain insight about the functional significance of the global changes in crocidolite-induced gene expression is to merge the individual networks and then identify nodes that are used frequently. Over 500 nodes were observed within the 16 networks, making presentation of the global cellular network difficult. Instead, the top five networks were merged using all known interactions in the knowledge-based database and the nodes arranged according to subcellular location resulting in Figure ##FIG##4##5A##. This representation comprises ~150 genes and their interactions and illustrates a transcriptome encoding an array of extracellular growth factors and cytokines. Even though a population of exposed cells undergoes apoptosis, some cells may survive and be stimulated to proliferate based on factors released from neighboring cells. Several high impact nodes including <italic>MYC, JUN</italic>, Akt, p38, and <italic>PDGF BB</italic>, all of which are established players in the response to asbestos, are also present. Other genes that formed prominent nodes in the prototypical cell or adjacent networks included <italic>PTGS2</italic>, <italic>SMARCA4</italic>, <italic>PTEN</italic>, and <italic>E2F1</italic>. They are shown as separate networks for clarity in Figures ##FIG##4##5B, C## and ##FIG##4##5D##. The <italic>PTGS2 </italic>product, Cox-2, PTEN and E2F1 have previously been implicated in carcinogenesis, but their roles in the epithelial cell response to asbestos have not been studied. Brg1, the protein product of <italic>SMARCA4</italic>, is a SWI/SNF related chromatin remodeling factor which recognizes acetylated lysine groups through bromo domains and is involved in cell growth arrest and apoptosis. Oxidative stress and TNF-α induce histone acetylation and NF-κB/AP-1 activation in alveolar epithelial cells [##REF##12162440##66##] suggesting a potential mechanism to alter gene transcription in lung inflammation using Brg1. Inspection of the network surrounding the <italic>E2F1 </italic>node identified several genes whose expression was differentially regulated by asbestos that also demonstrated molecular interactions with <italic>TNF</italic>. Given the relationship between TNF and NF-κB activation observed in mesothelial cells exposed to crocidolite [##REF##16798876##17##], and the recent identification of E2F1 as a transcriptional activator recruited by NF-κB [##REF##17707233##67##], investigation into the role that E2F1 plays in human lung epithelial cells exposed to crocidolite should be forthcoming.</p>", "<p>This analysis has provided the first function-based global view of the crocidolite-treated A549 transcriptome. Several new candidate crocidolite-related genes were identified in the context of experimentally observed findings. Apparent from the global analysis is a transcriptome bearing signatures of both apoptosis/cell death and cell survival/proliferation.</p>", "<title>Using Pathway Analysis to Probe the Role of p53</title>", "<p>Pathway Analysis also detected significance in p53-mediated processes. This result is consistent with the observation that both amosite and crocidolite induce p53 activation. Specifically, Kamp and co-workers who showed that p53 mediates amosite-induced apoptosis through mitochondrial dysfunction in A549 cells [##REF##16357363##10##]. Although the mechanism is not clear, ROS generated by the mitochondria, p53-mediated transcription, and translocation of p53/BAX appear to be necessary components for apoptosis to occur. The authors suggested that other pro-apoptotic pathways may also be activated and a more thorough study of p53-targeted transcription pathways was needed. Figure ##FIG##5##6## shows a scheme representing these findings overlaid with the expression changes from our data set and molecular interactions identified through network analysis. Since it is unknown whether ROS detection and p53 activation require new protein synthesis, we did not restrict this part of the analysis to differentially regulated genes. Several genes whose expression depends on p53 could be identified that were associated with both apoptosis and proliferation or survival. These results may reflect the expected heterogeneity in the population of cells after exposure to crocidolite, as discussed previously. Although crocidolite induces apoptosis in many of the cells, the bulk transcriptome shows evidence that transcripts are present which could tip the balance in favor of cell cycle arrest and/or cell survival or proliferation. Message levels of the p53-induced molecular switch p21^CIP/WAF1and KLF4 were upregulated in crocidolite-treated cells. Together these two products can have an anti-apoptotic effect [##REF##17016435##68##].</p>", "<p>The importance of p53 in mediating apoptosis in asbestos-treated A549 cells has been documented [##REF##16357363##10##]. Analysis of p53 targets upregulated in the crocidolite-treated A549 transcriptome identified several candidate genes that may function in the observed apoptosis. Interestingly, we also identified several p53 targets associated with cell survival/proliferation. This suggests that p53 may be an important molecular turning point in the decision of crocidolite-treated cells to undergo apoptosis or to proliferate, even in the presence of damaged DNA.</p>" ]

[ "<title>Results and Discussion</title>", "<title>Experimental Design</title>", "<p>Given the difficulties in obtaining sufficient primary human lung epithelial cells to study the complex response to asbestos, many studies have instead employed the A549 human adenocarcinoma cell line. In doing so one must keep in mind that the transformed cell line may not be entirely applicable to normal human lung cells. However, all processes noted below are recapitulated in primary human lung epithelial cells, suggesting that A549 cells represent a valid model system. Importantly, use of a human cell line avoids the inherent differences that are seen between individual patients. Alveolar epithelial type II cells are key participants in inflammation, fibrogenesis, and carcinogenesis [##REF##8909230##23##] and have been described as the targets of asbestos-associated lung carcinomas [##REF##15374964##24##].</p>", "<p>The conditions used for obtaining the gene expression profile for crocidolite treated A549 cells were chosen to mimic conditions where a variety of biochemical observations have previously been made in our laboratories. Exposure of A549 cells to 6 μg/cm²crocidolite for 24 hours had previously been shown to result in the α_vβ₅integrin receptor-mediated endocytosis of asbestos fibers [##REF##16169567##25##], mobilization of iron from the fibers within the cell [##REF##7979379##26##], upregulation of ferritin protein to combat the iron overload [##REF##9143343##27##], production of reactive oxygen intermediates [##REF##14766669##28##], efflux of reduced glutathione [##REF##9400737##9##], DNA damage [##REF##8579364##7##], PARP cleavage and activation of initiator caspases [##REF##12540492##29##]. Thus, at 6 μg/cm²of crocidolite the microarray results could be related to an extensive body of biochemical information already available in A549 cells. In addition, this cell line has been used by other investigators for several studies to explore the mechanisms of DNA damage [##REF##7900829##30##], apoptosis [##REF##16357363##10##], and invasiveness [##REF##17616677##31##]. Use of the A549 human lung epithelial cell line complements studies done in mesothelial cells [##REF##12839939##32##] and by the less carcinogenic chrysotile in bronchial epithelial cells [##REF##11062161##33##]. Our goal was to extend our results beyond lists of genes and ontological classifications to discover new pathways based on functional interactions. Rather than diffusing statistical power by examining differences among multiple time points and asbestos concentrations, this experiment focused on the use of chemically defined crocidolite asbestos, a single concentration of crocidolite versus a control condition, and a single exposure time. This focus allowed for three replicates of mRNA from control and crocidolite-treated cells to be analyzed using the Affymetrix HGU133 Plus 2.0 GeneChip to provide the most comprehensive whole genome expression profile.</p>", "<title>Analysis of the Microarray Data</title>", "<p>Graphical checks of the gene expression data revealed a high-quality data set, with no spatial artifacts in the chip images, and a high degree of reproducibility within both the control and treated replicates (Additional File ##SUPPL##0##1##). Using tools described in the Methods Section and a false discovery rate [##UREF##0##34##] of 0.05, 2,546 genes with q-values (FDR-adjusted p-values) less than 0.05 were called statistically significant. These results are represented in a volcano plot (Figure ##FIG##0##1##).</p>", "<title>Crocidolite Induces Large Changes in the Transcriptome of A549 Human Lung Epithelial Cells</title>", "<p>Among the 54,120 probe sets on the GeneChip, 1808 were significantly up-regulated (492 of which were two-fold or greater), and 738 were significantly down-regulated (27 of which were two-fold or greater) when A549 cells were exposed to 6 μg/cm²crocidolite asbestos for 24 h. Of the probe-sets that changed two-fold or greater, 234 correspond to known genes for the up-regulated probe sets, and 16 of the down-regulated probe sets correspond to known genes (some genes were represented more than once on the chip). Genes that increased in expression five-fold or greater or decreased two-fold or greater and were associated with q-values less than 0.05 are shown in Table ##TAB##0##1##. A complete table of all significant genes can be found as Additional File ##SUPPL##1##2##. The observation that most of the expression changes are upregulated is contradictory to a previous microarray study in A549 cells [##REF##17331233##22##] which used a smaller dose of crocidolite (2 μg/cm²). A direct comparison of the two data sets was difficult due to differences in experimental design. Namely, replicates at a single time point were used in the current study versus single chips over a time course, and a lower crocidolite concentration, which is a likely cause for some differences. Cells exposed to asbestos may demonstrate a hierarchical oxidative stress response [##REF##14522998##35##]. Additionally, small amounts of asbestos have been shown to result in proliferation [##REF##15374964##24##]. This may be attributed to a transient response to an increase in iron, which is limiting in cells in culture. However, comparison of individual expression changes in our data set to other known experimental results (discussed below) demonstrated that our data set is consistent with the literature.</p>", "<p>Hierarchical clustering analysis (Figure ##FIG##1##2A##) of our data set showed that the majority of the up-regulated probe sets clustered together in four different hierarchical clusters. The down-regulated probe sets were mainly in one hierarchical cluster, but had several individual genes spread throughout the dendrogram. Within the four up-regulated clusters, 24 genes that were upregulated 5-fold could be mapped by functional String analysis shown in Fig ##FIG##1##2B##. Most of the gene products are connected; i.e., could be linked functionally by way of known molecular interactions. Three major pathways (MAPK, JNK/SAPK and cytokine-cytokine receptor interactions) are represented in the cluster. This result is consistent with what is currently known about the effect of asbestos in epithelial and mesothelial cells. When the down-regulated genes were functionally clustered, only two (<italic>fyr </italic>and <italic>uvo</italic>) out of 16 had a connection (data not shown).</p>", "<title>Validation of the Microarray Data</title>", "<p>Validation of the microarray data was confirmed by quantitative RT-PCR on four of the genes (<italic>Egr1</italic>, <italic>ATF3</italic>, c-<italic>Jun</italic>, and <italic>JunB</italic>) and was further corroborated with previously noted results from experiments using human cells/cell lines (Table ##TAB##1##2##). Quantitative RT-PCR also demonstrated that increases in Egr-1, ATF3, c-Jun, and JunB message occurred after 6 hours and continued to increase through 24 hours (data not shown). Increased mRNA expression from <italic>ATF3</italic>, c-<italic>Jun</italic>, and <italic>JunB </italic>was also observed by quantitative RT-PCR in primary human epithelial cells from small airways (SAEC) treated with crocidolite (data not shown). Increased protein expression in A549 cells exposed to crocidolite was observed for ATF3, c-Jun, and JunB (data not shown). Finally, previous results using asbestos-treated A549 cells have demonstrated increased mRNA and/or protein levels for <italic>IL8, TP53, HMOX1, CDKN1A, SOD2 </italic>and c-<italic>myc </italic>(see Table ##TAB##1##2## for additional references). The reproducibility of the microarray replicates, the significance level of the expression changes, and the validation by quantitative RT-PCR suggest that a highly useful and validated data set was obtained in this study. Furthermore, the large number of significant genes allowed us to perform a comprehensive analysis of the crocidolite-induced transcriptome in human lung epithelial cells.</p>", "<title>Specific Changes in the Crocidolite-Treated Transcriptome</title>", "<p>Although it is clearly established that asbestos induces DNA damage in both primary cells and cell culture lines, the literature illustrates that the molecular mechanism underlying this process and how the fate of the cell is dictated are multifaceted. Although ROS are intimately tied to the mechanism of asbestos-induced fibrosis and carcinogenesis, ROS alone do not offer a complete understanding of the asbestos response. In order to identify genes for which expression level changes are specific for crocidolite compared to oxidative stress, we compared our data set to expression changes that occur in A549 cells when exposed to hydrogen peroxide. In a previous study that documented changes in the A549 cell transcriptome, Cotgreave and co-workers [##REF##15019973##36##] showed that treatment of A549 cells with hydrogen peroxide results in DNA damage and apoptosis. Both hydrogen peroxide and crocidolite asbestos induced the upregulation of <italic>TNFRS10B, PPP1R15A, GADD34, CDKN1A, BTG2, DUSP1, DUSP5, DUSP14, SDC4, GDF15, IL8, ADM, FST, IER3, FOS, HMOX1, ATF3</italic>, and <italic>ZFP36</italic>. Therefore, expression changes in these genes may represent a response to an oxidative stress. Several unique genes that are differentially regulated in the crocidolite data set are noted in Table ##TAB##0##1## and include some genes which are associated with carcinogenesis such as <italic>STC1, IL6, FN1, BRE</italic>, and <italic>PTGS2</italic>. Differences between the hydrogen peroxide-treated and crocidolite-treated transcriptomes may be due to the additional iron released from fibers, present in cells treated with crocidolite, or reactive nitrogen species, changes in glutathione content and/or the involvement of processes initiated at the cell surface by the fiber. It will be very interesting to investigate if these apparent crocidolite-specific gene regulations play a role in crocidolite-induced cytobiological endpoints.</p>", "<title>Ontological Analysis of the Crocidolite-Treated Lung Transcriptome</title>", "<p>In order to identify themes in the global expression pattern of crocidolite-treated A549 cells, we used Gene Ontology (GO) classification. The differentially expressed genes (up-regulated/down-regulated ± 2-fold with p-values less than 0.2) were analyzed using Onto-Express <ext-link ext-link-type=\"uri\" xlink:href=\"http://vortex.cs.wayne.edu/\"/>. The Biological Process tree was expanded to the fourth tier in the hierarchy as a balance between specificity and coverage. Processes affected by crocidolite are shown in Figure ##FIG##2##3A##. Within the Cellular Metabolism classification, processes involved in transcription and phosphorus metabolism were highly represented. Expansion of Molecular Functions to the third tier revealed a large number of genes with functions related to transcription (over-represented in Protein binding (Figure ##FIG##2##3B##)). This observation was expanded upon by performing a global test [##REF##14693814##37##, ####REF##15657105##38##, ##UREF##1##39####1##39##] to identify specific gene ontologies related to transcription, where the expression levels of all the genes in the ontology give useful information for predicting the clinical outcome (or in this case, a cellular outcome of crocidolite exposure). Ontologies of particular interest related to transcription factor activity (GO:0003700) are summarized in Figure ##FIG##2##3C##, with nodes colored to correspond to global test p-values; the lighter nodes have lower p-values. To reduce visual clutter, only the last four digits of each ontology's identifier are reported in Figure ##FIG##2##3C##. The ontological analysis illustrates that transcriptional corepressor activity and repressor activity are highly represented in the data set. Overall the transcriptome of crocidolite-treated human lung epithelial (A549) cells is heavily populated by gene products associated with transcription.</p>", "<p>We also noted that DNA repair terms were not highly represented in the data set. Although this result was initially surprising, we noted that the transcriptome of A549 cells exposed to hydrogen peroxide, which also induces DNA damage, was also underrepresented in DNA repair terms [##REF##15019973##36##]. In order to gain a better understanding of how the transcriptome of crocidolite-treated A549 cells is reorganized in response to the resulting DNA damage, the results of the global test discussed above were also applied to ontologies related to DNA damage/repair. Although this analysis (see Additional File ##SUPPL##2##3##) confirms the overall observation that many of the processes related to DNA repair/damage are not highly represented, the analysis also highlights specific nodes in the GO tree related to DNA damage-induced phosphorylation (GO:6975), DNA dealkylation (GO:6307), DNA methylation (GO:6306), and DNA alkylation (GO:6305). In light of the several studies directed at linking promoter methylation status and carcinogenesis (reviewed in [##REF##16699174##40##]), it is interesting to point out that in as little as 24 hours of crocidolite exposure, the A549 transcriptome may be poised to affect the DNA methylation status that is associated with lung cancer pathogenesis.</p>", "<title>Identification of Novel, Putative Crocidolite-Related Genes</title>", "<p>Even though this study was initiated to understand the broad changes that occur in the lung transcriptome upon crocidolite exposure, we also sought to identify novel genes that had no previous association with crocidolite and to identify genes that may be downstream targets of well-known crocidolite-related players. Given the complex effects that asbestos has on the lung system, we expected that a systems biology approach may provide novel avenues to study. <italic>NR4A1</italic>, <italic>NR4A2</italic>, and <italic>NR4A3 </italic>belong to the steroid nuclear hormone receptor superfamily of immediate early genes that are induced by serum, growth factors and receptor engagement and are thus implicated in cell mitogenic responses. Although previously characterized as pro-survival, studies have also suggested an important role for these receptors in cell transformation and tumorigenicity via their anti-apoptotic and pro-apoptotic functions [##REF##16493583##41##]. Thus, depending on cellular context, these gene products may serve as switches in determining cell fate. All three members of this family show increased expression in our data set (Additional File ##SUPPL##1##2##) but have not previously been implicated in crocidolite-induced pulmonary toxicity.</p>", "<p>Modulation of apoptosis can also be affected by BRE (brain and reproductive organ-expressed protein), a stress-modulating protein also known as TNFRSF1A modulator. <italic>BRE </italic>expression was upregulated &gt;7-fold in crocidolite-treated A549 cells. Exogenous overexpression of BRE can attenuate intrinsic apoptosis and promote growth of the transfected Lewis lung carcinoma line in mice [##REF##15582573##42##] which is consistent with the recent finding that BRE protein is overexpressed in human hepatocellular carcinomas [##REF##17704801##43##]. Given the ability of BRE to interact with both Fas [##REF##15465831##44##] and the TNF receptor 1 [##REF##9737713##45##], and the observation that TNFα can attenuate asbestos cytotoxicity in mesothelial cells [##REF##16798876##17##], it will be very interesting to investigate possible roles of BRE in crocidolite-treated human lung cells. Also noteworthy is the upregulation of several \"early response\" NF-κB targets [##REF##16191192##46##] in our dataset (Additional File ##SUPPL##1##2##) including <italic>TNFAIP3, IL8, IL6, CXCL1, CXCL2, CXCL3, PTGS2</italic>, and <italic>PLAU</italic>. Activation of the NF-κB pathway is thought to play a critical role in cell survival in asbestos-treated cells [##REF##16798876##17##], but only a few of the downstream targets of NF-κB have been identified.</p>", "<p>The relationship between asbestos and calcium has received little attention in recent years, but the initial studies suggest that calcium may have an important role to play (reviewed in [##REF##12757757##47##]). Perhaps most compelling is the ability of the calcium-chelator Quin-2 to prevent crocidolite-induced DNA breaks [##REF##7526185##48##]. Additionally, several players in the asbestos response are regulated by calcium levels, e.g., protein kinase C [##REF##17200189##15##]. We were therefore interested in determining if the crocidolite-treated transcriptome demonstrated any clues regarding the regulation of calcium homeostasis. We observed that expression of <italic>MCTP1 </italic>and <italic>STC1 </italic>were both upregulated in our data set by 7.3- and 12.9-fold, respectively. MCTP1 is a transmembrane protein that binds calcium ions via C₂domains. Unique properties of this protein suggest that these proteins function in Ca²⁺signaling at the membrane [##REF##15528213##49##]. Stanniocalcin 1 (STC1) has long been studied as a regulator of both phosphate and calcium homeostasis in bony fish, but has recently received attention in mammalian systems. STC1 is a glycoprotein present in a variety of mammalian tissues where it can function as a regulator of gene expression and modulator of transendothelial cell migration [##REF##17032941##50##], and can also affect cellular metabolism by perturbing mitochondrial electron transport chain and mitochondrial calcium transport [##REF##17092635##51##]. STC1 affects calcium homeostasis in the heart [##REF##17457011##52##,##REF##12663264##53##] and the brain [##REF##10725397##54##]. Growing evidence also points to a correlation between STC1 expression and the development of human cancers [##REF##14503913##55##,##REF##17395153##56##]. Quantitative RT-PCR also demonstrated a 30.7 ± 5.1-fold increase in STC1 message in primary human SAEC exposed to crocidolite.</p>", "<p>Finally, in recent years a significant number of studies have been directed at understanding how the disruption of dynamic chromatin remodeling is linked to carcinogenesis. Mechanisms including the previously mentioned DNA methylation status and the use of histone modifications have led to the discovery of prognostic biomarkers [##REF##17906200##57##] and the use of HDAC inhibitors as cancer therapeutics [##REF##16088937##58##]. It is of little surprise then to find several differentially regulated genes in crocidolite-treated A549 cells that could participate in chromatin remodeling including the Jumonji domain histone demethylases <italic>JMJD1C</italic>, <italic>JMJD3 </italic>and <italic>JMJD1A</italic>, all of which showed increased expression (Supplementary Table 1). Other genes of interest are discussed below.</p>", "<title>Pathway Analysis Provides Unique View of Function-Based Networks in Crocidolite-Treated Cells</title>", "<p>In order to extract novel biological insight from the large number of genes upregulated/downregulated in our study, we employed a structured network knowledge-based approach to analyze genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ingenuity.com\"/>. Networks are generated not only based on functional interactions but also statistical likelihood. Genes/gene products are represented as nodes and are color-coded to represent fold-change in expression level. Interactions between nodes are designated as edges, or lines, and represent physical, transcriptional, and enzymatic interactions.</p>", "<title>Statistically Significant Function-based Networks and Pathways</title>", "<p>Using expression changes that were differentially regulated by ± 2-fold and having p values less than or equal to 0.01, Ingenuity Pathway^®Analysis demonstrated a highly complex set of 16 interconnected networks. These networks were related to cell death, cancer, cell cycle, cellular growth and proliferation, and gene expression. All networks had at least one gene in common and many had two genes in common, underscoring the interplay and complexity of the crocidolite response. The top scoring network (Figure ##FIG##3##4A##) was composed of genes related to cell death, organism survival and cancer, and highlighted <italic>MYC</italic>, <italic>PDGF BB</italic>, and <italic>EPAS1/HIF2 </italic>as prominent nodes. In particular, <italic>EPAS1 </italic>was a node for four genes whose expression levels changed 6-fold or greater. EPAS1 (endothelial PAS domain protein-1, or HIF2α) is one of the transcription factors which belong to the basic helix-loop-helix PAS family. It shares sequence similarity to HIF-1α and analogously to HIF-1α, regulates transcription of <italic>VEGF </italic>and is observed to be upregulated at both the message and protein levels in A549 cells as a result of hypoxia [##REF##11751212##59##]. Prognostic significance of increased levels of EPAS1 mRNA and/or protein has been observed in liver [##REF##17589895##60##] and colon [##REF##17717129##61##] cancers. Interestingly, EPAS1 -/- mice show impaired reactive oxygen species homeostasis [##REF##12750163##62##], which may be linked to the role of EPAS1 in maintaining mitochondrial homeostasis [##REF##17322295##63##], creating a hypothetical link between EPAS1 function and response to crocidolite.</p>", "<p>This first network (Figure ##FIG##3##4A##) is linked to the Nrf2-mediated oxidative stress pathway (one of the top scoring canonical pathways in our data set shown in Figure ##FIG##3##4B##) via the <italic>MAFF </italic>node. Cellular use of this canonical pathway has been linked to tumor cell survival by maintaining cellular redox homeostasis and protection against oxidative insult. Heterozygous Nrf2 (+/-) mice exposed to crocidolite fibers exhibit accelerated development of malignant mesotheliomas compared to wild-type littermates [##REF##16920675##64##]. Several of the known Nrf2 targets did not show significant changes in expression levels in our data set (data not shown). Although not all of the downstream targets of <italic>NRF2 </italic>were differentially upregulated upon exposure to crocidolite at 6 μg/cm², message levels for many of the Nrf2 targets were present in above average amounts on both the control and treated chips. Furthermore, data suggests that this pathway may be activated in a hierarchical fashion [##REF##14522998##35##], dependent on exposure. Selective activation of the Nrf2 pathway may contribute to carcinogenicity of the crocidolite fibers, while dysfunctional constitutive activation of Nrf2 [##REF##17020408##65##] has been observed in non-small-cell lung cancer.</p>", "<p>The topscoring network illustrates the interplay between processes involved in both cell survival/proliferation and cell death/apoptosis when A549 cells are exposed to crocidolite. Activation of the Nrf2 cytoprotective pathway in the transcriptome of crocidolite-treated A549 cells is imperfect. The observed selective Nrf2 target expression would define an environment that is rich in hydrogen peroxide and incapable of redox homeostasis.</p>", "<title>A Global View of the Functional Networks in A549 Cells in Response to Crocidolite</title>", "<p>Another approach to gain insight about the functional significance of the global changes in crocidolite-induced gene expression is to merge the individual networks and then identify nodes that are used frequently. Over 500 nodes were observed within the 16 networks, making presentation of the global cellular network difficult. Instead, the top five networks were merged using all known interactions in the knowledge-based database and the nodes arranged according to subcellular location resulting in Figure ##FIG##4##5A##. This representation comprises ~150 genes and their interactions and illustrates a transcriptome encoding an array of extracellular growth factors and cytokines. Even though a population of exposed cells undergoes apoptosis, some cells may survive and be stimulated to proliferate based on factors released from neighboring cells. Several high impact nodes including <italic>MYC, JUN</italic>, Akt, p38, and <italic>PDGF BB</italic>, all of which are established players in the response to asbestos, are also present. Other genes that formed prominent nodes in the prototypical cell or adjacent networks included <italic>PTGS2</italic>, <italic>SMARCA4</italic>, <italic>PTEN</italic>, and <italic>E2F1</italic>. They are shown as separate networks for clarity in Figures ##FIG##4##5B, C## and ##FIG##4##5D##. The <italic>PTGS2 </italic>product, Cox-2, PTEN and E2F1 have previously been implicated in carcinogenesis, but their roles in the epithelial cell response to asbestos have not been studied. Brg1, the protein product of <italic>SMARCA4</italic>, is a SWI/SNF related chromatin remodeling factor which recognizes acetylated lysine groups through bromo domains and is involved in cell growth arrest and apoptosis. Oxidative stress and TNF-α induce histone acetylation and NF-κB/AP-1 activation in alveolar epithelial cells [##REF##12162440##66##] suggesting a potential mechanism to alter gene transcription in lung inflammation using Brg1. Inspection of the network surrounding the <italic>E2F1 </italic>node identified several genes whose expression was differentially regulated by asbestos that also demonstrated molecular interactions with <italic>TNF</italic>. Given the relationship between TNF and NF-κB activation observed in mesothelial cells exposed to crocidolite [##REF##16798876##17##], and the recent identification of E2F1 as a transcriptional activator recruited by NF-κB [##REF##17707233##67##], investigation into the role that E2F1 plays in human lung epithelial cells exposed to crocidolite should be forthcoming.</p>", "<p>This analysis has provided the first function-based global view of the crocidolite-treated A549 transcriptome. Several new candidate crocidolite-related genes were identified in the context of experimentally observed findings. Apparent from the global analysis is a transcriptome bearing signatures of both apoptosis/cell death and cell survival/proliferation.</p>", "<title>Using Pathway Analysis to Probe the Role of p53</title>", "<p>Pathway Analysis also detected significance in p53-mediated processes. This result is consistent with the observation that both amosite and crocidolite induce p53 activation. Specifically, Kamp and co-workers who showed that p53 mediates amosite-induced apoptosis through mitochondrial dysfunction in A549 cells [##REF##16357363##10##]. Although the mechanism is not clear, ROS generated by the mitochondria, p53-mediated transcription, and translocation of p53/BAX appear to be necessary components for apoptosis to occur. The authors suggested that other pro-apoptotic pathways may also be activated and a more thorough study of p53-targeted transcription pathways was needed. Figure ##FIG##5##6## shows a scheme representing these findings overlaid with the expression changes from our data set and molecular interactions identified through network analysis. Since it is unknown whether ROS detection and p53 activation require new protein synthesis, we did not restrict this part of the analysis to differentially regulated genes. Several genes whose expression depends on p53 could be identified that were associated with both apoptosis and proliferation or survival. These results may reflect the expected heterogeneity in the population of cells after exposure to crocidolite, as discussed previously. Although crocidolite induces apoptosis in many of the cells, the bulk transcriptome shows evidence that transcripts are present which could tip the balance in favor of cell cycle arrest and/or cell survival or proliferation. Message levels of the p53-induced molecular switch p21^CIP/WAF1and KLF4 were upregulated in crocidolite-treated cells. Together these two products can have an anti-apoptotic effect [##REF##17016435##68##].</p>", "<p>The importance of p53 in mediating apoptosis in asbestos-treated A549 cells has been documented [##REF##16357363##10##]. Analysis of p53 targets upregulated in the crocidolite-treated A549 transcriptome identified several candidate genes that may function in the observed apoptosis. Interestingly, we also identified several p53 targets associated with cell survival/proliferation. This suggests that p53 may be an important molecular turning point in the decision of crocidolite-treated cells to undergo apoptosis or to proliferate, even in the presence of damaged DNA.</p>" ]

[ "<title>Conclusion</title>", "<p>In this study, we have provided a statistically robust and comprehensive global gene expression profile of A549 human lung epithelial cells exposed to crocidolite asbestos. Our data reveal a much altered transcriptome in which a large number of genes show upregulated expression. Crocidolite-treated A549 cells are rich in transcripts encoding extracellular growth factors and cytokines and intracellular regulators/mediators of transcription. A global view based on functional molecular interactions illustrated an intricate network of paths associated with both apoptosis and proliferation/cell survival. This network allowed for the identification of novel, putative crocidolite-related genes, leading to several new hypotheses regarding genes which are important in the response of human lung epithelial cells to crocidolite.</p>", "<p>Our analysis demonstrates the power of a functional network genomics approach to 1) identify and explore relationships between genes of known importance 2) identify novel candidate genes, and 3) observe the complex interplay between genes/gene products that function in seemingly different processes. This study represents the first function-based global approach toward understanding the response of human lung epithelial cells to the carcinogen crocidolite. We have provided graphical representations of the highly interconnected networks that will be instrumental in modeling the impact of new research findings. Our global function-based approach introduces new insights and novel avenues which can now be investigated in more detail to understand the effects of crocidolite on the human lung.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Although exposure to asbestos is now regulated, patients continue to be diagnosed with mesothelioma, asbestosis, fibrosis and lung carcinoma because of the long latent period between exposure and clinical disease. Asbestosis is observed in approximately 200,000 patients annually and asbestos-related deaths are estimated at 4,000 annually[##REF##17375514##1##]. Although advances have been made using single gene/gene product or pathway studies, the complexity of the response to asbestos and the many unanswered questions suggested the need for a systems biology approach. The objective of this study was to generate a comprehensive view of the transcriptional changes induced by crocidolite asbestos in A549 human lung epithelial cells.</p>", "<title>Results</title>", "<p>A statistically robust, comprehensive data set documenting the crocidolite-induced changes in the A549 transcriptome was collected. A systems biology approach involving global observations from gene ontological analyses coupled with functional network analyses was used to explore the effects of crocidolite in the context of known molecular interactions. The analyses uniquely document a transcriptome with function-based networks in cell death, cancer, cell cycle, cellular growth, proliferation, and gene expression. These functional modules show signs of a complex interplay between signaling pathways consisting of both novel and previously described asbestos-related genes/gene products. These networks allowed for the identification of novel, putative crocidolite-related genes, leading to several new hypotheses regarding genes that are important for the asbestos response. The global analysis revealed a transcriptome that bears signatures of both apoptosis/cell death and cell survival/proliferation.</p>", "<title>Conclusion</title>", "<p>Our analyses demonstrate the power of combining a statistically robust, comprehensive dataset and a functional network genomics approach to 1) identify and explore relationships between genes of known importance 2) identify novel candidate genes, and 3) observe the complex interplay between genes/gene products that function in seemingly different processes. This study represents the first function-based global approach toward understanding the response of human lung epithelial cells to the carcinogen crocidolite. Importantly, our investigation paints a much broader landscape for the crocidolite response than was previously appreciated and reveals novel paths to study. Our graphical representations of the function-based global network will be a valuable resource to model new research findings.</p>" ]

[ "<title>Authors' contributions</title>", "<p>LO-B carried out the cell culture and RNA preparations. BG carried out the initial analysis of the raw microarray data and aided LO-B in the clustering of the data. JRS carried out further statistical analyses in order to compare the data set to others and performed the gene ontology analyses. JPH carried out RT-PCR confirmations. AEA and JMH conceived of the study. JMH performed the Pathway Analysis, coordinated all other analyses and wrote the manuscript. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to thank Dr. Daryll DeWald for thoughtful discussion regarding the manuscript. We also acknowledge the advice and microarray expertise of Bart Weimer of the Center for Integrated Biosystems (CIB). We thank Whitney Wooderchak for technical assistance with some of the RT-PCR experiments. Cell culture assistance was provided by Jed Benson. Work done by AEA and JMH was supported by a Utah State University NSF Advanced Seed Grant and a Utah State University CIB Seed Grant.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Volcano plot showing the magnitude of differential expression (log2 fold-change) compared to the measure of statistical significance (-log10 q-value). </bold>Color is on the density scale, so darker colors indicate over-plotting of points. Statistically significant genes are observed above the horizontal line, which corresponds to a q-value of 0.05. The low variability in the data caused a large number of genes (2,546) to be classified as statistically significant.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Unsupervised hierarchical clustering analysis of A549 probe sets in which the expression was altered by crocidolite.</bold><bold>(A) </bold>The main dendogram represents the intensity of each probe set in relation to the entire data set with green being low and red being high. Four major clusters of upregulated genes and two clusters of downregulated genes were observed and are shown as bracketed dendograms where the color represents the intensity of each probe set in relation to each specific cluster. <bold>(B) </bold>STRING analysis using the genes within the upregulated clusters demonstrated a functional relationship between 24 of the genes which encompassed cytokine, MAPkinase and JNK/SAPK signaling pathways.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Gene ontology analysis of the (<bold>A</bold>) Biological Processes and (<bold>B</bold>) Molecular Functions most affected by crocidolite in A549 cells.</bold> In (<bold>C</bold>) a global test to identify ontologies related to transcription was used to pinpoint significant functions. The p-values for each of the GO terms (abbreviated as the last four digits of each ontology's identifier) has been overlaid onto the hierarchical tree where the darkest gray node represents a p = 0.034 and the lightest represents a p = 0.017.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Spatial depiction of the top scoring network and canonical pathways detected in crocidolite-treated A549 cells by Ingenuity Pathway^®Analysis.</bold> The network was algorithmically generated based on the connectivity of each of the transcripts and the molecular interaction knowledge base. Each node represents a gene or gene product for which mRNA expression was upregulated (red) or downregulated (blue) in crocidolite-treated A549 cells. Edges/lines connecting the nodes represent molecular interactions between genes and/or gene products and are supported by at least one reference from the literature, a textbook, or from canonical pathway information stored in the Ingenuity Pathways Knowledge Base. The Nrf2-mediated oxidative stress canonical pathway identified by Pathway Analysis software shows differential upregulation of select genes within the cytoprotective arsenal.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Pathway analysis of representative genes involved in the response of A549 cells exposed to crocidolite.</bold> In <bold>(A) </bold>the top five scoring networks were merged to create a cellular model consisting of ~150 genes for which expression levels changed ± 2-fold and demonstrated p-values less than 0.01. Nodes representing genes are colored red for upregulation or blue for downregulation and the intensity of the color reflects the degree of up- or downregulation. Lines connecting the nodes are indicators of interactions found in the knowledge database or current literature. In (<bold>B</bold>) and <bold>(C) </bold>the networks surrounding <italic>PTGS2</italic>, <italic>SMARCA4</italic>, and <italic>PTEN </italic>have been expanded for clarity. In <bold>(D</bold>) the relationship between <italic>E2F1 </italic>and <italic>TNF </italic>is observed.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Asbestos induces a p53-mediated response in A549 lung cells. </bold>Experimental data is indicated by the thick blue edges and is discussed in more detail in the text. Known p53 targets which may have a role in the asbestos response and their biological effects are shown using thin gray lines. Nodes are color coded shades of red when expression levels increased and shades of blue when expression levels decreased. Nodes surrounded by dashed lines represent genes/gene products which were not represented on the gene chip but which displayed a functional relationship to queried nodes.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>List of genes for which expression increased five-fold or greater or decreased two-fold or greater</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Fold Change</bold></td><td align=\"left\"><bold>Gene Symbol</bold></td><td align=\"left\"><bold>Gene Name</bold></td></tr></thead><tbody><tr><td align=\"left\">115.7</td><td align=\"left\"><bold>EGR1</bold></td><td align=\"left\">Early growth response 1</td></tr><tr><td align=\"left\">38.3</td><td align=\"left\">FOS</td><td align=\"left\">v-Fos FBJ murine osteosarcoma viral oncogene homolog</td></tr><tr><td align=\"left\">25.3</td><td align=\"left\">ATF3</td><td align=\"left\">Activating transcription factor 3</td></tr><tr><td align=\"left\">19.5</td><td align=\"left\"><bold>GEM</bold></td><td align=\"left\">GTP binding protein overexpressed in skeletal muscle</td></tr><tr><td align=\"left\">17.1</td><td align=\"left\"><bold>NR4A2</bold></td><td align=\"left\">Nuclear receptor subfamily 4, group A, member 2</td></tr><tr><td align=\"left\">16.6</td><td align=\"left\">IL8</td><td align=\"left\">Interleukin 8</td></tr><tr><td align=\"left\">15.9</td><td align=\"left\">FST</td><td align=\"left\">Follistatin</td></tr><tr><td align=\"left\">15.6</td><td align=\"left\">PPP1R15A</td><td align=\"left\">Protein phosphatase 1, regulatory (inhibitor) subunit 15A</td></tr><tr><td align=\"left\">13.7</td><td align=\"left\"><bold>STC1</bold></td><td align=\"left\">Stanniocalcin 1</td></tr><tr><td align=\"left\">12.1</td><td align=\"left\"><bold>MAFF</bold></td><td align=\"left\">v-Maf musculoaponeurotic fibrosarcoma oncogene homolog F (avian)</td></tr><tr><td align=\"left\">11.2</td><td align=\"left\"><bold>CXCL2</bold></td><td align=\"left\">Chemokine (C-X-C motif) ligand 2</td></tr><tr><td align=\"left\">10.4</td><td align=\"left\"><bold>TNFAIP3</bold></td><td align=\"left\">Tumor necrosis factor, alpha-induced protein 3</td></tr><tr><td align=\"left\">9.4</td><td align=\"left\"><bold>MXD1</bold></td><td align=\"left\">MAX dimerization protein 1</td></tr><tr><td align=\"left\">9.1</td><td align=\"left\"><bold>ARID5B</bold></td><td align=\"left\">AT rich interactive domain 5B (MRF1-like)</td></tr><tr><td align=\"left\">9.0</td><td align=\"left\"><bold>NR4A3</bold></td><td align=\"left\">Nuclear receptor subfamily 4, group A, member 3</td></tr><tr><td align=\"left\">8.6</td><td align=\"left\"><bold>JUN</bold></td><td align=\"left\">v-Jun sarcoma virus 17 oncogene homolog (avian)</td></tr><tr><td align=\"left\">7.8</td><td align=\"left\"><bold>LOC153222</bold></td><td align=\"left\">adult retina protein</td></tr><tr><td align=\"left\">7.4</td><td align=\"left\"><bold>BRE</bold></td><td align=\"left\">brain and reproductive organ-expressed (TNFRSF1A modulator)</td></tr><tr><td align=\"left\">7.2</td><td align=\"left\"><bold>MCTP1</bold></td><td align=\"left\">Multiple C2 domains, transmembrane 1</td></tr><tr><td align=\"left\">7.2</td><td align=\"left\"><bold>DDIT3</bold></td><td align=\"left\">DNA-damage-inducible transcript 3</td></tr><tr><td align=\"left\">7.2</td><td align=\"left\"><bold>FOSB</bold></td><td align=\"left\">FBJ murine osteosarcoma viral oncogene homolog B</td></tr><tr><td align=\"left\">7.1</td><td align=\"left\">GDF15</td><td align=\"left\">Growth differentiation factor 15</td></tr><tr><td align=\"left\">6.9</td><td align=\"left\"><bold>CITED2</bold></td><td align=\"left\">Cbp/p300-interacting transactivator, with Glu/Asp-rich carboxy-terminal domain, 2</td></tr><tr><td align=\"left\">6.9</td><td align=\"left\"><bold>DUSP6</bold></td><td align=\"left\">Dual specificity phosphatase 6</td></tr><tr><td align=\"left\">6.6</td><td align=\"left\"><bold>CXCL1</bold></td><td align=\"left\">Chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha)</td></tr><tr><td align=\"left\">6.5</td><td align=\"left\"><bold>IL24</bold></td><td align=\"left\">Interleukin 24</td></tr><tr><td align=\"left\">6.3</td><td align=\"left\"><bold>SPRY2</bold></td><td align=\"left\">Sprouty homolog 2 (Drosophila)</td></tr><tr><td align=\"left\">6.1</td><td align=\"left\"><bold>PTGS2</bold></td><td align=\"left\">Prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase)</td></tr><tr><td align=\"left\">6.0</td><td align=\"left\"><bold>KLF6</bold></td><td align=\"left\">Kruppel-like factor 6</td></tr><tr><td align=\"left\">6.0</td><td align=\"left\"><bold>IL11</bold></td><td align=\"left\">Interleukin 11</td></tr><tr><td align=\"left\">5.6</td><td align=\"left\"><bold>IRAK2</bold></td><td align=\"left\">Interleukin-1 receptor-associated kinase 2</td></tr><tr><td align=\"left\">5.5</td><td align=\"left\"><bold>IL6</bold></td><td align=\"left\">Interleukin 6 (interferon, beta 2)</td></tr><tr><td align=\"left\">5.5</td><td align=\"left\"><bold>HIST1H4H</bold></td><td align=\"left\">Histone 1, H4h</td></tr><tr><td align=\"left\">5.4</td><td align=\"left\"><bold>FNIP1</bold></td><td align=\"left\">folliculin interacting protein 1</td></tr><tr><td align=\"left\">5.3</td><td align=\"left\"><bold>HIST2H2BE</bold></td><td align=\"left\">Histone 2, H2be</td></tr><tr><td align=\"left\">5.2</td><td align=\"left\"><bold>MCL1</bold></td><td align=\"left\">Myeloid cell leukemia sequence 1 (BCL2-related)</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>DUSP10</bold></td><td align=\"left\">Dual specificity phosphatase 10</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>DHRS2</bold></td><td align=\"left\">Dehydrogenase/reductase (SDR family) member 2</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>SYNE1</bold></td><td align=\"left\">Spectrin repeat containing, nuclear envelope 1</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>HAS2</bold></td><td align=\"left\">Hyaluronan synthase 2</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>PER1</bold></td><td align=\"left\">period homolog 1 (Drosophila)</td></tr><tr><td align=\"left\">5.1</td><td align=\"left\"><bold>ZBTB10</bold></td><td align=\"left\">zinc finger and BTB domain containing 10</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>FN1</bold></td><td align=\"left\">Fibronectin 1</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>BCL2L11</bold></td><td align=\"left\">BCL2-like 11 (apoptosis facilitator)</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>COL5A1</bold></td><td align=\"left\">collagen, type V, alpha 1</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>VAV3</bold></td><td align=\"left\">vav 3 oncogene</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>CSRP2BP</bold></td><td align=\"left\">CSRP2 binding protein</td></tr><tr><td align=\"left\">-2.0</td><td align=\"left\"><bold>PRSS23</bold></td><td align=\"left\">protease, serine, 23</td></tr><tr><td align=\"left\">-2.1</td><td align=\"left\"><bold>NRP2</bold></td><td align=\"left\">Neuropilin 2</td></tr><tr><td align=\"left\">-2.1</td><td align=\"left\"><bold>DAPK1</bold></td><td align=\"left\">Death-associated protein kinase 1</td></tr><tr><td align=\"left\">-2.1</td><td align=\"left\"><bold>CDH1</bold></td><td align=\"left\">Cadherin 1, type 1, E-cadherin (epithelial)</td></tr><tr><td align=\"left\">-2.2</td><td align=\"left\"><bold>ST8SIA4</bold></td><td align=\"left\">ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 4</td></tr><tr><td align=\"left\">-2.2</td><td align=\"left\"><bold>RNASE4</bold></td><td align=\"left\">Ribonuclease, RNase A family, 4</td></tr><tr><td align=\"left\">-2.2</td><td align=\"left\"><bold>FGG</bold></td><td align=\"left\">Fibrinogen gamma chain</td></tr><tr><td align=\"left\">-2.1</td><td align=\"left\"><bold>STAT4</bold></td><td align=\"left\">Signal transducer and activator of transcription 4</td></tr><tr><td align=\"left\">-2.1</td><td align=\"left\"><bold>NTRK3</bold></td><td align=\"left\">Neurotrophic tyrosine kinase, receptor, type 3</td></tr><tr><td align=\"left\">-2.3</td><td align=\"left\"><bold>PCDH9</bold></td><td align=\"left\">Protocadherin 9</td></tr><tr><td align=\"left\">-2.2</td><td align=\"left\"><bold>CYP4F3</bold></td><td align=\"left\">Cytochrome P450, family 4, subfamily F, polypeptide 3</td></tr><tr><td align=\"left\">-2.2</td><td align=\"left\">ST8SIA4</td><td align=\"left\">ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 4</td></tr><tr><td align=\"left\">-2.3</td><td align=\"left\"><bold>MAP2K6</bold></td><td align=\"left\">Mitogen-activated protein kinase kinase 6</td></tr><tr><td align=\"left\">-2.3</td><td align=\"left\"><bold>LXN</bold></td><td align=\"left\">latexin</td></tr><tr><td align=\"left\">-2.3</td><td align=\"left\"><bold>TM4SF20</bold></td><td align=\"left\">transmembrane 4 L six family member 20</td></tr><tr><td align=\"left\">-2.4</td><td align=\"left\"><bold>AKR1C1///AKR1C2</bold></td><td align=\"left\">Aldo-keto reductase family 1, member C1 (dihydrodiol dehydrogenase 1; 20-alpha (3-alpha)-hydroxysteroid dehydrogenase)///aldo-keto reductase family 1, member C2 (dihydrodiol dehydrogenase 2; bile acid binding protein; 3-alpha hydroxysteroid dehydrogenase, type III)</td></tr><tr><td align=\"left\">-2.7</td><td align=\"left\"><bold>SLC40A1</bold></td><td align=\"left\">Solute carrier family 40 (iron-regulated transporter), member 1</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Validation of the microarray data from crocidolite-treated human A549 cells</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Gene</bold></td><td align=\"center\"><bold>Alias for Protein Product</bold></td><td align=\"center\"><bold>Affymetrix* (fold change) this study</bold></td><td align=\"center\"><bold>QRT-PCR (fold change) this study</bold></td><td align=\"left\"><bold>Changes in mRNA levels in human cells observed by other groups</bold></td></tr></thead><tbody><tr><td align=\"left\"><italic>EGR1</italic></td><td align=\"center\">Egr1</td><td align=\"right\">115.7</td><td align=\"right\">281.7 ± 3.8</td><td/></tr><tr><td align=\"left\"><italic>ATF3</italic></td><td align=\"center\">ATF3</td><td align=\"right\">25.3</td><td align=\"right\">23.7 ± 0.1</td><td/></tr><tr><td align=\"left\">c-<italic>Jun</italic></td><td align=\"center\">c-Jun</td><td align=\"right\">8.6</td><td align=\"right\">10.5 ± 0.7</td><td/></tr><tr><td align=\"left\"><italic>JunB</italic></td><td align=\"center\">JunB</td><td align=\"right\">2.2</td><td align=\"right\">3.6 ± 0.2</td><td/></tr><tr><td align=\"left\"><italic>IL8</italic></td><td align=\"center\">Interleukin 8</td><td align=\"right\">16.6</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##8969274##73##]</td></tr><tr><td align=\"left\"><italic>TP53</italic></td><td align=\"center\">p53</td><td align=\"right\">1.8</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##14646501##16##,##REF##9400714##74##]</td></tr><tr><td align=\"left\"><italic>SOD2</italic></td><td align=\"center\">Mn-SOD</td><td align=\"right\">2.2</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##8118652##75##]^‡</td></tr><tr><td align=\"left\"><italic>HMOX1</italic></td><td align=\"center\">Heme oxygenase 1</td><td align=\"right\">2.1</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##8118652##75##,##REF##17365036##76##]^†</td></tr><tr><td align=\"left\">c-<italic>myc</italic></td><td align=\"center\">myc</td><td align=\"right\">2.0</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##11198217##77##]</td></tr><tr><td align=\"left\"><italic>CDKN1A</italic></td><td align=\"center\">p21, Cip1</td><td align=\"right\">1.9</td><td align=\"right\">N.D.</td><td align=\"left\">Increased [##REF##14646501##16##,##REF##9400714##74##]</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional File 1</title><p><bold>Low variability in the dataset</bold>. A comparison of the RMA expression values for the 54,675 probe sets on each of the six arrays. The tighter relationships within the Control and Treated groups are indicative of a data set with low variability. This low variability allowed the identification of a large number (2,546) of statistically significantly differentially expressed genes.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional File 2</title><p>List of genes for which expression was increased or decreased two-fold or greater.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional File 3</title><p><bold>Global test to identify specific gene ontologies related to DNA repair and damage</bold>. A global test (Goeman et al., 2004; Goeman et al., 2005; Goeman and Oosting 2007) was used to identify specific gene ontologies related to DNA repair and damage. The p-values for each of the GO terms (abbreviated as the last four digits of each ontology's identifier) has been overlaid onto the hierarchical tree where the darkest blue node represents a p = 0.15 and the lightest represents a p = 0.016.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>A549 human lung epithelial cells were exposed to crocidolite asbestos at 6 g/cm²for 24 h. Genes for which expression levels increased 5.0 fold or greater, or decreased 2.0 fold or greater, having q values less than 0.05 are shown. Probe sets associated with products of unknown function were not included. Bold-faced genes were not observed in the statistically upregulated expression profile of hydrogen-peroxide-treated A549 cells [##REF##15019973##36##]. A list of all genes for which expression levels changed 2.0 fold or greater can be found as Additional File ##SUPPL##1##2##.</p></table-wrap-foot>", "<table-wrap-foot><p>*represents significantly greater than control, q less than 0.05; N.D., not determined</p><p>^†chrysotile-treated A549 human lung epithelial cells</p><p>^‡crocidolite-treated human pleural mesothelial cells</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2164-9-376-1\"/>", "<graphic xlink:href=\"1471-2164-9-376-2\"/>", "<graphic xlink:href=\"1471-2164-9-376-3\"/>", "<graphic xlink:href=\"1471-2164-9-376-4\"/>", "<graphic xlink:href=\"1471-2164-9-376-5\"/>", "<graphic xlink:href=\"1471-2164-9-376-6\"/>" ]

[ "<media xlink:href=\"1471-2164-9-376-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-376-S2.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-376-S3.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Coeliac disease is a permanent intolerance to dietary prolamins from wheat, barley and rye. Ingestion of these proteins in susceptible individuals gives rise to an inflammatory lesion in the small intestine characterised by crypt hyperplasia and villous atrophy [##REF##16766754##1##]. While progress has been made in understanding the mechanisms by which prolamins activate the immune system, the molecular events that ultimately lead to the intestinal lesion are, as yet, ill defined.</p>", "<p>Coeliac disease has a strong HLA association with approximately 95% of coeliac patients expressing the HLA-DQ2 molecule [##REF##14530392##2##]. A large population-based study showed the disease concordance rate between monozygotic twins to be 75% [##REF##11950806##3##]. This rate is considerably higher than that for other multifactorial diseases such as Crohn's disease [##REF##8555939##4##] or insulin dependent diabetes mellitus [##REF##1473616##5##]. However, in the study by Greco <italic>et al</italic>, the concordance rate for coeliac disease in HLA-matched dizygotic twins was found to be only 11% [##REF##11950806##3##]. Thus, while the evidence points to a very strong HLA genetic contribution to coeliac disease, other non-HLA-linked genes must play a role.</p>", "<p>Additional linkage studies have been performed in coeliac disease in an attempt to identify susceptibility loci other than the 6p21 HLA locus. Evidence has been found for linkage with the non-HLA loci 2q33, 5q31-33 and 19p13 [##REF##12209133##6##] and candidate gene association studies within these loci have concentrated on genes known to be immunologically relevant to disease pathogenesis. Recent genome-wide association studies have identified a region harbouring IL-2 and IL-21 as a further potential genetic susceptibility region predisposing to celiac disease [##REF##18311140##7##,##REF##17558408##8##]. However, so far no gene has been conclusively proven to confer a risk of coeliac disease. Hence, a hypothesis-free approach to selecting genes for study, as employed here, may be useful.</p>", "<p>Much research in coeliac disease has focused on the role of T-cells and the pro-inflammatory cytokines they produce [##REF##8537046##9##, ####REF##9721152##10##, ##REF##12198691##11##, ##REF##15247173##12##, ##REF##15703686##13####15703686##13##]. It has been suggested that the direct effect of pro-inflammatory cytokines such as IFN-γ and TNF-α may contribute to the characteristic coeliac lesion [##REF##8537046##9##]. Members of the metalloproteinase (MMP) family have been implicated in coeliac disease pathology. These enzymes are capable of tissue remodelling by degradation of proteins in the extracellular matrix and basement membrane. Several studies have demonstrated elevated levels of MMP expression in the coeliac lesion [##REF##15608660##14##, ####REF##9862821##15##, ##REF##16964549##16####16964549##16##].</p>", "<p>It has been proposed that dysregulated differentiation of epithelial cells in the small intestine may also play a role in the generation of the coeliac lesion. Diosdado <italic>et al </italic>have suggested that stem cells in the villous crypt proliferate, but do not receive the signal to differentiate leading to the development of undifferentiated, hyperplastic crypts and subsequently, villous atrophy [##REF##15194641##17##]. It has recently been reported that gliadin can directly cause up-regulation of several epithelial cell surface molecules such as HLA-DR, ICAM-1 and MICA [##REF##12853196##18##]. Furthermore, other studies have reported increased expression of several cytokines in the epithelium of patients with active celiac disease including IL-15, MIF, TNF-α and iNOS [##REF##16105889##19##, ####REF##11531944##20##, ##REF##15936309##21####15936309##21##]. Thus, the intestinal enterocyte is emerging as a potential contributor to coeliac disease pathogenesis and must be studied further.</p>", "<p>The purpose of this study was to examine the role of the epithelial cell in coeliac disease, employing a gene microarray based technique. This allowed for the analysis of the simultaneous expression of thousands of gene transcripts, in a hypothesis-free manner [##REF##11034570##22##]. Epithelial cells were isolated from biopsies taken from coeliac patients with active disease and compared to controls, thereby examining the gluten-induced inflammatory environment of the coeliac lesion. In the study, 102 genes were found to have significantly altered expression. Further studies using RT-PCR and immunohistochemistry were used to validate altered expression of gap junction protein alpha 4 and small proline rich protein 3.</p>" ]

[ "<title>Methods</title>", "<title>Patients</title>", "<p>Duodenal biopsy specimens were obtained from each patient via oesophago-gastro-duodenoscopy. Five coeliac patients had active, untreated disease and five age and sex-matched patients undergoing endoscopy for investigation of upper gastrointestinal symptoms were used as a control group. The demographic and clinical details of these patients are given in Table ##TAB##3##4##. Eight biopsy samples from each patient were used in microarray and RT-PCR experiments and a further two biopsies were processed for routine histological evaluation.</p>", "<p>In the immuno-histochemical studies, duodenal biopsy samples from three further groups of patients were employed. Archived tissue blocks in St. James's Hospital, Dublin were the source of these samples. The study subjects included five additional coeliac patients (3 males, 2 females, mean age 60 years): samples taken before they had commenced a gluten free diet and after dietary treatment (mean 7 years) were investigated. Two disease control patient groups were also studied: these included five patients (2 female, 3 male, mean age 51 years) with Crohn's disease involving the duodenum; and five patients (2 female, 3 male, mean age 43 years) with peptic duodenitis. Finally, a further ten patients (6 female, 4 male, mean age 59 years) undergoing endoscopy for investigation of upper gastrointestinal symptoms were also studied: this entire latter group had normal duodenal histology.</p>", "<p>Ethical approval for this study was granted by the Joint Ethics Committee of St James's Hospital and Tallaght Hospital, Dublin, Ireland.</p>", "<title>Isolation of epithelial cells</title>", "<p>Enterocyte isolation was perfomed based upon previously published methods [##REF##11531944##20##]. The eight biopsies taken from each patient were transferred into RPMI culture medium containing 10% fetal calf serum and processed immediately. Biopsies were agitated in calcium and magnesium free HBSS (Gibco BRL, Scotland) containing 1 mM dithiothreitol (DTT) (Sigma, USA) and 1 mM EDTA (Sigma, USA) and incubated at 37°C for 40 minutes. The supernatant containing the epithelial cells was removed, washed twice and centrifuged at 800 rpm for 10 minutes. Cells were magnetically sorted to deplete CD3⁺T-cells, using MACS CD3 microbeads (Miltenyi Biotech, Germany) and an LD depletion column according to manufacturer's specifications (Miltenyi Biotech, Germany). Employing the anti-epithelial cell monoclonal antibody Ber-EP4 and the anti-T-cell monoclonal antibody CD3 (DAKO, Denmark), FACS analysis was performed on the eluted fraction in order to determine purity and values of 98–99% were repeatedly observed.</p>", "<title>RNA extraction</title>", "<p>Total RNA was extracted from the epithelial cells using the NucleoSpin^®RNA II kit (BD Biosciences Clontech, UK) according to manufacturer's instructions with the following exceptions: vigorous vortexing of cells in the lysis buffer was performed, after which samples were frozen and then thawed before continuing with extraction; RNA was eluted from the column in 40 μl RNase-free water and the eluate reloaded onto the column twice more in order to collect the maximum yield of RNA. The RNA was concentrated further using Microcon YM-30 concentrators (Millipore, Ireland). Total RNA was quantified at 260 nm, and the 260/280 nm ratio was measured to calculate purity of RNA from contaminating protein. Agarose gel electrophoresis was also carried out to assess the quality of RNA. The same RNA samples were used for both microarray and RT-PCR analysis.</p>", "<title>Synthesis of fluorescent-labelled cDNA probes</title>", "<p>Fluorescent-labelled cDNA probes were synthesised using the BD Atlas™ SMART™ Fluorescent Probe Amplification Kit (BD Biosciences Clontech, UK). Briefly, cDNA was reverse-transcribed from total RNA and purified from unincorporated nucleotides before amplification using the CyScribe GFX Purification Kit (Amersham Biosciences, UK). From each patient specimen, two probe samples were synthesised. For each sample, the optimum number of PCR cycles was determined in order to ensure the amplification process was stopped while still in the exponential phase. This was essential as over-cycled cDNA which has reached the plateau phase of amplification could result in a less representative probe when examining differential gene expression. Once complete, an aliquot of each sample was analysed on a 1.2% agarose/EtBr gel under UV light, to ensure the reactions were successful. The PCR product was purified using the CyScribe GFX Purification Kit. Absorbance was read at 260 nm to calculate quantity and the 260:280 nm ratio was measured to calculate purity. Purified PCR product was fluorescently labelled, according to manufacturer's instructions. Single-use aliquots of monoreactive Cy3-NHS ester and Cy5-NHS ester dyes (Amersham Biosciences, UK) dissolved in DMSO were used. The labelled probe was purified from unreacted dye using the CyScribe GFX Purification kit and further purified from particulate matter by filtering through a 0.22 μm spin filter. Quantity and quality of the labelled probe was determined by UV/visible spectrophotometry using a Genesys 5 spectrophotometer (Thermo Electron Corporation, US). The optimal volume of labelled probe to use in the hybridisation reaction was determined on the basis of absolute optical units (OU_λ), using the following formula:</p>", "<p></p>", "<p>where OU_λfor Cy3 and Cy5 is 0.01 (determined by BD Biosciences Clontech) and A_λis the measured absorbance maxima for each dye; 550 nm for Cy3 and 650 nm for Cy5.</p>", "<title>Microarray hybridisation and scanning</title>", "<p>The microarrays used in this study were Atlas Glass Human 3.8 I microarrays (BD Biosciences Clontech, UK). Five biological replicate experiments were conducted, each one comparing one untreated coeliac sample to one control sample. In each experiment, two technical replicates were performed. Onto one microarray, Cy3-labelled coeliac cDNA and Cy5-labelled control cDNA were co-hybridised. Onto the other microarray, Cy5-labelled coeliac cDNA and Cy3-labelled control cDNA were co-hybridised. In this manner any discrepancies in rates of incorporation of the different dyes during the labelling step are controlled for. The appropriate coeliac and control probe were combined together and hybridised onto the microarray according to manufacturer's specifications. The slides were scanned using an Affymetrix^®428™ Array Scanner. Fluorescence was measured after excitation at 532 nm and 635 nm. Separate raw images for each dye were acquired and images were analysed using the software package ImaGene^®5.0 (BioDiscovery, California). Quality control measures were performed on all spots to identify empty, poor and negative spots.</p>", "<title>Data analysis</title>", "<p>The raw data from image analysis was normalised using the free software ArrayNorm available at <ext-link ext-link-type=\"uri\" xlink:href=\"http://genome.tugraz.at\"/> (Graz University of Technology Bioinformatics group, Austria). All the data was subjected to a background subtraction followed by a Lowess normalisation performed separately on each block (subgrid) on each microarray. Once normalised, the technical replicates were averaged and the data saved as a text file. The normalised data was analysed using the software package GeneSpring^®7 (Silicon Genetics, California). A custom genome was created using the genes present on the microarrays used. The data was analysed using log of ratio and the cross gene error model was turned off. The data was filtered on confidence using the t-test with a p-value of 0.05 considered significant. Significantly differentially expressed genes were grouped into functional categories using MAPPFinder <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.GenMapp.org\"/> – a program that works with GenMAPP and the annotations from the Gene Ontology (GO) Consortium [##REF##12540299##66##].</p>", "<title>Validation of data by real time RT-PCR</title>", "<p>Genes to be validated were selected on the basis of significance and potential interest. The genes were chosen to represent a spread of p-values up to 0.1. Assays-on-Demand™ Gene Expression products (Applied Biosystems, UK) containing forward primer, reverse primer and probe labelled with FAM dye and MGB quencher in a single tube were used. These primer/probe mixtures were pre-designed by the manufacturer and pre-optimised to ensure high amplification efficiency (proprietary sequences).</p>", "<p>Total RNA was reverse transcribed by standard methods. cDNA samples were quantified using the Fluorescent DNA Quantitation Kit (Bio-Rad, UK) according to manufacturer's specifications, and 250 pg of cDNA sample was used per reaction. Fluorescence was measured on a Tecan GENios Fluorimeter (Tecan, UK). Quantification of gene expression was carried out in the ABI TaqMan 7000 (Applied Biosystems), using purified PCR products as standards [##REF##12600954##67##]. In order to compare the expression values to those obtained from the microarray analysis, the mean expression value of the five coeliac samples was divided by the mean expression value of the five control samples to give a single ratio value.</p>", "<title>Immunohistochemistry</title>", "<p>Immunohistochemical staining was performed on 3 μm thick sections, cut from formalin-fixed, paraffin-embedded biopsies, using the avidin-biotin-peroxidase complex detection method. Rabbit polyclonal anti-human SPRR3 (small proline-rich protein 3) (Apotech UK), was applied at a concentration of 1 in 1000 and rabbit polyclonal anti-mouse connexin 37 (Alpha Diagnostic, US) was used at a concentration of 1 in 150. The mouse connexin 37 immunogenic peptide has an 87% homology to human connexin 37. The selection of these two antibodies was based on their known ability to react with human tissue [##REF##15221970##68##,##REF##9038818##69##]. The staining procedure was carried out using the VECTASTAIN^®Universal Elite ABC-Peroxidase Kit (Vector Labs, USA), according to manufacturer's specifications. Slides were visualised using a Nikon eclipse TE300 microscope attached to a computer. Images were captured using Leica DC100 and Adobe Photoshop software.</p>" ]

[ "<title>Results</title>", "<title>Microarray analysis of coeliac duodenal epithelial cells</title>", "<p>DTT/EDTA treatment was employed to strip the epithelial layer from patient intestinal biopsies. Magenetic cell sorting was then used to deplete CD3⁺cells, and enterocyte suspensions with purities of 98–99% were routinely obtained (Figure ##FIG##0##1##). Using Atlas Glass Human 3.8I oligonucleotide micoarrays (BD Biosciences Clontech, UK), we analysed the gene expression profile of a homogeneous population of duodenal epithelial cells taken from patients with active coeliac disease, in comparison to control patients. Of the 3,800 genes present on the array (all of which have been previously annotated), 3549 had sufficient data across the five experiments for comparison. Many of these genes showed fold-change ratios with little or no deviation from 1. Thus, to focus on only differentially expressed genes, the list was filtered on a fold-change of 1.25-fold. A fold-change of 1.25 has been described in previously published microarray experiments [##REF##11983059##23##,##REF##15041046##24##] and has been shown to indicate reliable differences in gene expression [##REF##11983059##23##]. This filtering yielded a list of 1,256 genes with which to perform analysis. Of these 1,256 genes, 827 were up-regulated and 429 were down-regulated. A p-value of 0.05 was used as a cut-off to distinguish significantly expressed genes, which yielded a gene list of 102 (68 up-regulated and 34 down-regulated) genes which are presented in Table ##TAB##0##1##. These 102 genes were grouped according to functional categories, including protein transport, ion transport, proliferation, differentiation, anti-apoptosis/survival, structural, adhesion, metabolism, transcription, protein biosynthesis, signal transduction, cell cycle and DNA repair, and immune response and inflammation (categories of genes and up/down-regulation are summarised in Figure ##FIG##1##2## and Table ##TAB##1##2## respectively).</p>", "<title>Verification of Selected Genes by Real-time PCR</title>", "<p>In order to corroborate the microarray gene expression results genes were selected for validation by real-time RT-PCR using the same patient samples. Miron <italic>et al </italic>have demonstrated that the popular strategy of selecting genes with the greatest fold-increase generally fails as a global validation strategy while a random selection of genes for validation (10–25 genes) is a more robust technique [##REF##16822306##25##]. We therefore used random-stratified sampling as a gene selection method. Ten genes representing a range of p-values were randomly selected for quantitative RT-PCR analysis.</p>", "<p>The RT-PCR expression values were calculated from a standard curve and the mean of the values calculated for the coeliac samples was divided by the mean for the control samples to give a ratio. The RT-PCR ratios were then compared to the microarray ratios (Table ##TAB##2##3##). Eight of the ten genes showed up-regulation of expression in coeliac disease with both microarray and real-time RT-PCR analysis. One gene showed up-regulation of expression in coeliac disease with microarray analysis and non-differential expression with real-time RT-PCR. One gene showed down-regulation of expression in coeliac disease with microarray analysis and up-regulation of expression with real-time RT-PCR analysis. Thus, 80% of the genes tested in this study were found to be validated, which compares well to a reported average RT-PCR confirmation rate of 70% [##REF##15550577##26##].</p>", "<title>Immunohistochemical Analysis</title>", "<p>Two of the genes validated by real-time RT-PCR, were selected for immunohistochemical examination based upon their expression in the gastrointestinal tract and potential interest with respect to coeliac disease pathophysiology. Small proline-rich protein 3 (SPRR3) was selected for qualitative analysis because of its role as a structural protein and its potential to act as a substrate for tissue transglutaminase [##REF##10510474##27##]. Gap junction protein alpha 4 (GJA4) was selected because of recent literature suggesting the importance of gap junctions in the spreading of immune signals between epithelial cells, including small peptides [##REF##17467043##28##].</p>", "<p>Protein expression of SPRR3 was examined in biopsies from five further untreated coeliac patients and in corresponding biopsies taken from these same patients at a later date while consuming a gluten-free diet (Figure ##FIG##2##3##). Histology reports showed that while consuming gluten, all patients had Marsh 3 type lesions (one Marsh 3a, 2 Marsh 3b and 2 Marsh 3c). Upon adoption of a gluten-free diet, two patients had recovered to normal duodenal histology while three patients had recovered to type 3a lesions with only mild or variable villous blunting. These patients had been following a gluten-free diet for a mean of 7 years (range 4–11 years).</p>", "<p>In the untreated coeliac tissue the common finding was intense cytoplasmic staining of SPRR3 throughout the epithelial cell, with strongest staining observed on the apical side of the cell. Perinuclear staining was also detected, although less visible due to the intensity of the cytoplasmic staining. The staining was observed all along the epithelium with the top part of the villous showing the greatest intensity. Staining for SPRR3 was increased in the untreated coeliac disease samples when compared to the gluten-free diet samples in 4 out of 5 cases. In the fifth matched sample, staining was equivalent pre and post-treatment with the gluten-free diet. The treated coeliac tissue generally showed faint staining in the villous-tip epithelial cells, with occasional punctate staining of moderate intensity also occurring only in the villous-tip region. Biopsies from the five untreated coeliac patients who showed up-regulation of SPRR3 mRNA expression by microarray and RT-PCR analysis were also examined for protein expression of SPRR3. All five samples showed a similar intense staining picture as seen in the untreated coeliac biopsies described above. Biopsies from ten normal control patients and ten disease control patients (consisting of five with peptic duodenitis and five with Crohn's disease with duodenal involvement) showed minimal staining of the epithelium with only the villous-tip involved, in a similar pattern to that found in the treated coeliac tissue (data not shown).</p>", "<p>Expression of GJA4 protein was compared between the matched pairs of untreated and treated coeliac biopsies (Figure ##FIG##3##4##). In the untreated epithelial tissue, granular staining was predominantly seen in the cytoplasm of the epithelial cells, with an increasing intensity towards the brush border. Perinuclear staining was visible in some cells although nuclear staining was generally absent. In contrast, in the treated biopsies, nuclear staining of epithelial cells was common while weak cytoplasmic staining was only evident in the villous tips and brush border staining was absent. The intra-epithelial lymphocytes within the treated tissue showed the most intense nuclear staining while the staining of enterocytes appeared to be due to strong perinuclear staining. In biopsies from the five untreated coeliac patients, who showed up-regulation of GJA4 mRNA expression by microarray and RT-PCR analysis, staining was similar to that seen in the untreated coeliac biopsies described above. Biopsies from control patients, both normal and diseased, showed a similar staining pattern to that observed in treated coeliac tissue although fewer cells appeared to stain positively in these control tissues (data not shown). In particular, nuclear staining was less frequent than in the treated coeliac tissue while perinuclear staining remained a common finding.</p>" ]

[ "<title>Discussion</title>", "<p>This is the first study to examine the gene expression profile of a highly pure population of duodenal epithelial cells in active coeliac disease. Differences in gene expression between epithelial cells of coeliac patients on a normal, gluten containing diet and non-coeliac control patients also consuming gluten were measured. Many of the genes identified in the study are known to be expressed in intestinal epithelial cells, [##REF##1472483##29##, ####REF##12627002##30##, ##REF##12176020##31##, ##REF##12704209##32##, ##REF##12189517##33##, ##REF##14502558##34##, ##REF##11889581##35####11889581##35##] adding validity to the results profile described here. Of the 3,800 genes present on the array, 102 genes were found to have significantly altered expression in active coeliac disease. Of these, ten genes were selected for validation by real-time RT-PCR quantification and eight of the 10 showed up-regulation in both detection systems. Protein expression of the gene product was investigated in the case of two up-regulated genes and was increased in both.</p>", "<p>The genes which demonstrated altered expression included those involved in cell proliferation, cell differentiation and cell death, all events which play a key role in coeliac pathology. In the villous crypt compartment, stem cells continuously proliferate to provide sufficient cells for the epithelium to renew every five days [##REF##15933624##36##]. Survival of these crypt cells is key for the epithelium to maintain its self-renewing capacity. Crypt hyperplasia is a further important feature of the coeliac intestinal lesion and is said to be the first architectural change in the pathogenic process [##REF##10524652##37##]. In active coeliac disease, it has previously been noted that epithelial crypt cells proliferate at an increased rate [##REF##7534252##38##,##REF##9038662##39##]. In this study, genes for growth arrest-specific 6 (GAS6) and bone marrow stromal cell antigen 2 (BST2) were found to be up-regulated in active coeliac disease, and both have previously been reported to induce cell proliferation [##REF##11546821##40##,##REF##10329429##41##]. In addition, the PRKC apoptosis WT1 regulator gene (PAWR), known to act as a negative regulator of proliferation [##REF##15246161##42##], was found to be down-regulated. These results show that the transcriptional regulation of proliferation is altered in active coeliac disease and the findings are in keeping with those of Diosdado <italic>et al </italic>[##REF##15194641##17##] who also reported altered expression of genes which lead to increased cell proliferation.</p>", "<p>Differentiation is a key process in the intestinal epithelium, whereby immature crypt cells become specialised into mature enterocytes when they migrate up to the villous compartment. Altered expression of several genes which could affect this process was found in this study. Wnt7a was found to be up-regulated and this signalling pathway is known to have an important role in differentiation and embryogenesis [##REF##11748610##43##,##REF##15082716##44##]. The importance of the Wnt pathway in intestinal epithelium has been demonstrated in animal studies. In a study by Kuhnert (2004) the antagonism of Wnt signalling resulted in a marked decrease in intestinal epithelial proliferation and a degeneration of intestinal architechture [##REF##14695885##45##]. While up-regulation of Wnt7A expression may provide a differentiation signal to epithelial cells, signalling via Wnt7a has also been shown to induce transcription of matrix metallproteinase 12 (MMP-12) [##REF##15194641##17##], an enzyme that has been implicated in coeliac disease pathophysiology [##REF##16293556##46##].</p>", "<p>Altered expression of other genes points to a down-regulation of epithelial differentiation. For example, nuclear transcription factor Y alpha, a protein that has been shown to induce the expression of differentiation markers on CaCo-2 cells [##REF##12392713##47##], was found to be down-regulated in active coeliac disease. Expression of retinol binding protein 1 (RBP1) was also found to be reduced in active coeliac disease epithelium. Retinoids play an important role in fundamental physiological processes including differentiation of epithelial tissues. RBP1 is a protein that binds metabolites of vitamin A, which has been shown to play a role in the differentiation of epithelial cells. Given that altered retinol metabolism is thought to play a part in oncogenesis and RBP1 expression is lost in epithelial cells of ovarian cancer (Cvetkovic 2003) lower levels of RBP1 may be associated with the increased chance of malignancy in coeliac disease. Overall, these results provide evidence for decreased differentiation of epithelial cells in coeliac disease.</p>", "<p>Several of the genes found to have altered expression in this study would favour a decrease in apoptotic events. These include the up-regulation of TNFRSF18 (also known as glucocorticoid-induced TNFR-related gene) and the survival factor erythropoietin which has been shown to be involved in survival of human breast and cervix carcinoma cells [##REF##15363551##48##]. Moreover, protein tyrosine kinase 2 beta (PTK2B), which enhances apoptosis [##REF##11053415##49##] was found to be down-regulated in active coeliac disease. These findings concur with an earlier microarray study which found evidence of activation of the NFκB pathway [##REF##15194641##17##] which can enhance cell survival by counteracting cell-death pathways [##REF##17174931##50##]. Since crypt epithelial cells are in a hyper-proliferative state in coeliac disease, enhancement of cell survival by blocking apoptosis makes biological sense. Although an increase in enterocyte apoptosis has been reported in coeliac disease [##REF##12853196##18##,##REF##9038662##51##,##REF##11293896##52##], this is not pronounced and in one study only 2.4% of cells were apoptotic [##REF##9038662##51##]. Nonetheless, a certain level of apoptosis is to be expected, as terminally differentiated cells are extruded into the intestinal lumen from the villous tip. BRCA1 associated protein 1 (BAP1) was shown to have a significantly elevated expression level in this study (1.316 fold-change, p = 0.0185). This replicates a result generated by Juuti-Uusitalo <italic>et al </italic>(2007) [##REF##17888028##53##]. The significance of this result is unclear but BAP1 has been described as a candidate tumour suppressor gene.</p>", "<p>A number of genes involved in transport and metabolism were also found to be differentially expressed. As the epithelial layer in active coeliac disease is in disarray, the normal function of these cells is likely to become disordered. Such changes in metabolism may reflect the modified needs of rapidly renewing cells. Ion transport is known to be increased in coeliac disease [##REF##8537047##54##] and an up-regulation of genes involved in ion channels was found in this study. Examples of these include genes for the potassium voltage-gated channel, Isk-related family, member 1 (KCNE1) and calcium channel, voltage-dependent, L type, alpha 1C subunit (CACNA1C). A further gene involved in regulating iron transport, HFE, which is located on chromosome 6p21 (CELIAC locus 1) was also found to be up-regulated. Interestingly, over-expression of HFE can lead to reduced iron uptake [##REF##11110669##55##], another known feature of coeliac disease. Juuti-Uusitalo <italic>et al</italic>. [##REF##15041046##24##] also reported up-regulation of genes affecting transport in coeliac patients and in particular the transcription of several ion pumps were upregulated.</p>", "<p>Recent publications have suggested that activation of the innate immune system in the epithelium of the small intestine is a feature of coeliac disease. In this study we identified 5 genes with altered expression that are involved in the immune response. Mouse studies suggest that one of the genes, MAP/microtubule affinity-regulating kinase 2 (MARK2), plays a role in maintenance of immune system homeostasis and prevention of autoimmunity [##REF##11287624##56##]. The decreased expression of MARK2 may be associated with the generation of autoimmunity in coeliac disease. Another gene product, sialyltransferase 1 (beta-galactoside alpha-2,6-sialyltransferase), appears to be involved in the sialylation of O-glycans during the process of dendritic cell maturation [##REF##18080182##57##]. Increased expression of this protein may reflect the maturation of antigen presenting cells in the inflammatory lesion.</p>", "<p>In recent studies of coeliac disease, genes involved in the intestinal barrier have been examined. One study reported an increased association with the gene for myosin 9B (MyO9B), involved in actin remodelling of epithelial cells [##REF##16282976##58##]. A number of other studies, however, have not confirmed this association [##REF##16423886##59##,##REF##16948647##60##]. In this study, no significant alteration of expression of MyO9B was found and a fold-change of just 1.1 was noted. Some other genes, potentially involved in tight junction formation, did show an altered expression profile, although this did not reach statistical significance; these were myosin 7A (1.5 up-fold), claudin-5 (1.23 down-fold), cadherin-10 (1.39 down-fold) and actintin, alpha 1 (1.79 down-fold).</p>", "<p>Small proline-rich protein 3 (SPRR3) was found to have increased gene and protein expression in this study. Intense cytoplasmic staining of this protein was noted in the epithelial cells of untreated coeliac patients. SPRR3, also known as esophagin, is a structural protein and a member of the cornified cell envelope precursor family. The cornified cell envelope provides a vital physical barrier in certain specialised epithelia normally subjected to mechanical trauma. The envelope is assembled by transglutaminase cross-linking of several proteins including SPRR3, which has been shown to be a substrate for transglutaminase 1, 2 and 3 [##REF##10510474##27##]. Expression of SPRR3 is normally found in terminally differentiated epithelia such as the oesophagus but is up-regulated in response to epithelial injury or disease [##REF##10510474##27##]. The up-regulation of SPRR3 in active coeliac disease may be a defensive response to protect the mucosa from any further damage caused by the ingestion of gluten. The increased expression of transglutaminase 2 found in the enterocytes and basement membrane in active coeliac disease [##REF##12410804##61##, ####REF##15670145##62##, ##REF##15891906##63####15891906##63##] could cross-link with SPRR3 to form a cornified envelope-like barrier. While SPRR3 is clearly upregulated in enterocytes in the coeliac gut, it is not clear whether this response is gluten-specific or the result of the architechtural changes typical of coeliac disease. However, it is clear that SPRR3 protein is not expressed to the same degree in disease control samples.</p>", "<p>Gap junction protein, alpha 4 (GJA4) was also shown to have increased gene expression and altered protein expression in patients with active coeliac disease. Granular GJA4 protein staining was found in these patients with an increase towards the brush border. GJA4, also known as connexin 37, is a member of the connexin family of gap junction structural proteins. Gap junctional intercellular communication can play various roles in terms of cell proliferation, migration and differentiation [##REF##15193866##64##] and in atherosclerosis studies, connexin 37 expression has been shown to change location as the disease progresses [##REF##11834520##65##]. The potential influence of gap junctions on the immune system is frequently overlooked. These channels can facilitate the transfer of small molecules like ions, metabolites and peptides up to around 16 amino acids in length [##REF##17467043##28##]. Gap junctions may function as a method to spread immunological signals from, for example, viral infections from cell to cell towards an antigen presenting cell such as an interdigitating dendritic cell. The up-regulation of gap junction proteins may reflect a response to the local inflammatory mileu. Increased numbers of gap junctions could facilitate the passage of immunostimulatory gluten peptides between cells along the epithelial boundary.</p>" ]

[ "<title>Conclusion</title>", "<p>This study investigated gene expression in highly purified enterocytes from the duodenal biopsies of patients with untreated coeliac disease and compared the findings with age and sex-matched control subjects. By focusing on a single cell population, in contrast to analysis of whole biopsy tissue it was possible to exclude the contribution of genes expressed in a diverse range of other cell types within the coeliac lesion. Of the 102 genes found to have significantly altered expression, several code for pathological processes known to contribute to coeliac disease and other genes were identified which have not previously been associated with this disorder. Of the ten genes investigated by real-time RT-PCR, validation of altered gene expression was confirmed in 80% and in the case of two proteins, increased duodenal expression was confirmed by immunohistochemistry. The study demonstrates how the application of microarray technology to the investigation of a complex genetic disease such as coeliac disease can contribute to the elucidation of potential disease mechanisms.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Coeliac disease is a multifactorial inflammatory disorder of the intestine caused by ingestion of gluten in genetically susceptible individuals. Genes within the HLA-DQ locus are considered to contribute some 40% of the genetic influence on this disease. However, information on other disease causing genes is sparse. Since enterocytes are considered to play a central role in coeliac pathology, the aim of this study was to examine gene expression in a highly purified isolate of these cells taken from patients with active disease. Epithelial cells were isolated from duodenal biopsies taken from five coeliac patients with active disease and five non-coeliac control subjects. Contaminating T cells were removed by magnetic sorting. The gene expression profile of the cells was examined using microarray analysis. Validation of significantly altered genes was performed by real-time RT-PCR and immunohistochemistry.</p>", "<title>Results</title>", "<p>Enterocyte suspensions of high purity (98–99%) were isolated from intestinal biopsies. Of the 3,800 genes investigated, 102 genes were found to have significantly altered expression between coeliac disease patients and controls (p &lt; 0.05). Analysis of these altered genes revealed a number of biological processes that are potentially modified in active coeliac disease. These processes include events likely to contibute to coeliac pathology, such as altered cell proliferation, differentiation, survival, structure and transport.</p>", "<title>Conclusion</title>", "<p>This study provides a profile of the molecular changes that occur in the intestinal epithelium of coeliac patients with active disease. Novel candidate genes were revealed which highlight the contribution of the epithelial cell to the pathogenesis of coeliac disease.</p>" ]

[ "<title>Authors' contributions</title>", "<p>SB carried out the sample processing, RNA isolation and hybridisation, data analysis, RT-PCR, immunohistochemistry and drafted the manuscript. GB critically revised the manuscript. JK and JJ advised on study design and development. CF co-ordinated the study, arranged sample acquisition, revised and finalised the manuscript. All authors read and approved the final manuscipt.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to thank the staff and patients of the Department of Gastroenterology at St. James's Hospital, Dublin. We also like to acknowledge helpful discussions with Dr Shane Duggan and Dr Eugene Dempsey.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Flow cytometric analysis of purified epithelial cells</bold>. <bold>A: </bold>Size versus granularity plot. <bold>B </bold>and <bold>C </bold>correspond to the population of cells within gate 1; and demonstrate control antibody and BerEP-4 expression, respectively. <bold>D </bold>and <bold>E </bold>correspond to the population of cells within gate 2; and demonstrate control antibody and CD3 expression, respectively.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>102 differentially expressed genes organised by category.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Immunohistochemical detection of SPRR3 in duodenal tissue</bold>. <bold>A</bold>: treated coeliac, showing faint staining in villous-tip epithelial cells, with occasional punctate staining of moderate intensity; <bold>B</bold>: untreated coeliac (same patient as A) showing intense cytoplasmic staining throughout epithelial cells with strongest staining observed on apical side of cell; and <bold>C</bold>: normal control showing minimal staining of epithelium with only villous-tip involved.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Immunohistochemical detection of GJA4 in duodenal tissue</bold>. <bold>A</bold>: treated coeliac, nuclear staining of epithelial cells apparent while brush border staining absent; <bold>B</bold>: untreated coeliac (same patient as A), granular staining predominantly seen in cytoplasm of epithelial cells with increasing intensity towards brush border. Perinuclear staining visible in some cells although nuclear staining generally absent. <bold>C</bold>: normal control, showing perinuclear staining in the epithelium, similar to treated coeliac tissue, but with less frequent nuclear staining.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Differentially expressed genes.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Functional Category</td><td align=\"center\">Gene Name</td><td align=\"center\">GenBank Accession Number</td><td align=\"center\">Chromosome Location</td><td align=\"center\">Fold-change</td><td align=\"center\">p-value</td></tr></thead><tbody><tr><td align=\"center\">Protein Transport</td><td align=\"left\">peroxisome biogenesis factor 13</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002618\">NM_002618</ext-link></td><td align=\"center\">2p14-p16</td><td align=\"center\">2.276</td><td align=\"center\">0.00331</td></tr><tr><td/><td align=\"left\">gap junction protein, alpha 4, 37 kDa (connexin 37)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002060\">NM_002060</ext-link></td><td align=\"center\">1p35.1</td><td align=\"center\">1.952</td><td align=\"center\">0.00575</td></tr><tr><td/><td align=\"left\">syntaxin 3A</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004177\">NM_004177</ext-link></td><td align=\"center\">11q12.1</td><td align=\"center\">1.81</td><td align=\"center\">0.00578</td></tr><tr><td/><td align=\"left\">CD3G antigen, gamma polypeptide (TiT3 complex)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000073\">NM_000073</ext-link></td><td align=\"center\">11q23</td><td align=\"center\">1.547</td><td align=\"center\">0.00676</td></tr><tr><td/><td align=\"left\">retinol dehydrogenase 5 (11-cis and 9-cis)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002905\">NM_002905</ext-link></td><td align=\"center\">12q13-q14</td><td align=\"center\">1.446</td><td align=\"center\">0.0158</td></tr><tr><td/><td align=\"left\">exportin 1 (CRM1 homolog, yeast)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003400\">NM_003400</ext-link></td><td align=\"center\">2p15</td><td align=\"center\">1.847</td><td align=\"center\">0.0225</td></tr><tr><td/><td align=\"left\">A kinase (PRKA) anchor protein 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005751\">NM_005751</ext-link></td><td align=\"center\">7q21-q22</td><td align=\"center\">0.748</td><td align=\"center\">0.0248</td></tr><tr><td/><td align=\"left\">retinol binding protein 1, cellular</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002899\">NM_002899</ext-link></td><td align=\"center\">3q21-q23</td><td align=\"center\">0.692</td><td align=\"center\">0.0305</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Ion Transport</td><td align=\"left\">gamma-aminobutyric acid (GABA) A receptor, beta 3</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000814\">NM_000814</ext-link></td><td align=\"center\">15q11.2-q12</td><td align=\"center\">1.74</td><td align=\"center\">0.00286</td></tr><tr><td/><td align=\"left\">cholinergic receptor, nicotinic, alpha polypeptide 5</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000745\">NM_000745</ext-link></td><td align=\"center\">15q24</td><td align=\"center\">0.557</td><td align=\"center\">0.00605</td></tr><tr><td/><td align=\"left\">hemochromatosis</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000410\">NM_000410</ext-link></td><td align=\"center\">6p21.3</td><td align=\"center\">1.319</td><td align=\"center\">0.00924</td></tr><tr><td/><td align=\"left\">potassium voltage-gated channel, Isk-related family, member 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000219\">NM_000219</ext-link></td><td align=\"center\">21q22.12</td><td align=\"center\">1.369</td><td align=\"center\">0.00959</td></tr><tr><td/><td align=\"left\">calcium channel, voltage-dependent, L type, alpha 1C subunit</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000719\">NM_000719</ext-link></td><td align=\"center\">12p13.3</td><td align=\"center\">1.351</td><td align=\"center\">0.0112</td></tr><tr><td/><td align=\"left\">sorcin</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003130\">NM_003130</ext-link></td><td align=\"center\">7q21.1</td><td align=\"center\">1.316</td><td align=\"center\">0.0248</td></tr><tr><td/><td align=\"left\">ATPase, H+ transporting, lysosomal 70 kDa, V1 subunit A</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001691\">NM_001691</ext-link></td><td align=\"center\">3q13.2-q13.31</td><td align=\"center\">1.47</td><td align=\"center\">0.0364</td></tr><tr><td/><td align=\"left\">glutamate receptor, ionotropic, N-methyl D-aspartate 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000832\">NM_000832</ext-link></td><td align=\"center\">9q34.3</td><td align=\"center\">0.706</td><td align=\"center\">0.0368</td></tr><tr><td/><td align=\"left\">adenosine kinase</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001123\">NM_001123</ext-link></td><td align=\"center\">10q22.2</td><td align=\"center\">0.749</td><td align=\"center\">0.0406</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Proliferation</td><td align=\"left\">bone marrow stromal cell antigen 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004335\">NM_004335</ext-link></td><td align=\"center\">19p13.2</td><td align=\"center\">1.29</td><td align=\"center\">0.00975</td></tr><tr><td/><td align=\"left\">PRKC, apoptosis, WT1, regulator</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002583\">NM_002583</ext-link></td><td align=\"center\">12q21</td><td align=\"center\">0.73</td><td align=\"center\">0.0251</td></tr><tr><td/><td align=\"left\">v-Ha-ras Harvey rat sarcoma viral oncogene homolog</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005343\">NM_005343</ext-link></td><td align=\"center\">11p15.5</td><td align=\"center\">0.631</td><td align=\"center\">0.0282</td></tr><tr><td/><td align=\"left\">growth arrest-specific 6</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000820\">NM_000820</ext-link></td><td align=\"center\">13q34</td><td align=\"center\">1.576</td><td align=\"center\">0.0443</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Differentiation</td><td align=\"left\">nuclear transcription factor Y, alpha</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002505\">NM_002505</ext-link></td><td align=\"center\">6p21.3</td><td align=\"center\">0.714</td><td align=\"center\">0.0196</td></tr><tr><td/><td align=\"left\">homeo box A7</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006896\">NM_006896</ext-link></td><td align=\"center\">7p15-p14</td><td align=\"center\">1.701</td><td align=\"center\">0.0297</td></tr><tr><td/><td align=\"left\">ash2 (absent, small, or homeotic)-like (Drosophila)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004674\">NM_004674</ext-link></td><td align=\"center\">8p11.2</td><td align=\"center\">0.749</td><td align=\"center\">0.0368</td></tr><tr><td/><td align=\"left\">wingless-type MMTV integration site family, member 7A</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004625\">NM_004625</ext-link></td><td align=\"center\">3p25</td><td align=\"center\">1.33</td><td align=\"center\">0.044</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Anti-apoptosis/Survival</td><td align=\"left\">PTK2B protein tyrosine kinase 2 beta</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004103\">NM_004103</ext-link></td><td align=\"center\">8p21.1</td><td align=\"center\">0.719</td><td align=\"center\">0.00362</td></tr><tr><td/><td align=\"left\">dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 3</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001396\">NM_001396</ext-link></td><td align=\"center\">21q22.13</td><td align=\"center\">2.627</td><td align=\"center\">0.0304</td></tr><tr><td/><td align=\"left\">tumor necrosis factor receptor superfamily, member 18</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004195\">NM_004195</ext-link></td><td align=\"center\">1p36.3</td><td align=\"center\">1.941</td><td align=\"center\">0.0334</td></tr><tr><td/><td align=\"left\">Erythropoietin</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000799\">NM_000799</ext-link></td><td align=\"center\">7q22</td><td align=\"center\">2.738</td><td align=\"center\">0.0492</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Transcription</td><td align=\"left\">SRY (sex determining region Y)-box 14</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006942\">NM_006942</ext-link></td><td align=\"center\">17p13</td><td align=\"center\">0.732</td><td align=\"center\">0.0142</td></tr><tr><td/><td align=\"left\">hematopoietic cell-specific Lyn substrate 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005335\">NM_005335</ext-link></td><td align=\"center\">3q13</td><td align=\"center\">1.585</td><td align=\"center\">0.0164</td></tr><tr><td/><td align=\"left\">histone deacetylase 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001527\">NM_001527</ext-link></td><td align=\"center\">6q21</td><td align=\"center\">1.574</td><td align=\"center\">0.0178</td></tr><tr><td/><td align=\"left\">high-mobility group box 3</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002128\">NM_002128</ext-link></td><td align=\"center\">13q12</td><td align=\"center\">1.775</td><td align=\"center\">0.02</td></tr><tr><td/><td align=\"left\">ELK4, ETS-domain protein (SRF accessory protein 1)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001973\">NM_001973</ext-link></td><td align=\"center\">1q32</td><td align=\"center\">1.446</td><td align=\"center\">0.0216</td></tr><tr><td/><td align=\"left\">homeo box A11</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005523\">NM_005523</ext-link></td><td align=\"center\">7p15-p14</td><td align=\"center\">1.325</td><td align=\"center\">0.0246</td></tr><tr><td/><td align=\"left\">forkhead box G1B</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005249\">NM_005249</ext-link></td><td align=\"center\">14q13</td><td align=\"center\">1.558</td><td align=\"center\">0.0248</td></tr><tr><td/><td align=\"left\">notch homolog 3 (Drosophila)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000435\">NM_000435</ext-link></td><td align=\"center\">19p13.2-p13.1</td><td align=\"center\">1.271</td><td align=\"center\">0.0285</td></tr><tr><td/><td align=\"left\">paired box gene 8</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003466\">NM_003466</ext-link></td><td align=\"center\">2q12-q14</td><td align=\"center\">1.419</td><td align=\"center\">0.0289</td></tr><tr><td/><td align=\"left\">human T-cell leukemia virus enhancer factor</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002158\">NM_002158</ext-link></td><td align=\"center\">2p22-p16</td><td align=\"center\">1.267</td><td align=\"center\">0.0311</td></tr><tr><td/><td align=\"left\">methyl CpG binding protein 2 (Rett syndrome)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004992\">NM_004992</ext-link></td><td align=\"center\">Xq28</td><td align=\"center\">0.532</td><td align=\"center\">0.0326</td></tr><tr><td/><td align=\"left\">T-box 6</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004608\">NM_004608</ext-link></td><td align=\"center\">16p11.2</td><td align=\"center\">0.73</td><td align=\"center\">0.037</td></tr><tr><td/><td align=\"left\">TAF15 RNA polymerase II, TATA box binding protein (TBP)-associated factor, 68 kDa</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003487\">NM_003487</ext-link></td><td align=\"center\">17q11.1-q11.2</td><td align=\"center\">0.656</td><td align=\"center\">0.0432</td></tr><tr><td/><td align=\"left\">neuronal PAS domain protein 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002518\">NM_002518</ext-link></td><td align=\"center\">2q11.2</td><td align=\"center\">1.288</td><td align=\"center\">0.0497</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Metabolism</td><td align=\"left\">fructose-1,6-bisphosphatase 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000507\">NM_000507</ext-link></td><td align=\"center\">9q22.3</td><td align=\"center\">1.535</td><td align=\"center\">0.000296</td></tr><tr><td/><td align=\"left\">glucosidase, beta; acid (includes glucosylceramidase)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000157\">NM_000157</ext-link></td><td align=\"center\">1q21</td><td align=\"center\">1.258</td><td align=\"center\">0.000369</td></tr><tr><td/><td align=\"left\">3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 (soluble)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002130\">NM_002130</ext-link></td><td align=\"center\">5p14-p13</td><td align=\"center\">0.535</td><td align=\"center\">0.00679</td></tr><tr><td/><td align=\"left\">lipoprotein, Lp(a)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005577\">NM_005577</ext-link></td><td align=\"center\">6q26</td><td align=\"center\">1.653</td><td align=\"center\">0.0174</td></tr><tr><td/><td align=\"left\">dihydropyrimidinase</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001385\">NM_001385</ext-link></td><td align=\"center\">8q22</td><td align=\"center\">0.638</td><td align=\"center\">0.0205</td></tr><tr><td/><td align=\"left\">NADH dehydrogenase (ubiquinone) Fe-S protein 8, 23 kDa (NADH-coenzyme Q reductase)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002496\">NM_002496</ext-link></td><td align=\"center\">11q13</td><td align=\"center\">0.78</td><td align=\"center\">0.0242</td></tr><tr><td/><td align=\"left\">histatin 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002159\">NM_002159</ext-link></td><td align=\"center\">4q13</td><td align=\"center\">0.75</td><td align=\"center\">0.0256</td></tr><tr><td/><td align=\"left\">N-acetylgalactosaminidase, alpha-</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000262\">NM_000262</ext-link></td><td align=\"center\">22q13-qter; 22q11</td><td align=\"center\">0.783</td><td align=\"center\">0.0278</td></tr><tr><td/><td align=\"left\">choline kinase</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001277\">NM_001277</ext-link></td><td align=\"center\">11q13.2</td><td align=\"center\">1.507</td><td align=\"center\">0.0303</td></tr><tr><td/><td align=\"left\">6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 4</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004567\">NM_004567</ext-link></td><td align=\"center\">3p22-p21</td><td align=\"center\">0.648</td><td align=\"center\">0.032</td></tr><tr><td/><td align=\"left\">sterol regulatory element binding transcription factor 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004176\">NM_004176</ext-link></td><td align=\"center\">17p11.2</td><td align=\"center\">4.529</td><td align=\"center\">0.0354</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Structural</td><td align=\"left\">cytoplasmic linker 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003388\">NM_003388</ext-link></td><td align=\"center\">7q11.23</td><td align=\"center\">1.309</td><td align=\"center\">0.00603</td></tr><tr><td/><td align=\"left\">procollagen-lysine, 2-oxoglutarate 5-dioxygenase (lysine hydroxylase) 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000935\">NM_000935</ext-link></td><td align=\"center\">3q23-q24</td><td align=\"center\">1.563</td><td align=\"center\">0.00657</td></tr><tr><td/><td align=\"left\">spectrin, alpha, erythrocytic 1 (elliptocytosis 2)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003126\">NM_003126</ext-link></td><td align=\"center\">1q21</td><td align=\"center\">1.29</td><td align=\"center\">0.0108</td></tr><tr><td/><td align=\"left\">cystatin A (stefin A)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005213\">NM_005213</ext-link></td><td align=\"center\">3q21</td><td align=\"center\">1.48</td><td align=\"center\">0.0114</td></tr><tr><td/><td align=\"left\">integrin beta 4 binding protein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002212\">NM_002212</ext-link></td><td align=\"center\">20q12</td><td align=\"center\">2.356</td><td align=\"center\">0.0167</td></tr><tr><td/><td align=\"left\">envoplakin</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001988\">NM_001988</ext-link></td><td align=\"center\">17q25</td><td align=\"center\">0.69</td><td align=\"center\">0.0201</td></tr><tr><td/><td align=\"left\">tubulin-specific chaperone a</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004607\">NM_004607</ext-link></td><td align=\"center\">5q14.1</td><td align=\"center\">0.725</td><td align=\"center\">0.0239</td></tr><tr><td/><td align=\"left\">microtubule-associated protein 1A</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002373\">NM_002373</ext-link></td><td align=\"center\">15q13-qter</td><td align=\"center\">0.652</td><td align=\"center\">0.0395</td></tr><tr><td/><td align=\"left\">small proline-rich protein 3</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005416\">NM_005416</ext-link></td><td align=\"center\">1q21-q22</td><td align=\"center\">2.095</td><td align=\"center\">0.0398</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Adhesion</td><td align=\"left\">vinculin</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003373\">NM_003373</ext-link></td><td align=\"center\">10q22.2</td><td align=\"center\">1.752</td><td align=\"center\">0.00217</td></tr><tr><td/><td align=\"left\">matrix Gla protein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000900\">NM_000900</ext-link></td><td align=\"center\">12p13.1-p12.3</td><td align=\"center\">0.659</td><td align=\"center\">0.00909</td></tr><tr><td/><td align=\"left\">EGF-containing fibulin-like extracellular matrix protein 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004105\">NM_004105</ext-link></td><td align=\"center\">2p16</td><td align=\"center\">1.276</td><td align=\"center\">0.0273</td></tr><tr><td/><td align=\"left\">oligodendrocyte myelin glycoprotein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002544\">NM_002544</ext-link></td><td align=\"center\">17q11.2</td><td align=\"center\">2.008</td><td align=\"center\">0.0386</td></tr><tr><td/><td align=\"left\">growth factor receptor-bound protein 7matrix Gla protein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005310\">NM_005310</ext-link></td><td align=\"center\">17q12</td><td align=\"center\">1.564</td><td align=\"center\">0.0479</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Protein Synthesis</td><td align=\"left\">ribosomal protein L19</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000981\">NM_000981</ext-link></td><td align=\"center\">17q11.2-q12</td><td align=\"center\">1.744</td><td align=\"center\">0.00118</td></tr><tr><td/><td align=\"left\">eukaryotic translation elongation factor 1 beta 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001959\">NM_001959</ext-link></td><td align=\"center\">2q33-q34</td><td align=\"center\">1.413</td><td align=\"center\">0.0051</td></tr><tr><td/><td align=\"left\">ribosomal protein S29</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001032\">NM_001032</ext-link></td><td align=\"center\">14q</td><td align=\"center\">1.311</td><td align=\"center\">0.00579</td></tr><tr><td/><td align=\"left\">pyrroline-5-carboxylate reductase 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006907\">NM_006907</ext-link></td><td align=\"center\">17q25.3</td><td align=\"center\">1.31</td><td align=\"center\">0.0059</td></tr><tr><td/><td align=\"left\">aminolevulinate, delta-, synthase 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000688\">NM_000688</ext-link></td><td align=\"center\">3p21.1</td><td align=\"center\">1.453</td><td align=\"center\">0.0105</td></tr><tr><td/><td align=\"left\">eukaryotic translation initiation factor 4E binding protein 3</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003732\">NM_003732</ext-link></td><td align=\"center\">5q31.3</td><td align=\"center\">1.466</td><td align=\"center\">0.0143</td></tr><tr><td/><td align=\"left\">tyrosinase (oculocutaneous albinism IA)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000372\">NM_000372</ext-link></td><td align=\"center\">11q14-q21</td><td align=\"center\">1.272</td><td align=\"center\">0.0387</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Immune Response &amp; Inflammation</td><td align=\"left\">MAP/microtubule affinity-regulating kinase 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004954\">NM_004954</ext-link></td><td align=\"center\">11q12-q13</td><td align=\"center\">0.717</td><td align=\"center\">0.00307</td></tr><tr><td/><td align=\"left\">microseminoprotein, beta-</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002443\">NM_002443</ext-link></td><td align=\"center\">10q11.2</td><td align=\"center\">1.592</td><td align=\"center\">0.0113</td></tr><tr><td/><td align=\"left\">sialyltransferase 1 (beta-galactoside alpha-2,6-sialyltransferase)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003032\">NM_003032</ext-link></td><td align=\"center\">3q27-q28</td><td align=\"center\">1.547</td><td align=\"center\">0.0207</td></tr><tr><td/><td align=\"left\">pyruvate kinase, muscle</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002654\">NM_002654</ext-link></td><td align=\"center\">15q22</td><td align=\"center\">1.438</td><td align=\"center\">0.031</td></tr><tr><td/><td align=\"left\">superkiller viralicidic activity 2-like (S. cerevisiae)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006929\">NM_006929</ext-link></td><td align=\"center\">6p21</td><td align=\"center\">1.639</td><td align=\"center\">0.0401</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Signal Transduction</td><td align=\"left\">natriuretic peptide receptor A/guanylate cyclase A (atrionatriuretic peptide receptor A)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000906\">NM_000906</ext-link></td><td align=\"center\">1q21-q22</td><td align=\"center\">0.693</td><td align=\"center\">0.00936</td></tr><tr><td/><td align=\"left\">membrane protein, palmitoylated 3 (MAGUK p55 subfamily) member 3)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001932\">NM_001932</ext-link></td><td align=\"center\">17q21.31</td><td align=\"center\">1.259</td><td align=\"center\">0.0109</td></tr><tr><td/><td align=\"left\">GPI anchored molecule like protein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_007264\">NM_007264</ext-link></td><td align=\"center\">12q13.3</td><td align=\"center\">1.791</td><td align=\"center\">0.0116</td></tr><tr><td/><td align=\"left\">glutamate receptor, metabotropic 7</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000844\">NM_000844</ext-link></td><td align=\"center\">3p26.1-p25.1</td><td align=\"center\">0.768</td><td align=\"center\">0.026</td></tr><tr><td/><td align=\"left\">G protein-coupled receptor 7</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005285\">NM_005285</ext-link></td><td align=\"center\">8p22-q21.13</td><td align=\"center\">2.293</td><td align=\"center\">0.0265</td></tr><tr><td/><td align=\"left\">Ras-like without CAAX 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006912\">NM_006912</ext-link></td><td align=\"center\">1q22</td><td align=\"center\">1.306</td><td align=\"center\">0.0356</td></tr><tr><td/><td align=\"left\">retinal G protein coupled receptor</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002921\">NM_002921</ext-link></td><td align=\"center\">10q23</td><td align=\"center\">0.744</td><td align=\"center\">0.0458</td></tr><tr><td/><td align=\"left\">AND-1 protein</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_007086\">NM_007086</ext-link></td><td align=\"center\">14q22.3</td><td align=\"center\">1.659</td><td align=\"center\">0.0465</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Cell cycle &amp; DNA repair</td><td align=\"left\">developmentally regulated GTP binding protein 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004147\">NM_004147</ext-link></td><td align=\"center\">22q12.2</td><td align=\"center\">1.56</td><td align=\"center\">0.00551</td></tr><tr><td/><td align=\"left\">protein (peptidyl-prolyl cis/trans isomerase) NIMA-interacting, 4 (parvulin)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_006223\">NM_006223</ext-link></td><td align=\"center\">Xq13</td><td align=\"center\">0.628</td><td align=\"center\">0.0086</td></tr><tr><td/><td align=\"left\">flap structure-specific endonuclease 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004111\">NM_004111</ext-link></td><td align=\"center\">11q12</td><td align=\"center\">1.288</td><td align=\"center\">0.0167</td></tr><tr><td/><td align=\"left\">BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004656\">NM_004656</ext-link></td><td align=\"center\">3p21.31-p21.2</td><td align=\"center\">1.316</td><td align=\"center\">0.0185</td></tr><tr><td/><td align=\"left\">amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001164\">NM_001164</ext-link></td><td align=\"center\">11p15</td><td align=\"center\">2.218</td><td align=\"center\">0.0234</td></tr><tr><td/><td align=\"left\">ubiquitin protein ligase E3A (human papilloma virus E6-associated protein, Angelman syndrome)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000462\">NM_000462</ext-link></td><td align=\"center\">15q11-q13</td><td align=\"center\">0.771</td><td align=\"center\">0.0286</td></tr><tr><td/><td align=\"left\">nudix (nucleoside diphosphate linked moiety X)-type motif 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001161\">NM_001161</ext-link></td><td align=\"center\">9p13</td><td align=\"center\">2.209</td><td align=\"center\">0.037</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Miscellaneous</td><td align=\"left\">chromosome 18 open reading frame 1</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_004338\">NM_004338</ext-link></td><td align=\"center\">18p11.2</td><td align=\"center\">1.743</td><td align=\"center\">0.0298</td></tr><tr><td/><td align=\"left\">prion protein (p27-30) (Creutzfeld-Jakob disease, Gerstmann-Strausler-Scheinker syndrome, fatal familial insomnia)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_000311\">NM_000311</ext-link></td><td align=\"center\">20p13</td><td align=\"center\">0.539</td><td align=\"center\">0.00875</td></tr><tr><td/><td align=\"left\">oxidase (cytochrome c) assembly 1-like</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_005015\">NM_005015</ext-link></td><td align=\"center\">14q11.2</td><td align=\"center\">0.625</td><td align=\"center\">0.0241</td></tr><tr><td/><td align=\"left\">D-amino-acid oxidase</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001917\">NM_001917</ext-link></td><td align=\"center\">12q24</td><td align=\"center\">1.75</td><td align=\"center\">0.03</td></tr><tr><td/><td align=\"left\">chromosome X open reading frame 2</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_001586\">NM_001586</ext-link></td><td align=\"center\">Xq28</td><td align=\"center\">0.762</td><td align=\"center\">0.0308</td></tr><tr><td/><td align=\"left\">transmembrane 7 superfamily member 1 (upregulated in kidney)</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_003272\">NM_003272</ext-link></td><td align=\"center\">1q42-q43</td><td align=\"center\">0.761</td><td align=\"center\">0.0371</td></tr><tr><td/><td align=\"left\">ribonuclease, RNase A family, 4</td><td align=\"center\"><ext-link ext-link-type=\"gen\" xlink:href=\"NM_002937\">NM_002937</ext-link></td><td align=\"center\">14q11.1</td><td align=\"center\">1.279</td><td align=\"center\">0.0467</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Summary of microarray results by gene category.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Gene Category</td><td align=\"center\">Genes Upregulated</td><td align=\"center\">Genes Downregulated</td></tr></thead><tbody><tr><td align=\"center\">Protein Transport</td><td align=\"center\">6</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Ion Transport</td><td align=\"center\">6</td><td align=\"center\">3</td></tr><tr><td align=\"center\">Proliferation</td><td align=\"center\">2</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Differentiation</td><td align=\"center\">2</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Anti-apoptosis/Survival</td><td align=\"center\">3</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Transcription</td><td align=\"center\">10</td><td align=\"center\">4</td></tr><tr><td align=\"center\">Metabolism</td><td align=\"center\">5</td><td align=\"center\">6</td></tr><tr><td align=\"center\">Structural</td><td align=\"center\">5</td><td align=\"center\">4</td></tr><tr><td align=\"center\">Adhesion</td><td align=\"center\">4</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Protein Synthesis</td><td align=\"center\">7</td><td align=\"center\">0</td></tr><tr><td align=\"center\">Immune Response &amp; Inflammation</td><td align=\"center\">4</td><td align=\"center\">1</td></tr><tr><td align=\"center\">Signal Transduction</td><td align=\"center\">5</td><td align=\"center\">3</td></tr><tr><td align=\"center\">Cell Cycle &amp; DNA repair</td><td align=\"center\">5</td><td align=\"center\">2</td></tr><tr><td align=\"center\">Miscellaneous</td><td align=\"center\">3</td><td align=\"center\">4</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Comparison of fold-changes obtained for genes by microarray and by TaqMan RT-PCR</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Gene</td><td align=\"center\">RT-PCR fold-change</td><td align=\"center\">Microarray fold-change</td></tr></thead><tbody><tr><td align=\"center\">Peroxisome biogenesis factor 13 (PEX13)</td><td align=\"center\">1.62</td><td align=\"center\">2.28</td></tr><tr><td align=\"center\">Gap junction protein, alpha 4, (GJA4, aka connexin 37)</td><td align=\"center\">4.09</td><td align=\"center\">1.95</td></tr><tr><td align=\"center\">Syntaxin 3A (STX3A)</td><td align=\"center\">1.52</td><td align=\"center\">1.81</td></tr><tr><td align=\"center\">3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 (HMGCS1)</td><td align=\"center\">1.25</td><td align=\"center\">0.54</td></tr><tr><td align=\"center\">Sterol regulatory element binding transcription factor 1 (SREBF1)</td><td align=\"center\">1.26</td><td align=\"center\">4.53</td></tr><tr><td align=\"center\">Nudix (nucleoside diphosphate linked moiety X)-type motif 2</td><td align=\"center\">3.02</td><td align=\"center\">2.21</td></tr><tr><td align=\"center\">Small proline-rich protein 3 (SPRR3, aka Esophagin)</td><td align=\"center\">1.77</td><td align=\"center\">2.1</td></tr><tr><td align=\"center\">Sialic acid binding Ig-like lectin 6 (SIGLEC6)</td><td align=\"center\">3.14</td><td align=\"center\">1.89</td></tr><tr><td align=\"center\">Laminin 5, alpha 3 (LAMA3)</td><td align=\"center\">1.94</td><td align=\"center\">2.51</td></tr><tr><td align=\"center\">Low density lipoprotein receptor-related protein 6 (LRP6)</td><td align=\"center\">1.04</td><td align=\"center\">2.12</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Microarray Experiment Patient Clinical Details</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Patients</td><td align=\"center\">Sex</td><td align=\"center\">Age</td><td align=\"center\">Duodenal histology</td><td align=\"center\">Other histology, clinical information</td><td align=\"center\">Antibody status</td><td align=\"center\">Microarray number</td></tr></thead><tbody><tr><td align=\"center\">Coeliac</td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">1</td><td align=\"center\">Female</td><td align=\"center\">61</td><td align=\"center\">Grade 3a</td><td align=\"center\">none</td><td align=\"center\">tTG +</td><td align=\"center\">1</td></tr><tr><td align=\"center\">2</td><td align=\"center\">Female</td><td align=\"center\">45</td><td align=\"center\">Grade 3b</td><td align=\"center\">Barrett's oesophagus</td><td align=\"center\">tTG +</td><td align=\"center\">2</td></tr><tr><td align=\"center\">3</td><td align=\"center\">Female</td><td align=\"center\">22</td><td align=\"center\">Grade 1</td><td align=\"center\">none</td><td align=\"center\">tTG +</td><td align=\"center\">3</td></tr><tr><td align=\"center\">4</td><td align=\"center\">Female</td><td align=\"center\">31</td><td align=\"center\">Grade 3c</td><td align=\"center\">none</td><td align=\"center\">tTG +</td><td align=\"center\">4</td></tr><tr><td align=\"center\">5</td><td align=\"center\">Female</td><td align=\"center\">36</td><td align=\"center\">Grade 3c</td><td align=\"center\">mild reflux oesophagitis</td><td align=\"center\">tTG +</td><td align=\"center\">5</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"center\">Control</td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"center\">6</td><td align=\"center\">Female</td><td align=\"center\">58</td><td align=\"center\">NDM</td><td align=\"center\">mild reflux oesophagitis</td><td align=\"center\">nk</td><td align=\"center\">1</td></tr><tr><td align=\"center\">7</td><td align=\"center\">Female</td><td align=\"center\">51</td><td align=\"center\">NDM</td><td align=\"center\">moderate reflux oesophagitis</td><td align=\"center\">tTG -</td><td align=\"center\">2</td></tr><tr><td align=\"center\">8</td><td align=\"center\">Female</td><td align=\"center\">25</td><td align=\"center\">NDM</td><td align=\"center\">none</td><td align=\"center\">nk</td><td align=\"center\">3</td></tr><tr><td align=\"center\">9</td><td align=\"center\">Female</td><td align=\"center\">30</td><td align=\"center\">NDM</td><td align=\"center\">superficial acute and chronic gastric inflammation</td><td align=\"center\">nk</td><td align=\"center\">4</td></tr><tr><td align=\"center\">10</td><td align=\"center\">Female</td><td align=\"center\">26</td><td align=\"center\">NDM</td><td align=\"center\">mild reflux oesophagitis</td><td align=\"center\">tTG -</td><td align=\"center\">5</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1471-2164-9-377-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mtext>V</mml:mtext><mml:mrow><mml:mtext>opt</mml:mtext></mml:mrow></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>μ</mml:mi><mml:mtext>l</mml:mtext><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>,</mml:mo><mml:mn>000</mml:mn><mml:mo>×</mml:mo><mml:msub><mml:mrow><mml:mtext>OU</mml:mtext></mml:mrow><mml:mi>λ</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mtext>A</mml:mtext><mml:mi>λ</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></disp-formula>" ]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Genes are ranked within each category according to their significance.</p></table-wrap-foot>", "<table-wrap-foot><p>Histology grade: 0 = normal; 1 = raised intraepithelial lymphocytes (IELs); 2 = increase in IELs with crypt hyperplasia; 3a = increase in IELs, crypt hyperplasia, mild villous atrophy; 3b = increase in IELs, crypt hyperplasia, marked villous atrophy; 3c = total villous atrophy [##REF##10524652##37##]. NDM = normal duodenal mucosa. tTG, tissue transglutaminase antibody. nk, not known.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2164-9-377-1\"/>", "<graphic xlink:href=\"1471-2164-9-377-2\"/>", "<graphic xlink:href=\"1471-2164-9-377-3\"/>", "<graphic xlink:href=\"1471-2164-9-377-4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The growing availability of the whole-genome sequences of eukaryotes has accelerated large-scale functional studies to understand the mechanisms of animal development and evolution [##REF##16000021##1##, ####REF##12777501##2##, ##REF##11336667##3##, ##REF##12459721##4####12459721##4##]. Many of these studies have highlighted the importance of regulatory evolution and the fundamental role that transcription factors (TFs) play in this process. Alterations in TF function and regulation are linked to phenotypic variation [##REF##11117736##5##, ####REF##17632547##6##, ##REF##14758362##7####14758362##7##] as well as numerous pathologies, including cancers [##REF##17957143##8##,##REF##17661355##9##]. Therefore, a detailed analysis of sequence and function of TFs across animal phyla will provide important information about their evolutionary patterns, thereby increasing our ability to understand the molecular basis of diseases and organismal complexity. The nematode <italic>Caenorhabditis elegans </italic>serves as a powerful model organism to unravel TF function due to the wealth of available resources and the ease with which it can be reared, maintained, and manipulated in the laboratory [##REF##17549065##10##]. The completion of its genome sequence has aided in the design of large-scale experiments that are beginning to elucidate the complexity of transcriptional regulation and gene interaction networks in multicelllular eukaryotes [##REF##12142361##11##,##REF##14704431##12##]. The recent releases of the genome sequence of two other <italic>Caenorhabditid </italic>species, <italic>C. briggsae </italic>[##REF##14624247##13##] and <italic>C. remanei </italic>[##UREF##0##14##], provide an excellent opportunity for genome-wide study of the conservation and evolution of transcription factors across nematodes. These three species are estimated to have shared a common ancestor between 20–120 million years ago [##REF##14624247##13##, ####UREF##0##14##, ##REF##14635896##15####14635896##15##] and while they are morphologically similar, studies have shown differences in development and behavior [##REF##18050493##16##].</p>", "<p>As a first step in facilitating the comparative study of TFs in nematodes, we have compiled an updated list of putative TF genes in <italic>C. elegans </italic>and used it to identify orthologs in <italic>C. briggsae </italic>and <italic>C. remanei</italic>. Our results show that two-thirds of all <italic>C. elegans </italic>TF genes have 3-way one-to-one best reciprocal orthologs in the other two species, whereas the remaining third are either species-specific paralogs or too divergent to assign proper orthologous relationships. We observed that among <italic>Caenorhabditid </italic>species, although TF genes have a greater sequence divergence than the non-TF genes, they exhibit significantly more detectable interspecific orthologs than non-TF genes. We also identified 150 best reciprocal orthologs of the TF genes conserved among nematodes in fruit fly (<italic>Drosophila melanogaster</italic>), mouse (<italic>Mus musculus</italic>), and human (<italic>Homo sapiens</italic>) many of which are associated with known disorders. We also examined the relationship between gene function and interactions, the results of which demonstrate that conserved TF genes exhibit a significantly greater number of interactions and are more likely to be associated with mutant phenotypes when compared to those that lack detectable orthologs. Our findings provide a framework for future studies of nematode TFs and facilitate the development of resources allowing us to study morphological and developmental diversity in metazoans.</p>" ]

[ "<title>Methods</title>", "<title><italic>C. elegans</italic>, <italic>C. briggsae </italic>and <italic>C. remanei </italic>TF gene sets</title>", "<p>The <italic>C. elegans </italic>TF-encoding genes were searched using 8 GO terms (Table ##TAB##0##1##) within WS173 release of Wormbase. The <italic>C. briggsae </italic>and <italic>C. remanei </italic>TFs were identified using the HMMER [##UREF##3##22##,##REF##9918945##65##] and InParanoid programs [##REF##11743721##21##]. The complete genome sequences of each of the three <italic>Caenorhabditid </italic>species were downloaded from WormBase (<italic>C. elegans </italic>release WS173, <italic>C. briggsae </italic>release WS173 and <italic>C. remanei </italic>release 11/29/2005) [##UREF##1##17##]. As the <italic>C. remanei </italic>predicted peptide dataset is known to contain redundant copies of genes due to heterozygosity in the sequenced genome, (E. Schwartz, personal communication) we used the CD-HIT program (version 2007-0131) [##REF##16731699##66##] in order to cluster and remove all additional transcripts that had greater than or equal to 98% sequence similarity to other transcripts at the protein level. The original dataset of 25,948 transcripts was truncated down to 24,267 non-redundant transcripts that were used in further analysis [##REF##18281268##27##].</p>", "<p>InParanoid was run with default values, using blastall version 2.2.14 with –VT emulation, on all three complete genome predicted peptide datasets in pairwise comparisons. The results were collected and placed into species-specific paralogs, 2- and 3-way best-hit reciprocal ortholog categories using custom PERL scripts. Each category was searched for genes from the <italic>C. elegans </italic>TF set and the number of TFs in each category was identified (Additional files ##SUPPL##5##6## and ##SUPPL##6##7##). HMM alignment-based searches were carried out on the <italic>C. briggsae </italic>and <italic>C. remanei </italic>predicted peptides using previously established techniques [##UREF##3##22##,##REF##11697912##67##]. The HMMER signature files (profiles) of known DNA binding domains were retrieved from Pfam [##UREF##6##68##]. In most cases, a cut-off score of 0.1 was used. If a HMMER predicted TF gene in non-<italic>elegans </italic>species lacked a homolog in <italic>C. elegans</italic>, it was considered false positive and therefore removed creating the final, conservative datasets that were used in the study.</p>", "<p>The <italic>C. elegans </italic>orthologs of <italic>D. melanogaster</italic>, <italic>M. musculus </italic>and <italic>H. sapiens </italic>TFs were retrieved using the data available on the InParanoid database [##REF##15608241##23##,##UREF##7##69##].</p>", "<title>Identification of the TF gene families</title>", "<p>Genes were grouped into different families based on the presence of known DNA-binding domains according to the WormBase [##UREF##0##14##], Pfam [##UREF##6##68##], and InterPro [##UREF##8##70##] databases. Only well defined and unambiguous domains that are known to be involved in transcriptional regulation were considered. Families with fewer than 5 members were placed together in a miscellaneous category. The TF families shown in Figure ##FIG##2##3## are as follows. AP2: Activator protein-2 family; AT hook: AT hook DNA binding motif (preference to A/T rich region) family; bHLH: basic helix-loop-helix family; bZIP: basic leucine zipper family; CBFB/NF-YA: CCAAT binding factor family; CSD: Cold shock DNA binding domain family; HMG box: High mobility group box family; HOX: Homeobox family; MADF: Myb DNA binding domain family; SAND: DNA binding domain family named after Sp100, AIRE-1, NucP41/75, DEAF-1; SANT: Myb-like DNA binding domain; SMAD: SMAD (Mothers against decapentaplegic (MAD) homolog) domain family; T-box: T-box family; WH: Winged-helix family; WH-FH: Winged-helix and Forkhead domain family; WH-ETS: Winged-helix and ETS domain family; ZF-C2H2: C2H2-type zinc finger protein family; ZF-C2H2-BED: C2H2 and BED-type zinc finger protein family; ZF-BED: BED-type zinc finger family; ZF-C2H2-RING: C2H2 and RING-type zinc finger protein family; ZF-C4/NHR: C4-type zinc finger/Nuclear hormone receptor family; ZF-CCCH: C-x8-C-x5-C-x3-H class of zinc finger family; ZF-DHHC: DHHC-type zinc finger family; ZF-FLYWCH: FLYWCH-type of zinc finger family; ZF-GATA: GATA class of zinc finger family; ZF-PHD: C4HC3 zinc-finger-like motif family; ZF-others: zinc finger family members not listed above; ZF-DM: DM (dsx and mab-3) zinc finger family; ZF, AT hook: AT hook and zinc finger domain family; ZF, SANT: SANT and zinc finger domain family; Misc: Miscellaneous TF family not listed above.</p>", "<title>Generation of the chromosomal map</title>", "<p>The physical locations of <italic>C. elegans </italic>and <italic>C. briggsae </italic>TF and non-TF genes were retrieved from Wormbase (WS173 release) and grouped into non-overlapping windows of 200 kb (similar to the 250 kb used by [##REF##15268860##33##]). A 400 kb window analysis was also performed and the conclusions remain the same (data not shown). Since many genes are alternatively spliced, we eliminated transcript-specific bias by focusing on single open reading frame for each transcription factor. In the case of <italic>C. briggsae</italic>, a total of 1329 genes were not assigned to any of the chromosomes and hence were excluded from the analysis. For simplicity, we only used the average between the start and end positions as a proxy for the gene position. The significance of TF clustering on chromosomes was determined by comparing their frequency with the overall frequency of genes in a given window using a χ²test [##REF##15268860##33##]. Clusters with <italic>p </italic>value less than 0.05 were considered significant.</p>", "<title>Phylogenetic analysis of the nematode NHR genes</title>", "<p>The predicted <italic>C. elegans </italic>NHR gene dataset (283 genes) was used to identify orthologs and paralogs in <italic>C. briggsae </italic>and <italic>C. remanei </italic>using the complete genome INPARANOID datasets (see above). 204 and 152 potential homologs were identified in <italic>C. briggsae </italic>and <italic>C. remanei</italic>, respectively. The peptide dataset was aligned using Dialign 2.2 [##REF##10222408##71##] and then manually inspected. We identified two large conserved blocks within most predicted peptides and removed all sequences that did not align within these blocks. The remaining sequences were then realigned with Dialign 2.2 and truncated only to retain the two conserved domains. As per Robinson-Rechavi et al. [##REF##15983867##29##] we chose to use only ungapped sites and removed first sequences missing significant portions of the conserved domains and finally excluded all gapped sites. In the end, we retained 437 sequences (213 <italic>C. elegans</italic>, 106 <italic>C. briggsae </italic>and 118 <italic>C. remanei</italic>) for phylogenetic analysis.</p>", "<p>The phylogeny was constructed using a maximum likelihood based method as implemented in PhyML [##REF##14530136##72##] using the JTT substitution model [##REF##1633570##73##] with the default proportion of invariable sites (0.0) and rate heterogeneity between sites corrected by a gamma law (using the default gamma parameter of 1.0 and eight rate categories). The phylogeny was then bootstrapped by generating 1000 randomized datasets using SEQBOOT and assessing the percentage of consensus trees using CONSENSE, both in the PHYLIP package [##UREF##9##74##].</p>", "<title>Calculation of TF divergence</title>", "<p>DNA sequences from <italic>C. elegans</italic>, <italic>C. briggsae </italic>and <italic>C. remanei </italic>were aligned according to their protein alignment using Dialign 2.2 [##REF##15215344##75##] and RevTrans 1.4 [##REF##12824361##76##]. Rates of synonymous substitutions per synonymous site (<italic>d</italic>_{<italic>S</italic>}) and non-synonymous substitutions per non-synonymous site (<italic>d</italic>_{<italic>N</italic>}) were estimated using codeml from PAML [##REF##12032247##77##]. Evolutionary rates between TF and non-TF data sets were compared using a permuted Kruskal-Wallis rank sum test using 10,000 permutations.</p>", "<title>Curation of the mutant phenotypes of TFs</title>", "<p>The RNAi phenotypes of all known <italic>C. elegans </italic>genes were retrieved from Wormbase (WS170 release). A total of 13,648 phenotypes associated with 4,351 genes were analyzed and sorted into 82 different categories (Unc, Dpy, Vul etc.) (Additional files ##SUPPL##12##13## and ##SUPPL##13##14##).</p>", "<p>For phenotypes associated with <italic>C. elegans </italic>TF orthologs in fly, mouse, and human, we searched Flybase [##UREF##10##78##], NCBI OMIM [##UREF##11##79##], PubMed [##UREF##12##80##], and other public databases (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.informatics.jax.org\"/>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.bioscience.org/knockout/alphabet.htm\"/>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.dsi.univ-paris5.fr/genatlas\"/>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.genetests.org\"/>). Only those phenotypes that were unambiguous and did not show discrepancy between different published sources were included. In order to reduced any effect linked to a differential amount of genes annotated as involved in particular mutant phenotypes, all the analyses were performed within each phenotypic class by comparing the distribution of genes with mutant phenotypes among the different sets (non-TF genes, TF genes, <italic>C. elegans </italic>TF genes, TF genes conserved among the three nematode species, and TF genes with orthologs in nematodes, fly, mouse, and human).</p>", "<title>Construction of TF interaction network</title>", "<p>The <italic>C. elegans </italic>gene network was built using the genetic and protein-protein interaction data for transcription factors curated by BioGRID (version 2.0.27 release) [##UREF##4##37##,##REF##16381927##38##]. The network was visualized by using Cytoscape [##REF##14597658##81##].</p>" ]

[ "<title>Results</title>", "<title>The <italic>C. elegans </italic>TF gene set</title>", "<p>As a first step in the identification of TFs in <italic>Caenorhabditid </italic>species, we generated an updated list of putative <italic>C. elegans </italic>TF genes by searching its annotated genome sequence (Wormbase WS173 release) [##UREF##1##17##] for gene ontology (GO) terms associated with transcription factors. This led to the identification of 1271 putative TF genes (Table ##TAB##0##1##). Since our criteria for selecting a TF was the presence of a well-defined DNA binding domain that selectively modulates gene transcription (for example, bHLH or homeobox), we manually inspected the above list of putative TFs. This allowed us to reject 564 genes as false positives since these encode factors that are associated with the basal transcriptional apparatus (for example, DNA polymerases), chromatin alterations, DNA packaging (histones), as well as entries that were incorrectly curated in Wormbase (Additional files ##SUPPL##0##1##, ##SUPPL##1##2##, ##SUPPL##2##3##). To the remaining genes (707), we added 281 TF encoding genes found in published literature and other public database entries that were not identified in our initial search (See Materials and Methods). The final <italic>C. elegans </italic>TF set included a total of 988 genes (Table ##TAB##1##2## and additional file ##SUPPL##3##4##), of which 917 are shared with the previously annotated <italic>C. elegans </italic>TF set (wTF2.0, 934 genes) [##REF##16420670##18##]. The 17 genes in the wTF2.0 set that are not shared in our updated set either lack a known DNA binding domain or are annotated as pseudogenes (Additional file ##SUPPL##4##5##). The increased number of genes in the present TF set likely results from the availability of annotations published since the compilation of wTF2.0.</p>", "<title>Identification of transcription factors in nematodes and other phyla</title>", "<p>We used the newly defined <italic>C. elegans </italic>TF set to search for homologs in the fully sequenced genomes of <italic>C. briggsae </italic>(CB3 release) and <italic>C. remanei </italic>(11/29/2005 release) [##UREF##1##17##,##REF##17608563##19##,##UREF##2##20##]. We used InParanoid [##REF##11743721##21##] to identify 713 and 703 best reciprocal hit orthologs in <italic>C. briggsae </italic>and <italic>C. remanei</italic>, respectively (Table ##TAB##1##2##, see Material and Methods). To these lists, we added 282 <italic>C. briggsae </italic>and 390 <italic>C. remanei </italic>putative TF genes that were identified through Hidden Markov Model (HMM)-based searches [##UREF##3##22##]. Altogether, a total of 995 and 1093 potential TF encoding genes were identified in <italic>C. briggsae </italic>and <italic>C. remanei</italic>, respectively (Table ##TAB##1##2## and additional files ##SUPPL##5##6## and ##SUPPL##6##7##). Among the TF orthologs in the three nematode species, we identified 652 genes that exhibit a 3-way best reciprocal BLAST orthologous relationship (hereafter referred to as the nematode TF set) (Figure ##FIG##0##1##). The proportion of <italic>C. elegans </italic>TF genes with detectable orthologs in <italic>C. briggsae </italic>(713/995, 71.7%) is significantly higher compared to the proportion of all conserved genes between the two species (12858/20621, 62.4%) [##REF##14624247##13##] (χ²= 7.56, df = 1, <italic>p </italic>= 6.0 × 10^-3), which may indicate strong selective pressure to maintain these genes.</p>", "<p>To examine the evolutionary conservation of the nematode TF set of genes in other phyla, we searched for their orthologs in the genomes of fruit fly(<italic>D. melanogaster</italic>), mouse (<italic>M. musculus</italic>), and human (<italic>H. sapiens</italic>). Using the InParanoid database [##REF##15608241##23##] we identified a total of 150 TFs that exhibit reciprocal orthologous relationships between three nematode species and are conserved in fly, mouse, and human (Additional files ##SUPPL##3##4## and ##SUPPL##7##8##).</p>", "<title>Coding sequence divergence in nematode TF genes</title>", "<p>Best-hit reciprocal orthologs could not be identified for 215 TF genes in <italic>C. elegans</italic>, 211 in <italic>C. briggsae</italic>, and 310 in <italic>C. remanei </italic>(Figure ##FIG##0##1## and additional files ##SUPPL##3##4##, ##SUPPL##5##6##, and ##SUPPL##6##7##). It should be pointed out that <italic>C. briggsae </italic>and <italic>C. remanei </italic>TF genes are based on computational predictions and that the <italic>C. remanei </italic>genome has yet to be assembled; hence while many of the TF genes without detectable orthologs may have arisen by lineage-specific gene duplication, others could result from incomplete annotation of the <italic>C. briggsae </italic>and <italic>C. remanei </italic>genomes. Therefore, the actual number of divergent TF genes in these species is likely to be smaller than the numbers we have estimated. To further study this set of genes in <italic>C. briggsae </italic>(211), we searched for their closest homologs in <italic>C. elegans</italic>. This revealed 30 genes with weak sequence similarity (BLASTP E-value &gt; 10^-10) suggesting that these most likely represent candidate <italic>C. briggsae</italic>-specific TF genes (Additional file ##SUPPL##8##9##). The remaining 181 appear to be species-specific paralogs, of which 69 are zinc finger-C4/nuclear hormone receptor (ZF-C4/NHR) family members (see below).</p>", "<p>Previous studies in humans and other organisms have shown that TF genes tend to evolve more rapidly than non-transcription factor (non-TF) genes [##REF##16525476##24##, ####REF##16237444##25##, ##REF##17994087##26####17994087##26##], therefore we performed a similar analysis in nematodes by analyzing their coding sequence divergence and comparing it to non-TF genes. Due to the large divergence times between the three species [##REF##14624247##13##,##REF##14635896##15##], the rate of synonymous substitution per synonymous site (<italic>d</italic>_S) for many genes is likely to be saturated (<italic>d</italic>_S&gt; 3, Figure ##FIG##1##2A##). Therefore we restricted our analysis to the rate of non-synonymous substitution per non-synonymous site (<italic>d</italic>_N), which does not show such saturation [##REF##18281268##27##]. We found a significantly higher <italic>d</italic>_Nfor TF genes conserved among nematodes (652) when compared to 3-way conserved non-TF gene orthologs (10,827 genes; Kruskal-Wallis rank sum test, <italic>p </italic>&lt; 2.2 × 10^-16; Figure ##FIG##1##2B##), whereas no difference was detected between TF genes with orthologs in nematodes, fly, mouse, and human (150) and non-TF genes (Kruskal-Wallis test, <italic>p </italic>= 0.3498).</p>", "<title>Distribution of TF families in <italic>C. elegans</italic></title>", "<p>We studied the distribution of protein families among <italic>C. elegans </italic>TFs based on known DNA binding domains. This analysis revealed more than 50 distinct families of which 30 were found to contain 5 or more members (Figure ##FIG##2##3##). No significant difference was observed in the representation of various families between the <italic>C. elegans </italic>set and the set conserved among three nematodes (χ²= 35.05, df = 30, <italic>p </italic>= 0.2408), indicating that the distributions of TF families in these species may be similar. The majority of genes in <italic>C. elegans </italic>and nematode TF sets (28.6% and 20.5%, respectively) were found to encode the nuclear hormone receptors (NHRs), a C4-type sub-family of zinc finger proteins that play key roles in development and homeostasis [##REF##11427696##28##]. The NHR genes was previously shown to have undergone extensive lineage-specific expansion in <italic>C. elegans </italic>[##REF##15983867##29##]. Besides NHR, HOX genes that regulate cell fate specification and embryogenesis [##REF##16341070##30##] are also among the largest TF families in nematodes (11% of <italic>C. elegans </italic>TF genes, and 11.6% of nematode TF genes) (Figure ##FIG##2##3A, C##). In contrast, the distribution of TF families among the divergent <italic>C. elegans </italic>gene set (215 genes) differs significantly from that observed among the entire <italic>C. elegans </italic>TF set (χ²= 83.91, df = 30, <italic>p </italic>= 5.33 × 10^-7) due to its high proportion of NHR genes (52.6%, Figure ##FIG##2##3B##). Likewise, the representation of different families among TF genes with orthologs in nematodes, fly, mouse, and human also differs from that of the <italic>C. elegans </italic>TF set (χ²= 152.27, df = 30, <italic>p </italic>= 0, Figure ##FIG##2##3D##). Interestingly, the single largest conserved family represented among the orthologs in three different phyla is HOX (17.3%), supporting multiple previous studies indicating the importance of this family among all metazoans [##REF##16420670##18##,##REF##16341070##30##,##REF##17244357##31##].</p>", "<title>Chromosomal distribution of TF genes in <italic>C. elegans </italic>and <italic>C. briggsae</italic></title>", "<p>Studies in <italic>C. elegans </italic>as well as other organisms have shown that genes that are co-expressed and/or functionally related are frequently clustered together on chromosomes [##REF##12214599##32##, ####REF##15268860##33##, ##REF##12478293##34##, ##REF##12144710##35##, ##REF##11992122##36####11992122##36##]. To investigate whether TF genes in nematodes exhibit a similar pattern, we plotted the physical locations of <italic>C. elegans </italic>and <italic>C. briggsae </italic>TF genes using non-overlapping windows of 200 kb (the genome of <italic>C. remanei </italic>has not yet been assembled and therefore was not used in this analysis). Figure ##FIG##3##4## shows that TF genes in <italic>C. elegans </italic>and <italic>C. briggsae </italic>as well as those that are conserved among nematodes are non-randomly distributed on chromosomes. A total of 183 <italic>C. elegans </italic>TF genes were found to be located in 25 distinct clusters (marked with stars in Figure ##FIG##3##4A##, Table ##TAB##2##3##). A similar pattern was observed in <italic>C. briggsae </italic>(184 genes in 27 clusters) (Figure ##FIG##3##4B## and Table ##TAB##2##3##). Chromosome V carries highest number of clusters (and genes) in both species (<italic>C. elegans</italic>: 97 genes in 10 clusters; <italic>C. briggsae</italic>: 64 genes in 7 clusters) (Table ##TAB##2##3##) that are primarily composed of NHR family members (92% in <italic>C. elegans </italic>and 84% in <italic>C. briggsae</italic>, red bars in Figure ##FIG##3##4##).</p>", "<p>The analysis of the chromosomal distribution of TF genes also revealed that many members of the large TF families, such as ZF-C4/NHR, ZF-C2H2, T-box and HOX are arranged in perfect tandem arrays (defined as having a contiguous repetition of TF genes) (267 <italic>C. elegans </italic>genes in 103 arrays, 235 <italic>C. briggsae </italic>genes in 107 arrays), the largest of which consists of 8 NHR genes in <italic>C. elegans </italic>and 6 NHR genes in <italic>C. briggsae </italic>(Figure ##FIG##4##5## and additional files ##SUPPL##9##10## and ##SUPPL##10##11##). Although the majority of such arrays consists of genes of the same TF family (76.7% in <italic>C. elegans </italic>and 67.3% in <italic>C. briggsae</italic>), less than half of all genes found in such arrays have best-reciprocal hit orthologs between the two species (31.6% in <italic>C. elegans</italic>, 47.2% in <italic>C. briggsae</italic>) (Additional files ##SUPPL##9##10## and ##SUPPL##10##11##) suggesting significant lineage-specific duplication and expansion of the tandem arrays.</p>", "<title>Evolution of the Nuclear Hormone Receptor family in nematodes</title>", "<p>Our findings extend Robinson-Rechavi et al.'s analysis of the extensive lineage-specific expansion of NHR genes in <italic>C. elegans </italic>[##REF##15983867##29##] to the other two <italic>Caenorhabditid </italic>species (283, 232, and 256 NHR genes in <italic>C. elegans</italic>, <italic>C. briggsae</italic>, and <italic>C. remanei</italic>, respectively). The sequence analyses revealed a total of 134 NHR genes having 3-way best-reciprocal orthologs among the nematode species (Additional files ##SUPPL##3##4##, ##SUPPL##5##6##, and ##SUPPL##6##7##). The remaining NHRs are composed of what appear to be lineage-specific paralogs and those that have diverged sufficiently in sequence such that orthologous relationships could no longer be assigned.</p>", "<p>We constructed a phylogenetic tree of the nematode NHR family members (437 genes, see Materials and Methods) to study their inter– as well as intra-specific relationships. The most striking feature of the phylogeny is the frequent presence of several closely related NHRs located tandemly on the same chromosome (Additional file ##SUPPL##11##12##). Such groupings suggest the presence of extensive tandem duplications, which could explain the mechanism behind the expansion of the NHR gene family, and perhaps the independent occurrence of some NHR genes in the lineages of each of these species. In the case of <italic>C. elegans </italic>NHRs, we found at least 15 distinct groups on chromosome V including 7 that are located in one large cluster of the phylogeny (Additional file ##SUPPL##11##12##).</p>", "<p>The presence of NHRs in chromosomal clusters prompted us to study their distribution in further detail. We identified a total of 47 tandem arrays composed of contiguous repetitions of NHR genes in <italic>C. elegans</italic>, which are found on all chromosomes with the exception of chromosome III (Additional file ##SUPPL##9##10##). These include 10 arrays that are comprised of 5 or more genes, all of which are located on chromosome V. A similar analysis in <italic>C. briggsae </italic>identified 30 NHR arrays having 6 or fewer genes (Additional file ##SUPPL##10##11##). In total, 9 NHR arrays were partially or completely conserved between <italic>C. elegans </italic>and <italic>C. briggsae</italic>. One of these arrays, for instance, consists of 7 genes in <italic>C. elegans </italic>(<italic>nhr-136, nhr-153, nhr-154, nhr-206, nhr-207, nhr-208</italic>, and <italic>nhr-209</italic>) and the corresponding 4 in <italic>C. briggsae </italic>(<italic>CBG23383/Cbr-nhr-136, CBG23380/Cbr-nhr-153, CBG23380/Cbr-nhr-154 </italic>and <italic>CBG23379/Cbr-nhr-209</italic>). This suggests that either the array has expanded in <italic>C. elegans </italic>or perhaps lost 3 of the genes in <italic>C. briggsae</italic>. Examination of the <italic>C. remanei </italic>TFs revealed the presence of best reciprocal hit orthologs for all array members found in <italic>C. elegans </italic>with the exception of <italic>nhr-206 </italic>leading us to propose that <italic>nhr-207 </italic>and <italic>nhr-208 </italic>were most likely lost in the <italic>C. briggsae </italic>lineage. This analysis, however, carries a caveat in that the annotations of the <italic>C. briggsae </italic>and <italic>C. remanei </italic>genomes are based on computational predictions and lack experimental validation.</p>", "<p>Finally, we found that 7 tandem arrays in <italic>C. briggsae </italic>are composed of NHR genes that lack best reciprocal hit orthologs in <italic>C. elegans </italic>and <italic>C. remanei </italic>(Additional file ##SUPPL##10##11##). The largest of these is comprised of 6 NHR genes (<italic>CBG01243, CBG01244, CBG01245, CBG01246, CBG01247, CBG01248</italic>) (Figure ##FIG##4##5##). These <italic>C. briggsae</italic>-specific arrays may be caused by lineage-specific expansion although the possibility of a selective loss of their orthologs in other species cannot be ruled out.</p>", "<title>Comparison of TF gene sequence conservation and function in <italic>C. elegans</italic></title>", "<p>We investigated the relationship between sequence conservation and function of TF genes in <italic>C. elegans</italic>. From a comprehensive list of 13,647 RNAi phenotypes associated with 4,351 genes [##UREF##0##14##], we identified 281 TFs that exhibit one or more mutant phenotypes (Additional file ##SUPPL##12##13##). These consist of more than half of all TF genes conserved among nematodes, fly, mouse, and human (52.7%, 79 of 150), over one-third of genes conserved among the three nematode species (36.5%, 238 of 652), and one-fifth of the TF genes in <italic>C. elegans </italic>that did not have identifiable orthologs in the other nematode species (20%, 43 of 215). We also determined the number of distinct mutant phenotypes associated with TF genes in each of the above three groups as well as with non-TF genes. This analysis revealed that TF genes conserved among nematodes, fly, mouse, and human are linked to a significantly greater number of mutant phenotypes in <italic>C. elegans </italic>when compared to the other sets (4.38 ± 2.31, 3.36 ± 2.09, 2.91 ± 1.82 and 3.19 ± 1.84 phenotypes per gene for TF genes conserved across phyla, conserved in nematodes, <italic>C. elegans </italic>TF genes without detectable orthologs in the other nematode species and non-TF genes, respectively; Kruskal-Wallis rank sum test, <italic>p </italic>= 8.58 × 10^-3, 1.8 × 10^-3, 1.32 × 10^-15, respectively, after Bonferroni correction). No difference was found in pairwise comparisons between the other gene sets (Kruskal-Wallis rank sum test <italic>p </italic>= 1, in all comparisons after Bonferroni correction).</p>", "<p>To further analyze the roles of <italic>C. elegans </italic>TF genes in specific tissues and developmental processes, RNAi phenotypes were sorted into six broad categories: viability (embryonic and post-embryonic growth and survival), fertility (germline and germ cells), sex (sex determination and reproductive system), vulva (vulval cell proliferation and morphogenesis), body (cuticle, size, and morphology), and behavior (movement and feeding) (Additional files ##SUPPL##12##13## and ##SUPPL##13##14##). Among the six categories, \"viability\" ranks highest in terms of the proportion of TF and non-TF genes (Figure ##FIG##5##6##). However, it is important to keep in mind that this may be linked to a greater interest in identifying transcription factors that are involved in growth and survival of <italic>C. elegans</italic>. A further sub-classification of this category into \"embryonic viability\" and \"post-embryonic viability\" (based on the phenotype when lethality occurs in RNAi-treated animals) revealed that among the \"embryonic viability\" class TF genes conserved among nematode species are significantly under-represented when compared to the non-TFs (χ²= 7.39, df = 1, <italic>p </italic>= 6.56 × 10^-3) (Figure ##FIG##5##6##), while no difference was observed among the datasets for genes affecting post-embryonic viability (χ²= 0.77, df = 1, <italic>p </italic>= 0.38). By contrast, the TF genes conserved among nematodes, fly, mouse, and human showed no enrichment for any of these two categories (χ²= 3.59 and 0.39, df = 1, <italic>p </italic>= 0.059 and 0.53, respectively). Among other categories, we observed an over-representation of mutant phenotypes for nematode-conserved as well as nematode-fly-mouse-human-conserved TF gene sets associated with vulval development (χ²= 8.24 and 11.75, df = 1, <italic>p </italic>= 4.1 × 10^-3and 6.08 × 10^-4, respectively) and sex determination and reproductive system-related processes (χ²= 9.51 and 8.78, df = 1, <italic>p </italic>= 2.04 × 10^-3and 3.59 × 10^-3, respectively) when compared to the non-TF gene set.</p>", "<title>Phenotypes associated with nematode TF orthologs in fly, mouse, and human</title>", "<p>The above findings that more than half of <italic>C. elegans </italic>TF genes conserved across phyla are associated with RNAi phenotypes prompted us to examine their mutant phenotypes in other organisms. We found that 69 (46%) of TF genes conserved among nematodes, fly, mouse, and human are associated with lethal phenotype in fly (Additional file ##SUPPL##14##15##). In the case of mouse, out of a total of 81 orthologs for which knock out and mutant phenotypes are described (see Materials and Methods), 75 (92.6%) exhibit defects ranging from mild to gross abnormalities, including lethality (Additional file ##SUPPL##14##15##). A similar analysis in human revealed 35 TF genes linked to various diseases and genetic disorders (Table ##TAB##3##4##). In total, 44 (29.3%) TF genes regulating <italic>C. elegans </italic>development and behavior are also essential either in mouse or human or both. These include 30 genes that control viability in the fruit fly. Overall, 121 (80.7%) TF genes conserved among nematodes, fly, mouse, and human play important roles in at least one of these organisms. This is likely an underestimate due to technical limitations of RNAi experiments (e.g., strains, redundancy of factors or pathways) and that comparisons between organisms involve different experimental approaches (e.g., RNAi in <italic>C elegans </italic>and chromosomal mutations in <italic>D. melanogaster</italic>). Thus, functional studies of conserved TFs in <italic>C. elegans </italic>promise to elucidate mechanisms involved in biological processes conserved across phyla.</p>", "<title>Analysis of TF interaction networks in <italic>C. elegans</italic></title>", "<p>To further explore the mechanism of transcription factor function in metazoans, we generated an interaction map of <italic>C. elegans </italic>TF genes based on known physical and genetic interactions [##UREF##4##37##,##REF##16381927##38##]. The map consists of 1594 interactions involving 277 TF genes and their direct non-TF interactors (Figure ##FIG##6##7A## and additional file ##SUPPL##15##16##). The network appears to be scale free as seen by the presence of several nodes with high degree of connectivity (such as <italic>lin-35</italic>, which shows the highest number of interactions and is connected to more than one-third of all existing nodes; 521 of 1340) (Figure ##FIG##6##7B##). <italic>lin-35 </italic>is an ortholog of the human <italic>Retinoblastoma </italic>(<italic>Rb</italic>) gene which plays an important role in cell proliferation [##REF##9875852##39##,##REF##10502774##40##]. Among the <italic>lin-35 </italic>interacting genes, 43 (8%) encode TFs, of which 18 have best reciprocal hit orthologs in mouse and human. Other prominent hubs include <italic>pal-1 </italic>(conserved among nematode species), as well as other TF genes with orthologs in nematodes, fly, mouse, and human: <italic>tag-331, eya-1</italic>, and <italic>sma-4 </italic>(Figure ##FIG##6##7B##). Each of these genes plays important role in <italic>C. elegans </italic>development, and RNAi-mediated knock-downs cause defects such as slow growth (<italic>pal-1</italic>), lethality (<italic>pal-1, tag-331</italic>), larval arrest (<italic>eya-1, tag-331</italic>), uncoordinated movement (<italic>eya-1</italic>), and small size (<italic>sma-4</italic>) [##REF##16154558##41##, ####UREF##5##42##, ##REF##15791247##43##, ##REF##12529635##44####12529635##44##]. Interestingly, the subnetwork comprising of the hub gene <italic>tag-331 </italic>(human ortholog RNF113A) and its 32 direct interactors appears to be largely isolated. A closer examination revealed that two-thirds of these 22 genes are conserved in nematodes yet lack best reciprocal hit orthologs in fly, mouse, or human genomes. The remaining third includes four genes conserved in nematodes, fly, mouse, and human (<italic>zfp-1, R11F4.1, apl-1 </italic>and <italic>fcd-2</italic>) and whose human homologs are linked to disorders (AF10/MLLT10: leukemia, Glycerol kinase: hyperglycerolemia, APP: Alzheimer's, and FANCD2: Fanconi anemia). It remains to be determined if the human genes interact with RNF113A as well as whether RNF113A is involved in any of these diseases. Among the remaining hub genes, the <italic>eya-1 </italic>mammalian orthologs promote development of tissues and organs [##REF##16154558##41##,##REF##10655545##45##,##REF##17098221##46##] whereas the <italic>sma-4 </italic>ortholog SMAD4/DCP4 acts as a tumor suppressor [##REF##8553070##47##, ####REF##10340381##48##, ##REF##11791187##49####11791187##49##].</p>", "<p>In addition to analyzing the prominent hubs in the interaction network, we also examined the relationship between connectivity of TFs, sequence conservation, and known function. The results revealed a significantly greater number of interactions among <italic>C. elegans </italic>TFs that are conserved in nematodes, fly, mouse, and human, as compared to those that are not (Kruskal-Wallis rank sum test, <italic>p </italic>= 0.0207, after Bonferroni correction). We also found that TF genes associated with mutant phenotypes in RNAi assays exhibit significantly more interactions when compared to those that lack a detectable phenotype (Kruskal-Wallis rank sum test, <italic>p </italic>= 0.0069). These results are consistent with previous studies showing that highly connected hubs tend to be enriched in essential genes [##REF##16751849##50##,##REF##15616139##51##].</p>" ]

[ "<title>Discussion</title>", "<p>This paper presents the first genome-wide comparative study of TF genes in nematodes and their orthologs in fly (<italic>D. melanogaster</italic>), mouse (<italic>M. musculus</italic>), and human (<italic>H. sapiens</italic>). We took both computational and manual curation approaches to compile sets of TF genes in three <italic>Caenorhabditid </italic>species, leading to the identification of 988 genes in <italic>C. elegans</italic>, 995 in <italic>C. briggsae </italic>and 1093 in <italic>C. remanei</italic>. A comparison of these data sets has revealed 652 3-way best reciprocal orthologs among these species. Furthermore, using currently available genome annotations, we identified 150 TF gene orthologs shared among nematodes, fly, mouse, and human and shown that according to mutant phenotypes or associated disorders, many of these genes are functionally important. It should be noted that many of the TF genes identified in <italic>C. elegans </italic>as well as most of those identified as orthologs, paralogs, and divergent in the other two nematode species are based entirely on computational predictions, and thus await experimental validation. However, the results of our study suggest the most likely group of candidate genes from which further experimental tests of TF activity can be designed. In contrast, the majority of the orthologs identified in the two other phyla are annotated as TF genes themselves, owing to the extensive experimental validation performed in these organisms.</p>", "<p>The sequence comparison of orthologs among nematodes has revealed that TF genes conserved among the three nematodes species (652 genes) are evolving more rapidly than non-TF genes, which is in agreement with earlier reports from other species in which TF genes have been shown to be evolving more rapidly than the coding genome average, and that significantly more TF genes have been found to be evolving under positive selection when compared to the rest of the genome [##REF##16525476##24##,##REF##16237444##25##,##REF##17665086##52##,##REF##10022975##53##]. While our observation of a greater number of conserved orthologs among all three nematode species, coupled to an accelerated rate of divergence may seem paradoxical, it may be suggestive of widespread positive selection, and thus divergence, acting on genes that are otherwise functionally important. Given the wide estimates of the divergence time between the three nematode species considered in this study, it is unsurprising that the rate of synonymous substitution (<italic>d</italic>_S) is saturated, and is therefore not amenable for use in analyses that could test the hypothesis of widespread positive selection among TF genes. Additional data, such as a large-scale polymorphism analysis among multiple <italic>Caenorabditid </italic>nematodes could provide the sensitivity to test for evidence of differential selective pressure affecting specific gene groups.</p>", "<p>The analysis of TF families in nematodes has revealed several interesting features, such as the high proportion of C2H2 and C4/NHR class of zinc-finger family members relative to the other TF families in all three species (see Figure ##FIG##2##3##). It was previously shown that the NHR family has undergone significant lineage-specific expansion in <italic>C. elegans </italic>and <italic>C. briggsae </italic>[##REF##10022975##53##]. Considering, for example, that <italic>Drosophila </italic>and humans carry less than 50 identified NHR genes (21 and 48, respectively) [##REF##18050471##54##], the presence of more than 200 genes in <italic>Caenorhabditid </italic>species is striking. Although it remains to be seen whether all of these have important roles to play, studies in <italic>C. elegans </italic>have shown that roughly 10% of NHRs mediate diverse processes including molting (<italic>nhr-23, nhr-25, nhr-67</italic>), neuronal differentiation (<italic>unc-55, fax-1</italic>), sex determination (<italic>sex-1</italic>), and dauer formation (<italic>daf-12</italic>) [##REF##18050471##54##]. We found that roughly half of all NHRs in each of the <italic>Caenorhabditid </italic>species are conserved as 3-way best reciprocal orthologs and another 10% exhibit 2-way orthologous relationships with at least one of the other nematode species. The remaining NHRs are likely to have arisen from lineage-specific gene duplications, suggesting that this class of TF may have a significant role in many of those differences that make individual nematode species unique. While the expansion of the NHR family in nematodes is certainly unusual, other TF families show interesting lineage-specific features as well. Previous studies as well as results presented here indicate that TF families such as ZF-C2H2, HOX and T-box have also diverged between the <italic>C. elegans </italic>and <italic>C. briggsae </italic>lineages (see Figure ##FIG##2##3B## and additional file ##SUPPL##8##9##) [##REF##17244357##31##].</p>", "<p>Our work demonstrates that TF genes are non-randomly distributed in the genomes of both <italic>C. elegans </italic>and <italic>C. briggsae</italic>. We found that members of gene families such as NHR, HOX, and T-box are frequently clustered and present in tandem arrays. A subset of the rapidly evolving NHR family of TF genes in <italic>C. elegans </italic>was previously shown to be located on chromosome V [##REF##10022975##53##,##REF##11275326##55##,##REF##16291650##56##]. We have shown not only that <italic>C. briggsae </italic>exhibits a similar pattern, but also that the majority of the chromosome V NHRs in both species is tandemly arrayed. Our finding that many NHRs appear to be lineage-specific paralogs suggests that gene duplication has played a significant role in the expansion of this gene family in nematodes. The phenomenon of gene clustering has been observed not only in <italic>C. elegans</italic>, but also in other species such as <italic>D. melanogaster </italic>and mouse [##REF##12214599##32##, ####REF##15268860##33##, ##REF##12478293##34####12478293##34##,##REF##11275326##55##,##REF##11279525##57##], and in some cases these clusters are composed of genes that are co-expressed [##REF##12214599##32##,##REF##12478293##34##]. While the precise mechanism of the origin of such clusters remains to be determined, these may be caused by small-scale regional translocations and illegitimate recombination events leading to tandem gene duplications [##REF##10198121##58##,##REF##14704166##59##].</p>", "<p>Our study has revealed that <italic>C. elegans </italic>TF genes conserved across multiple phyla are more likely to be associated with mutant phenotypes when compared to the remaining TF and non-TF genes. Likewise, the fly, mouse, and human orthologs of <italic>C. elegans </italic>TF genes are enriched in essential genes when compared to <italic>C. elegans </italic>TF genes without detectable orthologs (46%, 50% and 23.3%, respectively). The analysis of the relationship between gene function and interactions revealed that TF genes conserved across phyla exhibit greater number of interactions and mutant phenotypes when compared to those that are divergent. Among the TFs with described interactions, <italic>lin-35 </italic>(human <italic>Rb </italic>ortholog) appears to have an exceptionally large number of interactions. <italic>lin-35 </italic>is known to interact with cell cycle-related and chromatin remodeling factors to regulate tissue growth and morphology [##REF##15574590##60##,##REF##17075059##61##]. We found that among the <italic>lin-35 </italic>interacting genes, 43 (8%) encode TFs, of which 18 have best reciprocal hit orthologs in mouse and human. It is important to keep in mind that conservation in sequence does not indicate the roles of orthologous genes in regulating similar biological processes. Instead, it simply means that genes that are evolutionarily conserved are very likely to play important roles in the development and functioning of the organism. Our results are also consistent with studies in other organisms that have found a significant correlation between connectivity, rate of evolution and gene dispensability (according to lethal or sterile phenotype), even across multiple metazoan phyla. In general, hubs with high degree of connectivity tend to be enriched in essential genes and appear to evolve relatively slower than genes with lower connectivity [##REF##18281268##27##,##REF##16751849##50##,##REF##12769820##62##, ####REF##11976460##63##, ##REF##15746013##64####15746013##64##].</p>" ]

[ "<title>Conclusion</title>", "<p>This study describes a genome-wide analysis of TF genes in three <italic>Caenorhabditid </italic>nematode species (<italic>C. elegans</italic>, <italic>C. briggsae </italic>and <italic>C. remanei</italic>) as well as their orthologs in fruit fly (<italic>D. melanogaster</italic>), mouse (<italic>M. musculus</italic>) and human (<italic>H. sapiens</italic>). We observed a significantly higher conservation of orthology for the TF genes among <italic>Caenorhabditid </italic>species, while also noting that the coding sequence of TF genes diverges more rapidly than the coding genome average. Finally, the analyses of sequence conservation, gene interactions, and function revealed that TF set conserved in nematodes, fly, mouse, and human is significantly more enriched in essential genes compared to those that lack orthologs in other phyla. Our findings will serve as a resource in aiding us to understand transcriptional networks and their conservation and divergence among metazoa. The compilation of the TF sets also serves as a stepping-stone in generating various resources such as knock-out mutants, cDNA and promoter clones, and reporter gene expressing lines, with the intent of systematically mapping and studying TF function in nematodes. In parallel with many of ongoing initiatives in <italic>C. elegans </italic>these resources will provide foundation for future studies of the conservation of TF function and interaction across the breadth of biodiversity.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Much of the morphological diversity in eukaryotes results from differential regulation of gene expression in which transcription factors (TFs) play a central role. The nematode <italic>Caenorhabditis elegans </italic>is an established model organism for the study of the roles of TFs in controlling the spatiotemporal pattern of gene expression. Using the fully sequenced genomes of three <italic>Caenorhabditid </italic>nematode species as well as genome information from additional more distantly related organisms (fruit fly, mouse, and human) we sought to identify orthologous TFs and characterized their patterns of evolution.</p>", "<title>Results</title>", "<p>We identified 988 TF genes in <italic>C. elegans</italic>, and inferred corresponding sets in <italic>C. briggsae </italic>and <italic>C. remanei</italic>, containing 995 and 1093 TF genes, respectively. Analysis of the three gene sets revealed 652 3-way reciprocal 'best hit' orthologs (nematode TF set), approximately half of which are zinc finger (ZF-C2H2 and ZF-C4/NHR types) and HOX family members. Examination of the TF genes in <italic>C. elegans </italic>and <italic>C. briggsae </italic>identified the presence of significant tandem clustering on chromosome V, the majority of which belong to ZF-C4/NHR family. We also found evidence for lineage-specific duplications and rapid evolution of many of the TF genes in the two species. A search of the TFs conserved among nematodes in <italic>Drosophila melanogaster</italic>, <italic>Mus musculus </italic>and <italic>Homo sapiens </italic>revealed 150 reciprocal orthologs, many of which are associated with important biological processes and human diseases. Finally, a comparison of the sequence, gene interactions and function indicates that nematode TFs conserved across phyla exhibit significantly more interactions and are enriched in genes with annotated mutant phenotypes compared to those that lack orthologs in other species.</p>", "<title>Conclusion</title>", "<p>Our study represents the first comprehensive genome-wide analysis of TFs across three nematode species and other organisms. The findings indicate substantial conservation of transcription factors even across distant evolutionary lineages and form the basis for future experiments to examine TF gene function in nematodes and other divergent phyla.</p>" ]

[ "<title>Abbreviations</title>", "<p><italic>d</italic>_N: non-synonymous substitutions per non-synonymous site; <italic>d</italic>_S: synonymous substitutions per synonymous site; NHR: Nuclear hormone receptor; TF: Transcription factor; ZF: Zinc finger.</p>", "<title>Authors' contributions</title>", "<p>The laboratories of BPG and RSS contributed to this publication. BPG and NK identified the <italic>C. elegans </italic>TF set, protein families, chromosomal maps, and mutant phenotypes. WH identified nematode TF orthologs in fly, mouse, and human and carried out most of the sequence alignments, and interaction network analysis. CA performed the InParanoid orthology searches creating the <italic>C. briggsae </italic>and <italic>C. remanei </italic>TF gene sets and constructed NHR phylogenetic tree. BPG, WH and CA drafted the manuscript. BPG conceived and coordinated the study. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Phil Cumbo, Eric Schwartz, Jack Chen, and anonymous reviewers for constructive comments and advice. This work was supported by Natural Sciences and Engineering Research Council of Canada (NSERC) funds to BPG and RSS. CA is supported by an NSERC Post-Graduate Doctoral Scholarship and NK was an NSERC undergraduate summer trainee.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>TF-encoding genes in <italic>C. elegans</italic>, <italic>C. briggsae </italic>and <italic>C. remanei</italic>.</bold> The total number of TF genes in each of the species is given inside the brackets. The numbers of divergent TF genes and those conserved among the three nematode species are shown along the vertices and inside of the triangle, respectively.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Sequence divergence of transcription factors in <italic>C. elegans</italic>.</bold> Rates of synonymous substitutions per synonymous site (<italic>d</italic>_S) (A) and non-synonymous substitutions per non-synonymous site (<italic>d</italic>_N) (B) as calculated under model 0 in PAML (Yang) for non-TF (10,827), TF genes conserved in nematodes, fly, mouse, and human (150) and TF genes conserved among the three nematode species (652) are shown. The boxplot indicates the first and third quartiles and the dotted lines the 5th and 95th percentiles. The notches indicate the level of uncertainty associated with the median.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Distribution of TF gene families in <italic>C. elegans</italic>.</bold> The pie charts show distributions of all (A), divergent (B), nematode-conserved (C), and nematode-fly-mouse-human-conserved (D) TF genes in <italic>C. elegans</italic>. For details on various gene families please refer to Materials and Methods.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Chromosomal distribution of TF genes in <italic>C. elegans </italic>(A) and <italic>C. briggsae </italic>(B).</bold> The maps have been plotted by taking all TF genes in non-overlapping 200 kb windows. The color codes are as follows. Red: NHR genes, blue: non-NHR TF genes, green: TF genes conserved among the three nematode species. Gene clustering was analyzed by comparing the numbers of TF and non-TF genes located in each window using a χ²test. Gene clusters that are significantly enriched have been marked with stars (*: P &lt; 0.05; ** P &lt; 0.01; ***: P &lt; 0.0001).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Tandem arrays of NHR genes in <italic>C. elegans </italic>and <italic>C. briggsae</italic>.</bold> The snapshots of the genomic regions, visualized by Wormbase genome browser, show 8 genes in <italic>C. elegans </italic>and 6 in <italic>C. briggsae</italic>. The colors of the open reading frames indicate their orientation (blue: leftward, pink: rightward).</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Functional classification of <italic>C. elegans </italic>TF genes.</bold> The six broad categories are based on the mutant phenotypes in RNAi studies. Non-TF genes have been plotted for comparison. Viability-E and viability-PE are based on the embryonic and post-embryonic stage lethality phenotypes in RNAi assays, respectively. Refer to text for the description of other categories.</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>The interaction network of <italic>C. elegans </italic>TF genes.</bold> (A) The breakdowns of TF nodes, non-TF nodes and gene interactions in the network for each of the TF categories. The <italic>C. elegans</italic>-divergent category refers to TF genes that lack unique reciprocal orthologs in other nematode species. (B) The network exhibits several high degree nodes, five of which – <italic>tag-331, eya-1, lin-35, sma-4</italic>, and <italic>pal-1 </italic>– are boxed and shown at high magnification on the right (marked by arrows). The node colors mark different TF genes (red: conserved among nematodes, fly, mouse, and human; yellow: conserved among the three nematode species; green: <italic>C. elegans</italic>-divergent). The network was visualized by using Cytoscape [##REF##14597658##81##].</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>GO term-based searches of TF genes in <italic>C. elegans</italic>.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">GO ID</td><td align=\"left\">Term</td><td align=\"center\">TF genes</td><td align=\"center\">Unique</td></tr></thead><tbody><tr><td align=\"center\">0003700</td><td align=\"left\">Transcription Factor activity</td><td align=\"center\">614</td><td align=\"center\">6</td></tr><tr><td align=\"center\">0043565</td><td align=\"left\">DNA binding, sequence specific</td><td align=\"center\">515</td><td align=\"center\">6</td></tr><tr><td align=\"center\">0003677</td><td align=\"left\">DNA binding</td><td align=\"center\">858</td><td align=\"center\">352</td></tr><tr><td align=\"center\">0030528</td><td align=\"left\">Transcription regulator activity</td><td align=\"center\">75</td><td align=\"center\">9</td></tr><tr><td align=\"center\">0006355</td><td align=\"left\">Regulation of transcription, DNA dependent</td><td align=\"center\">768</td><td align=\"center\">78</td></tr><tr><td align=\"center\">0045449</td><td align=\"left\">Regulation of transcription</td><td align=\"center\">199</td><td align=\"center\">19</td></tr><tr><td align=\"center\">0000122</td><td align=\"left\">Negative regulation of transcription from RNA pol II promoter</td><td align=\"center\">8</td><td align=\"center\">4</td></tr><tr><td align=\"center\">004544</td><td align=\"left\">Positive regulation of transcription from RNA pol II promoter</td><td align=\"center\">24</td><td align=\"center\">10</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>The breakdowns of TF genes in each of the nematode species genomes based on various search categories.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Search method</bold></td><td align=\"center\" colspan=\"3\"><bold>Number of TF genes</bold></td></tr><tr><td/><td colspan=\"3\"><hr/></td></tr><tr><td/><td align=\"center\"><bold><italic>C. elegans</italic></bold></td><td align=\"center\"><bold><italic>C. briggsae</italic></bold></td><td align=\"center\"><bold><italic>C. remanei</italic></bold></td></tr></thead><tbody><tr><td align=\"left\">GO term-based</td><td align=\"center\">707</td><td align=\"center\">ND</td><td align=\"center\">NA</td></tr><tr><td align=\"left\">Orthologs (InParanoid and reciprocal BLAST)</td><td align=\"center\">ND</td><td align=\"center\">713</td><td align=\"center\">703</td></tr><tr><td align=\"left\">Manual curation</td><td align=\"center\">281</td><td align=\"center\">NA</td><td align=\"center\">NA</td></tr><tr><td align=\"left\">HMM alignments</td><td align=\"center\">ND</td><td align=\"center\">282</td><td align=\"center\">390</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>TOTAL:</bold></td><td align=\"center\"><bold>988</bold></td><td align=\"center\"><bold>995</bold></td><td align=\"center\"><bold>1093</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Chromosome-wise breakdown of TF gene clusters in <italic>C. elegans </italic>and <italic>C. briggsae</italic>.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Chromosome</bold></td><td align=\"center\" colspan=\"2\"><bold><italic>C. elegans</italic></bold></td><td align=\"center\" colspan=\"2\"><bold><italic>C. briggsae</italic></bold></td></tr><tr><td/><td colspan=\"2\"><hr/></td><td colspan=\"2\"><hr/></td></tr><tr><td/><td align=\"center\"><bold>Number of clusters</bold></td><td align=\"center\"><bold>Number of genes</bold></td><td align=\"center\"><bold>Number of clusters</bold></td><td align=\"center\"><bold>Number of genes</bold></td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">2</td><td align=\"center\">12</td><td align=\"center\">3</td><td align=\"center\">19</td></tr><tr><td align=\"center\">2</td><td align=\"center\">4</td><td align=\"center\">24</td><td align=\"center\">5</td><td align=\"center\">34</td></tr><tr><td align=\"center\">3</td><td align=\"center\">1</td><td align=\"center\">5</td><td align=\"center\">3</td><td align=\"center\">17</td></tr><tr><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">29</td><td align=\"center\">4</td><td align=\"center\">21</td></tr><tr><td align=\"center\">5</td><td align=\"center\">10</td><td align=\"center\">97</td><td align=\"center\">7</td><td align=\"center\">64</td></tr><tr><td align=\"center\">X</td><td align=\"center\">3</td><td align=\"center\">16</td><td align=\"center\">5</td><td align=\"center\">29</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\"><bold>TOTAL</bold></td><td align=\"center\"><bold>25</bold></td><td align=\"center\"><bold>183</bold></td><td align=\"center\"><bold>27</bold></td><td align=\"center\"><bold>184</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Genetic disorders linked to human TF genes conserved among nematodes, fly, mouse, and human.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold><italic>C. elegans </italic>gene</bold></td><td align=\"left\"><bold>Human ortholog</bold></td><td align=\"left\"><bold>Human disorder</bold></td></tr></thead><tbody><tr><td align=\"left\"><italic>vab-3</italic></td><td align=\"left\"><italic>Pax6</italic></td><td align=\"left\">Aniridia type II, Peters anomaly with cataract, foveal hypoplasia</td></tr><tr><td align=\"left\"><italic>Y38H8A.5</italic></td><td align=\"left\"><italic>FEZF1</italic></td><td align=\"left\">Beckwith-Wiedemann syndrome</td></tr><tr><td align=\"left\"><italic>ceh-33</italic></td><td align=\"left\"><italic>SIX1</italic></td><td align=\"left\">Branchiootic syndrome 3</td></tr><tr><td align=\"left\"><italic>mab-9</italic></td><td align=\"left\"><italic>TBX20</italic></td><td align=\"left\">Cardiomyopathy, atrial septal defect 1</td></tr><tr><td align=\"left\"><italic>tag-192</italic></td><td align=\"left\"><italic>CHD7</italic></td><td align=\"left\">CHARGE syndrome</td></tr><tr><td align=\"left\"><italic>ceh-24</italic></td><td align=\"left\"><italic>TITF1</italic></td><td align=\"left\">Congenital hypothyroidism, neonatal respiratory insufficiency</td></tr><tr><td align=\"left\"><italic>dve-1</italic></td><td align=\"left\"><italic>SATB2</italic></td><td align=\"left\">Cleft palate isolated</td></tr><tr><td align=\"left\"><italic>ceh-14</italic></td><td align=\"left\"><italic>LHX3</italic></td><td align=\"left\">Combined pituitary hormone deficiency 3</td></tr><tr><td align=\"left\"><italic>unc-86</italic></td><td align=\"left\"><italic>Pou4f3</italic></td><td align=\"left\">DFNA15 syndrome</td></tr><tr><td align=\"left\"><italic>elt-1</italic></td><td align=\"left\"><italic>GATA1</italic></td><td align=\"left\">Dyserythropoietic anemia with thrombocytopenia</td></tr><tr><td align=\"left\"><italic>K02H8.1</italic></td><td align=\"left\"><italic>MBNL2</italic></td><td align=\"left\">Dystrophia myotonica 1</td></tr><tr><td align=\"left\"><italic>fax-1</italic></td><td align=\"left\"><italic>Nr2e3</italic></td><td align=\"left\">Enhanced s-cone syndrome</td></tr><tr><td align=\"left\"><italic>ceh-17</italic></td><td align=\"left\"><italic>PHOX2A</italic></td><td align=\"left\">Congenital fibrosis of the extraocular muscles 2</td></tr><tr><td align=\"left\"><italic>ceh-32</italic></td><td align=\"left\"><italic>SIX3</italic></td><td align=\"left\">Holoprosencephaly 2</td></tr><tr><td align=\"left\"><italic>sbp-1</italic></td><td align=\"left\"><italic>Srebf1</italic></td><td align=\"left\">Hypercholesterolemia, familial</td></tr><tr><td align=\"left\"><italic>lin-28</italic></td><td align=\"left\"><italic>LIN28B</italic></td><td align=\"left\">Hypomyelination and cataract</td></tr><tr><td align=\"left\"><italic>alr-1</italic></td><td align=\"left\"><italic>ARX</italic></td><td align=\"left\">Lissencephaly, X-linked, with ambiguous genitalia</td></tr><tr><td align=\"left\"><italic>hmg-5</italic></td><td align=\"left\"><italic>Tfam</italic></td><td align=\"left\">Kearns-Sayre syndrome</td></tr><tr><td align=\"left\"><italic>cnd-1</italic></td><td align=\"left\"><italic>NEUROD1</italic></td><td align=\"left\">Maturity-onset diabetes of the young</td></tr><tr><td align=\"left\"><italic>lim-6</italic></td><td align=\"left\"><italic>LMX1B</italic></td><td align=\"left\">Nail patella syndrome NPS1</td></tr><tr><td align=\"left\"><italic>grh-1</italic></td><td align=\"left\"><italic>GRHL2</italic></td><td align=\"left\">Neurosensory deafness 28</td></tr><tr><td align=\"left\"><italic>sma-4</italic></td><td align=\"left\"><italic>Smad4</italic></td><td align=\"left\">Pancreatic cancer, Hemorrhagic Telangiectasia Syndrome (HTT)</td></tr><tr><td align=\"left\"><italic>nhr-6</italic></td><td align=\"left\"><italic>NR4A2</italic></td><td align=\"left\">PARK14</td></tr><tr><td align=\"left\"><italic>ceh-6</italic></td><td align=\"left\"><italic>POU3F3</italic></td><td align=\"left\">Perilymphatic gusher-deafness syndrome</td></tr><tr><td align=\"left\"><italic>zag-1</italic></td><td align=\"left\"><italic>ZEB1</italic></td><td align=\"left\">Posterior polymorphous corneal dystrophy 3</td></tr><tr><td align=\"left\"><italic>eor-1</italic></td><td align=\"left\"><italic>MYNN</italic></td><td align=\"left\">Promyelocytic leukemia</td></tr><tr><td align=\"left\"><italic>R07E5.3</italic></td><td align=\"left\"><italic>Smarcb1</italic></td><td align=\"left\">Rhabdoid tumor</td></tr><tr><td align=\"left\"><italic>cbp-1</italic></td><td align=\"left\"><italic>CREBBP</italic></td><td align=\"left\">Rubinstein-taybi syndrome, acute myeloid leukemia</td></tr><tr><td align=\"left\"><italic>ceh-43</italic></td><td align=\"left\"><italic>DLX5</italic></td><td align=\"left\">Split-hand/foot malformation</td></tr><tr><td align=\"left\"><italic>ing-3</italic></td><td align=\"left\"><italic>ING3</italic></td><td align=\"left\">Squamous cell carcinoma</td></tr><tr><td align=\"left\"><italic>ast-1</italic></td><td align=\"left\"><italic>FLI1</italic></td><td align=\"left\">Thrombocytopenia, Paris-Trousseau type</td></tr><tr><td align=\"left\"><italic>nhr-64</italic></td><td align=\"left\"><italic>HNF4A</italic></td><td align=\"left\">Maturity-onset diabetes of the young</td></tr><tr><td align=\"left\"><italic>tbx-2</italic></td><td align=\"left\"><italic>Tbx2</italic></td><td align=\"left\">Ulnar mammary syndrome</td></tr><tr><td align=\"left\"><italic>K02D7.2</italic></td><td align=\"left\"><italic>SNAI2</italic></td><td align=\"left\">Waardenburg syndrome, piebaldism</td></tr><tr><td align=\"left\"><italic>F53F8.1</italic></td><td align=\"left\"><italic>KLF3</italic></td><td align=\"left\">Wilms tumor</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>List of 314 incorrect entries (non-TFs) in <italic>C. elegans</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>List of 167 genes that encode chromatin remodeling, general transcription and DNA/RNA binding factors in <italic>C. elegans</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>List of 83 histone-encoding genes in <italic>C. elegans</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>List of 988 TF genes in <italic>C. elegans</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>List of 17 false positives in wTF2.0.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p>List of 995 TF genes in <italic>C. briggsae</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S7\"><caption><title>Additional file 7</title><p>List of 1093 TF genes in <italic>C. remanei</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S8\"><caption><title>Additional file 8</title><p>List of 150 TF orthologs in <italic>Drosophila melanogaster</italic>, <italic>M. musculus</italic>, and <italic>H. sapiens</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S9\"><caption><title>Additional file 9</title><p>BLASTP hits of <italic>C. briggsae</italic>-divergent TFs in <italic>C. elegans </italic>genome.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S10\"><caption><title>Additional file 10</title><p>Tandem arrays of TF genes in <italic>C. elegans</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S11\"><caption><title>Additional file 11</title><p>Tandem arrays of TF genes in <italic>C. briggsae</italic>.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S12\"><caption><title>Additional file 12</title><p>Phylogenetic tree of NHR genes in <italic>Caenorhabditid </italic>nematode species. Colors mark NHR genes in different species (blue: <italic>C. elegans</italic>, red: <italic>C. briggsae </italic>and light green: <italic>C. remanei</italic>). Tandemly along chromosomes and phylogenetically clustered genes are indicated by vertical bars. Chromosomes carrying NHR clusters are indicated by roman numerals. The sub-branch comprised of seven groups of NHR genes on chromosome V has been marked by a star (*). Scale bar represents 0.5 substitutions per site.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S13\"><caption><title>Additional file 13</title><p><italic>C. elegans </italic>genes and their mutant phenotypes in RNAi assays.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S14\"><caption><title>Additional file 14</title><p>RNAi phenotypes sorted into six broad categories.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S15\"><caption><title>Additional file 15</title><p>List of the worm (<italic>C. elegans</italic>) fly (<italic>D. melanogaster</italic>) and mouse (<italic>M. musculus</italic>) mutant phenotypes associated with conserved TF genes.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S16\"><caption><title>Additional file 16</title><p>List of TF genes and their interactors. The columns A and B merely list gene pairs that interact with each other and do not indicate the direction of regulation.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>The table lists numbers of all TF genes as well as those uniquely identified by each of the terms.</p></table-wrap-foot>", "<table-wrap-foot><p>NA: not applicable, ND: not done.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2164-9-399-1\"/>", "<graphic xlink:href=\"1471-2164-9-399-2\"/>", "<graphic xlink:href=\"1471-2164-9-399-3\"/>", "<graphic xlink:href=\"1471-2164-9-399-4\"/>", "<graphic xlink:href=\"1471-2164-9-399-5\"/>", "<graphic xlink:href=\"1471-2164-9-399-6\"/>", "<graphic xlink:href=\"1471-2164-9-399-7\"/>" ]

[ "<media xlink:href=\"1471-2164-9-399-S1.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S2.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S3.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S4.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S5.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S6.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S7.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S8.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S9.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S10.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S11.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S12.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S13.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S14.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S15.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2164-9-399-S16.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>During the last two decades, several clinical and pathological parameters have been used to evaluate the prognosis of breast cancer (BC) patients. Although different guidelines have been developed to assist clinicians in selecting patients who should receive adjuvant therapy, such as the St Gallen consensus criteria [##REF##12847142##1##], the NIH guidelines [##REF##11438563##2##] or Adjuvant! Online [##REF##15837986##3##], it still remains a challenge to distinguish those patients who would really need adjuvant systemic therapy from those who could be spared such a treatment.</p>", "<p>With the advent of array-based technology and the sequencing of the human genome, new insights into BC biology and prognosis have emerged. Interestingly, several groups conducted comprehensive genome-wide assessments of gene expression profiling and identified prognostic gene expression signatures [##REF##16478745##4##, ####REF##11823860##5##, ##REF##15721472##6####15721472##6##]. To this end, different approaches have been used: 1/ the \"top-down\" (data-driven) approach and 2/ the \"bottom-up\" (hypothesis-driven) approach.</p>", "<p>Examples of signatures which were developed using the first approach, i.e. by seeking gene expression profiles that are associated or correlated with clinical outcome without any a priori biological assumption, are the 70- and 76-gene signatures developed by the Netherlands Cancer Institute in Amsterdam with Rosetta Informatics-Merck, and the Erasmus MC in Rotterdam together with Veridex, respectively [##REF##11823860##5##,##REF##15721472##6##]. Although these signatures were built using a different microarray platform and had only a small gene overlap, a feature common to both signatures is that they correctly identified the high-risk patients while also identifying a higher number of low-risk patients not needing treatment compared to the clinical guidelines. In order to investigate the enormous potential of these signatures towards better individualization of treatment options in BC therapy, TRANSBIG, a network for translational research established by the Breast International Group (BIG), recently conducted a validation study of the 70-gene and 76-gene signatures which demonstrated the reproducibility and robustness of the 70- and 76-gene signatures [##REF##16954471##7##,##REF##17545524##8##]. This important validation work has led to the implementation of one of the first prospective clinical trials, MINDACT (Microarray In Node-negative Disease may Avoid Chemotherapy Trial) which evaluates the benefit/risk ratio of chemotherapy when the assessment of prognosis based on clinico-pathological features differs from that provided by the 70-gene signature assessed by the MammaPrint™ [##REF##17878518##9##].</p>", "<p>An example of deriving a prognostic gene expression signature using a hypothesis-driven approach was the study reported by our group that focused on histological grade, a well-established pathological parameter rooted in the cell biology of BC [##REF##16478745##4##]. Indeed, clinicians face a huge problem with respect to patients who have intermediate-grade tumors (grade 2), as these tumors, which represent 30% to 60% of cases, are the major source of inter-observer discrepancy and may display intermediate phenotype and survival, making treatment decisions for these patients a great challenge, with subsequent under- or over-treatment. Performing a supervised analysis, we developed a Gene expression Grade Index (GGI) score based on 97 genes. These genes were mainly involved in cell cycle regulation and proliferation and were consistently differentially expressed between low and high grade breast carcinomas. Interestingly, the GGI was able to reclassify patients with histological grade 2 tumors into two groups with distinct clinical outcomes similar to those of histological grade 1 and 3, respectively.</p>", "<p>In addition to the signatures described above, many other research groups have contributed gene expression signatures that are predictive of clinical outcome in BC [##REF##17585334##10##]. However, given the fact that their performances were evaluated on different datasets with limited or no independent validation and that there is only little gene overlap between the different gene sets, which can be attributed to the different platforms, training sets, and/or statistical tools used, it is unclear which is the best. The public availability of the TRANSBIG series gives the opportunity to perform a thorough comparison of several gene signatures. Indeed, this dataset of untreated primary BC patients is the only one on which three gene signatures, the 70-gene, the 76-gene and the GGI signatures, were computed using the original algorithms and microarray platforms [##REF##16954471##7##,##REF##17545524##8##], providing also the advantage that this population was not used for the development of any of these signatures. Here, we statistically compared these three signatures in terms of predicting clinical outcome for the individual patient using two performance criteria.</p>" ]

[ "<title>Methods</title>", "<title>Gene expression and clinical data</title>", "<p>Gene expression and clinical data of TRANSBIG series [##REF##16954471##7##,##REF##17545524##8##] were retrieved from EMBL-EBI ArrayExpress (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ebi.ac.uk/microarray-as/aer/\"/>, accession number E-TABM-77) and NCBI GEO (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/projects/geo/\"/>, accession number GSE7390) databases, for the validation of the 70-gene signature (TBAGD) and of the 76-gene signature (TBVDX), respectively. The original TRANSBIG series included 309 patients for whom the 70-gene signature was computed using the Agendia clinical MammaPrint™ 1.9 k Agilent custom microarray chip. This series is referred to as TBAGD. In a second time, the 76-gene signature was computed for a subset of these patients for whom there was enough material left. The Affymetrix HG-U133A research GeneChip™ was used for the signature computation. This series of 198 patients is referred to as TBVDX. Finally, we were able to compute the gene expression grade index in TBVDX as this series used Affymetrix technology. In this paper, we used the TBVDX patient's series for which we had the official classification for the three gene signatures, i.e. the 70-gene, 76-gene and the gene expression grade index.</p>", "<title>Risk status</title>", "<p>We considered only the binary risk status for the survival analysis, as the continuous risk scores are not publicly available for 70- and 76-gene signatures in the TBAGD and TBVDX series, respectively. The TBAGD series is composed of 307 BC patients and the TBVDX series is composed of 198 BC patients who are also included in the TBAGD series. In order to use the GGI as a prognostic signature, we first identified a threshold that allows to define the binary risk status according to the GGI scores, on the dataset of 286 patients used by Wang <italic>et al</italic>. (VDX, [##REF##15721472##6##]). Indeed, the threshold used in the original publication [##REF##16478745##4##] was selected to optimize the discrimination between patients with histological grade 1 and 3 tumors. As this threshold was not suited for survival analysis, we used the same training set as the 76-gene signature to keep the TRANSBIG series fully independent. We did not attempt to select a threshold optimizing some performance criteria, e.g. hazard ratio or logrank p-value, in order to avoid overfitting in VDX. Instead, we selected a threshold based on tertiles (the third of the patients having the lowest GGI scores being defined as low-risk and the remaining patients as high-risk) leading to similar repartition of patients in low- and high-risk groups to the 76-gene signature. The GGI score was computed as in Sotiriou <italic>et al</italic>. [##REF##16478745##4##] except that we performed a robust scaling instead of the original scaling method to avoid the use of histological grade information. After the robust scaling, the GGI scores have an interquartile range equals 1 and a median equals 0 within the dataset. The risk status computed using the threshold based on tertiles, yielded good classification performance on the VDX dataset (HR of 2.12; 95% CI: 1.35–3.34; p = 0.001). The GGI continuous risk scores for TBVDX were computed as for VDX and the GGI binary risk status was defined using the threshold identified on VDX. The clinical risk status was defined using the Adjuvant! Online software (AOL, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.adjuvantonline.com\"/>) as in the validation study conducted by the TRANSBIG consortium [##REF##16954471##7##,##REF##17545524##8##].</p>", "<title>Classification association</title>", "<p>We used Cramer's V statistic [##UREF##0##11##] to quantify the strength of the association between two gene signature classifications. The values range from 0 to 1, with 0 indicating no association and 1 indicating a perfect association. Traditionally, values of 0.36 to 0.49 indicate a substantial association, and values of 0.50 or more indicate a strong association. The significance of such an association was computed using a chi-squared test.</p>", "<title>Survival analysis</title>", "<p>We considered the distant metastasis free survival (DMFS), time to distant metastasis (TDM) and overall survival (OS) of BC patients as the survival endpoints. We performed the survival analyses by censoring the survival data at 10 years and by considering the full follow-up. We show the results for DMFS censored at 10 years in the article. The results for TDM and OS censored at 10 years are reported in [Additional File ##SUPPL##0##1##]. The survival analyses with the full follow-up are also reported in [Additional File ##SUPPL##0##1##]. Sensitivity and specificity were estimated at 3, 5 (the endpoint used to derive the 70- and 76-gene signatures), 10 and 15 years and by considering the full follow-up as well. Sensitivity was defined as the probability that a patient who experienced the event of interest was in the high-risk group and specificity as the probability that a patient who did not experience the event of interest was in the low-risk group. We used the nearest neighbors estimator defined in [##REF##10877287##12##] in order to take into account the time of events and the censoring. Hazard ratios between two groups were estimated through univariate Cox's proportional hazard regression models, stratified by clinical center to account for the possible heterogeneity in patient selection or other potential confounders among the various centers. Hazard ratios for the risk groups defined by the gene signature were also estimated with stratification for clinical risk in order to reflect the prognostic impact of the gene signature over and above that of clinicopathological variables (\"adjusted hazard ratios\"), as reported previously in [##REF##16954471##7##,##REF##17545524##8##]. In addition to the hazard ratio, we used the concordance index to quantify the predictive ability of a survival model [##REF##8668867##13##]. It estimates the probability that, of a pair of randomly chosen comparable patients, the patient in the high-risk group will recur before the patient in the low-risk group. A pair of patients is comparable if one of the patients recurred before the other patient and if the patients are in different risk groups. Standard error for the concordance index was estimated based on the asymptotic normality of its estimate [##REF##15211606##14##]. The difference in hazard ratios and concordance indices were computed using a paired Student t test. Survival curves were computed through the Kaplan-Meier product limit estimator and their difference was tested in a univariate Cox model, stratified when required.</p>", "<p>All p-values were two-tailed and p-values &lt; 0.05 were considered statistically significant. All statistical analyses were carried out using R version 2.5.1 [##UREF##1##15##].</p>" ]

[ "<title>Results</title>", "<title>Risk status computed by the prognostic signatures</title>", "<p>We used the original algorithms and microarray platforms to compute the risk status of 198 patients used in the second TRANSBIG validation study [##REF##17545524##8##]. Similarly to the GENE70 [##REF##11823860##5##] and GENE76 [##REF##15721472##6##] signatures, we performed a calibration step in order to compute GGI classification in this independent series. This step makes the prediction of a single patient challenging, as it requires a large number of samples. However, the standardization of hybridization protocols, the setup of a central laboratory to carry out the microarray experiments and the use of test samples to calibrate the process might help to avoid this issue. The MAQC consortium [##REF##16964229##16##] is specifically studying this problem in order to bring the microarray-based gene signatures into clinic.</p>", "<title>Patient characteristics according to the prognostic signatures</title>", "<p>The patients were younger than the age of 61 (median age 47), had node-negative, T1–T2 (≤ 5 cm) tumors and did not receive any adjuvant treatment. The tumor samples from these patients were previously hybridized on the Agilent platform to define the 70-gene signature [##REF##15721472##6##,##REF##17074082##17##], as well as on the Affymetrix platform, from which the 76-gene signature [##REF##15721472##6##] and Gene expression Grade Index (GGI, [##REF##16478745##4##]) were computed. Patient characteristics are shown in Table ##TAB##0##1##, organized according to their genomic risk of recurrence as defined by the 70-gene and the 76-gene signatures as well as by the GGI, and by their clinical risk as defined by Adjuvant! Online (AOL, [##REF##15837986##3##,##REF##16954471##7##,##REF##17545524##8##]). The distribution of the risk categories was similar for the different signatures in terms of patient's age and tumor size. However, differences in risk distribution were observed between the 76-gene signature and the two others in terms of tumor grade and estrogen receptor (ER) status. Indeed, the 76-gene signature identified a higher proportion of high-risk grade 2 tumors and low-risk grade 3 tumors, high-risk ER-positive and low-risk ER-negative tumors. When looking at the distribution of the high and low-risk patients according to the ER status, it appears clearly that these signatures mainly impact on the prediction of clinical outcome on ER-positive patients. Compared to the different genomic risk classifications, the clinical risk classification (AOL) identifies a higher proportion of high-risk patients in the older subgroup or in the group of patients with large tumors. None of the patients whose tumors were moderately/poorly differentiated or ER-negative are considered as low-risk by AOL.</p>", "<title>Concordance of classification of samples</title>", "<p>Figure ##FIG##0##1## illustrates the classification of the tumor samples according to the prognostic signatures. We observed agreement in prediction in 135 of 198 patients (68%) when considering the three signatures. When comparing the signatures two by two, agreement in prediction was 71% for the 70- and 76-gene signatures, 76% for the 76-gene signature and the GGI, and 88% for the 70-gene signature and the GGI. The strength of the concordance of classifications, quantified through Cramer's V statistic, was 0.33 for the 70- and 76-gene signatures, 0.47 for the 76-gene signature and the GGI, and 0.76 for the 70-gene signature and the GGI.</p>", "<title>Survival analyses</title>", "<p>In this section, we report the results from the survival analyses using the DMFS censored at 10 years and with the full follow-up. We performed these two separate analyses in order to highlight the time-dependency of the gene signatures as shown in [##REF##16954471##7##,##REF##17545524##8##].</p>", "<title>Survival data censored at 10 years</title>", "<p>To assess the prognostic ability of the three signatures, we first compared their concordance index, which is used to quantify the predictive ability of a survival model. Although all three concordance indices were highly significant, the 70-gene signature and GGI displayed a higher concordance index compared to the 76-gene signature (0.90 compared to 0.80; Figure ##FIG##1##2A##). However, this difference was not statistically significant (Table ##TAB##1##2##). In contrast, the clinical risk calculated using AOL displayed a lower concordance index value (0.69) compared to either ones generated by the genomic signatures.</p>", "<p>We next performed univariate and multivariate Cox analyses, which included the traditional clinico-pathological parameters, for each signature separately. The univariate hazard ratios (HR) were 7.12 (95% CI: 2.52–20.11; p = 2.1 × 10^-4), 3.18 (95% CI: 1.35–7.53; p = 8.4 – 10^-3) and 5.85 (95% CI: 2.3–15; p = 2.1 – 10^-4) for the 70-gene signature, 76-gene signature and the GGI respectively. We additionally computed the HR for the clinical risk as defined by AOL, which was not statistically significant for DMFS evaluation in this cohort of patients (2.01; 95% CI: 0.89–4.5; p = 0.091). The log2 of these HR are illustrated in Figure ##FIG##1##2B##. Although the HR of the 70-gene signature and the GGI were higher than the HR of the 76-gene signature, the differences were not statistically significant (see Table ##TAB##1##2##). Figure ##FIG##2##3## illustrates the Kaplan-Meier estimates of DMFS for the four groups of patients (two groups with concordant results in risk assessment and two with discordant results) for the different signatures two by two.</p>", "<p>From the multivariate analyses (Table ##TAB##2##3##), we can conclude that the three signatures added significant information to the traditional parameters and were the strongest predictive variables of DMFS, as reflected by their lowest p-values compared to the other variables. The additional information of these signatures over the clinical risk was also confirmed by the fact that the univariate HRs for the three signatures remained similar when adjusted for the clinical risk, with a HR of 7.25 (95% CI: 2.4–21.5; p = 3.5 – 10^-4), 2.8 (95% CI: 1.2–6.8; p = 0.018) and 6.25 (95% CI: 2.3–17; p = 3.3 – 10^-4) for the 70-gene signature, 76-gene signature and the GGI respectively.</p>", "<p>Lastly, we combined the three gene signatures in order to assess the potential improvement in BC prognostication. We used a simple combination scheme that defined the risk of a patient as the sum of the classifications (low-risk = 0 and high-risk = 1) by the three gene signatures. As illustrated in Supplementary Figure 1 in [Additional File ##SUPPL##0##1##], the patients for whom the three gene signature classifications were concordant are well defined, with only 2 patients relapsing in the low-risk group after 9 years of follow up. However, the patients with discordant classifications exhibited good survival and their survival curves were not distinguishable. The combination of the three gene signatures did not yield significant improvement in prognostication (the hazard ratio between the concordant cases, i.e. 'All Low' and 'All High', is not significantly higher than when each gene signature was considered separately), maybe due to their high concordance and the sample size of the TBVDX series</p>", "<title>Survival data with the full follow-up</title>", "<p>We computed the concordance index of all the gene signatures using the survival data with the full follow-up. The three concordance indices were significant. We observed higher concordance indices for the 70-gene signature and GGI compared to the 76-gene signature (0.84 and 0.79 for GENE70 and GGI respectively compared to 0.71 for GENE76; Supplementary Figure 12 in [Additional File ##SUPPL##0##1##]). This difference was not statistically significant (Supplementary Table 5 in [Additional File ##SUPPL##0##1##]) although we noted a trend for GENE70 to have a higher concordance index (p = 0.065). In contrast, the clinical risk calculated using AOL displayed a lower concordance index value (0.69) compared to either ones generated by the genomic signatures.</p>", "<p>We next performed univariate and multivariate Cox analyses, which included the traditional clinico-pathological parameters, for each signature separately. The univariate hazard ratios (HR) were 2.77 (95% CI: 1.41–5.43; p = 3.1 – 10^-3), 1.76 (95% CI: 0.92–3.34; p = 0.086) and 2.41 (95% CI: 1.29–4.5; p = 5.9 – 10^-3) for the 70-gene signature, 76-gene signature and the GGI respectively. We additionally computed the HR for the clinical risk as defined by AOL, which was not statistically significant for DMFS evaluation in this cohort of patients (1.5; 95% CI: 1.29–4.5; p = 0.11). The log2 of these HR are illustrated in Supplementary Figure 13 in [Additional File ##SUPPL##0##1##]. Although the HR of the 70-gene signature and the GGI were higher than the HR of the 76-gene signature, the differences were not statistically significant (see Supplementary Table 5 in [Additional File ##SUPPL##0##1##]). Supplementary Figures 14–16 in [Additional File ##SUPPL##0##1##] illustrate the Kaplan-Meier estimates of DMFS for the four groups of patients for the different signatures two by two.</p>", "<p>From the multivariate analyses (Supplementary Table 6 in [Additional File ##SUPPL##0##1##]), we can conclude that the three signatures added significant information to the traditional parameters and were the strongest predictive variables of DMFS, as reflected by their lowest p-values compared to the other variables. We computed the univariate HRs adjusted for the clinical risk, i.e. 2.8 (95% CI: 1.35–5.82; p = 5.8 – 10^-3), 1.55 (95% CI: 0.81–2.97; p = 0.18) and 2.13 (95% CI: 1.12–4.02; p = 0.02) for the 70-gene signature, 76-gene signature and the GGI respectively.</p>", "<p>Contrary to the analyses using the survival data censored at 10 years, the HRs with and without adjustment for clinical risk were not significant for GENE76, highlighting the decrease in performance we observed by using the survival data with the full follow-up. This performance degradation was due to a group of late relapses occurring after 10 years of follow-up, classified as low-risk by the three gene signatures (see Supplementary Figure 17 in [Additional File ##SUPPL##0##1##]).</p>", "<p>We combined the three gene signatures using the method described previously. In agreement with the results from survival data censored at 10 years, the combination did not yield significant improvement in prognostication (see Section 2.1.1 in [Additional File ##SUPPL##0##1##]).</p>", "<title>Sensitivity and specificity</title>", "<p>We computed the sensitivity and the specificity for DMFS at 5 years for the three signatures as well as for the clinical risk as defined by AOL. These signatures exhibited high sensitivities (0.97 to 1) compared to the clinical risk (0.88). Similarly to the results reported in previous publications [##REF##11823860##5##, ####REF##15721472##6##, ##REF##16954471##7##, ##REF##17545524##8####17545524##8##,##REF##12490681##18##,##REF##16505412##19##], the gene signatures exhibited low specificities (0.33 to 0.42) which were however higher than the specificity associated with clinical risk assessment (0.26). The estimations of sensitivity and specificity for DMFS, TDM and OS at 3, 5, 10, and 15 years and by considering the full follow-up, are given in Supplementary Tables 7, 10 and 13 [see Additional File ##SUPPL##0##1##]. Although the gene signatures yielded higher sensitivities and specificities than clinical risk until 10 years, we observed a decrease in performance with increasing follow-up duration (10 years and more). The specificities of the gene signatures remained higher than clinical risk but their sensitivities were slightly lower.</p>", "<p>The results were highly concordant between the survival endpoints, namely DMFS, TDM and OS [see Additional File ##SUPPL##0##1##].</p>" ]

[ "<title>Discussion and conclusion</title>", "<p>The objective of this study was to conduct an unbiased comparison of three different prognostic signatures. To this end, the signatures had to be evaluated on their original platform and computed with their original algorithms on an independent population of untreated BC patients. All these requirements were met by the TRANSBIG validation series [##REF##16954471##7##,##REF##17545524##8##]. The results showed that the three evaluated signatures had similar capabilities of predicting DMFS (TDM and OS [see Additional File ##SUPPL##0##1##]) in this set of patients and added significant prognostic information to that provided by the classical parameters.</p>", "<p>Two groups recently undertook to compare different prognostic signatures. Fan <italic>et al</italic>. reported that the intrinsic subtypes and several prognostic signatures [##REF##11823860##5##,##REF##15721472##6##,##REF##14737219##20##, ####REF##15591335##21##, ##REF##10963602##22##, ##REF##11553815##23##, ##REF##12829800##24####12829800##24##] gave similar outcome predictions for the individual patient when investigated on a single dataset [##REF##16899776##25##]. Although this study yielded promising conclusions, some issues remained open: 1/ the dataset which was considered for this study was used for the development of some gene sets and could then not be considered as a true independent validation set for all the evaluated signatures and 2/ since some of these signatures were developed on another platform, the initial algorithms could not be applied. Thomassen <italic>et al</italic>. compared nine prognostic signatures in a cohort of low-malignancy BC patients [##REF##17875763##26##]. In their study, they also compared the same signatures as we did, but computed the associated risk classification from data generated on a different platform, with as consequence that not all the genes from the 76-gene signature and the GGI were represented and that they could not use the original algorithms. Although the proportions of samples that they reported with identical classification were slightly higher to ours, the rank of concordances was similar with 83% between the 70- and 76-gene signatures, 85% between the 76-gene signature and the GGI, and 92% (the highest agreement) between the 70-gene signature and the GGI.</p>", "<p>Thanks to the long follow-up of the TRANSBIG series (up to 25 years), we were able to assess the performance of the three gene signatures with respect to the time. In agreement with Buyse <italic>et al</italic>. [##REF##16954471##7##] and Desmedt <italic>et al</italic>. [##REF##17545524##8##], we observed a strong time dependence of the classification performance. The gene signatures yielded good performance at 10 years but we observed a strong degradation when considering the full follow-up due to the poor identification of late relapses (after 10 years). That might be due to: (i) the biology, Klein <italic>et al. </italic>have suggested that the biological phenomenon responsible for the appearance of early and late relapses might be different [##REF##12241875##27##,##REF##12808139##28##]; (ii) the statistical method, the GENE70 and GENE76 signatures have been developed to predict early relapses (distant metastasis before 5 years) as in the original publications, the authors controlled the sensitivity and the specificity of these signatures for early relapses only; (iii) the quality of survival data, although it is hard to quantify, one could intuitively think that the quality of survival data decreases with respect to the duration of follow-up since it is difficult to follow patients during a long period (high level of censoring).</p>", "<p>While there are only partial or very small to no overlaps between the different prognostic gene signatures [##REF##17894856##29##], there is still a relatively high agreement of classification of the patients between the different signatures. We may assume that these similar outcome predictions are based on representation of largely overlapping biological processes. This is supported by several reports. Indeed, Thomassen <italic>et al</italic>. found that cell cycle and cell proliferation represented the predominant overlaps in gene ontology categories of the nine prognostic signatures they compared [##REF##17875763##26##]. Yu <italic>et al</italic>. also conducted pathway analyses of five published prognostic gene signatures and also found that the signatures had many pathways in common such as cell cycle, regulation of cell cycle, mitosis, apoptosis, etc [##REF##17894856##29##]. Our group also investigated in a large meta-analysis of publicly available gene expression data extensive analysis how different gene lists may give rise to signatures with equivalent prognostic performance and found by dissecting these signatures according to the main molecular processes involved in BC, that proliferation may be the common driving force of several prognostic signatures [##REF##18698033##30##]. This might explain why the combination of the three gene signatures evaluated in this study did not yield significant improvement in prognostication.</p>", "<p>Until now, the generation of the prognostic signatures has been done on global sets of BC patients. However, since it is clear that BC is a molecular heterogeneous disease, with subgroups defined primarily by the estrogen (ER) and HER2 receptors, prognosis could be refined to these molecularly homogeneous subgroups of patients. We showed for example in our meta-analysis that proliferation is the strongest parameter predicting clinical outcome in the ER+/HER2- subgroup of patients only, whereas immune response and tumor invasion appear to be the main biological processes associated with prognosis in the ER-/HER2- and HER2+ subgroups respectively [##REF##18698033##30##]. This could also have implications with regard to the evaluation of response to different therapies [##REF##16115903##31##] and help to define new therapeutic strategies in the specific molecular subgroups of BC patients.</p>", "<p>To conclude, our study showed that although prognostic signatures may have been developed using a different approach, different platforms and statistical tools on different sets of comparable patients, with a small overlap in gene identity as a consequence, they can result in similar predictions of outcome. Although the technology used has been shown to be ready for clinical practice [##REF##16964229##16##], and can be used as one parameter in combination with current clinical parameters, these signatures need to be prospectively validated to prove their superiority and benefit above and beyond the use of standard clinico-pathological prognosis variables to guide the choice of adjuvant therapy. Two gene signatures, the 70-gene signature which has been studied in this paper, and the recurrence score [##REF##15591335##21##] have reached the final step of prospective testing in the MINDACT (Microarray in Node Negative Disease May Avoid Chemotherapy) and TAILORx trials, respectively. We believe that the results from these studies will help to guide future BC treatment.</p>" ]

[ "<title>Discussion and conclusion</title>", "<p>The objective of this study was to conduct an unbiased comparison of three different prognostic signatures. To this end, the signatures had to be evaluated on their original platform and computed with their original algorithms on an independent population of untreated BC patients. All these requirements were met by the TRANSBIG validation series [##REF##16954471##7##,##REF##17545524##8##]. The results showed that the three evaluated signatures had similar capabilities of predicting DMFS (TDM and OS [see Additional File ##SUPPL##0##1##]) in this set of patients and added significant prognostic information to that provided by the classical parameters.</p>", "<p>Two groups recently undertook to compare different prognostic signatures. Fan <italic>et al</italic>. reported that the intrinsic subtypes and several prognostic signatures [##REF##11823860##5##,##REF##15721472##6##,##REF##14737219##20##, ####REF##15591335##21##, ##REF##10963602##22##, ##REF##11553815##23##, ##REF##12829800##24####12829800##24##] gave similar outcome predictions for the individual patient when investigated on a single dataset [##REF##16899776##25##]. Although this study yielded promising conclusions, some issues remained open: 1/ the dataset which was considered for this study was used for the development of some gene sets and could then not be considered as a true independent validation set for all the evaluated signatures and 2/ since some of these signatures were developed on another platform, the initial algorithms could not be applied. Thomassen <italic>et al</italic>. compared nine prognostic signatures in a cohort of low-malignancy BC patients [##REF##17875763##26##]. In their study, they also compared the same signatures as we did, but computed the associated risk classification from data generated on a different platform, with as consequence that not all the genes from the 76-gene signature and the GGI were represented and that they could not use the original algorithms. Although the proportions of samples that they reported with identical classification were slightly higher to ours, the rank of concordances was similar with 83% between the 70- and 76-gene signatures, 85% between the 76-gene signature and the GGI, and 92% (the highest agreement) between the 70-gene signature and the GGI.</p>", "<p>Thanks to the long follow-up of the TRANSBIG series (up to 25 years), we were able to assess the performance of the three gene signatures with respect to the time. In agreement with Buyse <italic>et al</italic>. [##REF##16954471##7##] and Desmedt <italic>et al</italic>. [##REF##17545524##8##], we observed a strong time dependence of the classification performance. The gene signatures yielded good performance at 10 years but we observed a strong degradation when considering the full follow-up due to the poor identification of late relapses (after 10 years). That might be due to: (i) the biology, Klein <italic>et al. </italic>have suggested that the biological phenomenon responsible for the appearance of early and late relapses might be different [##REF##12241875##27##,##REF##12808139##28##]; (ii) the statistical method, the GENE70 and GENE76 signatures have been developed to predict early relapses (distant metastasis before 5 years) as in the original publications, the authors controlled the sensitivity and the specificity of these signatures for early relapses only; (iii) the quality of survival data, although it is hard to quantify, one could intuitively think that the quality of survival data decreases with respect to the duration of follow-up since it is difficult to follow patients during a long period (high level of censoring).</p>", "<p>While there are only partial or very small to no overlaps between the different prognostic gene signatures [##REF##17894856##29##], there is still a relatively high agreement of classification of the patients between the different signatures. We may assume that these similar outcome predictions are based on representation of largely overlapping biological processes. This is supported by several reports. Indeed, Thomassen <italic>et al</italic>. found that cell cycle and cell proliferation represented the predominant overlaps in gene ontology categories of the nine prognostic signatures they compared [##REF##17875763##26##]. Yu <italic>et al</italic>. also conducted pathway analyses of five published prognostic gene signatures and also found that the signatures had many pathways in common such as cell cycle, regulation of cell cycle, mitosis, apoptosis, etc [##REF##17894856##29##]. Our group also investigated in a large meta-analysis of publicly available gene expression data extensive analysis how different gene lists may give rise to signatures with equivalent prognostic performance and found by dissecting these signatures according to the main molecular processes involved in BC, that proliferation may be the common driving force of several prognostic signatures [##REF##18698033##30##]. This might explain why the combination of the three gene signatures evaluated in this study did not yield significant improvement in prognostication.</p>", "<p>Until now, the generation of the prognostic signatures has been done on global sets of BC patients. However, since it is clear that BC is a molecular heterogeneous disease, with subgroups defined primarily by the estrogen (ER) and HER2 receptors, prognosis could be refined to these molecularly homogeneous subgroups of patients. We showed for example in our meta-analysis that proliferation is the strongest parameter predicting clinical outcome in the ER+/HER2- subgroup of patients only, whereas immune response and tumor invasion appear to be the main biological processes associated with prognosis in the ER-/HER2- and HER2+ subgroups respectively [##REF##18698033##30##]. This could also have implications with regard to the evaluation of response to different therapies [##REF##16115903##31##] and help to define new therapeutic strategies in the specific molecular subgroups of BC patients.</p>", "<p>To conclude, our study showed that although prognostic signatures may have been developed using a different approach, different platforms and statistical tools on different sets of comparable patients, with a small overlap in gene identity as a consequence, they can result in similar predictions of outcome. Although the technology used has been shown to be ready for clinical practice [##REF##16964229##16##], and can be used as one parameter in combination with current clinical parameters, these signatures need to be prospectively validated to prove their superiority and benefit above and beyond the use of standard clinico-pathological prognosis variables to guide the choice of adjuvant therapy. Two gene signatures, the 70-gene signature which has been studied in this paper, and the recurrence score [##REF##15591335##21##] have reached the final step of prospective testing in the MINDACT (Microarray in Node Negative Disease May Avoid Chemotherapy) and TAILORx trials, respectively. We believe that the results from these studies will help to guide future BC treatment.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>During the last years, several groups have identified prognostic gene expression signatures with apparently similar performances. However, signatures were never compared on an independent population of untreated breast cancer patients, where risk assessment was computed using the original algorithms and microarray platforms.</p>", "<title>Results</title>", "<p>We compared three gene expression signatures, the 70-gene, the 76-gene and the Gene expression Grade Index (GGI) signatures, in terms of predicting distant metastasis free survival (DMFS) for the individual patient. To this end, we used the previously published TRANSBIG independent validation series of node-negative untreated primary breast cancer patients. We observed agreement in prediction for 135 of 198 patients (68%) when considering the three signatures. When comparing the signatures two by two, the agreement in prediction was 71% for the 70- and 76-gene signatures, 76% for the 76-gene signature and the GGI, and 88% for the 70-gene signature and the GGI. The three signatures had similar capabilities of predicting DMFS and added significant prognostic information to that provided by the classical parameters.</p>", "<title>Conclusion</title>", "<p>Despite the difference in development of these signatures and the limited overlap in gene identity, they showed similar prognostic performance, adding to the growing evidence that these prognostic signatures are of clinical relevance.</p>" ]

[ "<title>Competing interests</title>", "<p>Christos Sotiriou, Mauro Delorenzi and Martine Piccart are named inventors on a patent application for the Genomic Grade signature used in this study. Laura van't Veer is founder and stock owner of Agendia. There are no other conflicts of interest.</p>", "<title>Authors' contributions</title>", "<p>BH–K, CD, CS were responsible for the design and execution of the study, data and statistical analysis and interpretation, and final manuscript writing; FP, MB, GB, FC, LV, MP supported the data and statistical analysis and interpretation; GB, CS supervised the study. MP, CS provided the study funding. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to thank Carolyn Straehle for her editorial comments. This work was supported by the Belgian National Foundation for Cancer Research FNRS (CD, BHK, CS), the MEDIC Foundation (CS), the European Union 6^thFramework program TRANSBIG.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Venn diagram illustrating the classification of the tumor sample according to the prognostic signatures.</bold> Dark red = high-risk patients and blue = low-risk patients. GENE70 = 70-gene signature, GENE76 = 76-gene signature, and GGI = Gene expression Grade Index.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Forest plots (and 95% CI) for the three gene signatures and the Adjuvant! Online classification showing: A/the concordance indices, and B/the log2 hazard ratios.</bold> GENE70 = 70-gene signature, GENE76 = 76-gene signature, GGI = Gene expression Grade Index and AOL = Adjuvant! Online.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Kaplan-Meier curves for distant metastasis free survival for: A/the 70-gene signature vs the 76-gene signature; B/the 70-gene signature vs the Gene expression Grade Index, and C/the 76-gene signature vs the Gene expression Grade Index.</bold> GENE70 = 70-gene signature, GENE76 = 76-gene signature and GGI = Gene expression Grade Index.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Characteristics of patients of the TRANSBIG validation series (n = 198), according to the 70-gene signature (GENE70), the 76-gene signature (GENE76), the Gene expression Grade Index (GGI) and the Adjuvant! Online (AOL) risk classifications.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Signature</td><td align=\"center\" colspan=\"2\">GENE70</td><td align=\"center\" colspan=\"2\">GENE76</td><td align=\"center\" colspan=\"2\">GGI</td><td align=\"center\" colspan=\"2\">AOL</td></tr></thead><tbody><tr><td align=\"left\">Number of patients</td><td align=\"center\">Low-risk <break/>(N = 66)</td><td align=\"center\">High-risk <break/>(N = 132)</td><td align=\"center\">Low-risk <break/>(N = 55)</td><td align=\"center\">High-risk <break/>(N = 143)</td><td align=\"center\">Low-risk <break/>(N = 69)</td><td align=\"center\">High-risk <break/>(N = 129)</td><td align=\"center\">Low-risk <break/>(N = 46)</td><td align=\"center\">High-risk <break/>(N = 152)</td></tr><tr><td colspan=\"9\"><hr/></td></tr><tr><td align=\"left\">Age</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> &lt; 41 years</td><td align=\"center\">11</td><td align=\"center\">31</td><td align=\"center\">10</td><td align=\"center\">32</td><td align=\"center\">10</td><td align=\"center\">32</td><td align=\"center\">4</td><td align=\"center\">38</td></tr><tr><td align=\"left\"> 41–50 years</td><td align=\"center\">33</td><td align=\"center\">67</td><td align=\"center\">24</td><td align=\"center\">76</td><td align=\"center\">33</td><td align=\"center\">67</td><td align=\"center\">33</td><td align=\"center\">67</td></tr><tr><td align=\"left\"> 51–60 years</td><td align=\"center\">33</td><td align=\"center\">34</td><td align=\"center\">24</td><td align=\"center\">35</td><td align=\"center\">26</td><td align=\"center\">30</td><td align=\"center\">9</td><td align=\"center\">47</td></tr><tr><td align=\"left\">Size</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> T1ab (&lt; 1 cm)</td><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">4</td><td align=\"center\">5</td><td align=\"center\">8</td><td align=\"center\">1</td></tr><tr><td align=\"left\"> T1c (1–2 cm)</td><td align=\"center\">24</td><td align=\"center\">35</td><td align=\"center\">17</td><td align=\"center\">42</td><td align=\"center\">25</td><td align=\"center\">34</td><td align=\"center\">21</td><td align=\"center\">38</td></tr><tr><td align=\"left\"> T2 (2–5 cm)</td><td align=\"center\">38</td><td align=\"center\">92</td><td align=\"center\">34</td><td align=\"center\">96</td><td align=\"center\">40</td><td align=\"center\">90</td><td align=\"center\">17</td><td align=\"center\">113</td></tr><tr><td align=\"left\">Tumor grade</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Good differentiation</td><td align=\"center\">17</td><td align=\"center\">13</td><td align=\"center\">14</td><td align=\"center\">16</td><td align=\"center\">20</td><td align=\"center\">10</td><td align=\"center\">23</td><td align=\"center\">7</td></tr><tr><td align=\"left\"> Intermediate</td><td align=\"center\">42</td><td align=\"center\">41</td><td align=\"center\">21</td><td align=\"center\">62</td><td align=\"center\">44</td><td align=\"center\">39</td><td align=\"center\">23</td><td align=\"center\">60</td></tr><tr><td align=\"left\"> Poor differentiation</td><td align=\"center\">7</td><td align=\"center\">76</td><td align=\"center\">20</td><td align=\"center\">63</td><td align=\"center\">5</td><td align=\"center\">78</td><td align=\"center\">0</td><td align=\"center\">83</td></tr><tr><td align=\"left\"> Unknown</td><td align=\"center\">0</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">2</td><td align=\"center\">0</td><td align=\"center\">2</td></tr><tr><td align=\"left\">Estrogen receptors</td><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"> Positive</td><td align=\"center\">63</td><td align=\"center\">71</td><td align=\"center\">41</td><td align=\"center\">93</td><td align=\"center\">65</td><td align=\"center\">69</td><td align=\"center\">46</td><td align=\"center\">88</td></tr><tr><td align=\"left\"> Negative</td><td align=\"center\">3</td><td align=\"center\">61</td><td align=\"center\">14</td><td align=\"center\">50</td><td align=\"center\">4</td><td align=\"center\">60</td><td align=\"center\">0</td><td align=\"center\">64</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>P-values of the Student t test for the difference between concordance indices and hazard ratios for the 70-gene signature (GENE70), the 76-gene signature (GENE76), and the Gene expression Grade Index (GGI) risk classifications.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\">p-value for difference in concordance indices</td><td align=\"center\">p-value for difference in hazard ratios</td></tr></thead><tbody><tr><td align=\"left\">GENE70 vs GENE76</td><td align=\"center\">0.15</td><td align=\"center\">0.11</td></tr><tr><td align=\"left\">GENE70 vs GGI</td><td align=\"center\">0.53</td><td align=\"center\">0.42</td></tr><tr><td align=\"left\">GENE76 vs GGI</td><td align=\"center\">0.22</td><td align=\"center\">0.19</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Multivariate Cox analyses for the 70-gene signature (GENE70), the 76-gene signature (GENE76) and the Gene expression Grade Index (GGI) risk classifications.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"2\">GENE70</td><td align=\"center\" colspan=\"2\">GENE76</td><td align=\"center\" colspan=\"2\">GGI</td></tr><tr><td/><td colspan=\"6\"><hr/></td></tr><tr><td/><td align=\"center\">HR <break/>(95% CI)</td><td align=\"center\">p-value</td><td align=\"center\">HR <break/>(95% CI)</td><td align=\"center\">p-value</td><td align=\"center\">HR <break/>(95% CI)</td><td align=\"center\">p-value</td></tr></thead><tbody><tr><td align=\"left\">Age (≤ or &gt;50 years)</td><td align=\"center\">1.51 (0.82–2.79)</td><td align=\"center\">0.3</td><td align=\"center\">1.78 (0.97–3.25)</td><td align=\"center\">0.062</td><td align=\"center\">1.73 (0.94–3.16)</td><td align=\"center\">0.077</td></tr><tr><td align=\"left\">Tumor Size (≤ or &gt;2 cm)</td><td align=\"center\">1.3 (0.72–2.5)</td><td align=\"center\">0.36</td><td align=\"center\">1.27 (0.68–2.37)</td><td align=\"center\">0.45</td><td align=\"center\">1.22 (0.65–2.29)</td><td align=\"center\">0.53</td></tr><tr><td align=\"left\">ER status</td><td align=\"center\">0.82 (0.43–1.6)</td><td align=\"center\">0.57</td><td align=\"center\">0.6 (0.31–1.17)</td><td align=\"center\">0.13</td><td align=\"center\">0.78 (0.4–1.51)</td><td align=\"center\">0.46</td></tr><tr><td align=\"left\">Grade</td><td align=\"center\">0.93 (0.34–2.53)</td><td align=\"center\">0.89</td><td align=\"center\">1.51 (0.53–4.28)</td><td align=\"center\">0.5</td><td align=\"center\">0.75 (0.27–2.08)</td><td align=\"center\">0.58</td></tr><tr><td align=\"left\">Risk according to the gene signature</td><td align=\"center\">7.1 (2.4–21)</td><td align=\"center\">4 × 10^-4</td><td align=\"center\">3.39 (1.41–8.12)</td><td align=\"center\">6 × 10^-3</td><td align=\"center\">6.42 (2.36–17.45)</td><td align=\"center\">3 × 10^-4</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Supplementary information.</p></caption></supplementary-material>" ]

[]

[ "<graphic xlink:href=\"1471-2164-9-394-1\"/>", "<graphic xlink:href=\"1471-2164-9-394-2\"/>", "<graphic xlink:href=\"1471-2164-9-394-3\"/>" ]

[ "<media xlink:href=\"1471-2164-9-394-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>In the last few years, the real-time polymerase chain reaction (PCR) has rapidly become the most widely used technique in modern molecular biology [##REF##7764001##1##, ####REF##11846607##2##, ##REF##15331581##3##, ##REF##15650028##4####15650028##4##]. This technique relies on fluorescence-based detection of amplicon DNA and allows the kinetics of PCR amplification to be monitored in real time, making it possible to quantify nucleic acids with extraordinary ease and precision. With a large dynamic range (7–8 magnitudes) and a high degree of sensitivity (5–10 molecules), the real-time PCR addresses the evident requirement for quantitative data analysis in molecular medicine, biotechnology, microbiology and diagnostics [##REF##16171460##5##,##REF##17406449##6##].</p>", "<p>Although, the real-time PCR analysis has gained considerable attention in many fields of molecular biology, it is far from being a standard assay. One of the problems associated with this assay, which has a direct impact on its reliability, is inconsistent data analysis. At the present, real-time PCR analysis is highly subjective and, if carried out inappropriately, confuses the actual results [##REF##15255547##7##]. Many different options for data processing are currently available. The basic choice in real time PCR calculations is between absolute quantification, based on standard curve, and relative quantification, based on PCR efficiency calculation. Using the software currently available, analysis of real-time PCR data is generally based on the \"cycle-threshold\" method. The cycle-threshold is defined as the fractional cycle number in the log-linear region of PCR amplification in which the reaction reaches fixed amounts of amplicon DNA. There are two methods for determining the cycle-threshold value; one method, namely fit point, is performed by drawing a line parallel to the x-axis of the real-time fluorescence intensity curve (<italic>Ct</italic>) [##UREF##0##8##]. The second, namely second derivative, calculates the fractional cycle where the second derivative of the real-time fluorescence intensity curve reaches the maximum value (<italic>Cp</italic>) [##REF##15727135##9##]. Standard curve method requires generating serial dilutions of a given sample and performing multiple PCR reactions on each dilution [##UREF##1##10##,##REF##12907745##11##], the threshold-cycle values are then plotted versus the log of the dilution and a linear regression is performed from which the mean efficiency can be derived. This approach is only valid if the threshold-cycle values are measured from the exponential phase of the PCR reaction and if the efficiency is identical between amplifications. Furthermore, this efficiency is assumed to be the same for all the standard dilutions, but some authors have reported that this assumption may be questionable [##REF##8717060##12##].</p>", "<p>It is well-recognized that template quality is one of the most important determinants of real-time PCR reliability and reproducibility [##REF##12930979##13##], and numerous authors have shown the significant reduction in the sensitivity and kinetics of real-time PCR assays caused by inhibitory components frequently found in biological samples [##REF##14635021##14##, ####REF##14996458##15##, ##REF##15746310##16##, ##REF##16882221##17####16882221##17##]. The inhibiting agents may be reagents used during nucleic acid extraction or copurified components from the biological sample such as bile salts, urea, haeme, heparin, and immunoglobulin G. Inhibitors can generate strongly inaccurate quantitative results; while, a high degree of inhibition may even create false-negative results.</p>", "<p>The <italic>Ct </italic>method is the most widely used method even though its calculation is user-dependent. The <italic>Ct </italic>method is quite stable and straightforward but the accuracy of estimates is strongly impaired if efficiency is not equal in all reactions. Indeed, uniform reaction efficiency is the most important assumption of the <italic>Ct </italic>method.</p>", "<p>An alternative approach, proposed by Liu and Saint [##REF##12051718##18##], assumes a dynamic change in efficiency fitting PCR amplification with a sigmoid function (<underline>S</underline>igmoidal <underline>c</underline>urve <underline>f</underline>itting method, <italic>SCF</italic>). One of the advantages of this regression analysis is that it allows us to estimate the initial template amount directly from the non-linear regression, eliminating the need for a standard curve. These pioneering works showed that it was possible to obtain absolute quantification from real-time fluorescence curve shape. However, recent reports have demonstrated that, in an optimized assay, the <italic>Ct </italic>method remains the gold standard due to the inherent errors of the multiple estimates used in non-linear regression [##REF##16515700##19##,##REF##17445280##20##].</p>", "<p>We propose, in this report, a modified standard curve-based method (named <italic>Cy</italic>_{<italic>0</italic>}) that does not require the assumption of uniform reaction efficiency between standards and unknown and does not involve any choice of threshold level by the user.</p>", "<p>The aim of this work was also to compare the accuracy and precision of the <italic>SCF</italic>, <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods in presence of varying PCR kinetics. Our results clearly show that the proposed data processing procedure can effectively be applied in the quantification of samples characterized by slight amplification inhibition obtaining reliable and precise results.</p>" ]

[ "<title>Methods</title>", "<title>Experimental design</title>", "<p>The absolute quantification method relies on the comparison of distinct samples, such as the comparison of a biological sample with a standard curve of known initial concentration [##REF##11013345##21##]. We wondered how accuracy and precision change when a standard curve is compared with unknown samples characterized by different efficiencies. A natural way of studying the effect of efficiency differences among samples on quantification would be to compare the amounts of a quantified gene.</p>", "<p>A slight amplification inhibition in the quantitative real-time PCR experiments was obtained by using two systems: decreasing the amplification mix used in the reaction and adding varying amounts of IgG, a known PCR inhibitor.</p>", "<p>For the first system, we amplified the MT-ND1 gene by real-time PCR in reactions having the same initial amount of DNA but different amounts of SYBR Green I Master mix. A standard curve was performed over a wide range of input DNA (3.14 × 10⁷–3.14 × 10¹) in the presence of optimal amplification conditions (100% amplification mix), while the unknowns were run in the presence of the same starting DNA amounts but with amplification mix quantities ranging from 60% to 100%. This produced different reaction kinetics, mimicking the amplification inhibition that often occurs in biological samples [##REF##16882221##17##,##REF##15036369##22##].</p>", "<p>Furthermore, quantitative real-time PCR quantifications were performed in the presence of an optimal amplification reaction mix added with serial dilutions of IgG (0.0625 – 2 μg/ml) thus acting as the inhibitory agent [##REF##16524557##23##].</p>", "<p>The reaction efficiency obtained was estimated by the LinReg method [##REF##12618301##24##]. This approach identifies the exponential phase of the reaction by plotting the fluorescence on a log scale. A linear regression is then performed leading to the estimation of the efficiency of each PCR reaction.</p>", "<title>Quantitative Real-Time PCR</title>", "<p>The DNA standard consisted of a pGEM-T (Promega) plasmid containing a 104 bp fragment of the mitochondrial gene NADH dehydrogenase 1 (MT-ND1) as insert. This DNA fragment was produced by the ND1/ND2 primer pair (forward ND1: 5'-ACGCCATAAAACTCTTCACCAAAG-3' and reverse ND2: 5'-TAGTAGAAGAGCGATGGTGAGAGCTA-3'). This plasmid was purified using the Plasmid Midi Kit (Qiagen) according to the manufacturer's instructions. The final concentration of the standard plasmid was estimated spectophotometrically by averaging three replicate A₂₆₀absorbance determinations.</p>", "<p>Real time PCR amplifications were conducted using LightCycler^®480 SYBR Green I Master (Roche) according to the manufacturer's instructions, with 500 nM primers and a variable amount of DNA standard in a 20 μl final reaction volume. Thermocycling was conducted using a LightCycler^®480 (Roche) initiated by a 10 min incubation at 95°C, followed by 40 cycles (95°C for 5 s; 60°C for 5 s; 72°C for 20 s) with a single fluorescent reading taken at the end of each cycle. Each reaction combination, namely starting DNA and amplification mix percentage, was conducted in triplicate and repeated in four separate amplification runs. All the runs were completed with a melt curve analysis to confirm the specificity of amplification and lack of primer dimers. <italic>Ct </italic>(fit point method) and <italic>Cp </italic>(second derivative method) values were determined by the LightCycler^®480 software version 1.2 and exported into an MS Excel data sheet (Microsoft) for analysis after background subtraction (available as Additional file ##SUPPL##0##1##). For <italic>Ct </italic>(fit point method) evaluation a fluorescence threshold manually set to 0.5 was used for all runs.</p>", "<title>Description of the <italic>SCF </italic>method</title>", "<p>Fluorescence readings were used to fit the following 4-parameter sigmoid function using nonlinear regression analysis:</p>", "<p></p>", "<p>where <italic>x </italic>is the cycle number, <italic>F</italic>_{<italic>x </italic>}is the reaction fluorescence at cycle <italic>x</italic>, <italic>F</italic>_{<italic>max </italic>}is the maximal reaction fluorescence, <italic>c </italic>is the fractional cycle at which reaction fluorescence reaches half of <italic>F</italic>_{<italic>max</italic>}, <italic>b </italic>is related to the slope of the curve and <italic>F</italic>_{<italic>b </italic>}is the background reaction fluorescence. <italic>F</italic>_{<italic>max </italic>}quantifies the maximal fluorescence read by the instrument and does not necessarily indicate the amount of DNA molecules present at the end of the reaction. The fact that <italic>F</italic>_{<italic>max </italic>}does not necessarily represent the final amount of DNA might be due to un-saturating dye concentration or to fluorescence quenching by inhibitors. For each run a nonlinear regression analysis was performed and these four parameters were evaluated. A simple derivative of Eq. 1 allowed us to estimate <italic>F</italic>_{<italic>0</italic>}, when <italic>x </italic>= 0:</p>", "<p></p>", "<p>where <italic>F</italic>_{<italic>0 </italic>}represents the initial target quantity expressed in fluorescence units. Conversion of <italic>F</italic>_{<italic>0 </italic>}to the number of target molecules was obtained by a calibration curve in which the log input DNA was related to the log of <italic>F</italic>_{<italic>0 </italic>}[##REF##12051718##18##]. Subsequently, this equation was used for quantification with log transformation of fluorescence data to increase goodness-of-fit as described in Goll <italic>et al</italic>. 2006 [##REF##16515700##19##].</p>", "<title>Description of the <italic>Cy</italic>_{<italic>0 </italic>}method</title>", "<p>The <italic>Cy</italic>_{<italic>0 </italic>}value is the intersection point between the abscissa axis and tangent of the inflection point of the Richards curve obtained by the non-linear regression of raw data (Fig. ##FIG##0##1##).</p>", "<p>The <italic>Cy</italic>_{<italic>0 </italic>}method was performed by nonlinear regression fitting of the Richards function [##UREF##2##25##], an extension of logistic growth curve, in order to fit fluorescence readings to the 5-parameter Richards function:</p>", "<p></p>", "<p>where <italic>x </italic>is the cycle number, <italic>F</italic>_{<italic>x </italic>}is the reaction fluorescence at cycle <italic>x</italic>, <italic>F</italic>_{<italic>max </italic>}is the maximal reaction fluorescence, <italic>x </italic>is the fractional cycle of the turning point of the curve, <italic>d </italic>represents the Richards coefficient, and <italic>F</italic>_{<italic>b </italic>}is the background reaction fluorescence. The inflection point coordinate (<italic>Flex</italic>) was calculated as follows (Additional file ##SUPPL##1##2##):</p>", "<p></p>", "<p>and the tangent slope (<italic>m</italic>) was estimated as:</p>", "<p></p>", "<p>When <italic>d </italic>= 1, the Richards equation becomes the logistic equation shown above. The five parameters that characterized each run were used to calculate the <italic>Cy</italic>_{<italic>0 </italic>}value by the following equation:</p>", "<p></p>", "<p>Although the <italic>Cy</italic>_{<italic>0 </italic>}is a single quantitative entity, as is the <italic>Ct </italic>or <italic>Cp </italic>for threshold methodologies, it accounts for the reaction kinetic because it is calculated on the basis of the slope of the inflection point of fluorescence data.</p>", "<title>Statistical data analysis</title>", "<p>Nonlinear regressions (for 4-parameter sigmoid and 5-parameter Richards functions) were performed determining unweighted least squares estimates of parameters using the Levenberg-Marquardt method. Accuracy was calculated using the following equation:</p>", "<p>, where was the relative error, while and were the estimated and the true number of DNA molecules for each combination of input DNA (<italic>n</italic>_{<italic>Dna</italic>}) and amplification mix percentage (<italic>%</italic>_{<italic>mix</italic>}) used in the PCR. Precision was calculated as:</p>", "<p>, where was the coefficient of variation, and were the mean and the standard deviation for each combination of n_Dnaand %_mix. In order to verify that the Richards curves, obtained by nonlinear regression of fluorescence data, were not significantly different from the sigmoidal curves, the values of <italic>d </italic>parameter were compared to the expected value <italic>d </italic>= 1, using <italic>t </italic>test for one sample. For each combination of <italic>n</italic>_{<italic>Dna</italic>}, <italic>%</italic>_{<italic>mix</italic>}, the <italic>t </italic>values were calculated as follow:</p>", "<p>, where and were the mean and the standard error of <italic>d </italic>values for each combination of <italic>n</italic>_{<italic>Dna </italic>}and <italic>%</italic>_{<italic>mix</italic>}, with p(<italic>t</italic>) &lt; 0.05 for significance level. values were reported using 3-d scatterplot graphic, a complete second order polinomial regression function was shown to estimate the trend of accuracy values. where also reported using 3-d contour plots using third-order polynomials spline fitting. All elaborations and graphics were obtained using Excel (Microsoft), Statistica (Statsoft) and Sigmaplot 10 (Systat Software Inc.).</p>" ]

[ "<title>Results</title>", "<title>Experimental system 1: reduction of amplification mix percentage</title>", "<p>With our experimental set up, the mean PCR reaction efficiency was 88% under optimal amplification conditions and slightly decreased in the presence of smaller amplification mix up to 84%. Moreover, for decreasing amplification mix amounts, the PCR reaction efficiencies showed higher dispersion levels than optimal conditions leading to increasing quantitative errors (Variation Interval, VI_100%= 92%–85% and VI_60%= 90%–77%; Fig. ##FIG##1##2##). Subsequently, the fluorescence data obtained in these reactions were used to calculate the initial DNA amount using four different procedures: <italic>SCF</italic>, <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0</italic>}.</p>", "<title>Precision and accuracy of the <italic>SCF </italic>method</title>", "<p>Previous studies have shown that the <italic>SCF </italic>approach can lead to quantification without prior knowledge of amplification efficiency [##REF##12051718##18##,##REF##16515700##19##,##REF##15601990##26##]; therefore, we evaluated the performance of this method on our data set. To assess the effect of unequal efficiencies on accuracy, the calculated input DNA, expressed as molecular number, was compared to the expected value obtaining the relative error (RE). The precision was further evaluated measuring the variation coefficient (CV%) of the estimated initial DNA in the presence of different PCR efficiencies and input DNA.</p>", "<p>In our experimental design, the <italic>SCF </italic>method showed a very poor precision (mean CV% = 594.74%) and low accuracy (mean RE = -5.05). The impact of amplification efficiency decline on accuracy was very strong resulting in an underestimate of samples of up to 500% (Additional file ##SUPPL##2##3##). The log transformation of fluorescence data before sigmoidal fitting significantly reduced the CV% and RE to 66.12% and -0.20, respectively; however, the overall bias remained the same [##REF##16515700##19##]. Finally, we also tested an improved <italic>SCF </italic>approach based on a previous study by Rutledge 2004 [##REF##15601990##26##] without obtaining significant amelioration (Additional file ##SUPPL##3##4##).</p>", "<title>The <italic>Cy</italic>_{<italic>0 </italic>}method</title>", "<p>The <italic>SCF </italic>model assumes that the fluorescence signal is proportional to the amount of product, which is often the case for SYBR-Green I real-time PCR performed with saturing concentrations of dye. In such conditions, centrally symmetric amplification curves are expected. However, in our experience, we found several non-symmetric amplification curves shown to have good amplification efficiency using standard curve analysis (Additional file ##SUPPL##0##1## and ##SUPPL##2##3##). In order to find a suitable mathematical representation of the complete PCR kinetic curve we compared the standard error of estimate obtained by several equations that generate S-shaped curves (Tab. ##TAB##0##1##). As shown in Figure ##FIG##0##1##, these results demonstrated that real-time PCR readouts can be effectively modelled using the 5-parameter Richards function (Eq. 3). The Richards equation is an extension of the sigmoidal growth curve; specifically, when <italic>d </italic>coefficient is equal to 1, the sigmoidal and Richards curves are the same. Hence, we analysed the variation of the <italic>d </italic>coefficient in the presence of different input DNA and PCR efficiencies. Figure ##FIG##2##3## shows that the <italic>d </italic>value is close to 1 at amplification mix percentages ranging from 100% to 90% while at lower amplification mix contents, where PCR efficiency decreases, the <italic>d </italic>coefficient was significantly higher than 1 regardless of the starting DNA content (Fig. ##FIG##2##3##; Tab. ##TAB##1##2##). These data demonstrate that sigmoidal fitting represents a good approximation of real-time PCR kinetic only in the presence of optimal amplification conditions while the Richards curve is more suited when PCR is inhibited. Since the Richards growth equation includes sigmoidal amplification curves, when <italic>d </italic>= 1, this nonlinear fitting was used in our method.</p>", "<p>Despite the good fitting obtained by the Richards equation, the application of kinetic parameters to estimate <italic>F</italic>_{<italic>0 </italic>}values showed a very low degree of precision and accuracy (Additional file ##SUPPL##2##3##). In an attempt to increase the reproducibility of outcomes a log transformation of fluorescence data was performed, however no satisfactory results were obtained (Additional file ##SUPPL##2##3##). To overcome these problems, we formulated an alternative method for starting DNA estimation that defines a new quantitative entity, <italic>Cy</italic>_{<italic>0</italic>}. <italic>Cy</italic>_{<italic>0 </italic>}can be considered similar to <italic>Ct </italic>or <italic>Cp </italic>but the main advantage of the <italic>Cy</italic>_{<italic>0 </italic>}method is that it takes into account the kinetic parameters of amplification curve. This new method is based on the fit of Eq. 3 to real-time PCR data by nonlinear regression in order to obtain the best fit estimators of reaction parameters. In addition, these parameters were used to calculate the <italic>Cy</italic>_{<italic>0 </italic>}value using Eq. 6. From a mathematical standpoint, the <italic>Cy</italic>_{<italic>0 </italic>}value represents the cross point between the x-axis and the tangent crossing the inflection point of the real-time PCR fluorescence curve. For example, in Figure ##FIG##3##4##, three real-time PCR quantifications starting from the same amount of DNA but in the presence of decreasing amplification mix are shown. In these amplification conditions, the <italic>Ct </italic>method clearly underestimated the samples due to the shift towards the right of <italic>Ct </italic>(Fig. ##FIG##3##4A##). On the contrary, using the <italic>Cy</italic>_{<italic>0 </italic>}methods this shift was clearly correct. In fact, in the presence of PCR inhibition, the fluorescence values of curve inflection points decreased as did the slope of the curve in that point. This resulted in a very small variation of <italic>Cy</italic>_{<italic>0 </italic>}values (CV% = 0.6%; Fig. ##FIG##3##4B##), while the same fluorescence data analysed by <italic>Ct </italic>methods produced a CV% of 1.45% (Fig. ##FIG##3##4A##).</p>", "<title>Precision and accuracy of the <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods</title>", "<p>The performance of the <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods was compared in terms of precision and accuracy over a wide range of input DNA concentrations and under different reaction efficiencies obtained by decreasing the amount of amplification mix as reported in Liu and Saint [##REF##12051718##18##,##REF##17349040##27##]. As shown in Figure ##FIG##4##5A##, the <italic>Ct </italic>method is highly rigorous at maximum reaction efficiency regardless of the starting DNA template. However, the absolute value of RE increased almost linearly with the decrease of efficiency regardless of the template concentrations resulting in an underestimation of the unknown of about 50% at the lowest amplification efficiencies. The <italic>Cp </italic>was more accurate than the <italic>Ct </italic>method in the presence of different amounts of amplification mix. Indeed, the relative error in the presence of 100% amplification mix tended towards zero as it did using the <italic>Ct </italic>method. However, when the efficiency declined, the RE increased initially in the same manner at low and high input DNA concentrations, while at 60–70% of the amplification mix, this method markedly underestimated at low concentrations (mean RE_{60% mix;}= -0.58; Fig. ##FIG##4##5C##). Finally, the <italic>Cy</italic>_{<italic>0 </italic>}method was more accurate than the <italic>Cp </italic>method (mean RE -0.12 versus -0.18, respectively; Fig. ##FIG##4##5C, E##), which in turn was better than the <italic>Ct </italic>method (mean RE = -0.31). Notably, at optimal amplification conditions (90–100% of the amplification mix) the <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods were equivalent, but at decreasing efficiencies, the <italic>Cy</italic>_{<italic>0 </italic>}accuracy was more stable than that of the <italic>Cp </italic>in the concentration range from 3.14 × 10⁷to 3.14 × 10⁵molecules. At lower DNA concentrations, from 3.14 × 10⁴to 3.14 × 10²molecules, the RE proportionally increased with the efficiency decline, but this underestimate was less marked than that of the <italic>Cp </italic>method at the same starting DNA (Fig. ##FIG##4##5C, E##). Regarding the precision of the three methods, the variation coefficients were determined for each combination of initial template amount and amplification mix percentage. The random error of quantification achieved by the <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}method was similar (mean CV% 21.8% and 22.5%, respectively), while the <italic>Ct </italic>procedure produced an overall CV% of about 39.7% (Tab. ##TAB##2##3##). When the CV was analysed in relation to PCR efficiency and input DNA, an area of low variation coefficients for the three methods was found between 3.14 × 10⁴and 3.14 × 10⁷molecules as starting material (Fig. ##FIG##4##5B, D, F##). With DNA amounts ranging from 3.14 × 10³to 3.14 × 10²molecules, the precision progressively decreased in each analysis procedure. These variations were not efficiency-dependent, but were related to initial DNA quantity as shown by the shapes of level curves reported in Figure ##FIG##4##5B, D## and ##FIG##4##5F##, which were perpendicular to the input template amounts.</p>", "<title>Experimental system 2: Real-time PCR quantification in the presence of the inhibitor IgG</title>", "<p>The real-time amplification plot of 4.05 × 10⁶DNA molecules with increasing concentrations of IgG demonstrates the effects of PCR inhibition on amplification efficiency and accumulated fluorescence (Fig. ##FIG##5##6A##). As inhibitor concentrations increased, the amplification curves showed lower plateau fluorescence levels and a shift towards the right and the bottom of the inflection points, leading to amplification curves that were less steep and not as symmetric as those obtained in absence of the inhibitor agent (Fig. ##FIG##5##6A##). As shown in figure ##FIG##5##6A## the amplification curves inhibited by IgG showed a shape very similar to those resulting from the system of amplification mix reduction (system 1; Fig. ##FIG##3##4A##). Quantitative data analysis of these amplification plots showed that the estimated DNA quantities were systematically underestimated in the presence of IgG concentrations higher than 0.25 μg/ml and 1 μg/ml using <italic>Ct </italic>and <italic>Cp </italic>methods, respectively. However, the <italic>Cy</italic>_{<italic>0 </italic>}method was able to adjust this bias minimizing the RE at high IgG concentrations (RE = 4.98%; CV = 4.33%; Fig. ##FIG##5##6B##). Furthermore, in presence of high IgG concentrations, the <italic>SCF </italic>approach, modified according to Rutledge 2004 [##REF##15601990##26##], was inapplicable because it was impossible to minimize <italic>F</italic>_{<italic>0 </italic>}value (Additional file ##SUPPL##4##5##).</p>" ]

[ "<title>Discussion</title>", "<p>None of the current quantitative PCR data treatment methods is in fact fully assumption-free, and their statistical reliability are often poorly characterized. In this study, we evaluated whether known real-time elaboration methods could estimate the amount of DNA in biological samples with precision and accuracy when reaction efficiencies of the unknown are different from those of the standard curve.</p>", "<p>Our experimental systems consisted in the quantification of samples with the same known starting template amount but the amplification reaction, performed for the real-time PCR assay, had a slightly decreasing efficiency. This is clearly not in agreement with the main assumption of the threshold approach which holds that the amplification efficiency of samples has to be identical to, or not significantly different from, that predicted by the standard curve. However, such an assumption has been reported to be patently invalid for many cases in medical diagnostics. In fact, some, if not all, of the biological samples may contain inhibitors that are not present in the standard nucleic acid samples used to construct the calibration curve, leading to an underestimation of the DNA quantities in the unknown samples [##REF##11333300##28##,##REF##12507960##29##]. In our study, slightly decreasing efficiencies were obtained by two systems: diluting the master enzyme mix or adding IgG, a known inhibitor of PCR. Although, the first system is an \"in vitro\" simulation of PCR inhibition, it produces amplification curves very similar to those obtained in the presence of a biological inhibitor like IgG.</p>", "<p>Notably, our experimental setup is not characterized by aberrant amplification reactions. On the contrary, the reactions show a slight mean efficiency decrease which is always the case of biological samples. This PCR inhibition remains undetected when using a threshold approach leading to target underestimation. Moreover, small differences in amplification efficiency produce large quantitative errors and the frequency and magnitude of these errors are virtually impossible to ascertain using a threshold approach. It has been shown that a difference as small as 4% in PCR efficiency could translate into a 400% error in comparative <italic>Ct </italic>method based quantification [##REF##12618301##24##].</p>", "<p>Considering previous works [##REF##12051718##18##,##REF##16515700##19##] which demonstrated the capability of the <italic>SCF </italic>method to quantify a sample without prior knowledge of amplification efficiency, our first choice was to process the experimental data by the <italic>SCF </italic>method. The effectiveness of the <italic>SCF </italic>approach is based on curve fitting of raw data so that variations unique to each amplification reaction are incorporated into the analysis. Hence, the results reported herein surprisingly demonstrated that the accuracy and precision of the <italic>SCF </italic>method was markedly impaired when efficiency fell. In fact, when PCR efficiency decreased by about 2.5% (88.8% efficiency value in the presence of 100% of the amplification mix dropped to 84.4% efficiency in the presence of 60% of the mix), we observed, using the <italic>SCF </italic>method with log-transformation, that the RE and CV went from 15% to 43% and from 61% to 55%, respectively.</p>", "<p>Furthermore, we found that, when the amplification curve was inhibited, by IgG, the method proposed by Rutledge [##REF##15601990##26##] can not be applied because for each cut-off cycle eliminated from the plateau phase the <italic>F</italic>_{<italic>0 </italic>}value progressively decreased without ever reaching a minimum value. These observations are in agreement with two recent studies, which reported that it is possible to obtain absolute quantification from real-time data without a standard curve, but the <italic>Ct </italic>method remains a gold standard due to the inherent errors of the multiple estimates used in nonlinear regression [##REF##16515700##19##,##REF##17445280##20##]. These observations are in accordance with Feller's conclusions that different S-shaped curves can be effectively fitted with various sigmoid models [##UREF##3##30##], each providing distinct <italic>F</italic>_{<italic>0 </italic>}values. Thus sigmoid fit methods such as the logistic model, used in the <italic>SCF </italic>approach, are purely descriptive and quantitative results may be unreliable. This led us to develop a new mathematical data treatment method, named <italic>Cy</italic>_{<italic>0</italic>}, based on nonlinear regression fitting of real-time fluorescence data. The proposed method's main advantages are its use of the Richards equation for obtaining the coordinate of the inflection point and the determination of the quantitative entity <italic>Cy</italic>_{<italic>0 </italic>}using the five parameters of reaction curve.</p>", "<p>Although the logistic growth equation generates a curve that tends towards an exponential form at low fluorescence values, making this curve ideal to model PCR reaction, its maximum slope, or inflection point, is always imposed to be at half the value of the upper asymptote, (<italic>F</italic>_{<italic>max</italic>}-<italic>F</italic>_{<italic>b</italic>})/2. This is unsatisfactory because the factors that determine the growth rate are complex and some amplification systems, although characterized by good reaction efficiency, as assessed by standard curve, do not have the center of symmetry in the inflection point. The Richards equation is a more flexible growth function because it has an additional parameter, which is a shape parameter that can make the Richards equation equivalent to the logistic, Gompertz, or monomolecular equations [##UREF##4##31##,##REF##12547689##32##]. Variation of the shape parameter allows the point of inflection of the curve to be at any value between the minimum and the upper asymptote; when <italic>d </italic>= 1 the Eq. 3 becomes the sigmoidal equation.</p>", "<p>Furthermore, since very small errors of the multiple estimates used in non-linear regression lead to large variations in <italic>F</italic>_{<italic>0 </italic>}values, the real-time PCR kinetic parameters were used to define a new quantitative entity, the <italic>Cy</italic>_{<italic>0</italic>}. The <italic>Cy</italic>_{<italic>0 </italic>}relies on the inflection point position and on the slope of the fluorescence curve at that point, so that its value slightly changes in relation to PCR efficiency. In particular, in a slightly inhibited amplification reaction, the fluorescence curves are shifted towards the right and/or they are less steep; this generates higher <italic>Ct </italic>values than those found under optimal amplification conditions, underestimating the target amount. In the <italic>Cy</italic>_{<italic>0 </italic>}method, the tangents, calculated from different PCR efficiency, tend to intersect at a common point near the x-axis leading to small variations in the <italic>Cy</italic>_{<italic>0 </italic>}values (Fig. ##FIG##3##4##).</p>", "<p>The standard curve approach was chosen for the proposed method because currently there no genuine mathematical model for PCR efficiency assessment. The main complication is that actual efficiency amplification is not constant through the PCR run being high in exponential phase and gradually declining towards the plateau phase [##REF##16843498##33##, ####REF##16241897##34##, ##REF##16170827##35####16170827##35##]. However, most current methods of PCR efficiency assessment report \"overall\" efficiency as a single value [##REF##12930979##13##,##REF##12618301##24##,##REF##12853650##36##,##REF##14530455##37##]. Moreover, recent publications on PCR efficiency assessment have concentrated on the analysis of individual shapes of fluorescence plots in order to estimate a dynamic efficiency value [##REF##16515700##19##,##REF##17445280##20##,##REF##17349040##27##,##REF##11846375##38##]. This proliferation of new methods to assess PCR efficiency demonstrates that, at present, there is not an accepted procedure to evaluate PCR efficiency from a single run, hence some methods can \"overestimate\" and others \"underestimate\" the \"true\" PCR efficiency [##UREF##0##8##]. In contrast, the standard curve method is based on a simple approximation of data obtained in standard dilutions to unknown samples. In this procedure PCR efficiency assessment is based on the slope of the standard curve. Indeed, the original method (<italic>Ct</italic>) does not account for PCR efficiencies in individual target samples. The proposed procedure overcomes this limitation by evaluating single amplification variations using Richards curve fitting and subsequently produces a <italic>Cy</italic>_{<italic>0 </italic>}value that minimizes the dependence of its value on PCR kinetic.</p>", "<p>We then compared our method with the <italic>Ct </italic>method, the actual \"gold standard\" in real-time PCR quantification and the <italic>Cp </italic>method which is also used in molecular diagnostics. Both methods are based on standard curve methodology and are the most frequently used in this field. The <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods were evaluated on the same data set using two criteria: precision and accuracy. We defined the accuracy of a model as its ability to provide expected concentrations of the known dilutions under different PCR amplification efficiencies. On the contrary, precision is related to the variability of the results obtained from a given model, and it indicates whether reliable results may be obtained from a small data collection. Our results clearly demonstrated that, under optimal amplification conditions, these three methods were equally precise and accurate. However, when the PCR efficiency decreased, due to amplification mix dilution or IgG presence, the <italic>Ct </italic>method was markedly impaired and the <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods proved to be significantly more accurate than the <italic>Ct </italic>method. Notably, the <italic>Cy</italic>_{<italic>0 </italic>}method showed accuracy levels higher than the <italic>Cp </italic>method maintaining the same precision.</p>", "<p>The ability to carry out reliable nuclei acid quantification even in sub-optimal amplification conditions is particularly useful when PCR optimization is not possible, as in the case of high-throughput screening of gene expression or biological samples difficult to cleanse of PCR inhibitors.</p>", "<p>Furthermore, the <italic>Cy</italic>_{<italic>0 </italic>}method is completely objective and assumption-free. Indeed, it does not require the choice of a threshold value and the assumption of similar amplification efficiency between the standard curve and biological samples, necessary in the <italic>Ct </italic>method. Moreover, there is no need to assume that base pair composition and amplicon size do not impact the fluorescence characteristics of SYBR Green I, required in optical calibration methods like <italic>SCF </italic>[##REF##16515700##19##]. Our procedure may have future applications in TaqMan assays, where the Taq DNA polymerase digests a probe labelled with a fluorescent reporter and quencher dye and the signal diverges from the product resulting in non-symmetric amplification curves that can be effectively modelled by Richards equation [##REF##7580930##39##]. Further work is needed to extensively verify the accuracy and precision of the <italic>Cy</italic>_{<italic>0 </italic>}method in the presence of other known PCR inhibitors like phenol, haemoglobin, fat and tannic acid [##REF##16882221##17##,##REF##15036369##22##].</p>" ]

[ "<title>Conclusion</title>", "<p>Real-time PCR analysis is becoming increasingly important in biomedical research because of its accuracy, sensitivity and high efficiency. Although, real-time PCR analysis has gained considerable attention, it is far from being a standard assay. The standard methods are quite stable and straightforward but the accuracy of estimates is strongly impaired if efficiency is not equal in all reactions. Furthermore, the assumption of uniform efficiency has been reported to be invalid in many cases regarding medical diagnostics. In fact, the biological samples may contain inhibitors that could lead to different amplification efficiencies among samples.</p>", "<p>We propose, in this report, a modified standard curve-based method, called <italic>Cy</italic>_{<italic>0</italic>}, that does not require the assumption of uniform reaction efficiency between standards and unknown.</p>", "<p>To the best of our knowledge, this is the first method in which the stability and reliability of a standard curve approach is combined with a fitting procedure to overcome the key problem of PCR efficiency determination in real-time PCR nucleic acid quantification. The data reported herein clearly show that the <italic>Cy</italic>_{<italic>0 </italic>}method is a valid alternative to the standard method for obtaining reliable and precise nucleic acid quantification even in sub-optimal amplification conditions, such as those found in the presence of biological inhibitors like IgG.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Real-time PCR analysis is a sensitive DNA quantification technique that has recently gained considerable attention in biotechnology, microbiology and molecular diagnostics. Although, the cycle-threshold (<italic>Ct</italic>) method is the present \"gold standard\", it is far from being a standard assay. Uniform reaction efficiency among samples is the most important assumption of this method. Nevertheless, some authors have reported that it may not be correct and a slight PCR efficiency decrease of about 4% could result in an error of up to 400% using the <italic>Ct </italic>method. This reaction efficiency decrease may be caused by inhibiting agents used during nucleic acid extraction or copurified from the biological sample.</p>", "<p>We propose a new method (<italic>Cy</italic>_{<italic>0</italic>}) that does not require the assumption of equal reaction efficiency between unknowns and standard curve.</p>", "<title>Results</title>", "<p>The <italic>Cy</italic>_{<italic>0 </italic>}method is based on the fit of Richards' equation to real-time PCR data by nonlinear regression in order to obtain the best fit estimators of reaction parameters. Subsequently, these parameters were used to calculate the <italic>Cy</italic>_{<italic>0 </italic>}value that minimizes the dependence of its value on PCR kinetic.</p>", "<p>The <italic>Ct</italic>, second derivative (<italic>Cp</italic>), sigmoidal curve fitting method (<italic>SCF</italic>) and <italic>Cy</italic>_{<italic>0 </italic>}methods were compared using two criteria: precision and accuracy. Our results demonstrated that, in optimal amplification conditions, these four methods are equally precise and accurate. However, when PCR efficiency was slightly decreased, diluting amplification mix quantity or adding a biological inhibitor such as IgG, the <italic>SCF</italic>, <italic>Ct </italic>and <italic>Cp </italic>methods were markedly impaired while the <italic>Cy</italic>_{<italic>0 </italic>}method gave significantly more accurate and precise results.</p>", "<title>Conclusion</title>", "<p>Our results demonstrate that <italic>Cy</italic>_{<italic>0 </italic>}represents a significant improvement over the standard methods for obtaining a reliable and precise nucleic acid quantification even in sub-optimal amplification conditions overcoming the underestimation caused by the presence of some PCR inhibitors.</p>" ]

[ "<title>Abbreviations</title>", "<p>Cp: crossing point; Ct: threshold cycle; CV: coefficient of variation; IgG: immunoglobulin G; RE: relative error; SCF: sigmoidal curve fitting.</p>", "<title>Authors' contributions</title>", "<p>MG and DS carried out the design of the study, participated in data analysis, developed the <italic>Cy</italic>_{<italic>0 </italic>}method and drafted the manuscript. MBLR participated in data collection and analysis and critically revised the manuscript. LS carried out the real-time PCR. VS participated in the design of the study and critically revised the manuscript. All authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We thank Dr. Pasquale Tibollo for technical assistance and Dr. Giosuè Annibalini for helpful comments on the manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Example of modelling PCR amplification with a 5-parameter Richards function</bold>. Effectiveness of this model is illustrated by the predicted values generated by Eq. 3 (open circles) that agree with the observed fluorescence (dot and line). Curve-fitting of experimentally derived fluorescence dataset to Eq. 3 generates values for the kinetic parameters from which the inflection point (solid black rhombus) and the slope of the curve can be derived. The quantitative entity <italic>Cy</italic>_{<italic>0 </italic>}(solid black dot), used in the proposed method, shows the cross point between the x-axis and the tangent crossing the inflection point of real-time PCR fluorescence curve.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Estimation of PCR efficiency using LinReg method</bold>. Efficiency values were determined from 420 independent reactions using a combination of 3.14 × 10⁷–3.14 × 10¹DNA molecules as starting template and amplification mix quantities ranging from 60% to 100%. The graph shows the distribution of PCR efficiencies in relation to the percentage of amplification mix used in the reaction. The solid black squares (▪) represent the mean of each distribution.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Distribution of Richards coefficients (<italic>d</italic>) estimated from PCR fluorescence curves using Eq. 3 in nonlinear fitting procedure</bold>. Richards coefficient values were determined from 420 independent PCR reactions. The data have been reported in Log₁₀scale, and represented as mean and standard deviation.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Plot of fluorescence observations versus cycle number obtained from the same starting DNA but in presence of decreasing amounts of amplification mix</bold>. This slight PCR inhibition produces curves which are less steep than controls and shifted towards the right. When analysed by the threshold method, these curves showed higher <italic>Ct </italic>values with a CV% of 1.45% (A). An example of <italic>Cy</italic>_{<italic>0 </italic>}procedure has been reported for the same data set (B). In this method, the amplification reactions are described by the tangent crossing the inflection point of fluorescence curves. As shown in this figure, the straight-lines originating from PCRs, characterized by slightly different PCR efficiency and the same starting amounts, tend to cross into a common point near the x-axis leading to small variations in the <italic>Cy</italic>_{<italic>0 </italic>}values (CV% = 0.6%).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Comparison of the <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods in terms of precision and accuracy</bold>. The accuracy of each method has been reported as Relative Error (RE = expected value – estimated value) while the precision was evaluated measuring the variation coefficient (CV%). The 3D plots show the variation of relative error in relation to amplification mix percentage and log₁₀input DNA for the <italic>Ct </italic>(A), <italic>Cp </italic>(C) and <italic>Cy</italic>_{<italic>0 </italic>}(E) methods. The areas in the level curve graphs represent the CV% values obtained for each amplification mix percentage and Log₁₀input DNA combination using the <italic>Ct </italic>(B), <italic>Cp </italic>(D) and <italic>Cy</italic>_{<italic>0 </italic>}(F) methods.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Real-time PCR amplification plots obtained from the same starting DNA in the presence of IgG acting as reaction inhibitor</bold>. This inhibition system produces curves which are progressively less steep than non-inhibited reactions with increasing IgG concentrations (A). When analysed by the <italic>Ct</italic>, <italic>Cp </italic>and <italic>Cy</italic>_{<italic>0 </italic>}methods these curves showed a RE% of -25.37%, -9.02% and 4.98% and a CV% of 25.62%, 10.66% and 4.33%%, respectively (B).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Comparison of five S-shaped models to fit the PCR curve: Sigmoid, Richards, Gompertz, Hill and Chapman. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold><italic>Name</italic></bold></td><td align=\"left\"><bold><italic>Equation</italic></bold></td><td align=\"center\" colspan=\"5\"><bold><italic>Estimated Parameters</italic></bold></td><td align=\"center\"><bold><italic>R</italic></bold>²</td><td align=\"center\"><bold><italic>Adj R</italic></bold>²</td><td align=\"center\"><bold><italic>Standard Error of Estimate</italic></bold></td></tr><tr><td/><td/><td colspan=\"5\"><hr/></td><td/><td/><td/></tr><tr><td/><td/><td align=\"center\"><bold><italic>F</italic></bold>_{<italic>max</italic>}</td><td align=\"center\"><bold><italic>b</italic></bold></td><td align=\"center\"><bold><italic>c</italic></bold></td><td align=\"center\"><bold><italic>F</italic></bold>_{<italic>b</italic>}</td><td align=\"center\"><bold><italic>d</italic></bold></td><td/><td/><td/></tr></thead><tbody><tr><td align=\"left\"><bold>Sigmoid</bold></td><td align=\"left\"><italic>f </italic>= <italic>F</italic>_{<italic>b</italic>}+<italic>F</italic>_{<italic>max</italic>}/(1+exp(-(<italic>x</italic>-<italic>c</italic>)/<italic>b</italic>))</td><td align=\"center\">45.11</td><td align=\"center\">1.49</td><td align=\"center\">22.37</td><td align=\"center\">-0.03</td><td/><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">0.1354</td></tr><tr><td align=\"left\"><bold>Richards</bold></td><td align=\"left\"><italic>f </italic>= <italic>F</italic>_{<italic>b</italic>}+(<italic>F</italic>_{<italic>max</italic>}/(1+exp(-(1/<italic>b</italic>)*(<italic>x</italic>-<italic>c</italic>)))^<italic>d</italic>)</td><td align=\"center\">45.11</td><td align=\"center\">1.58</td><td align=\"center\">21.95</td><td align=\"center\">0.02</td><td align=\"center\">1.20</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\"><bold>0.0926</bold></td></tr><tr><td align=\"left\"><bold>Gompertz</bold></td><td align=\"left\"><italic>f </italic>= <italic>F</italic>_{<italic>b</italic>}+<italic>F</italic>_{<italic>max </italic>}*exp(-exp(-(<italic>x</italic>-<italic>c</italic>)/<italic>b</italic>))</td><td align=\"center\">45.19</td><td align=\"center\">2.15</td><td align=\"center\">21.45</td><td/><td align=\"center\">0.29</td><td align=\"center\">0.9992</td><td align=\"center\">0.9992</td><td align=\"center\">0.6006</td></tr><tr><td align=\"left\"><bold>Hill</bold></td><td align=\"left\"><italic>f </italic>= <italic>F</italic>_{<italic>b</italic>}+<italic>F</italic>_{<italic>max </italic>}*<italic>x</italic>^<italic>b</italic>/(<italic>d</italic>^<italic>b</italic>+<italic>x</italic>^<italic>b</italic>)</td><td align=\"center\">45.18</td><td align=\"center\">14.95</td><td/><td align=\"center\">0.08</td><td align=\"center\">22.34</td><td align=\"center\">1</td><td align=\"center\">1</td><td align=\"center\">0.1351</td></tr><tr><td align=\"left\">Chapman</td><td align=\"left\"><italic>f </italic>= <italic>F</italic>_{<italic>b</italic>}+<italic>F</italic>_{<italic>max </italic>}*(1-exp(-<italic>b</italic>*<italic>x</italic>))^<italic>d</italic></td><td align=\"center\">45.19</td><td align=\"center\">0.46</td><td/><td align=\"center\">0.29</td><td align=\"center\">20615</td><td align=\"center\">0.9992</td><td align=\"center\">0.9992</td><td align=\"center\">0.6006</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p><italic>t </italic>statistic values obtained for all variable combinations.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\" colspan=\"5\"><bold>Amplification mix percentage</bold></td></tr><tr><td/><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\"><bold>Log</bold>₁₀<bold>input DNA</bold></td><td align=\"center\"><bold>100%</bold></td><td align=\"center\"><bold>90%</bold></td><td align=\"center\"><bold>80%</bold></td><td align=\"center\"><bold>70%</bold></td><td align=\"center\"><bold>60%</bold></td></tr></thead><tbody><tr><td align=\"center\"><bold>7.5</bold></td><td align=\"center\">0.28348</td><td align=\"center\">1.15431</td><td align=\"center\">2.9303*</td><td align=\"center\">5.43493**</td><td align=\"center\">4.26067**</td></tr><tr><td align=\"center\"><bold>6.5</bold></td><td align=\"center\">-3.0233*</td><td align=\"center\">-0.5329</td><td align=\"center\">7.8552**</td><td align=\"center\">8.68609**</td><td align=\"center\">7.28178**</td></tr><tr><td align=\"center\"><bold>5.5</bold></td><td align=\"center\">-2.2195*</td><td align=\"center\">2.70419*</td><td align=\"center\">4.7185**</td><td align=\"center\">8.61406**</td><td align=\"center\">4.60465**</td></tr><tr><td align=\"center\"><bold>4.5</bold></td><td align=\"center\">0.97856</td><td align=\"center\">1.32162</td><td align=\"center\">2.34*</td><td align=\"center\">16.5192**</td><td align=\"center\">17.5903**</td></tr><tr><td align=\"center\"><bold>3.5</bold></td><td align=\"center\">1.00647</td><td align=\"center\">-1.038</td><td align=\"center\">2.3307*</td><td align=\"center\">13.2572**</td><td align=\"center\">4.65683**</td></tr><tr><td align=\"center\"><bold>2.5</bold></td><td align=\"center\">-1.731</td><td align=\"center\">-0.5995</td><td align=\"center\">5.8385**</td><td align=\"center\">6.90378**</td><td align=\"center\">6.13465**</td></tr><tr><td align=\"center\"><bold>1.5</bold></td><td align=\"center\">0.14417</td><td align=\"center\">1.25452</td><td align=\"center\">-0.898</td><td align=\"center\">1.87978</td><td align=\"center\">3.69668**</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Comparison of mean Relative Error and mean Variation Coefficient among the <italic>Ct, Cp, Cy</italic>_{<italic>0 </italic>}and <italic>SCF </italic>methods.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold><italic>Ct</italic></bold></td><td align=\"center\"><bold><italic>Cp</italic></bold></td><td align=\"center\"><bold><italic>Cy</italic></bold>_{<italic>0</italic>}</td><td align=\"center\"><bold><italic>SCF</italic></bold></td><td align=\"center\"><bold><italic>Log</italic></bold>₁₀<bold><italic>SCF</italic></bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Mean CV%</bold></td><td align=\"center\">39.70%</td><td align=\"center\">21.80%</td><td align=\"center\">22.52%</td><td align=\"center\">594.74%^a</td><td align=\"center\">66.12%^a</td></tr><tr><td align=\"left\"><bold>Mean RE</bold></td><td align=\"center\">-0.318</td><td align=\"center\">-0.184</td><td align=\"center\">-0.128</td><td align=\"center\">-5.058^a</td><td align=\"center\">-0.205^a</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula id=\"bmcM1\"><label>(1)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1471-2105-9-326-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mi>b</mml:mi></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>x</mml:mi><mml:mo>−</mml:mo><mml:mi>c</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:mfrac><mml:mo>+</mml:mo><mml:msub><mml:mi>F</mml:mi><mml:mi>b</mml:mi></mml:msub></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM2\"><label>(2)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\" name=\"1471-2105-9-326-i2\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mfrac><mml:mi>c</mml:mi><mml:mi>b</mml:mi></mml:mfrac><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM3\"><label>(3)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\" name=\"1471-2105-9-326-i3\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mi>b</mml:mi></mml:mfrac><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>x</mml:mi><mml:mo>−</mml:mo><mml:mi>c</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msup></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mi>d</mml:mi></mml:msup></mml:mrow></mml:mfrac><mml:mo>+</mml:mo><mml:msub><mml:mi>F</mml:mi><mml:mi>b</mml:mi></mml:msub></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM4\"><label>(4)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\" name=\"1471-2105-9-326-i4\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>F</mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mi>x</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mi>c</mml:mi><mml:mo>+</mml:mo><mml:mi>b</mml:mi><mml:mi>ln</mml:mi><mml:mo>⁡</mml:mo><mml:mi>d</mml:mi><mml:mo>;</mml:mo><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mi>d</mml:mi><mml:mrow><mml:mi>d</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mi>d</mml:mi></mml:msup><mml:mo>+</mml:mo><mml:msub><mml:mi>F</mml:mi><mml:mi>b</mml:mi></mml:msub></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM5\"><label>(5)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M5\" name=\"1471-2105-9-326-i5\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>m</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow><mml:mi>b</mml:mi></mml:mfrac><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mi>d</mml:mi><mml:mrow><mml:mi>d</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>d</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula id=\"bmcM6\"><label>(6)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M6\" name=\"1471-2105-9-326-i6\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>C</mml:mi><mml:mrow><mml:mi>y</mml:mi><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mi>c</mml:mi><mml:mo>+</mml:mo><mml:mi>b</mml:mi><mml:mi>ln</mml:mi><mml:mo>⁡</mml:mo><mml:mi>d</mml:mi><mml:mo>−</mml:mo><mml:mi>b</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>d</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>d</mml:mi></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mi>b</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>d</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>d</mml:mi></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mi>d</mml:mi></mml:msup></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M7\" name=\"1471-2105-9-326-i7\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>R</mml:mi><mml:msub><mml:mi>E</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>n</mml:mi></mml:munderover><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mrow><mml:msub><mml:mi>i</mml:mi><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mrow><mml:msub><mml:mi>i</mml:mi><mml:mrow><mml:mi>exp</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M8\" name=\"1471-2105-9-326-i8\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>R</mml:mi><mml:msub><mml:mi>E</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M9\" name=\"1471-2105-9-326-i9\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mrow><mml:msub><mml:mi>i</mml:mi><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi></mml:mrow></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M10\" name=\"1471-2105-9-326-i10\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mrow><mml:msub><mml:mi>i</mml:mi><mml:mrow><mml:mi>exp</mml:mi><mml:mo>⁡</mml:mo></mml:mrow></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M11\" name=\"1471-2105-9-326-i11\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>x</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>x</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M12\" name=\"1471-2105-9-326-i12\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M13\" name=\"1471-2105-9-326-i13\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>x</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M14\" name=\"1471-2105-9-326-i14\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>x</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>s</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M15\" name=\"1471-2105-9-326-i15\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>d</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mi>S</mml:mi><mml:msub><mml:mi>E</mml:mi><mml:mrow><mml:msub><mml:mi>d</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M16\" name=\"1471-2105-9-326-i16\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mover accent=\"true\"><mml:mi>d</mml:mi><mml:mo>¯</mml:mo></mml:mover><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M17\" name=\"1471-2105-9-326-i17\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>S</mml:mi><mml:msub><mml:mi>E</mml:mi><mml:mrow><mml:msub><mml:mi>d</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M18\" name=\"1471-2105-9-326-i8\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>R</mml:mi><mml:msub><mml:mi>E</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M19\" name=\"1471-2105-9-326-i12\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>n</mml:mi><mml:mrow><mml:mi>D</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi></mml:mrow></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>%</mml:mi><mml:mrow><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>" ]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Windows Excel file containing PCR readouts and non-linear fittings.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Windows Word file containing first and second derivative of Richards equation and the mathematical formulas for obtaining the coordinate of the <italic>Cy</italic>_{<italic>0 </italic>}point.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Windows Excel file containing the <italic>Ct Cp Cy</italic>_{<italic>0 </italic>}<italic>SCF Log</italic>₁₀<italic>SCF </italic>elaborations.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>Windows Excel file containing the results obtained with the <italic>SCF </italic>approach based on a previous study by Rutledge 2004.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>Windows Excel file containing the results obtained with the <italic>SCF </italic>approach based on a previous study by Rutledge 2004 in presence of IgG.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>In this table, <italic>f </italic>is the fluorescence at cycle <italic>x</italic>; <italic>F</italic>_{<italic>max </italic>}represents the maximum fluorescence value; <italic>F</italic>_{<italic>b </italic>}is the background reaction fluorescence; <italic>b</italic>, <italic>c </italic>and <italic>d </italic>determine the shape of each curve. For each model the determination coefficient (R²), the adjusted determination coefficient (Adj R²) and the standard error of estimate have been calculated.</p></table-wrap-foot>", "<table-wrap-foot><p>When <italic>t </italic>&lt; 0 the Richards coefficient is lower than 1, while for <italic>t </italic>&gt; 0 the Richards coefficient is higher than 1. Significance levels: * 0.05 &lt;<italic>p </italic>&lt; 0.01; ** <italic>p </italic>&lt; 0.01</p></table-wrap-foot>", "<table-wrap-foot><p>The reported data were calculated on 420 PCRs except for ^a) in which the reaction number was 210.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2105-9-326-1\"/>", "<graphic xlink:href=\"1471-2105-9-326-2\"/>", "<graphic xlink:href=\"1471-2105-9-326-3\"/>", "<graphic xlink:href=\"1471-2105-9-326-4\"/>", "<graphic xlink:href=\"1471-2105-9-326-5\"/>", "<graphic xlink:href=\"1471-2105-9-326-6\"/>" ]

[ "<media xlink:href=\"1471-2105-9-326-S1.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-326-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-326-S3.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-326-S4.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-326-S5.xls\" mimetype=\"application\" mime-subtype=\"vnd.ms-excel\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<title>Statement of Problem</title>", "<p>Innumerable biological investigations require comparing different members of a collection of entities with respect to one or more properties. The conclusions to be drawn from such studies are based on an analysis of the degree of similarity or dissimilarity among the different members. For example, one might compare the activity of different isoforms or fragments of a protein of interest, or compare wild type protein(s) with various mutant versions of a protein that causes a disease state. Many additional examples come from comparisons of data sets derived from microarray and proteomics studies, as well as population genetics. Given the technical advances of recombinant DNA technology and the explosion in genomics over the past few years, it is a certainty that the number of these sorts of comparative studies, and the number of entities to be compared within each study, will increase dramatically in the near future. Unfortunately, the vast majority of such comparative studies are currently performed manually, with investigators searching for similarities and dissimilarities among different test entities \"by eye\". This is especially difficult when each member of the collection is being characterized by multiple criteria. The analytical process is time consuming, likely to miss subtleties and is susceptible to inadvertent bias and human errors. Development and application of computer-assisted modeling and visualization can provide extraordinarily valuable data analyses and interpretive tools for assessing relationships among different members in a study.</p>", "<title>Microtubules and Microtubule Dynamics</title>", "<p>Microtubules represent one of the three main components of the eukaryotic cellular cytoskeleton [##UREF##0##1##]. They are hollow, unbranched cylinders, formed by the non-covalent association of <italic>αβ tubulin </italic>dimer subunits. Microtubules serve a wide variety of essential structural and transport functions, including the segregation of chromosomes during cell division and the transport of vesicular cargo up and down long axonal processes in neurons.</p>", "<p>Microtubules are highly dynamic structures, gaining and losing tubulin dimer subunits by a stochastic process known as <italic>dynamic instability </italic>[##REF##6504138##2##,##REF##15057285##3##]. A large body of data, both pharmacological and somatic cell genetics, has led to the conclusion that proper regulation of microtubule dynamics is essential in order for microtubules to perform their many critical cellular functions (for review, see [##REF##15615645##4##]). For example, the effectiveness of the anti-cancer drug taxol derives from its ability to suppress microtubule dynamics, thereby interfering with the ability of cancer cells to proliferate [##UREF##1##5##]. Given the importance of properly regulated microtubule dynamics, it is not surprising that cells have evolved a host of regulatory proteins that finely tune microtubule dynamics, including tau, MAP2, MAP4, SCG10 and stathmin.</p>", "<title>The Microtubule Associated Protein Tau</title>", "<p>The microtubule associated protein <italic>tau </italic>is essential for the normal development and maintenance of the nervous system [##REF##2105469##6##, ####REF##8056843##7##, ##REF##11228161##8####11228161##8##]. It binds directly to microtubules [##UREF##2##9##,##REF##329285##10##], and its ability to regulate microtubule dynamics [##REF##1421571##11##, ####UREF##3##12##, ##UREF##4##13####4##13##] is itself tightly regulated by both alternative RNA splicing [##REF##2560640##14##] and phosphorylation (for review, see [##REF##15615646##15##]). Alternative RNA splicing leads to the synthesis of two classes of tau, known as 3-repeat tau and 4-repeat tau (See Figure ##FIG##0##1## for a schematic). Whereas normal human fetal brain expresses only 3-repeat tau, adult human brain expresses approximately equal amounts of 3-repeat and 4-repeat tau. Despite this dramatic developmental shift in expression profiles, the functional and mechanistic differences between 3-repeat and 4-repeat tau remain poorly understood. While it is well-established that 4-repeat tau is a more potent regulator of microtubule dynamics than 3-repeat tau, there have been indications over the years that the two classes of tau isoforms may also have inherent qualitative differences as well [##UREF##3##12##,##UREF##5##16##, ####REF##9190213##17##, ##UREF##6##18##, ##UREF##7##19####7##19##].</p>", "<p>Abnormal tau action has long been correlated with neurodegeneration. Indeed, the classic neurofibrillary tangle pathology of Alzheimers and many related dementias are composed primarily of aberrant tau (for example, see [##REF##2424016##20##]). In 1998, a direct cause and effect relationship between errors in tau action and/or regulation and neurodegeneration was established by the genetic linkage between mutations in the tau gene and FTDP-17, a fronto-temporal dementia with many similarities to Alzheimers disease [##REF##9789048##21##, ####REF##9641683##22##, ##REF##9636220##23####9636220##23##]. Two classes of tau mutations have been described. The first collection of mutations are structural in nature, caused by various amino acid substitutions in tau. The second class of mutations are especially subtle and provocative – they are caused by errors in alternative tau RNA splicing that alter the expression ratio of otherwise normal 4-repeat and 3-repeat tau molecules. Specifically, rather than a ~50/50 ratio in adult human brain, the mutant ratio is closer to ~75/25. In both the structural and regulatory mutations, the result is early onset of neuronal cell death and dementia.</p>", "<p>Unfortunately, the molecular mechanisms underlying tau-mediated neuronal cell death remain unclear. One widely held model suggests that errors in tau action lead to the aggregation of tau into neurofibrillary tangles, which are in turn cytotoxic [##REF##9836646##24##]. An alternative model suggests that tau-mediated neuronal cell death results from the inability of tau to properly maintain microtubule dynamics within a narrow range of activities required for cell viability [##REF##15615645##4##,##UREF##4##13##,##UREF##7##19##,##REF##15020716##25##]. Additional models have also been proposed (see <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.alzforum.org/res/adh/cur/default.asp\"/>).</p>", "<title>Computational Perspectives</title>", "<p>To quantitatively investigate the regulation of microtubule dynamics under varying conditions (for example, with different tau isoforms or tau:tubulin molar ratios), cell biologists employ video microscopy to visualize and record images of dynamic microtubules in real time. For each condition being assessed, many different individual microtubules must be imaged, tracked and analyzed [##UREF##7##19##]. From the resulting microtubule \"life history plots\" (Figure ##FIG##1##2##), the dynamic behaviors of similarly treated microtubules can be determined, such as average growth or shortening rates. Subsequently, the behavior of microtubules under different conditions can be compared.</p>", "<p>Computer-assisted methods are especially attractive for time series investigations of this sort. In the specific case of analyzing the regulation of microtubule dynamics, inadvertent bias and non-reproducibility in data interpretation among different labs and different investigators when defining the beginning and end points of individual growth, shortening or attenuation events could become significant. Despite the fact that these events are explicitly defined, investigators must make many judgment calls. In contrast, computer-assisted methods offer a faster and more objective assessment of the data. More importantly, these methods can also provide analytical tools as much as determine the fit of the data to various statistical models, thereby testing various conceptual representations of the underlying molecular mechanisms of action of the system under study. Modeling can also generate testable mechanistic predictions for subsequent investigations. In a general sense, sophisticated computational tools have the potential to make major contributions to many areas of biological research.</p>" ]

[ "<title>Methods</title>", "<title>Modeling</title>", "<p>The different models described in this section capture different characteristics of microtubule dynamicity. Comparison of conditions across these models highlights different features of tau action.</p>", "<title>Microtubule Events</title>", "<p>Three kinds of events are used to characterize microtubule dynamics: growth, shortening and attenuation (\"pause\"). Each kind of event can be <italic>simple </italic>or <italic>complex</italic>. An event is simple when it is characterized between two consecutive tracked time-points. Simple events are coalesced together to form bigger complex events. Complex events, therefore, can be defined over a contiguous set of more than two time-points. Identification of simple events are easy, but identifying the start and end points of complex events require sub-sequence analysis.</p>", "<p>The simple events are classified in the following manner. The different parameters for defining these events used in this particular study are indicated next. An event is a <italic>simple growth </italic>if and only if: (i) the rate of increase of microtubule length is at least 0.5 <italic>μm</italic>/<italic>min</italic>, and (ii) the increase in length is at least 0.05 <italic>μm</italic>. The corresponding parameters for a <italic>simple shortening </italic>event are: (i) the rate of decrease of length is at least 0.5 <italic>μm</italic>/<italic>min</italic>, and (ii) the decrease in length is at least 0.5 <italic>μm</italic>. A <italic>simple attenuation </italic>event must have (i) a rate of change of length outside the range for simple growth and simple shortening events, i.e., between -0.5 <italic>μm</italic>/<italic>min </italic>and +0.5 <italic>μm</italic>/<italic>min</italic>, and (ii) a total time duration of at least 4 <italic>s</italic>. Any event that does not fall in any of the above categories are <italic>excluded </italic>from the analysis. Due to errors in human tracking and image resolution issues, such events are likely to be part of the input noise, and are hence, discarded. Simple events are used for Markov Chain analysis.</p>", "<p>The complex events have their corresponding parameter cut-offs as well. However, the more important consideration in the analysis of complex events is the identification of where it starts and where it ends. A survey of such methods from the time-series literature can be found in [##UREF##18##37##]. These methods have been successfully used to segment time-series streams into different partitions in various application domains, most notably for stock market analysis. An interesting way to combine different segmentation outputs has been proposed in [##UREF##19##38##]. However, none of these methods have employed priority rules to analyze adjacency relationships.</p>", "<p>We now describe our bottom-up approach of identifying complex events by merging together simple events. First, all consecutive simple events of the same type are merged together to form a longer complex event of the same type. Next, each complex event is subjected to the rule set for classifying into growth, shortening, and attenuation. An event that does not pass any of the three rule sets is classified temporarily as an error. Also, the cause of its failure is noted. More specifically, any event where there is an increase in length but which cannot be classified as a growth is assigned into two kinds of failure: (i) rate, where it did not pass the growth rate threshold, and (ii) length, where it did not pass the growth length threshold. The failed shortening events are classified similarly. Note that there are no attenuation failure classes.</p>", "<p>The priority rules are applied next. A growth rate failure event is most likely to be part of an attenuation. Thus, its neighbors are examined and if possible, it is combined with adjacent attenuation events to form a bigger attenuation event. If this fails, then attempts to incorporate with neighboring growth events, if any, are made. If, however, the growth failure event is due to the length cutoff and not the rate, then this event is most likely to be part of a growth event. The error in length may be due to human tracking and image resolution issues. Hence, attempts to combine this with neighboring growth events are first carried out. The rules for absorbing the shortening failure events are similar.</p>", "<p>The complex event cut-offs are: (i) Growth: rate ≥ 0.5 <italic>μm</italic>/<italic>min</italic>, length ≥ 0.06 <italic>μm</italic>; (ii) Shortening: rate ≤ -0.5 <italic>μm</italic>/<italic>min</italic>, length ≤ -0.6 <italic>μm</italic>; and (iii) Attenuation: rate between -0.5 <italic>μm</italic>/<italic>min </italic>and +0.5 <italic>μm</italic>/<italic>min</italic>, time ≥ 30 <italic>s</italic>. The growth rates and the growth distributions are calculated using the complex events.</p>", "<p>Figure ##FIG##1##2## shows a comparison of the manually marked complex events and the automatically measured ones. The solid line indicates the simple events. As evident from the figure, these tracked lengths are noisy. The complex events get rid of the noise by smoothing over a range of simple events. However, while the automatic method marks three events – two growth events separated by a shortening event – a human may simply mark the entire time-history as a single growth event. Clearly, this human bias will differ from one experimenter to another, and may even vary from time to time. Note that this explains why growth rates obtained from the automatic measurements vary (become slightly higher) from those obtained through the manual method.</p>", "<p>The parameters for the different events have been chosen empirically by biologists based on experimenting with different kinds of microtubule samples. The event definitions have been used consistently and have become the <italic>de facto </italic>\"industry standard,\" as evident from [##REF##15615645##4##].</p>", "<title>Growth Rate</title>", "<p>The growth rate for a particular experimental condition was calculated as the average of the growth rates of all the complex growth events of the microtubules for that condition.</p>", "<p>In order to understand whether the differences between the automatically computed growth rate values using the above event analysis technique and the manually measured ones are statistically significant, we calculated the <italic>p</italic>-<italic>values </italic>in the following way. Two groups were formed, one with the automatically identified growth events, and the other with the manually marked growth events. We then performed a t-test [##UREF##20##39##] to determine whether the means of the growth rates of the two groups are different. The p-values thus obtained are reported in Tables ##TAB##0##1## and ##TAB##1##2##.</p>", "<title>Growth Rate Distribution Histogram</title>", "<p>For each condition, a growth rate distribution histogram was computed in the following manner. The rates for the complex growth events were divided into 18 bins of width 0.4 <italic>μm</italic>/<italic>min </italic>each (consistent with analysis by [##UREF##7##19##]), starting from 0.5 <italic>μm</italic>/<italic>min </italic>up to 7.7 <italic>μm</italic>/<italic>min</italic>. Once again, these parameters conform to the standards set in the microtubule event analysis literature [##REF##15615645##4##]. All the higher growth rate events were collected in another bin. Thus, the histograms had 19 bins in total. The bin heights were normalized such that they add up to 1, yielding a growth rate distribution. In order to generate histograms with a fixed number of bins, say <italic>b</italic>, the width of each bin was specified as .</p>", "<title>Haar Wavelets</title>", "<p>Wavelets are mathematical functions that describe time-series data in terms of various frequency components with resolutions matched to their scales [##UREF##12##31##]. The orthonormal basis vectors, called the <italic>mother wavelets</italic>, that describe the various wavelet components are given by:</p>", "<p></p>", "<p>where <italic>s </italic>denote the scaling factor and <italic>l </italic>the localization in time. The Haar wavelet basis functions [##UREF##11##30##] are the simplest:</p>", "<p></p>", "<p>Haar wavelets are also the fastest to calculate with respect to other wavelet bases. They work by progressively retaining the most important parameters of a signal. The first coefficient is the \"sum\" (actually, scaled average) of the entire signal and the next gives the \"detail\" (difference of the two halves) of the signal. The later coefficients give more and more details about each half of the signal they model.</p>", "<p>In general, more wavelet parameters mean more detailed description; however, they also mean more data and more noise. Further, the error in embedding is directly proportional to the number of parameters of the original data. Thus, 16 coefficients of each microtubule time-series were retained. These 16 coefficients were then averaged over all the microtubules from a particular experimental condition to yield the coefficients for that condition.</p>", "<title>Markov Chain</title>", "<p>A <italic>Markov Chain </italic>(MC) [##UREF##13##32##] is a discrete time stochastic process that models the observations of a dynamic system (such as the growth or the shortening of a microtubule) as the states of the system. The number of states is finite and there is a state corresponding to each observation symbol. In a first-order MC, the probability of occurrence of the future state (or observation) depends only on the current state; past states are inconsequential. This property is called the <italic>Markov property</italic>. (In a <italic>k</italic>^thorder Markov Chain, the future state depends on the current state and <italic>k </italic>- 1 past states.)</p>", "<p>Formally, an MC <italic>λ </italic>is defined as:</p>", "<p></p>", "<p>where <italic>n </italic>is the <italic>number of states</italic>, <italic>π </italic>is the <italic>start state probability vector </italic>of length <italic>n</italic>, and <italic>τ </italic>is the <italic>n </italic>× <italic>n transition matrix</italic>; <italic>π</italic>(<italic>u</italic>) denotes the probability of being in state <italic>u </italic>in the first time-step; and, <italic>τ </italic>(<italic>u, v</italic>) denotes the probability of reaching state <italic>v </italic>from state <italic>u </italic>in a single time-step.</p>", "<p>In the work of [##UREF##7##19##], microtubules were in a non-equilibrium phase, exhibiting very little shortening and many microtubules never shortened at all. Therefore, the microtubule events were discretized into two symbols: <italic>G </italic>for growth, and <italic>N </italic>for non-growth (shortening or attenuation). The Markov Chains were built with these two states – growth and non-growth. Since shortening events were very rare, modeling it as a separate state would have lacked statistical validity.</p>", "<p>The transition probabilities for the MCs were estimated in the following manner. Every microtubule time-series was denoted as a string of symbols, with each symbol representing a simple event. Then, pairs of consecutive symbols (states) were read and appropriate entries in the transition matrix were incremented. When all the microtubules in an experimental condition were processed, the transition matrix was normalized such that the sum of transition probabilities from each state form a probability distribution (adds up to 1). The start state probabilities were estimated in a similar manner by reading the first symbol for every microtubule time-series; if it is growth, the entry for <italic>G </italic>is incremented, otherwise that for <italic>N </italic>is incremented. Finally, normalization was performed such that the probabilities add up to 1. Since most of the microtubules started with growth, these vectors were very close to [1, 0].</p>", "<title>Lomb-Scargle Periodograms</title>", "<p>The periodicity analysis of the microtubule data was performed by extracting Lomb-Scargle coefficients [##UREF##14##33##,##UREF##15##34##] from each time-series. Lomb-Scargle periodograms capture the different frequency components in a time-series and can handle missing values and unequal sampling intervals. Four low frequency components (corresponding to periodicities of 4, 8, 16, and 32 s) were retained for each microtubule. The Lomb-Scargle coefficients for the condition were computed as the average of the corresponding coefficients of the individual microtubules.</p>", "<title>Dissimilarity Functions</title>", "<p>In order to compare a pair of models, an appropriate similarity or dissimilarity function is necessary. The dissimilarity or distance measure is used to compute the distance matrix among the conditions; this distance matrix is then embedded in a two-dimensional vector space as described later in the Visualization section.</p>", "<title>Growth Rate</title>", "<p>The dissimilarity between a pair of conditions with respect to the growth rates was measured by their <italic>difference</italic>. The difference can be also viewed as a <italic>Minkowski </italic>form of distance or <italic>L</italic>_{<italic>k </italic>}norm. The <italic>L</italic>_{<italic>k </italic>}norm between two vectors <italic>p </italic>and <italic>q </italic>of length <italic>k </italic>each is defined as:</p>", "<p></p>", "<title>Growth Rate Distribution Histogram</title>", "<p>Growth rate histograms can be viewed as vectors and <italic>L</italic>_{<italic>k </italic>}norms can be employed to capture the dissimilarity between a pair of histograms. These measures, however, do not capture the relationship among the different histogram bins. For example, suppose there are three bins in each histogram corresponding to low rate of growth, medium rate of growth and high rate of growth. If <italic>A </italic>= [1, 0, 0], <italic>B </italic>= [0, 1, 0] and <italic>C </italic>= [0, 0, 1], then <italic>L</italic>_{<italic>k </italic>}norms treat these histograms as equidistant from each other, even though <italic>A </italic>should be more different from <italic>C </italic>than <italic>B</italic>. To capture such spatial properties of the bins, <italic>match distance </italic>[##UREF##10##29##,##UREF##21##40##] was employed.</p>", "<p>To calculate the match distance between a pair of histograms p and q, a distance matrix among the bins of the histogram are specified – the distance between two bins <italic>i </italic>and <italic>j </italic>is <italic>c</italic>_{<italic>ij </italic>}= |<italic>i </italic>- <italic>j</italic>|. The match distance is defined as the minimum work required to be done in order to transform the histogram <italic>p </italic>into the histogram <italic>q </italic>by moving values or \"flows\" from the bins of <italic>p </italic>to those in <italic>q </italic>and vice versa. Having a flow <italic>f</italic>_{<italic>ij </italic>}from bin <italic>i </italic>of <italic>p </italic>to bin <italic>j </italic>of <italic>q </italic>or vice versa is considered as <italic>c</italic>_{<italic>ij</italic>·}<italic>f</italic>_{<italic>ij </italic>}amount of work. Finding the match distance then reduces to finding the flows <italic>f</italic>_{<italic>ij </italic>}such that the total work done is minimum. The minimum work done is the match distance:</p>", "<p></p>", "<p>For the example histograms <italic>A</italic>, <italic>B</italic>, and <italic>C </italic>mentioned above, the match distances are <italic>MD</italic>(<italic>A, B</italic>) = 1, <italic>MD</italic>(<italic>B, C</italic>) = 1, and <italic>MD</italic>(<italic>A, C</italic>) = 2. Clearly, this captures the relatively larger dissimilarity of <italic>A </italic>from <italic>C </italic>as compared to that from <italic>B</italic>.</p>", "<p>For one-dimensional histograms where the sum of the bin values add up to the same number (here, 1), match distance can be calculated more easily as the <italic>L</italic>₁distance between the cumulative bin values of the two histograms:</p>", "<p></p>", "<p>where and are the cumulative histogram bin values.</p>", "<title>Haar Wavelets</title>", "<p>Since the relative importance of the wavelet parameters differ, a simple distance function such as <italic>L</italic>₁would be inappropriate. Coefficients that summarize the entire time-series, such as the \"sum\" value and the overall \"detail\" value is more important, and therefore, should get higher weights than the coefficients describing parts of the time-series.</p>", "<p>Thus, in order to determine the dissimilarity between two conditions with respect to their Haar wavelet coefficients, we used the <italic>weighted L</italic>₁norm or the <italic>weighted Manhattan </italic>distance. The levels of the wavelet tree were weighted such that the overall sum and the overall detail coefficient were the most significant values, the next level detail coefficients getting an exponentially lower weight and so on. The weight vector, of length 16, was [8, 8, 4, 4, 2, 2, 2 2, 1, 1, 1, 1, 1, 1, 1, 1]. For two vectors <italic>p </italic>and <italic>q</italic>, and a weight vector <italic>w</italic>, all of length <italic>k</italic>, the weighted <italic>L</italic>₁distance between <italic>p </italic>and <italic>q </italic>is measured as:</p>", "<p></p>", "<p>The <italic>L</italic>₂norm or the Euclidean distance was applied to measure the distances between a pair of conditions for both the Markov Chain parameters and the Lomb-Scargle coefficients.</p>", "<title>Visualization</title>", "<p>The distances among the experimental conditions, calculated by using the above methods, were visualized by plotting the conditions onto a two-dimensional vector space. This allows for easy comparison of the conditions and immediate comprehension of the structure of the data. The aim of the embedding method is to assign coordinates such that the Euclidean distance between any pair of conditions in the embedded space is as close as possible to the dissimilarity calculated between their models. The method can embed a given set of points into any dimensional space; here, we have chosen two for easy visualization purposes.</p>", "<p>Formally, suppose there are two models, <italic>α </italic>and <italic>β</italic>, and the dissimilarity between them is <italic>d</italic>(<italic>α</italic>, <italic>β</italic>) according to some dissimilarity function <italic>d</italic>. If the embeddings of these two models in the two-dimensional vector space (<italic>x</italic>, <italic>y </italic>space) is given by <italic>e</italic>(<italic>α</italic>) = (<italic>x</italic>_{<italic>α</italic>}, <italic>y</italic>_{<italic>α</italic>}) and <italic>e</italic>(<italic>β</italic>) = (<italic>x</italic>_{<italic>β</italic>}, <italic>y</italic>_{<italic>β</italic>}), then the aim of the embedding function is to choose the coordinates <italic>e</italic>(<italic>α</italic>) and <italic>e</italic>(<italic>β</italic>) such that the relative difference between <italic>L</italic>₂(<italic>e</italic>(<italic>α</italic>), <italic>e</italic>(<italic>β</italic>)) and <italic>d</italic>(<italic>α</italic>, <italic>β</italic>) is minimum. When there are n such models, the embedding function should be chosen such that the relative cumulative difference for all the <italic>n</italic>(<italic>n </italic>- 1)/2 pairs is minimized.</p>", "<p>Principal component analysis (PCA) [##UREF##9##28##] can also be used to project data onto a two-dimensional space. PCA chooses the axes along which the original data shows the highest variance. It does not take into account the distances among the points. More importantly, PCA cannot work with any general distance matrix and is used mostly as a dimensionality reduction technique.</p>", "<p>We used the Sammon projection method [##UREF##8##27##] as the embedding procedure. This method has been successfully used to embed proteins on a two-dimensional space for clustering purposes [##UREF##22##41##]. The method starts with a random point (random <italic>x</italic>, <italic>y </italic>coordinates) for each model. In each iteration, the points are updated according to a <italic>steepest descent </italic>algorithm such that the following <italic>error </italic>function <italic>E</italic>(<italic>x</italic>, <italic>y</italic>), which measures the relative differences between the original distances and the embedded distances, is decreased.</p>", "<p></p>", "<p>where</p>", "<p></p>", "<p>In each iteration, a correction step is added to every dimension of every point. The direction of the correction is towards the gradient of the error. The coordinates of the point <italic>α </italic>in iteration <italic>i </italic>+ 1 are updated as follows:</p>", "<p></p>", "<p>where <italic>E</italic>^{(<italic>i</italic>)}is the error after iteration <italic>i </italic>and <italic>f </italic>is a factor to control the step sizes. We used <italic>f </italic>= 0.2. The method stops after a certain number of steps or when there is no significant improvement in the error. We stopped the iterations either when the change in error went below 0.01% or up to a maximum of 1000 steps. The number of steps was set as an additional check in order to come out of any local error problems, e.g., oscillating error values. In practice, after 250–300 iterations, the error stopped changing, and the algorithms stopped. In addition, in order to counter the problem of bad initialization, the algorithms were run 5 times for each embedding and the one with the lowest error was picked. The final coordinates or the directions of the axes do <italic>not </italic>have any significance; <italic>only </italic>the Euclidean distances among the embedded points matter.</p>", "<p>For any dimensionality reduction or embedding technique, an important measure of quality is <italic>distortion</italic>. Distortion measures the largest amount of discrepancy from an original distance value to the corresponding embedded distance. It is measured as</p>", "<p></p>", "<p>where <italic>original dist </italic>refers to an original dissimilarity measure between two models and <italic>embedded dist </italic>refers to the Euclidean distance between the corresponding embedded points. For ideal embeddings, where all the original distances have been maintained exactly, the distortion is 1. For others, the distortion is greater than 1. In general, lower the distortion value, better the embedding. The individual distortions are measured by the ratio of <italic>embedded dist </italic>to <italic>original dist</italic>.</p>", "<p>For models with only a single parameter, any dissimilarity between a pair of them is equal to the difference between their single parameters. Such distance matrices can be always embedded into two dimensions with distortion equal to 1. The models have to be simply embedded as points on a straight line with the order and the distances maintained, e.g., as (<italic>parameter</italic>, 0) or (<italic>parameter</italic>/, <italic>parameter</italic>/) points. In our implementation, we have not forced this explicitly; the method itself converges to a straight line plot. For models with two parameters, if the dissimilarity function is Euclidean, then, it is again possible to devise an embedding with distortion 1. The original parameter values will form the coordinates in the embedded space. For higher number of parameters or with other dissimilarity functions, in general, it is not possible to design embeddings with distortion 1. The distortions of each of the graphs are mentioned in the captions. Additional file ##SUPPL##2##3## reports the individual distortions for each of the distances for all the embeddings.</p>" ]

[ "<title>Results</title>", "<p>The main goal of this work is to develop general computational tools to quantitatively assess the differences among samples of interest and to visualize those differences in a manner that facilitates their comparison. The data being analyzed is derived from an earlier work in which video microscopy was used to visualize and assess the abilities of 3-repeat and 4-repeat tau to regulate various parameters of microtubule dynamics in <italic>in vitro </italic>reactions (Levy et al., 2005) [##UREF##7##19##]. Samples contained purified tubulin dimers and purified recombinant human tau. The two primary variables were (i) the presence of 3-repeat tau, 4-repeat tau or no tau, and (ii) the molar ratio of tau to tubulin. In vivo, the molar ratio of tau:tubulin varies from cell to cell. Further, the ratio can vary even among different regions within single cells, such as cell body versus axon versus growth cone. The different ratios examined are likely to span the range of biologically meaningful values [##REF##2997236##26##].</p>", "<title>Automated Life History Plot Analysis</title>", "<p>We first developed an automated method to identify the different events – growth, shortening, and attenuation (\"pause\") – on microtubule life-history plots, using a set of pre-defined rules (see the Methods section for details). We then compared the ability of this automated method to determine average microtubule growth rates with standard manual analysis, using data sets assessing the ability of tau to regulate microtubule dynamics from [##UREF##7##19##]. In this earlier work, microtubule dynamics were assayed under nine different experimental conditions. As seen in Table ##TAB##0##1##, the deviation between automatic and manually determined rates ranges from 3.33% to 12.68%, with an average deviation of 6.59%. Statistically, the differences between the manually determined values and the automatically measured values are not significant (as shown by the p-values), except for one condition. The p-value is computed by performing a t-test of the manually determined growth rates against the automatically computed ones for each condition (details are in the Methods section). More importantly, the relative order of the conditions do not change, and the degrees of separation are well maintained. Table ##TAB##1##2## shows the comparison for the same set of conditions using a different tubulin preparation from [##UREF##7##19##]. Again, our automated method accurately recapitulates manual analysis with increased objectivity. Additionally, it markedly reduces the time required to conduct these investigations.</p>", "<p>It is also important to note that inherent biological variability exists in the microtubule growth rate data. This likely results from biochemical variations between different tubulin preparations, such as different tubulin isoform expression ratios and/or varying degrees of post-translational modifications, such as phosphorylation, acetylation or tyrosination. For example, assuming each growth rate determination is within a variation of ± 0.1 <italic>μm</italic>/<italic>min</italic>, the rank order of the conditions for each of the two data sets is quite similar, although the 4R-1:55 and 3R-1:38 conditions are reversed (see Table ##TAB##2##3##). This inherent biological variability could limit the utility of some sophisticated and highly sensitive statistical models to make testable predictions regarding mechanisms underlying the regulation of microtubule dynamics. At the minimum, multiple data sets might be necessary and all predictions would need to be considered tentative until tested directly by other biological means.</p>", "<title>Modeling and Embedding Strategy</title>", "<p>Next, we sought to develop mathematical and statistical models to capture different dynamic aspects of microtubule behavior and to embed them in a two-dimensional space for visualization and easy comparison of different conditions. We used the Sammon projection method [##UREF##8##27##] for embedding and visualization. In short, the embedding process displays each experimental condition with an (<italic>x</italic>, <italic>y</italic>) position; the relative distance between the (<italic>x</italic>, <italic>y</italic>) positions of any pair of experimental conditions corresponds to their relative degree of relatedness (details are in the Methods section). The conditions of interest can be compared based on numerous parameters and the computational method is applicable to all kinds of numerical parameters.</p>", "<p>The outline of our method is as follows. First, the experimental measurements are analyzed based on an appropriate mathematical model. Then, an appropriate dissimilarity function is applied to calculate the relative distances between the models of each pair of conditions. Finally, the conditions are embedded on a two-dimensional space such that the inherent structure of the data is approximately preserved. This is achieved by assigning points (<italic>x </italic>and <italic>y </italic>coordinates) to the models such that the Euclidean distance between any pair of points in this space is as close to the original dissimilarity measure between their models as possible. Unlike principal component analysis (PCA) [##UREF##9##28##], this method works with any distance matrix. The quality of the embedding is measured by <italic>distortion</italic>. For ideal embeddings, where all dissimilarity values are maintained exactly as Euclidean distances in the embedded space, the distortion is 1. The details of the models, the dissimilarity functions, the embedding algorithm, and the distortion computations are presented in the Methods section.</p>", "<title>Two-Dimensional Embedding Analysis</title>", "<title>Microtubule Growth Rate</title>", "<p>As a proof-of-principle exercise, we used the automatically measured values from Table ##TAB##0##1## and applied our embedding strategy to compare the abilities of each tau isoform to regulate the growth rate of microtubules. Since these growth rate data are one-dimensional, the distortion is 1, and the embedding procedure should yield a straight line. Figure ##FIG##2##3## shows the two-dimensional embedding of the conditions. The requirement for the distances are fulfilled and the points are on a straight line. Additionally, consistent with [##UREF##7##19##], we observe that very low ratios of 3-repeat and 4-repeat tau:tubulin have opposite effects on the dynamic behavior of microtubules. More specifically, while 1:55 and 1:45 3-repeat tau and 1:55 4-repeat tau are all relatively close to the control (no-tau) point, the two 3-repeat tau conditions decrease the microtubule growth rate while the 1:55 4-repeat tau condition increases it as compared to the no-tau condition. Additionally, any increase in the tau:tubulin ratio beyond these low levels causes a relatively large increase in growth rate, since the distance between the no-tau point and all other tau points is relatively large. Thus, there are two clusters of growth rates rather than a simple linear relationship, consistent with a threshold effect. Further, as the tau:tubulin ratio increases (for both tau isoform classes), the difference with the no-tau point increases. Finally, for any given tau:tubulin ratio, 4-repeat tau is always more distant from the no-tau point than 3-repeat tau is; this demonstrates that 4-repeat tau is a more potent regulator of microtubule dynamics than 3-repeat tau. Thus, these data establish the validity of our automated life history analytical method and the two-dimensional embedding method.</p>", "<p>Figure ##FIG##3##4## shows the plot for another set of samples corresponding to the values in Table ##TAB##1##2##. This second sample corresponds to tubulin preparation 1 mentioned in Table II of [##UREF##7##19##]. The low ratios of 3-repeat and 4-repeat tau:tubulin behave similar to the control (no-tau) point. The higher ratios cluster separately.</p>", "<title>Microtubule Growth Rate Distribution Histogram</title>", "<p>Next, we used two-dimensional embedding to compare the effects of 3-repeat tau and 4-repeat tau upon the distribution of growth rates within the growing population of microtubules. As demonstrated in [##UREF##7##19##], a histogram analysis of control populations of growing microtubules yields two pools – a more abundant and slower growing pool and a less abundant and faster growing pool. Based on fitting mixture of two Gaussians to the histograms, the authors concluded that both tau isoforms cause an increase in the abundance of the faster growing pool and a decrease in the abundance of the slower growing pool, with 4-repeat causing the population change at lower tau:tubulin ratios than 3-repeat tau. Other than these conclusions, there was no other comparison possible between the histograms.</p>", "<p>We subjected the growth rate distribution data to our two-dimensional embedding analysis method (Figure ##FIG##4##5##). Each distribution histogram had 19 bins (similar to the analysis in [##UREF##7##19##]), and the dissimilarities among the histograms were computed by the match distance [##UREF##10##29##]. Conceptually, the match distance takes into account both the height of a histogram bin and the spatial position of the bin in the histogram; two histograms that differ in far-off bins are more distant than histograms that differ in adjacent bins. The details of the procedure are presented in the Methods section. As was true for the growth rates (Figure ##FIG##2##3##), the histogram distribution data reveals that there are only minor differences among the control (no-tau) sample and low levels of tau (3-repeat tau at both 1:55 and 1:45 tau:tubulin ratio and 4-repeat tau at a 1:55 tau:tubulin ratio). Moreover, in a manner parallel to the growth rates, 3-repeat and 4-repeat tau regulate microtubule dynamics in different directions, as indicated by the fact that the 4-repeat tau (1:55 ratio) is closer to the no-tau point than it is to either of the 3-repeat tau (1:55 or 1:45) samples.</p>", "<p>Additionally, it is also clear that 4-repeat tau is more potent than 3-repeat tau at any given tau:tubulin ratio (i.e., the distance between the 4-repeat tau point and the no-tau point is greater than the distance between the 3-repeat tau point and the no-tau point for all molar ratios). Finally, similar to the growth rate analysis in Figure ##FIG##2##3##, there are two clusters of behaviors rather than a continuum. One cluster contains the no-tau point and the lower tau:tubulin ratio samples and the other cluster contains the higher tau:tubulin ratio samples. Such non-linearity coupled with different functional effects could have significant mechanistic effects in the alternative RNA splicing class of tau FTDP-17 mutations in which relatively subtle increases in the 4-repeat tau concentration have dramatic consequences. By assessing the histogram landscape of the conditions, the two-dimensional embedding procedure complements the previous analyses using Gaussian mixture models [##UREF##7##19##]. The two-dimensional embedding plot is more sensitive in picking out the differences between a pair of conditions or among multiple conditions; on the other hand, it shows distances that lack physical meaning.</p>", "<p>Figure ##FIG##5##6## shows the corresponding embedding plot of the growth rate distribution histograms for another set of samples. This second sample corresponds to tubulin preparation 1 mentioned in Table ##TAB##1##II## of [##UREF##7##19##]. Similar to the case presented in Figure ##FIG##4##5##, the low ratios of 3-repeat and 4-repeat tau:tubulin cluster together with the control (no-tau) point. The higher ratios of tau:tubulin induce shifts in the growth rates.</p>", "<p>Additional file ##SUPPL##0##1## shows the effect of the number of bins on the embedding plots. Histograms were generated by varying the number of bins from 4 to 29 in variations of 5. The plots show only minor differences. In all of them, the lower tau:tubulin ratios (4-repeat tau at 1:55, and 3-repeat tau at 1:55 and 1:45) and the control (no-tau) point are far away from the higher tau:tubulin ratios.</p>", "<title>Microtubule Dynamics and Haar Wavelets</title>", "<p>Finally, we compared the two-dimensional embeddings of the Haar wavelet features [##UREF##11##30##] to 3-repeat tau, 4-repeat tau and the control (no-tau) samples. Wavelets [##UREF##12##31##] are powerful statistical tools that are used for a wide range of applications, including signal description and data compression. One of the main advantages of wavelets is that they offer a simultaneous localization in both time and frequency domains. Further, they can provide a multi-resolution view of the original time-series by changing the width of the \"window\" over which the coefficients are computed. Haar wavelets [##UREF##11##30##] are the simplest and the fastest to calculate among all the different types of wavelet functions. The specific window sizes and the details of how the dissimilarities among the conditions are computed are described in the Methods section. Additional file ##SUPPL##1##2## shows the plots for the two different samples. The disparity in the two plots likely arises from the inherent variability in the biological data. The first plot (corresponding to the data set presented in Table ##TAB##0##1##) suggests two distinct clusters, one corresponding to the 3-repeat tau conditions and the other to the 4-repeat tau conditions, consistent with the notion that 3-repeat and 4-repeat tau might interact with microtubules in qualitatively distinct manners. The lack of similar behavior for the second data set (see Table ##TAB##1##2##) makes the conclusions from the plots tentative, requiring independent corroboration.</p>", "<p>We also used two-dimensional embedding to compare the effects of 3-repeat and 4-repeat tau with respect to the Markov Chain models. A Markov Chain (MC) [##UREF##13##32##] captures the underlying dynamics of the physical phenomena or entity by a generative model that emits a sequence of symbols. The primary advantage of Markov Chains over other models of time-series data is their ability to characterize an entire family of sequences. MCs are fairly easy to build, require a small set of sequences and allow very fast searching and comparison. There was no obvious clustering of points with respect to either the tau:tubulin ratio or 3-repeat tau versus 4-repeat tau (plot not shown). We used other time-series models as well, like the Lomb-Scargle periodograms [##UREF##14##33##,##UREF##15##34##] that can assess periodic behaviors (akin to Fourier analysis [##UREF##16##35##]) even in the presence of missing data and unequal sampling frequencies. Unfortunately, the embedding plot did not reveal any clear patterns, with the exception that the control (no-tau) point was on a distant corner of the plot and the tau samples with lower molar ratios of tau:tubulin are closer to the no-tau point than the samples with higher ratios (data not shown). Another class of models – the auto-regressive moving average (ARMA) models [##UREF##17##36##] – has often been used in analyzing time-series data. These models assume that the data is stationary, i.e., both the mean and the variance is fixed. Since the microtubules are clearly growing, we did not consider these models.</p>" ]

[ "<title>Discussion</title>", "<p>This work addresses the need of the biological research community for rigorously quantitative and generally applicable computational tools to compare the complex behaviors of individual members of groups of molecules, cells or even organisms. Presently, the vast majority of such comparisons are performed manually, or \"by eye\". As such, they are time-consuming, susceptible to inadvertent bias and errors and can be insensitive to subtleties. Using the regulatory effects of the microtubule associated protein tau upon the dynamic behavior of microtubules as a system of study, we have developed a novel modeling and visualization strategy allowing investigators (i) to assess the relative degree of similarity/dissimilarity among individual tau isoforms with respect to numerous parameters of interest under varying experimental conditions, and (ii) to visualize all the conditions with respect to each other. More importantly, the same computational strategy should be generally applicable to a great many other applications.</p>", "<p>The validity of the two-dimensional embedding strategy presented in this paper is established by comparing the plot presented in Figure ##FIG##2##3## with the growth rate data in Table ##TAB##0##1##. The relative positions of all points in Figure ##FIG##2##3## are in complete agreement with the quantitative growth rate data determined both automatically and manually. Additionally, the semi-quantitative analysis of the histograms shown in Figure ##FIG##3##4## of [##UREF##7##19##] are confirmed and extended by the more rigorous quantitative analysis leading to the two-dimensional embedding plot shown in Figure ##FIG##4##5##. In this case, 19 different bins of microtubule growth rates were integrated into the analysis for each of the nine experimental conditions tested. The resulting two-dimensional plot in Figure ##FIG##4##5## presents the investigator with novel perspectives on the data set, including the existence of two clusters of histogram distributions based on growth rate as well as the distinct behavior of low ratios of 3-repeat tau:tubulin relative to all other tested reactions.</p>", "<p>Finally, although the molecular mechanisms underlying behaviors suggested by various statistical models may not be clear, these models could suggest mechanisms that could not be drawn using the standard manual analytical methods generally utilized in biological investigations. Indeed, one of the most important and generally applicable features of our computational strategy is the ability to detect subtle relationships between different molecules or conditions that might escape manual investigation.</p>" ]

[ "<title>Conclusion</title>", "<p>In this manuscript, we present (i) an automated method for quantitatively characterizing microtubule dynamics as a function of time, and (ii) a novel and generally applicable computational tool for two-dimensional visualization and modeling of entities of interest for comparative studies. Comparison of our automated tracking method with manually acquired data demonstrates its accuracy. This tool greatly increases the rate at which microtubule tracking data can be acquired as well as improve upon its objectivity and accuracy. Our embedding strategy accurately recapitulates and extends previous biological observations that were collected and analyzed manually. Importantly, our methods facilitate the integration of sophisticated statistical modeling with biological investigations, which should promote novel and deeper mechanistic insights into biological phenomena as well as the development of testable hypotheses for subsequent investigation. In the future, we anticipate applying these methods to compare wild-type tau action versus various tau mutants causing neurodegeneration and dementia, seeking to identify novel mechanistic effects. Additionally, we envision using new models and embedding strategies.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Innumerable biological investigations require comparing collections of molecules, cells or organisms to one another with respect to one or more of their properties. Almost all of these comparisons are performed manually, which can be susceptible to inadvertent bias as well as miss subtle effects. The development and application of computer-assisted analytical and interpretive tools could help address these issues and thereby dramatically improve these investigations.</p>", "<title>Results</title>", "<p>We have developed novel computer-assisted analytical and interpretive tools and applied them to recent studies examining the ability of 3-repeat and 4-repeat tau to regulate the dynamic behavior of microtubules in vitro. More specifically, we have developed an automated and objective method to define growth, shortening and attenuation events from real time videos of dynamic microtubules, and demonstrated its validity by comparing it to manually assessed data. Additionally, we have used the same data to develop a general strategy of building different models of interest, computing appropriate dissimilarity functions to compare them, and embedding them on a two-dimensional plot for visualization and easy comparison. Application of these methods to assess microtubule growth rates and growth rate distributions established the validity of the embedding procedure and revealed non-linearity in the relationship between the tau:tubulin molar ratio and growth rate distribution.</p>", "<title>Conclusion</title>", "<p>This work addresses the need of the biological community for rigorously quantitative and generally applicable computational tools for comparative studies. The two-dimensional embedding method retains the inherent structure of the data, and yet markedly simplifies comparison between models and parameters of different samples. Most notably, even in cases where numerous parameters exist by which to compare the different samples, our embedding procedure provides a generally applicable computational strategy to detect subtle relationships between different molecules or conditions that might otherwise escape manual analyses.</p>" ]

[ "<title>Authors' contributions</title>", "<p>AB built the models, computed the pairwise distances, and embedded them on two dimensions for comparisons. AL, SL and MG collected the data and manually tracked the microtubules. AKS advised on the choice of the models and the distance functions. SCF and LW provided the biological interpretations. AB and SCF wrote the manuscript with inputs from the other authors. All the authors read and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We acknowledge grants from the NSF, USA (NSF ITR-0331697 to SCF, AKS, and LW), the NIH, USA (NIH NS-35010 to SCF and NIH NS-13560 to LW), and IIT, Kanpur, India (INI/IITK/CSE/20080069 to AB) for supporting this work. We also thank the anonymous referees whose comments helped improve the paper immensely.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Isoforms of tau</bold>. Schematic of two classes of tau isoforms – 4-repeat tau and 3-repeat tau. In 3-repeat tau, the region between repeats 1 and 2 and the second repeat structures are missing by virtue of alternative RNA splicing.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Example life history plot</bold>. An example of a typical \"life history\" plot of a microtubule, i.e., microtubule length as a function of time plot. The microtubule shown here is from the 3-repeat tau sample at a tau:tubulin molar ratio of 1:38.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Growth rate (sample 1)</bold>. Embedding of the growth rates of tau conditions for sample 1 (corresponding to Table 1). The distortion is 1, indicating no error in embedding. The automatically computed growth rates maintain the relationship of the conditions as described in the Results section and in [##UREF##7##19##]. Distortion = 1.00.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Growth rate (sample 2)</bold>. Embedding of the growth rates of tau conditions for sample 2 (corresponding to Table 2). The distortion is 1, indicating no error in embedding. The automatically computed growth rates maintain the relationship of the conditions as described in the Results section and in [##UREF##7##19##]. Distortion = 1.00.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Growth rate distribution histogram (sample 1)</bold>. Embedding of the microtubule growth rate distributions at varying tau:tubulin molar ratios for sample 1. The growth behavior of microtubules for low molar ratios of tau:tubulin for both 4-repeat and 3-repeat taus are similar to those in no-tau conditions. In higher molar ratios, however, the behavior is quite different. Distortion = 1.84.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Growth rate distribution histogram (sample 2)</bold>. Embedding of the microtubule growth rate distributions at varying tau:tubulin molar ratios for sample 2. The growth behavior of microtubules for low molar ratios of tau:tubulin for both 4-repeat and 3-repeat taus are similar to those in no-tau conditions. In higher molar ratios, however, the behavior is quite different. Distortion = 1.69.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Growth rates of tau conditions (sample 1)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Condition</td><td align=\"center\">Manual</td><td align=\"center\">Automatic</td><td align=\"center\">Difference</td><td align=\"center\">Deviation</td><td align=\"center\">P-value</td></tr></thead><tbody><tr><td align=\"center\">3R-1:20</td><td align=\"center\">3.99</td><td align=\"center\">4.19</td><td align=\"center\">0.20</td><td align=\"center\">4.93%</td><td align=\"center\">0.15</td></tr><tr><td align=\"center\">3R-1:38</td><td align=\"center\">3.58</td><td align=\"center\">3.76</td><td align=\"center\">0.18</td><td align=\"center\">4.80%</td><td align=\"center\">0.05</td></tr><tr><td align=\"center\">3R-1:45</td><td align=\"center\">2.02</td><td align=\"center\">2.27</td><td align=\"center\">0.25</td><td align=\"center\">12.58%</td><td align=\"center\">0.05</td></tr><tr><td align=\"center\">3R-1:55</td><td align=\"center\">2.02</td><td align=\"center\">2.28</td><td align=\"center\">0.26</td><td align=\"center\">12.68%</td><td align=\"center\">0.03</td></tr><tr><td align=\"center\">4R-1:20</td><td align=\"center\">4.71</td><td align=\"center\">4.56</td><td align=\"center\">0.15</td><td align=\"center\">3.33%</td><td align=\"center\">0.85</td></tr><tr><td align=\"center\">4R-1:38</td><td align=\"center\">3.96</td><td align=\"center\">4.19</td><td align=\"center\">0.23</td><td align=\"center\">5.86%</td><td align=\"center\">0.15</td></tr><tr><td align=\"center\">4R-1:45</td><td align=\"center\">3.51</td><td align=\"center\">3.65</td><td align=\"center\">0.14</td><td align=\"center\">4.14%</td><td align=\"center\">0.23</td></tr><tr><td align=\"center\">4R-1:55</td><td align=\"center\">2.59</td><td align=\"center\">2.84</td><td align=\"center\">0.25</td><td align=\"center\">9.45%</td><td align=\"center\">0.05</td></tr><tr><td align=\"center\">No-Tau</td><td align=\"center\">2.30</td><td align=\"center\">2.53</td><td align=\"center\">0.23</td><td align=\"center\">10.13%</td><td align=\"center\">0.27</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Average</td><td/><td/><td align=\"center\">0.21</td><td align=\"center\">6.59%</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Growth rates of tau conditions (sample 2)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Condition</td><td align=\"center\">Manual</td><td align=\"center\">Automatic</td><td align=\"center\">Difference</td><td align=\"center\">Deviation</td><td align=\"center\">P-value</td></tr></thead><tbody><tr><td align=\"center\">3R-1:20</td><td align=\"center\">3.90</td><td align=\"center\">4.02</td><td align=\"center\">0.12</td><td align=\"center\">3.07%</td><td align=\"center\">0.22</td></tr><tr><td align=\"center\">3R-1:38</td><td align=\"center\">2.67</td><td align=\"center\">2.87</td><td align=\"center\">0.20</td><td align=\"center\">7.49%</td><td align=\"center\">0.73</td></tr><tr><td align=\"center\">3R-1:45</td><td align=\"center\">2.16</td><td align=\"center\">2.39</td><td align=\"center\">0.23</td><td align=\"center\">10.65%</td><td align=\"center\">0.13</td></tr><tr><td align=\"center\">3R-1:55</td><td align=\"center\">2.34</td><td align=\"center\">2.47</td><td align=\"center\">0.13</td><td align=\"center\">5.56%</td><td align=\"center\">0.35</td></tr><tr><td align=\"center\">4R-1:20</td><td align=\"center\">4.93</td><td align=\"center\">4.99</td><td align=\"center\">0.06</td><td align=\"center\">1.22%</td><td align=\"center\">0.63</td></tr><tr><td align=\"center\">4R-1:38</td><td align=\"center\">4.39</td><td align=\"center\">4.63</td><td align=\"center\">0.24</td><td align=\"center\">5.47%</td><td align=\"center\">0.43</td></tr><tr><td align=\"center\">4R-1:45</td><td align=\"center\">3.87</td><td align=\"center\">3.87</td><td align=\"center\">0.00</td><td align=\"center\">0.00%</td><td align=\"center\">0.75</td></tr><tr><td align=\"center\">4R-1:55</td><td align=\"center\">3.25</td><td align=\"center\">3.47</td><td align=\"center\">0.22</td><td align=\"center\">6.77%</td><td align=\"center\">0.14</td></tr><tr><td align=\"center\">No-Tau</td><td align=\"center\">2.77</td><td align=\"center\">2.95</td><td align=\"center\">0.18</td><td align=\"center\">6.50%</td><td align=\"center\">0.36</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"center\">Average</td><td/><td/><td align=\"center\">0.15</td><td align=\"center\">4.55%</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Rank order of different conditions</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\">Rank</td><td align=\"center\" colspan=\"2\">Condition (growth rate)</td></tr><tr><td/><td colspan=\"2\"><hr/></td></tr><tr><td/><td align=\"center\">Table III of (Levy et al., 2005) [##UREF##7##19##] (Table 1 of this paper)</td><td align=\"center\">Table II of (Levy et al., 2005) [##UREF##7##19##] (Table 2 of this paper)</td></tr></thead><tbody><tr><td align=\"center\">1</td><td align=\"center\">4R-1:20 (4.7)</td><td align=\"center\">4R-1:20 (4.9)</td></tr><tr><td align=\"center\">2</td><td align=\"center\">4R-1:38 (4.0)</td><td align=\"center\">4R-1:38 (4.4)</td></tr><tr><td align=\"center\">3</td><td align=\"center\">3R-1:20 (4.0)</td><td align=\"center\">3R-1:20 (3.9)</td></tr><tr><td align=\"center\">4</td><td align=\"center\">4R-1:45 (3.5)</td><td align=\"center\">4R-1:45 (3.9)</td></tr><tr><td align=\"center\">5</td><td align=\"center\">3R-1:38 (3.6)</td><td align=\"center\">4R-1:55 (3.3)</td></tr><tr><td align=\"center\">6</td><td align=\"center\">4R-1:55 (2.6)</td><td align=\"center\">3R-1:38 (2.7)</td></tr><tr><td align=\"center\">7</td><td align=\"center\">No-Tau (2.3)</td><td align=\"center\">No-Tau (2.8)</td></tr><tr><td align=\"center\">8</td><td align=\"center\">3R-1:45 (2.0)</td><td align=\"center\">3R-1:45 (2.2)</td></tr><tr><td align=\"center\">9</td><td align=\"center\">3R-1:55 (2.0)</td><td align=\"center\">3R-1:55 (2.3)</td></tr></tbody></table></table-wrap>" ]

[ "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1471-2105-9-339-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mfrac><mml:mrow><mml:mn>7.7</mml:mn><mml:mo>−</mml:mo><mml:mn>0.5</mml:mn></mml:mrow><mml:mi>b</mml:mi></mml:mfrac><mml:mi>μ</mml:mi><mml:mi>m</mml:mi><mml:mo>/</mml:mo><mml:mi>m</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula><italic>ψ</italic>_{<italic>s,l</italic>}(<italic>x</italic>) = 2^{-<italic>s</italic>/2}<italic>ψ</italic>(2^{-<italic>s </italic>}<italic>x </italic>- <italic>l</italic>)</disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\" name=\"1471-2105-9-339-i2\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>ψ</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mtable columnalign=\"left\"><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mn>0</mml:mn><mml:mo>≤</mml:mo><mml:mi>x</mml:mi><mml:mo>&lt;</mml:mo><mml:mn>1</mml:mn><mml:mo>/</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mn>1</mml:mn><mml:mo>/</mml:mo><mml:mn>2</mml:mn><mml:mo>≤</mml:mo><mml:mi>x</mml:mi><mml:mo>&lt;</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mtd></mml:mtr><mml:mtr columnalign=\"left\"><mml:mtd columnalign=\"left\"><mml:mn>0</mml:mn></mml:mtd><mml:mtd columnalign=\"left\"><mml:mrow><mml:mtext>otherwise</mml:mtext></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:mrow></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><italic>λ </italic>= {<italic>n</italic>, <italic>π</italic>, <italic>τ</italic>}</disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\" name=\"1471-2105-9-339-i3\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mi>k</mml:mi></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>p</mml:mi><mml:mo>,</mml:mo><mml:mi>q</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mo>∀</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:munder><mml:mrow><mml:msup><mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>q</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>|</mml:mo></mml:mrow></mml:mrow><mml:mi>k</mml:mi></mml:msup></mml:mrow></mml:mstyle></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>/</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:msup></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\" name=\"1471-2105-9-339-i4\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>M</mml:mi><mml:mi>D</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>p</mml:mi><mml:mo>,</mml:mo><mml:mi>q</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:munder><mml:mrow><mml:mi>min</mml:mi><mml:mo>⁡</mml:mo></mml:mrow><mml:mi>f</mml:mi></mml:munder><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>,</mml:mo><mml:mi>j</mml:mi></mml:mrow></mml:munder><mml:mrow><mml:msub><mml:mi>c</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mi>f</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mstyle></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><italic>MD</italic>(<italic>p, q</italic>) = <italic>L</italic>₁(<italic>P, Q</italic>)</disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M5\" name=\"1471-2105-9-339-i5\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:msubsup><mml:mo>∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>i</mml:mi></mml:msubsup><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M6\" name=\"1471-2105-9-339-i6\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>Q</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:msubsup><mml:mo>∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>i</mml:mi></mml:msubsup><mml:mrow><mml:msub><mml:mi>q</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></inline-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M7\" name=\"1471-2105-9-339-i7\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>p</mml:mi><mml:mo>,</mml:mo><mml:mi>q</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>k</mml:mi></mml:munderover><mml:mrow><mml:msub><mml:mi>w</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mrow><mml:mo>|</mml:mo><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>q</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>|</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M8\" name=\"1471-2105-9-339-i8\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>E</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>x</mml:mi><mml:mo>,</mml:mo><mml:mi>y</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mi>c</mml:mi></mml:mfrac><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mo>∀</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi><mml:mo>,</mml:mo><mml:mi>α</mml:mi><mml:mo>≠</mml:mo><mml:mi>β</mml:mi></mml:mrow></mml:munder><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:msup><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>d</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>−</mml:mo><mml:msub><mml:mi>L</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>e</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>α</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>,</mml:mo><mml:mi>e</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>β</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mrow><mml:mi>d</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mfrac></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M9\" name=\"1471-2105-9-339-i9\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>c</mml:mi><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:munder><mml:mo>∑</mml:mo><mml:mrow><mml:mo>∀</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi></mml:mrow></mml:munder><mml:mrow><mml:mi>d</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>β</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M10\" name=\"1471-2105-9-339-i10\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mtable><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>x</mml:mi><mml:mi>α</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:msubsup><mml:mi>x</mml:mi><mml:mi>α</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:mi>f</mml:mi><mml:mo>×</mml:mo><mml:mfrac><mml:mrow><mml:mo>∂</mml:mo><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mo>∂</mml:mo><mml:mi>x</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:mrow><mml:msup><mml:mo>∂</mml:mo><mml:mn>2</mml:mn></mml:msup><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mo>∂</mml:mo><mml:msup><mml:mi>x</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mo>|</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mrow><mml:msubsup><mml:mi>y</mml:mi><mml:mi>α</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:msubsup><mml:mi>y</mml:mi><mml:mi>α</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msubsup><mml:mo>−</mml:mo><mml:mi>f</mml:mi><mml:mo>×</mml:mo><mml:mfrac><mml:mrow><mml:mo>∂</mml:mo><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mo>∂</mml:mo><mml:mi>y</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:mrow><mml:msup><mml:mo>∂</mml:mo><mml:mn>2</mml:mn></mml:msup><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>i</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msup><mml:mo>/</mml:mo><mml:mo>∂</mml:mo><mml:msup><mml:mi>y</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mo>|</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M11\" name=\"1471-2105-9-339-i11\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi>max</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi><mml:mtext> </mml:mtext><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mrow><mml:mi>e</mml:mi><mml:mi>m</mml:mi><mml:mi>b</mml:mi><mml:mi>e</mml:mi><mml:mi>d</mml:mi><mml:mi>d</mml:mi><mml:mi>e</mml:mi><mml:mi>d</mml:mi><mml:mtext> </mml:mtext><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:mfrac></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>min</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi><mml:mtext> </mml:mtext><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi></mml:mrow><mml:mrow><mml:mi>e</mml:mi><mml:mi>m</mml:mi><mml:mi>b</mml:mi><mml:mi>e</mml:mi><mml:mi>d</mml:mi><mml:mi>d</mml:mi><mml:mi>e</mml:mi><mml:mi>d</mml:mi><mml:mtext> </mml:mtext><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:mfrac></mml:mrow><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M12\" name=\"1471-2105-9-339-i12\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msqrt><mml:mn>2</mml:mn></mml:msqrt></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M13\" name=\"1471-2105-9-339-i12\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msqrt><mml:mn>2</mml:mn></mml:msqrt></mml:mrow></mml:semantics></mml:math></inline-formula>" ]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>This file shows the effect of number of bins on the growth rate distribution histograms.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>This file shows the two-dimensional embedding plots of the Haar wavelet coefficients of microtubules with varying tau:tubulin molar ratios for both the samples.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>This file shows the individual distortions of all the pairwise distances between the conditions for all the different models described.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>The manual data is reproduced from Table III of (Levy et al., 2005) [##UREF##7##19##]. The third column shows growth rates (in <italic>μm</italic>/<italic>min</italic>) automatically computed from the manually tracked tips of the microtubules using an objective set of rules with no human interference. The relative ranks of the conditions remain the same.</p></table-wrap-foot>", "<table-wrap-foot><p>The manual data is reproduced from Table II of (Levy et al., 2005) [##UREF##7##19##]. The third column shows growth rates (in <italic>μm</italic>/<italic>min</italic>) automatically computed from the manually tracked tips of the microtubules using an objective set of rules with no human interference. The relative ranks of the conditions remain the same.</p></table-wrap-foot>", "<table-wrap-foot><p>The ranks of the conditions remain almost the same across the two samples (considering a variation of 0.1 <italic>μm</italic>/<italic>min</italic>) except that the 4R-1:55 and the 3R-1:38 conditions are reversed.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2105-9-339-1\"/>", "<graphic xlink:href=\"1471-2105-9-339-2\"/>", "<graphic xlink:href=\"1471-2105-9-339-3\"/>", "<graphic xlink:href=\"1471-2105-9-339-4\"/>", "<graphic xlink:href=\"1471-2105-9-339-5\"/>", "<graphic xlink:href=\"1471-2105-9-339-6\"/>" ]

[ "<media xlink:href=\"1471-2105-9-339-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-339-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2105-9-339-S3.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>A phylogenetic tree models the evolutionary history of a set of taxa from their most recent common ancestor. The assumptions of strict divergence and vertical inheritance render trees appropriate for modeling the evolutionary histories of several groups of species or organisms. However, when <italic>reticulate </italic>evolutionary events such as horizontal gene transfer or interspecific recombination occur, the evolutionary history is more appropriately modeled by an evolutionary network.</p>", "<p>Evidence of reticulate evolution has been shown in various domains in the Tree of Life. Bacteria obtain a large proportion of their genetic diversity through the acquisition of sequences from distantly related organisms, via horizontal gene transfer (HGT) [##REF##10830951##1##]. Furthermore, more evidence of widespread HGT in plants is emerging recently [##REF##12853958##2##, ####REF##15598737##3##, ##REF##15538356##4####15538356##4##]. Interspecific recombination is believed to be ubiquitous among viruses [##REF##12429687##5##,##REF##11847565##6##], and hybrid speciation is a major evolutionary mechanisms in plants, and groups of fish and frogs [##REF##11607681##7##, ####REF##10849068##8##, ##REF##10688138##9##, ##REF##18677414##10####18677414##10##]. All of these processes result in networks, rather than trees, of evolutionary relationships, even though at the gene level evolutionary histories may be treelike, as we now describe.</p>", "<p>Figure ##FIG##0##1## illustrates the three major events that result in networks of evolutionary relationships among species, namely horizontal gene transfer, interspecific recombination, and hybrid speciation. The tubes depict the evolutionary network of the species, within which two gene trees are shown. In each box, the two possible gene trees <italic>T </italic>and <italic>T</italic>' are shown separately, as well as the network <italic>N </italic>at an abstract level. In an evolutionary scenario involving horizontal transfer, certain sites (specified by a specific substring within the DNA sequence of the species into which the horizontally transferred DNA was inserted) are inherited from another species (the tree <italic>T</italic>' in dashed lines in Figure ##FIG##0##1(a)##), while all others are inherited from the parent (the tree <italic>T </italic>in solid lines in Figure ##FIG##0##1(a)##). Thus, each site evolves down one of the trees contained inside the network.</p>", "<p>In the case of interspecific recombination, as illustrated in Figure ##FIG##0##1(b)##, some genetic material is exchanged between pairs of species; in this example, species <italic>B </italic>and <italic>C </italic>exchange genetic material. The genes involved in this exchange have an evolutionary history (gene tree <italic>T</italic>') that is different from that of the genes that are vertically transmitted (gene tree <italic>T</italic>).</p>", "<p>In the case of hybrid speciation, as illustrated in Figure ##FIG##0##1(c)##, the two parents contribute equally to the genetic material of the hybrid: in <italic>diploid </italic>hybridization, each parent contributes a single copy of each of its chromosomes, while in <italic>polyploid </italic>hybridization, each parent contributes all copies of its chromosomes. Thus, each set of \"orthologous sites\" from all taxa has an evolutionary history that is depicted by one of the trees inside the network.</p>", "<p>A few software tools for analyzing reticulate evolutionary relationships have been developed recently. The SplitsTree4 tool, which incorporates several algorithms that have been developed by Daniel Huson and his co-workers, is a tool for reconstructing and visualizing splits networks [##REF##16221896##11##]. The tool enables constructing networks from several types of data, including sequence data, distance matrices, and sets of trees. Two major differences exist between SplitsTree4 and PhyloNet. First, SplitsTree4 constructs and analyzes splits networks, which are graphical models of incompatibility in the data, whereas PhyloNet constructs and analyzes evolutionary networks, which are rooted, directed, acyclic graphs, that represent evolutionary relationships. Second, the two tools differ in the utilities they provide, and we view them as complementary. While SplitsTree4 is mainly aimed at reconstructing networks, PhyloNet has several utilities for evaluating networks.</p>", "<p>Programs such as EEEP [##REF##16472400##12##], HorizStory [##REF##15819979##13##], LatTrans [##UREF##0##14##], and T-REX [##REF##11448889##15##] are aimed at detecting horizontal gene transfer by reconciling a pair of species/gene trees. The PhyloNet software package that we developed contains an extended implementation of the RIATA-HGT algorithm [##UREF##1##16##] with several improved algorithmic techniques for computing multiple solutions and handling non-binary trees [##UREF##2##17##]. The new version of RIATA-HGT significantly outperforms, in terms of speed, EEEP, HorizStory and LatTrans, and performs at least as well in terms of accuracy [##UREF##2##17##,##REF##17572027##18##]. We have recently added a new heuristic for inferring the support of HGT moves from bootstrap values of gene tree edges. Further, we have added the capability of visualizing the networks computed by RIATA-HGT. Besides RIATA-HGT, the PhyloNet software package implements methods for comparing and characterizing evolutionary networks, which include: (1) evolutionary network representation: reading/writing evolutionary networks in a newly devised compact form; (2) evolutionary network characterization: analyzing evolutionary networks in terms of three basic building blocks – trees, clusters, and tripartitions; (3) evolutionary network comparison: comparing two evolutionary networks in terms of topological dissimilarities, as well as fitness to sequence evolution under a maximum parsimony criterion; and (4) evolutionary network reconstruction: reconstructing an evolutionary network from a species tree and a set of gene trees. Furthermore, since various evolutionary network utilities use functionalities from the phylogenetic trees domain, PhyloNet provides a set of standalone phylogenetic tree analysis tools.</p>" ]

[]

[ "<title>Results and discussion</title>", "<title>The evolutionary network model</title>", "<p>In this paper, we assume the \"evolutionary network\" model, which was formulated independently by Moret <italic>et al</italic>. [##REF##17048405##19##] and Baroni <italic>et al</italic>. [##UREF##3##20##]. We now describe the model as well as some basic definitions and notations that we will use later.</p>", "<p>Let <italic>T </italic>= (<italic>V</italic>, <italic>E</italic>) be a tree, where <italic>V </italic>and <italic>E </italic>are the <italic>tree nodes </italic>and <italic>tree edges</italic>, respectively, and let <italic>L</italic>(<italic>T</italic>) denote the tree's leaf set. Further, let <italic>χ </italic>be a set of taxa (organisms). Then, <italic>T </italic>is a <italic>phylogenetic tree </italic>over <italic>χ </italic>if there is a bijection between <italic>χ </italic>and <italic>L</italic>(<italic>T</italic>). Henceforth, we will identify the taxa set with the leaves they are mapped to, and let [<italic>n</italic>] = {1,..., <italic>n</italic>} denote the set of leaf-labels. A tree <italic>T </italic>is said to be <italic>rooted </italic>if the set of edges <italic>E </italic>is directed and there is a single node <italic>r </italic>∈ <italic>V </italic>with in-degree 0. Let <italic>T </italic>be a phylogenetic tree on set <italic>χ </italic>of taxa, and let <italic>χ</italic>' ⊆ <italic>χ </italic>be a subset of taxa; then, we denote by <italic>T</italic>|<italic>χ</italic>' the subtree with minimum number of nodes and edges that spans the leaves in <italic>χ</italic>' (in other words, <italic>T</italic>|<italic>χ</italic>' is the tree <italic>T </italic>restricted to subset <italic>χ</italic>' of its leaves).</p>", "<p>An evolutionary (phylogenetic) network <italic>N </italic>= (<italic>V</italic>, <italic>E</italic>) over the set <italic>χ </italic>of taxa is a rooted, directed, acyclic graph such that there is a bijection between <italic>χ </italic>and the set <italic>L</italic>(<italic>N</italic>) of the network's leaves (see Figure ##FIG##1##2##). The set <italic>V </italic>is partitioned into two sets: <italic>V</italic>_{<italic>T</italic>}, the set of <italic>tree nodes</italic>, which are the nodes with in-degree smaller than two, and <italic>V</italic>_{<italic>N</italic>}, the set of <italic>network nodes</italic>, which are the nodes with in-degree greater than or equal to two. Similarly, the set <italic>E </italic>is partitioned into two sets: <italic>E</italic>_{<italic>T</italic>}, the set of <italic>tree edges</italic>, which are edges incident into tree nodes, and <italic>E</italic>_{<italic>N</italic>}, the set of <italic>network edges</italic>, which are the edges incident into network nodes.</p>", "<p>For two nodes <italic>u </italic>and <italic>v </italic>in directed graph <italic>G</italic>, we say that <italic>v </italic>is reachable from <italic>u</italic>, denoted by if there exists a directed path from <italic>u </italic>to <italic>v </italic>in the tree <italic>G</italic>. For three nodes <italic>u</italic>, <italic>v </italic>and <italic>x </italic>in directed graph <italic>G</italic>, we write if all directed paths from <italic>u </italic>to <italic>v </italic>go through node <italic>x</italic>; if no directed paths from <italic>u </italic>to <italic>v </italic>go through node <italic>x</italic>; and if at least one directed path from <italic>u </italic>to <italic>v </italic>goes through node <italic>x </italic>and at least one directed path from <italic>u </italic>to <italic>v </italic>does not go through node <italic>x</italic>. For example, in network <italic>N</italic>₁in Figure ##FIG##1##2##, rooted at node r₁, we have , , and .</p>", "<title>Evolutionary network representation</title>", "<p>The Newick format for representing and storing phylogenetic trees was adopted in 1986 [##REF##3024605##21##], and it has been the standard for almost all phylogeny software packages ever since. This format captures an elegant correspondence between leaf-labeled trees and matched parentheses, where the leaves are represented by their names and the internal nodes by a matched pair of parentheses that contains a list of the Newick representation of all its children. Shown in Figure ##FIG##2##3## are three trees along with their representations in the Newick format.</p>", "<p>Existing phylogenetic network software tools store these networks as adjacency lists of their underlying graphs, which are usually very large and necessitate translation of representations among the different tools. Morin and Moret [##REF##16717070##22##] proposed a modified version of the Newick format for representing such networks. In their format, network nodes are represented by nodes labeled with #H, and those nodes are considered as two separate nodes in the normal Newick format for trees. See Figure ##FIG##3##4## for an example. We have independently proposed a new method of <italic>tree decomposition </italic>of evolutionary networks, which provides the basis for a new format, <italic>extended Newick </italic>(or eNewick for short), and used it as a compact representation of evolutionary networks. The idea in our method is to break the network into a set of trees, and then represent the network as a collection of Newick representations of those trees. Since the eNewick format is nothing but a collection of trees in the Newick format, it follows that eNewick can represent unrooted networks. However, both in this paper as well as in the PhyloNet utilities, rooting is assumed, since different ways of rooting the same evolutionary networks may imply different evolutionary relationships.</p>", "<p>Let <italic>N </italic>= (<italic>V </italic>= (<italic>V</italic>_{<italic>N </italic>}∪ <italic>V</italic>_{<italic>T</italic>}); <italic>E</italic>) be an evolutionary network, with |<italic>V</italic>_{<italic>N</italic>}| = ℓ. We create a forest of ℓ trees as follows.</p>", "<p>• For every <italic>u</italic>_{<italic>i </italic>}∈ <italic>V</italic>_{<italic>N</italic>}</p>", "<p>- Compute the set <italic>V</italic>_{<italic>i </italic>}= {<italic>v </italic>∈ <italic>V </italic>: (<italic>v</italic>, <italic>u</italic>_{<italic>i</italic>}) ∈ <italic>E</italic>} of <italic>u</italic>_{<italic>i</italic>}'s parents;</p>", "<p>- Create <italic>k </italic>new leaves, all labeled with <italic>x</italic>_{<italic>i </italic>}({<italic>x</italic>_{<italic>i</italic>}} ∩ <italic>L</italic>(<italic>N</italic>) = ∅);</p>", "<p>- Delete from <italic>V </italic>the set of all edges in <italic>V</italic>_{<italic>i </italic>}× {<italic>u</italic>_{<italic>i</italic>}};</p>", "<p>- Add to <italic>V </italic>the set of edges <italic>V</italic>_{<italic>i </italic>}× {<italic>x</italic>_{<italic>i</italic>}};</p>", "<p>- Assign <italic>x</italic>_{<italic>i </italic>}as the name of the tree rooted at node <italic>u</italic>_{<italic>i</italic>};</p>", "<p>The result is a forest of trees = {<italic>t</italic>₁,..., <italic>t</italic>_ℓ} such that (1) |<italic>L</italic>(<italic>t</italic>_{<italic>i</italic>})| ≥ 1 for every 1 ≤ <italic>i </italic>≤ ℓ, (2) and (3) <italic>L</italic>(<italic>t</italic>_{<italic>i</italic>}) ∩ <italic>L</italic>(<italic>t</italic>_{<italic>j</italic>}) = ∅ for every 1 ≤ <italic>i</italic>, <italic>j </italic>≤ ℓ and <italic>i </italic>≠ <italic>j</italic>. We call the <italic>tree decomposition </italic>of <italic>N</italic>. Then, the eNewick representation of <italic>N </italic>is the ℓ-tuple ⟨<italic>n</italic>(<italic>t</italic>₁);...; <italic>n</italic>(<italic>t</italic>_ℓ)⟩, where <italic>n</italic>(<italic>t</italic>_{<italic>i</italic>}) is the Newick representation of tree <italic>t</italic>_{<italic>i</italic>}. Figure ##FIG##2##3## shows the tree decomposition and eNewick representation of the network <italic>N</italic>₁in Figure ##FIG##1##2##.</p>", "<p>In the case of modeling networks with horizontal gene transfer events, it is often very helpful to the biologist to know what the species tree is and what the additional set of HGT events are. Such information is \"lost\" in an eNewick representation, unless the representation is extended further to keep a record of the \"species tree parent\" of each network node. Therefore, in this case (which is the output of RIATA-HGT) we opt for the format of a species tree <italic>T</italic>, in Newick format, followed by a list of the HGT edges, each written as <italic>X </italic>→ <italic>Y</italic>, where <italic>X </italic>and <italic>Y </italic>are two nodes in <italic>T</italic>.</p>", "<title>Evolutionary network characterization</title>", "<p>As we described in the background section, an evolutionary network induces, or contains, a set of trees. We now formalize this concept and characterize networks in terms of the trees they induce. A tree <italic>T </italic>is induced by a network <italic>N </italic>if <italic>T </italic>is obtained from <italic>N </italic>as follows: (1) for each node of in-degree larger than one, remove all but one of the network edges incident into it, and (2) for every node of in-degree and out-degree 1, and whose parent is <italic>u </italic>and child is <italic>v</italic>, remove the two edges incident with it, and add an edge from <italic>u </italic>to <italic>v</italic>. We denote by (<italic>N</italic>) the set of all trees induced by <italic>N</italic>. Figure ##FIG##4##5## shows the sets (<italic>N</italic>₁) and (<italic>N</italic>₂) for the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2##. It is important to note that this set of trees is completely different from the set of trees obtained by the tree decomposition we introduced to facilitate the eNewick format. An evolutionary network <italic>N </italic>with <italic>V</italic>_{<italic>N </italic>}= {<italic>v</italic>₁,..., <italic>v</italic>_ℓ}, such that <italic>indegree</italic>(<italic>v</italic>_{<italic>i</italic>}) = <italic>ρ</italic>_{<italic>i</italic>}, induces <italic>m </italic>trees, where </p>", "<p>Given an evolutionary network <italic>N</italic>, the set (<italic>N</italic>) is unique. Further, this set informs about the possible gene histories that the network reconciles.</p>", "<p>In addition to characterizing evolutionary networks by the set of trees they induce, we consider a <italic>cluster</italic>-based characterization. This view of evolutionary networks is very important for understanding the relationships among the \"evolutionary perspective\" of evolutionary networks and the \"cluster, or splits, perspective\", which is adopted in various methods [##REF##9520503##23##,##UREF##4##24##]. Let <italic>T </italic>= (<italic>V</italic>, <italic>E</italic>) be a phylogenetic tree on set <italic>χ </italic>of taxa and rooted at node <italic>r</italic>. Each edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) ∈ <italic>E </italic>induces a <italic>cluster </italic>of taxa, denoted <italic>c</italic>_{<italic>e</italic>}, which is the set . The (nontrivial) clusters of tree <italic>T </italic>is the set (<italic>T</italic>) = {<italic>c</italic>_{<italic>e </italic>}: <italic>e </italic>is an internal edge in <italic>E</italic>}. The topology of a tree is a compact graphical representation of its clusters, where the root of the clade that corresponds to cluster <italic>c</italic>_{<italic>e</italic>'}lies on the path from the root of the tree to the root of the clade that corresponds to cluster <italic>c</italic>_{<italic>e </italic>}if and only if <italic>c</italic>_{<italic>e </italic>}⊆ <italic>c</italic>_{<italic>e</italic>'}. Hence, clusters play an important role in phylogenetic tree characterization and reconstruction. A straightforward way to extend this concept to evolutionary networks is to define the set of clusters of evolutionary network <italic>N </italic>as . The clusters of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##0##1##.</p>", "<p>In this form of cluster-based characterization, clusters are unweighted; equivalently, all clusters are weighted equally. One option of weighting the clusters is by considering the fraction of trees in which it appears. In other words, the weight of a cluster <italic>c</italic>_{<italic>e </italic>}can be computed as</p>", "<p></p>", "<p>This weighting scheme informs not only about the clusters of taxa that the network represents, but also how many gene trees in the input share each cluster. It is important to note here that this weighting of a cluster should not be confused with, or used in lieu of, support values of clusters, since a cluster may appear in only one gene tree and have a high support (e.g., by having a high bootstrap value on the edge that defines it) whereas a poorly supported cluster may appear in several trees.</p>", "<p>Nakhleh and colleagues have recently introduced a new characterization of evolutionary networks based on the <italic>tripartitions </italic>of their edges [##REF##17048405##19##]. Let <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) be an edge in an evolutionary network on set <italic>χ </italic>of taxa and rooted at node <italic>r</italic>. We define three disjoint sets <italic>A</italic>_{<italic>e </italic>}= , <italic>B</italic>_{<italic>e </italic>}= , and <italic>C</italic>_{<italic>e </italic>}= . Then, the tripartition induced by edge <italic>e</italic>, denoted <italic>θ</italic>_{<italic>e</italic>}, is the triplet ⟨<italic>A</italic>_{<italic>e</italic>}; <italic>B</italic>_{<italic>e</italic>}; <italic>C</italic>_{<italic>e</italic>}⟩. Roughly speaking, the tripartition induced by an edge is the three sets of taxa reachable from the root only through that edge (<italic>A</italic>_{<italic>e</italic>}), reachable through that edge but not exclusively (<italic>B</italic>_{<italic>e</italic>}), and not reachable through that edge (<italic>C</italic>_{<italic>e</italic>}). The set of (nontrivial) tripartitions induced by a evolutionary network <italic>N</italic>, denoted by <italic>θ</italic>(<italic>N</italic>), is {<italic>θ</italic>_{<italic>e </italic>}: <italic>e </italic>is an internal edge in <italic>E</italic>}. The tripartitions of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##1##2##.</p>", "<p>Tripartition-based characterization of an evolutionary network helps to identify clades across which no genetic transfer occurred. If <italic>A</italic>_{<italic>e </italic>}= <italic>X </italic>and <italic>B</italic>_{<italic>e </italic>}= ∅ for an edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>), this implies that the clade rooted at node <italic>v </italic>has set <italic>X </italic>of leaves, and there does not exist any exchange or transfer of genetic material between any organism in <italic>X </italic>and another organism that is not in <italic>X</italic>. Equivalently, an evolutionary network can be partitioned into a collection {<italic>N</italic>₁, <italic>N</italic>₂,..., <italic>N</italic>_{<italic>k</italic>}} of evolutionary networks that result from <italic>N </italic>by deleting every edge <italic>e </italic>for which <italic>B</italic>_{<italic>e </italic>}= ∅. Such a partition informs about the \"locality\" of reticulation events: each event in <italic>N </italic>is local to one of the <italic>k </italic>components in {<italic>N</italic>₁, <italic>N</italic>₂,..., <italic>N</italic>_{<italic>k</italic>}}. Further, this partition implies that each of the trees in (<italic>N</italic>) has <italic>k </italic>clades that have the sets {<italic>L</italic>(<italic>N</italic>₁), <italic>L</italic>(<italic>N</italic>₂),..., <italic>L</italic>(<italic>N</italic>_{<italic>k</italic>})} of leaves.</p>", "<title>Evolutionary network comparison</title>", "<p>Researchers are often interested in quantifying the similarities and differences between two phylogenies reconstructed either from two different sources of data or from two different reconstruction methods. Such a quantification provides insights into agreements and disagreements among analyses, confidence values for different parts of the phylogenies, and metrics for comparing the performance of phylogenetic reconstruction methods. In the context of phylogenetic trees, this quantification is most commonly done based on one of two criteria:</p>", "<p>• <italic>Topological differences</italic>. The topologies, or shapes, of two phylogenetic trees are compared, and their differences are quantified. Several measures have been introduced to quantify topological differences and similarities between a pair of trees, such as the Robinson-Foulds measure and the SPR distance; see [##UREF##5##25##,##UREF##6##26##] for a description of several such measures.</p>", "<p>• <italic>Fitness to sequence evolution</italic>. When two phylogenies are reconstructed from the same sequence data set, it is common to compare them in terms of how well they model the evolution of the sequences. The most commonly used criteria for measuring such fitness are maximum parsimony, maximum likelihood, and the Bayesian posterior probability; see [##UREF##5##25##] for a detailed discussion of all three criteria.</p>", "<p>In this section, we report on the capabilities in PhyloNet for comparing two evolutionary networks in terms of their topological differences and similarities, as well as in terms of their fitness to sequence evolution based on the maximum parsimony criterion.</p>", "<p>For quantifying the dissimilarity between two evolutionary network topologies <italic>N</italic>₁and <italic>N</italic>₂, we want a measure <italic>m</italic>(·,·) that satisfies three conditions:</p>", "<p><italic>Identity</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) = 0 if and only if <italic>N</italic>₁and <italic>N</italic>₂are <italic>equivalent</italic>;</p>", "<p><italic>Symmetry</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) = <italic>m</italic>(<italic>N</italic>₂, <italic>N</italic>₁); and</p>", "<p><italic>Triangle inequality</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₃) + <italic>m</italic>(<italic>N</italic>₃, <italic>N</italic>₂) ≥ <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) for any evolutionary network <italic>N</italic>₃.</p>", "<p>This issue of evolutionary network equivalence was discussed in [##REF##17048405##19##]. The three characterizations of evolutionary networks that we described above induce three measures which we now define. Let <italic>N</italic>₁and <italic>N</italic>₂be two evolutionary networks on the same set <italic>X </italic>of leaves; we define the three measures as follows.</p>", "<title>Tree-based comparison</title>", "<p>Let (<italic>N</italic>₁) and (<italic>N</italic>₂) be the two sets of all trees induced by the two networks, and let <italic>d</italic>(·,·) be a distance metric on trees (see [##UREF##6##26##] for examples of such metrics). The idea is to compare the two networks based on how similar their corresponding sets of trees are. We formalize this as follows. Construct a weighted complete bipartite graph <italic>G</italic>(<italic>U</italic>₁, <italic>U</italic>₂, <italic>E</italic>), where |<italic>U</italic>_{<italic>i</italic>}| = |(<italic>N</italic>_{<italic>i</italic>})|, and there are two bijections <italic>f</italic>_{<italic>i </italic>}: <italic>U</italic>_{<italic>i </italic>}→ (<italic>N</italic>_{<italic>i</italic>}) for <italic>i </italic>= 1, 2. The weight of an edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) ∈ <italic>E </italic>for <italic>u </italic>∈ <italic>U</italic>₁and <italic>v </italic>∈ <italic>U</italic>₂, <italic>w</italic>(<italic>e</italic>) = <italic>d</italic>(<italic>f</italic>₁(<italic>u</italic>), <italic>f</italic>₂(<italic>v</italic>)). Then, the tree-based measure <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) is defined as the weight of a minimum-weight edge cover of <italic>G </italic>divided by, the number of the edges in the cover. In its current implementation, PhyloNet uses the Robinson-Foulds distance measure [##UREF##7##27##] for <italic>d</italic>. The tree-based measure was first introduced by Nakhleh <italic>et al</italic>. [##UREF##8##28##]. An illustration of tree-based comparison of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## is given in Figure ##FIG##5##6##. Shown on the left of Figure ##FIG##5##6## is the bipartite graph <italic>G </italic>built from the sets (<italic>N</italic>₁) and (<italic>N</italic>₂) of trees induced by the two networks; these two sets are shown in Figure ##FIG##4##5##. The weight of each edge connecting two nodes in <italic>G </italic>is the RF distance between the two trees corresponding to these two nodes. These weights can be normalized by the number of internal edges in the trees. Since each of the eight trees has six internal edges, the weight of each edge in <italic>G </italic>can be divided by six to normalize it.</p>", "<p>Shown on the right of Figure ##FIG##5##6## is the minimum-weight edge cover of <italic>G</italic>, which is the set of edges that satisfies two conditions: (1) each node in <italic>G </italic>must be the endpoint of at least one edge in the set, and (2) the sum of the weights of the edges in the set is minimum among all sets of edges satisfying condition 1. In this case, the four edges shown are a cover, since each node in <italic>G </italic>is \"covered\" by at least one edge (here, each node is covered by exactly one edge). Further, it is of minimum weight, which equals 2, since a simple inspection yields that every other cover has a weight larger than 2. Since the cover has four edges in it, we have <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = (0 + 0 + 1/6 + 1/6)/4 = 1/12. If we use the raw RF values, then <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = (0 + 0 + 1 + 1)/4 = 1/2.</p>", "<title>Cluster-based comparison</title>", "<p>Let <italic>C</italic>₁= (<italic>N</italic>₁) and <italic>C</italic>₂= (<italic>N</italic>₂) be the two sets of all clusters induced by the two networks. We define the measure based on these two sets to be</p>", "<p></p>", "<p>The rationale behind this measure is that it is the sum of the ratios of clusters present in one but not both networks. The cluster-based measure was first introduced by Nakhleh <italic>et al</italic>. [##UREF##9##29##]. The sets <italic>C</italic>₁= (<italic>N</italic>₁) and <italic>C</italic>₂= (<italic>N</italic>₂) of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##0##1##, with |<italic>C</italic>₁| = |<italic>C</italic>₂| = 14. Since |<italic>C</italic>₁- <italic>C</italic>₂| = |<italic>C</italic>₂- <italic>C</italic>₁| = 2 (the two highlighted clusters in Table ##TAB##0##1##), we have <italic>m</italic>^{<italic>cluster</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = 1/7. A similar weighting scheme to that described in the previous section can be used to incorporate the fraction of trees in which a cluster appears into the measure calculation.</p>", "<title>Tripartition-based comparison</title>", "<p>Let <italic>θ</italic>₁= <italic>θ</italic>(<italic>N</italic>₁) and <italic>θ</italic>₂= <italic>θ</italic>(<italic>N</italic>₂) be the two sets of all tripartitions induced by the two networks. We define the measure based on these two sets to be</p>", "<p></p>", "<p>This measure views the two networks in terms of the sets of edges they define (where an edge is in a 1-1 correspondence with a tripartition) and computes the sum of the ratios of edges present in one but not both networks. The tripartition-based measure was devised by Moret <italic>et al</italic>. [##REF##17048405##19##]. The sets <italic>θ</italic>₁= <italic>θ</italic>(<italic>N</italic>₁) and <italic>θ</italic>₂= <italic>θ</italic>(<italic>N</italic>₂) of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##1##2##, with |<italic>θ</italic>₁| = |<italic>θ</italic>₂| = 12. Since |<italic>θ</italic>₁- <italic>θ</italic>₂| = |<italic>θ</italic>₂- <italic>θ</italic>₁| = 1 (the highlighted tripartition in Table ##TAB##1##2##), we have <italic>m</italic>^{<italic>tripartition</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = 1/12.</p>", "<title>Which measure to use?</title>", "<p>Several distance measures, such as the Robinson-Fould measure and the Subtree Prune and Regraft (SPR) distance, have been introduced over the years to quantify the difference between the topologies of a pair of phylogenetic trees; e.g., see [##UREF##5##25##,##UREF##6##26##] for description of many of these measures. Even though these measures may compute different distance values on the same pair of trees, there has been no consensus as to which measure should be used in general [##UREF##10##30##]. It may be the case that the Robinson-Foulds measure is more commonly used than the others, but this may be a mere reflection of its very low time requirements as compared to the other, more compute-intensive, measures.</p>", "<p>Regarding the three measures for comparing networks, a scenario analogous to that in phylogenetic trees arises here: each measure gives a different quantification of the dissimilarity between two networks based on one of the three ways to characterize a given network. As shown in the examples above, some or all of these measures may compute the same value for a given pair of networks, but that may not always be the case. Tree-based comparison of networks can be viewed as a method to quantify how similar, or dissimilar, two networks are in terms of their quality as a summary of a collection of trees. In some cases, even though two networks \"look different,\" they may be identical in terms of the trees they induce – this is the issue of indistinguishability of networks from a collection of trees that Nakhleh and colleagues discussed in [##REF##17048405##19##]. In such a case, using the tree-based comparison, or equivalently the cluster-based comparison, is most appropriate. However, if the similarity/dissimilarity of two networks means something close to an <italic>isomorphism</italic>, then the tripartition-based measure is more appropriate. However, it is important to note that none of the three measures described here is a metric on the general space of all evolutionary networks labeled by a given set of taxa.</p>", "<p>A practical distinction among the three measures can be derived based on the methods used to infer the evolutionary history of the set of species under study. Methods such as SplitsTree [##REF##9520503##23##] and NeighborNet [##UREF##4##24##] represent the evolutionary history as a set of splits, or clusters, hence making it more natural to use cluster-based comparison to study their performance. Methods such as RIATA-HGT [##UREF##1##16##] and LatTrans [##UREF##0##14##] compute evolutionary networks that are rooted, directed, acylic graphs, where internal nodes have an evolutionary implication in terms of ancestry. For these two methods, all three measures are appropriate. When the evolutionary history of a set of species is represented as a collection of its constituent gene trees, the tree-based measure is most appropriate.</p>", "<p>Finally, a clear distinction can be made among the methods in terms of computational requirements. In their current implementations, the tripartition-based measure is very fast in practice, taking time that is polynomial in the size of the two networks. On the other hand, the tree- and cluster-based measures are much slower, taking time that is exponential in the number of network nodes in the two networks (since these measures compute explicitly all trees inside each of the two networks). In light of recent complexity results that we obtained [##UREF##11##31##], it is very likely that no polynomial-time algorithms exist for computing the tree- and cluster-based measures in general.</p>", "<title>Parsimony of evolutionary networks</title>", "<p>Nakhleh and colleagues have recently formalized a maximum parsimony (MP) criterion for evolutionary networks [##REF##16447967##32##] and demonstrated its utility in reconstructing evolutionary networks on both biological and synthetic data sets [##REF##17068107##33##]. In this section, we describe a PhyloNet utility that allows for comparing two evolutionary networks in terms of their fitness to the evolution of a sequence data set, based on the MP criterion. We first begin with a brief review of the MP criterion, based on the exposition in [##REF##16447967##32##].</p>", "<p>The relationship between an evolutionary network and its constituent trees, as described in the background section, is the basis for the MP extension to evolutionary networks.</p>", "<p><bold>Definition 1 </bold><italic>The Hamming distance between two equal-length sequences x and y, denoted by H</italic>(<italic>x</italic>, <italic>y</italic>)<italic>, is the number of positions j such that x</italic>_{<italic>j </italic>}≠ <italic>y</italic>_{<italic>j</italic>}.</p>", "<p>Given a fully-labeled tree <italic>T</italic>, i.e., a tree in which each node <italic>v </italic>is labeled by a sequence <italic>s</italic>_{<italic>v </italic>}over some alphabet Σ, we define the Hamming distance of an edge <italic>e </italic>∈ <italic>E</italic>(<italic>T</italic>), denoted by <italic>H</italic>(<italic>e</italic>), to be <italic>H</italic>(<italic>s</italic>_{<italic>u</italic>}, <italic>s</italic>_{<italic>v</italic>}), where <italic>u </italic>and <italic>v </italic>are the two endpoints of <italic>e</italic>. We now define the parsimony score of a tree <italic>T</italic>.</p>", "<p><bold>Definition 2 </bold><italic>The parsimony score of a fully-labeled tree T, is Σ</italic>_{<italic>e </italic>∈ <italic>E</italic>(<italic>T</italic>)}<italic>H</italic>(<italic>e</italic>)<italic>. Given a set S of sequences, a maximum parsimony tree for S is a tree leaf-labeled by S and assigned labels for the internal nodes, of minimum parsimony score</italic>.</p>", "<p>The parsimony definitions can be extended in a straightforward manner to incorporate different site substitution matrices, where different substitutions do not necessarily contribute equally to the parsimony score, by simply modifying the formula <italic>H</italic>(<italic>x</italic>, <italic>y</italic>) to reflect the weights. Let Σ be the set of states that the two sequences <italic>x </italic>and <italic>y </italic>can take (e.g., Σ = {<italic>A</italic>, <italic>C</italic>, <italic>T</italic>, <italic>G</italic>} for DNA sequences), and <italic>W </italic>the site substitution matrix such that <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] is the weight of replacing <italic>σ</italic>₁by <italic>σ</italic>₂, for every <italic>σ</italic>₁, <italic>σ</italic>₂∈ Σ. In particular, the <italic>identity </italic>site substitution matrix satisfies <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] = 0 when <italic>σ</italic>₁= <italic>σ</italic>₂, and <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] = 1 otherwise. The weighted Hamming distance between two sequence is <italic>H</italic>(<italic>x</italic>, <italic>y</italic>) = Σ_{1 ≤ <italic>i </italic>≤ <italic>k </italic>}<italic>W</italic>(<italic>x</italic>_{<italic>i</italic>}, <italic>y</italic>_{<italic>i</italic>}), where <italic>k </italic>is the length of the sequences <italic>x </italic>and <italic>y</italic>. The rest of the definitions are identical to the simple Hamming distance case. As described above, the evolutionary history of a single (non-recombining) gene is modeled by one of the trees contained inside the evolutionary network of the species containing that gene. Therefore the evolutionary history of a site <italic>s </italic>is also modeled by a tree contained inside the evolutionary network. A natural way to extend the tree-based parsimony score to fit a dataset that evolved on a network is to define the parsimony score for each site as the minimum parsimony score of that site over all trees contained inside the network.</p>", "<p><bold>Definition 3 </bold><italic>(</italic>[##REF##16447967##32##]<italic>) The parsimony score of a network N leaf-labeled by a set S of taxa, is</italic></p>", "<p></p>", "<p><italic>where TCost</italic>(<italic>T</italic>, <italic>s</italic>_{<italic>i</italic>}) <italic>is the parsimony score of site s</italic>_{<italic>i </italic>}<italic>on tree T</italic>.</p>", "<p>Notice that as usually large segments of DNA, rather than single sites, evolve together, Definition 3 can be extended easily to reflect this fact, by partitioning the sequences <italic>S </italic>into non-overlapping blocks <italic>b</italic>_{<italic>i </italic>}of sites, rather than sites <italic>s</italic>_{<italic>i</italic>}, and replacing <italic>s</italic>_{<italic>i </italic>}by <italic>b</italic>_{<italic>i </italic>}in Definition 3. This extension may be very significant if, for example, the evolutionary history of a gene includes some recombination events, and hence that evolutionary history is not a single tree. In this case, the recombination breakpoint can be detected by experimenting with different block sizes.</p>", "<p>The MP utility in PhyloNet allows the user to specify two evolutionary networks (either or both of which can be a tree) <italic>N</italic>₁and <italic>N</italic>₂and a sequence data set <italic>S</italic>, and computes the parsimony scores <italic>NCost</italic>(<italic>N</italic>₁, <italic>S</italic>) and <italic>NCost</italic>(<italic>N</italic>₂, <italic>S</italic>). The user can then compare the two scores and evaluate the fitness of the networks to the data set <italic>S </italic>based on the difference in the scores. Further, the utility allows the user, for example, to evaluate the significance of each network edge in a network <italic>N </italic>by comparing the parsimony scores of two different versions of <italic>N </italic>that contain different subsets of the network edges in <italic>N</italic>.</p>", "<title>Reconstructing evolutionary networks from species/gene trees</title>", "<p>Assuming incongruence among gene and species trees is the result of HGT events only, the <italic>Phylogeny-based HGT Reconstruction Problem</italic>, or HGT Reconstruction Problem for short, is defined as follows:</p>", "<p><bold>Problem 1 </bold><italic>(HGT Reconstruction Problem)</italic></p>", "<p><bold>Input: </bold><italic>A species tree ST and a set </italic> = {<italic>T</italic>₁,..., <italic>T</italic>_{<italic>p</italic>}}<italic>of gene trees</italic>.</p>", "<p><bold>Output: </bold><italic>An evolutionary network N, obtained by adding a minimal set of edges Ξ to T, such that N contains every tree T</italic>_{<italic>i </italic>}∈ </p>", "<p>The minimization criterion is a reflection of Occam's razor: in the absence of any additional biological knowledge, HGT events should be used sparingly to explain data features otherwise explainable under a tree model. The problem of finding a minimum-cardinality set of HGT events whose occurrence on species tree <italic>ST </italic>would give rise to the gene trees in set is computationally hard [##UREF##12##34##]. In [##UREF##1##16##], Nakhleh <italic>et al</italic>. introduced an accurate, polynomial-time heuristic, RIATA-HGT, for solving the HGT Reconstruction Problem for a pair of species and gene trees (in other words, RIATA-HGT currently handles the case where || = 1). In a nutshell, the method computes the maximum agreement subtree [##UREF##13##35##] of the species tree and each of the gene trees, and adds HGT edges to connect all subtrees that do not appear in the maximum agreement subtree. Theoretically, RIATA-HGT may not compute the minimum-cardinality set of HGT events; nonetheless, experimental results show very good empirical performance on synthetic as well as biological data [##UREF##1##16##].</p>", "<title>Computing multiple solutions and the graphical output</title>", "<p>RIATA-HGT was designed originally to compute a single solution to the problem, and was mainly aimed at binary trees. Later, Than and Nakhleh [##UREF##2##17##] extended the method to compute multiple solutions and to handle non-binary trees. These two features are very significant: the former allows biologists to explore multiple potential HGT scenarios, whereas the latter allows for analyzing trees in which some edges were contracted due to inaccuracies (see [##UREF##14##36##] for example). We have conducted an experimental study to compare the performance of RIATA-HGT with LatTrans [##REF##17572027##18##]. Although RIATA-HGT and LatTrans [##UREF##0##14##] have almost the same performance in terms of the number of HGT solutions and the solution size, the former runs much faster than the latter.</p>", "<p>For a compact representation of multiple solutions, we introduce four terms:</p>", "<p>• An <italic>event</italic>: this is a single HGT edge, written in the form of <italic>X </italic>→ <italic>Y</italic>, where <italic>X </italic>and <italic>Y </italic>are two nodes in the species tree.</p>", "<p>• A <italic>subsolution</italic>: this is an <italic>atomic </italic>set of events, which forms a part of an overall solution. In other words, either all or none of the events of a subsolution are taken in a solution.</p>", "<p>• A <italic>component</italic>: a set of components and/or subsolutions. Two components at the same level of decomposition are independent, in that an element of each component is needed to form a solution.</p>", "<p>• A <italic>solution</italic>: the union of a single element from each component at the highest level.</p>", "<p>To illustrate these concepts, consider species tree (((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>), (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>))) and the gene tree (((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>), ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>)). Observe, that each HGT event required to reconcile the two trees has both endpoints in the subtree ((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>) or both endpoints in the subtree (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>)), and no HGT event has endpoints in both subtrees. In this case, RIATA-HGT divides the pair of trees into two pairs:</p>", "<p>• Pair 1: ((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>) and ((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>)</p>", "<p>• Pair 2: (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>)) and ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>),</p>", "<p>and solves the HGT Reconstruction Problem on each of the two pairs <italic>independently</italic>. The set of solutions of each pair is a component. Notice that for each pair there are three possible ways to reconcile them; each such way is a called a subsolution. Each subsolution is a set of events, which in this case is only one event. Figure ##FIG##6##7(a)## shows the screen captures of two graphical outputs that correspond to two solutions on this pair of trees. Notice that if a component can be further divided into independent components, RIATA-HGT would do so, which will result in components at different levels, with the largest components being at the highest level.</p>", "<p>The compact representation of RIATA-HGT's output in terms of subsolutions and components is especially helpful when the number of solutions is large. RIATA-HGT also has an option to display all complete solutions. RIATA-HGT enumerates all complete solutions that are compactly represented as described in the preceding paragraphs. Each solution, which is a set of HGT events, along with the species tree defines an evolutionary network, which RIATA-HGT displays in the eNewick format. For example, for the trees (((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>), (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>))) and (((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>), ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>)), RIATA-HGT outputs 9 different networks in the eNewick format, if RIATA-HGT's option for displaying complete solutions is on. Figure ##FIG##6##7(b)## shows the corresponding eNewick representations.</p>", "<p>From the multiple comparisons between a species and a set of trees, RIATA-HGT offers a (strict) consensus network. For each pair of species tree and gene tree, RIATA-HGT computes a set of HGT events for reconciling them. To obtain the consensus network, RIATA-HGT retains only HGT events that appear in every set of solutions for every pair of species tree and gene tree. Those events are then added to the species to build the consensus network.</p>", "<p>We note here that while offering a simple summary of solutions, this way of computing consensus networks may not be appropriate in general; work is under way to address this issue more properly.</p>", "<p>Finally, RIATA-HGT may report '[time violation?]' next to an inferred HGT <italic>X </italic>→ <italic>Y</italic>. If this is the case, this indicates that node <italic>X </italic>lies on the path from <italic>Y </italic>to the root of the species tree. Theoretically, this indicates that two nodes that do not co-exist in time, <italic>X </italic>and <italic>Y </italic>in this case, shared genetic material, and hence the warning of 'time violation.' However, this may be the case simply due to incomplete taxon sampling, as discussed in [##REF##17048405##19##]. Therefore, the warning is issued in this case so as to alert that user that this inferred HGT edge is worth further inspection.</p>", "<title>Assessing the support of HGT edges</title>", "<p>In [##UREF##15##37##] we proposed a method for assessing the support of HGT edges. Roughly speaking, the support value of HGT edge <italic>X </italic>→ <italic>Y </italic>in the species tree, where <italic>Y</italic>'is the sibling of <italic>Y</italic>, is derived from the bootstrap values of the gene tree branches that separate the clade under <italic>Y </italic>from the clade under <italic>Y</italic>'. The rationale behind the idea is that if <italic>Y</italic>' and <italic>Y </italic>are well separated in the gene trees (i.e., some branches in the path from <italic>Y </italic>to <italic>Y</italic>' have high bootstrap values), HGT is necessary to move <italic>Y </italic>away from <italic>Y</italic>'). For example, the support of HGT edge <italic>X </italic>→ <italic>Y </italic>in Figure ##FIG##7##8(a)## is calculated based on the bootstrap values of the branches separating <italic>B </italic>from <italic>A </italic>in the gene tree, and it is 80 (which is the maximum bootstrap value of all edges on the path separating <italic>A </italic>and <italic>B </italic>in the gene tree). More technical details can be found in [##UREF##15##37##].</p>", "<p>Than <italic>et al</italic>. [##UREF##15##37##] have studied the reliability of this method for assessing the support of HGT edges on various data sets from [##REF##15598737##38##]. In this paper, we illustrate the output of RIATA-HGT on a pair of species/gene trees from [##REF##15598737##38##], as shown in Figure ##FIG##8##9##. The output of RIATA-HGT on this pair of trees is shown in Figure ##FIG##9##10##. RIATA-HGT computed four solutions, each of which has nine HGT edges. To allow for a compact representation of the solutions, they are divided into two components (which are computed automatically by RIATA-HGT), and each solution is formed by taking one subsolution from each component. HGT edges for the solutions are divided into two components, which means that a complete solution is formed by taking one solution from each component. Each component is labeled by the name of the internal node that is the root of the clade corresponding to that component. In the case of the solutions presented in Figure ##FIG##9##10##, each solution contains nine HGT edges, eight of which form a single subsolution in Component I18 and the ninth is the only edge in the only subsolution in Component I8. The value in parentheses next to each HGT edge is its support value computed from the bootstrap values of the gene tree branches (Figure ##FIG##8##9(b)##). Bergthorsson <italic>et. al</italic>. [##REF##15598737##38##] reported three HGTs involving <italic>Amborella</italic>: one HGT with donor being a species in the <italic>Moss </italic>group (species <italic>Brachythecium</italic>, <italic>Hypnum</italic>, and <italic>Thuidium</italic>, under the internal node I14 in the species tree) and the other two with donors being species in the <italic>Eudicot </italic>group (species <italic>Arabidopsis</italic>, <italic>Beta</italic>, <italic>Brassica</italic>, <italic>Daucus</italic>, <italic>Petunia</italic>, and <italic>Oenothera</italic>, under the internal node I5 in the species tree). The HGT from <italic>Moss </italic>has high SH support value [##UREF##16##39##]. RIATA-HGT finds this event, I14 → <italic>Amborella_H_M</italic>, with bootstrap value 98.0%. The other two HGT events from <italic>Eudicot </italic>do not have significant SH support values. RIATA-HGT also finds these events, I5 → <italic>Amborella_H_E1 </italic>and I2 → <italic>Amborella_H_E2</italic>. However, their support values are 73.0%, much smaller than that of the event from <italic>Moss</italic>. In addition to these three HGT edges, RIATA-HGT identified six more edges, four out of which had support values smaller than 50.0% (RIATA-HGT does not display support values that are smaller than 50.0%). The HGT edge from Component I8, which is shared among all four solutions, has support value of 100.0%. This edge was not reported in [##REF##15598737##38##]. A similar situation arises with the HGT edge I5 → I8, which is part of the three solutions that contain subsolutions 1, 3, and 4 from Component I18: the HGT edge has support of 100.0%, and was not reported in [##REF##15598737##38##], which may be a reflection that the authors focused only on HGT events involving <italic>Amborella</italic>. The ninth HGT edge in Subsolution2 of Component I18 has support value smaller than 50.0%.</p>", "<title>Other utilities</title>", "<p>As evident from the description of the methods above, there are fundamental correlations between phylogenetic trees and networks. Hence, many of the evolutionary network utilities use functionalities from the phylogenetic trees domain, which we have implemented and provide as standalone tools in PhyloNet:</p>", "<p>• A tool for computing the maximum agreement subtree (MAST) of a pair of trees using the algorithm of Steel and Warnow [##UREF##13##35##]. We also extended the algorithm so that it computes <italic>all </italic>MASTs of a pair of tree, and this feature is implemented as well.</p>", "<p>• A tool for computing the Robinson-Foulds distance measure between two phylogenetic trees [##UREF##7##27##].</p>", "<p>• A tool for computing the <italic>last common ancestor </italic>(lca) of a set of nodes in a phylogenetic tree.</p>", "<p>Additionally, PhyloNet provides an implementation of the parsimony-based method RECOMP of Ruths and Nakhleh [##REF##18048130##40##,##UREF##17##41##] for detecting interspecific recombination in a sequence alignment.</p>" ]

[ "<title>Results and discussion</title>", "<title>The evolutionary network model</title>", "<p>In this paper, we assume the \"evolutionary network\" model, which was formulated independently by Moret <italic>et al</italic>. [##REF##17048405##19##] and Baroni <italic>et al</italic>. [##UREF##3##20##]. We now describe the model as well as some basic definitions and notations that we will use later.</p>", "<p>Let <italic>T </italic>= (<italic>V</italic>, <italic>E</italic>) be a tree, where <italic>V </italic>and <italic>E </italic>are the <italic>tree nodes </italic>and <italic>tree edges</italic>, respectively, and let <italic>L</italic>(<italic>T</italic>) denote the tree's leaf set. Further, let <italic>χ </italic>be a set of taxa (organisms). Then, <italic>T </italic>is a <italic>phylogenetic tree </italic>over <italic>χ </italic>if there is a bijection between <italic>χ </italic>and <italic>L</italic>(<italic>T</italic>). Henceforth, we will identify the taxa set with the leaves they are mapped to, and let [<italic>n</italic>] = {1,..., <italic>n</italic>} denote the set of leaf-labels. A tree <italic>T </italic>is said to be <italic>rooted </italic>if the set of edges <italic>E </italic>is directed and there is a single node <italic>r </italic>∈ <italic>V </italic>with in-degree 0. Let <italic>T </italic>be a phylogenetic tree on set <italic>χ </italic>of taxa, and let <italic>χ</italic>' ⊆ <italic>χ </italic>be a subset of taxa; then, we denote by <italic>T</italic>|<italic>χ</italic>' the subtree with minimum number of nodes and edges that spans the leaves in <italic>χ</italic>' (in other words, <italic>T</italic>|<italic>χ</italic>' is the tree <italic>T </italic>restricted to subset <italic>χ</italic>' of its leaves).</p>", "<p>An evolutionary (phylogenetic) network <italic>N </italic>= (<italic>V</italic>, <italic>E</italic>) over the set <italic>χ </italic>of taxa is a rooted, directed, acyclic graph such that there is a bijection between <italic>χ </italic>and the set <italic>L</italic>(<italic>N</italic>) of the network's leaves (see Figure ##FIG##1##2##). The set <italic>V </italic>is partitioned into two sets: <italic>V</italic>_{<italic>T</italic>}, the set of <italic>tree nodes</italic>, which are the nodes with in-degree smaller than two, and <italic>V</italic>_{<italic>N</italic>}, the set of <italic>network nodes</italic>, which are the nodes with in-degree greater than or equal to two. Similarly, the set <italic>E </italic>is partitioned into two sets: <italic>E</italic>_{<italic>T</italic>}, the set of <italic>tree edges</italic>, which are edges incident into tree nodes, and <italic>E</italic>_{<italic>N</italic>}, the set of <italic>network edges</italic>, which are the edges incident into network nodes.</p>", "<p>For two nodes <italic>u </italic>and <italic>v </italic>in directed graph <italic>G</italic>, we say that <italic>v </italic>is reachable from <italic>u</italic>, denoted by if there exists a directed path from <italic>u </italic>to <italic>v </italic>in the tree <italic>G</italic>. For three nodes <italic>u</italic>, <italic>v </italic>and <italic>x </italic>in directed graph <italic>G</italic>, we write if all directed paths from <italic>u </italic>to <italic>v </italic>go through node <italic>x</italic>; if no directed paths from <italic>u </italic>to <italic>v </italic>go through node <italic>x</italic>; and if at least one directed path from <italic>u </italic>to <italic>v </italic>goes through node <italic>x </italic>and at least one directed path from <italic>u </italic>to <italic>v </italic>does not go through node <italic>x</italic>. For example, in network <italic>N</italic>₁in Figure ##FIG##1##2##, rooted at node r₁, we have , , and .</p>", "<title>Evolutionary network representation</title>", "<p>The Newick format for representing and storing phylogenetic trees was adopted in 1986 [##REF##3024605##21##], and it has been the standard for almost all phylogeny software packages ever since. This format captures an elegant correspondence between leaf-labeled trees and matched parentheses, where the leaves are represented by their names and the internal nodes by a matched pair of parentheses that contains a list of the Newick representation of all its children. Shown in Figure ##FIG##2##3## are three trees along with their representations in the Newick format.</p>", "<p>Existing phylogenetic network software tools store these networks as adjacency lists of their underlying graphs, which are usually very large and necessitate translation of representations among the different tools. Morin and Moret [##REF##16717070##22##] proposed a modified version of the Newick format for representing such networks. In their format, network nodes are represented by nodes labeled with #H, and those nodes are considered as two separate nodes in the normal Newick format for trees. See Figure ##FIG##3##4## for an example. We have independently proposed a new method of <italic>tree decomposition </italic>of evolutionary networks, which provides the basis for a new format, <italic>extended Newick </italic>(or eNewick for short), and used it as a compact representation of evolutionary networks. The idea in our method is to break the network into a set of trees, and then represent the network as a collection of Newick representations of those trees. Since the eNewick format is nothing but a collection of trees in the Newick format, it follows that eNewick can represent unrooted networks. However, both in this paper as well as in the PhyloNet utilities, rooting is assumed, since different ways of rooting the same evolutionary networks may imply different evolutionary relationships.</p>", "<p>Let <italic>N </italic>= (<italic>V </italic>= (<italic>V</italic>_{<italic>N </italic>}∪ <italic>V</italic>_{<italic>T</italic>}); <italic>E</italic>) be an evolutionary network, with |<italic>V</italic>_{<italic>N</italic>}| = ℓ. We create a forest of ℓ trees as follows.</p>", "<p>• For every <italic>u</italic>_{<italic>i </italic>}∈ <italic>V</italic>_{<italic>N</italic>}</p>", "<p>- Compute the set <italic>V</italic>_{<italic>i </italic>}= {<italic>v </italic>∈ <italic>V </italic>: (<italic>v</italic>, <italic>u</italic>_{<italic>i</italic>}) ∈ <italic>E</italic>} of <italic>u</italic>_{<italic>i</italic>}'s parents;</p>", "<p>- Create <italic>k </italic>new leaves, all labeled with <italic>x</italic>_{<italic>i </italic>}({<italic>x</italic>_{<italic>i</italic>}} ∩ <italic>L</italic>(<italic>N</italic>) = ∅);</p>", "<p>- Delete from <italic>V </italic>the set of all edges in <italic>V</italic>_{<italic>i </italic>}× {<italic>u</italic>_{<italic>i</italic>}};</p>", "<p>- Add to <italic>V </italic>the set of edges <italic>V</italic>_{<italic>i </italic>}× {<italic>x</italic>_{<italic>i</italic>}};</p>", "<p>- Assign <italic>x</italic>_{<italic>i </italic>}as the name of the tree rooted at node <italic>u</italic>_{<italic>i</italic>};</p>", "<p>The result is a forest of trees = {<italic>t</italic>₁,..., <italic>t</italic>_ℓ} such that (1) |<italic>L</italic>(<italic>t</italic>_{<italic>i</italic>})| ≥ 1 for every 1 ≤ <italic>i </italic>≤ ℓ, (2) and (3) <italic>L</italic>(<italic>t</italic>_{<italic>i</italic>}) ∩ <italic>L</italic>(<italic>t</italic>_{<italic>j</italic>}) = ∅ for every 1 ≤ <italic>i</italic>, <italic>j </italic>≤ ℓ and <italic>i </italic>≠ <italic>j</italic>. We call the <italic>tree decomposition </italic>of <italic>N</italic>. Then, the eNewick representation of <italic>N </italic>is the ℓ-tuple ⟨<italic>n</italic>(<italic>t</italic>₁);...; <italic>n</italic>(<italic>t</italic>_ℓ)⟩, where <italic>n</italic>(<italic>t</italic>_{<italic>i</italic>}) is the Newick representation of tree <italic>t</italic>_{<italic>i</italic>}. Figure ##FIG##2##3## shows the tree decomposition and eNewick representation of the network <italic>N</italic>₁in Figure ##FIG##1##2##.</p>", "<p>In the case of modeling networks with horizontal gene transfer events, it is often very helpful to the biologist to know what the species tree is and what the additional set of HGT events are. Such information is \"lost\" in an eNewick representation, unless the representation is extended further to keep a record of the \"species tree parent\" of each network node. Therefore, in this case (which is the output of RIATA-HGT) we opt for the format of a species tree <italic>T</italic>, in Newick format, followed by a list of the HGT edges, each written as <italic>X </italic>→ <italic>Y</italic>, where <italic>X </italic>and <italic>Y </italic>are two nodes in <italic>T</italic>.</p>", "<title>Evolutionary network characterization</title>", "<p>As we described in the background section, an evolutionary network induces, or contains, a set of trees. We now formalize this concept and characterize networks in terms of the trees they induce. A tree <italic>T </italic>is induced by a network <italic>N </italic>if <italic>T </italic>is obtained from <italic>N </italic>as follows: (1) for each node of in-degree larger than one, remove all but one of the network edges incident into it, and (2) for every node of in-degree and out-degree 1, and whose parent is <italic>u </italic>and child is <italic>v</italic>, remove the two edges incident with it, and add an edge from <italic>u </italic>to <italic>v</italic>. We denote by (<italic>N</italic>) the set of all trees induced by <italic>N</italic>. Figure ##FIG##4##5## shows the sets (<italic>N</italic>₁) and (<italic>N</italic>₂) for the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2##. It is important to note that this set of trees is completely different from the set of trees obtained by the tree decomposition we introduced to facilitate the eNewick format. An evolutionary network <italic>N </italic>with <italic>V</italic>_{<italic>N </italic>}= {<italic>v</italic>₁,..., <italic>v</italic>_ℓ}, such that <italic>indegree</italic>(<italic>v</italic>_{<italic>i</italic>}) = <italic>ρ</italic>_{<italic>i</italic>}, induces <italic>m </italic>trees, where </p>", "<p>Given an evolutionary network <italic>N</italic>, the set (<italic>N</italic>) is unique. Further, this set informs about the possible gene histories that the network reconciles.</p>", "<p>In addition to characterizing evolutionary networks by the set of trees they induce, we consider a <italic>cluster</italic>-based characterization. This view of evolutionary networks is very important for understanding the relationships among the \"evolutionary perspective\" of evolutionary networks and the \"cluster, or splits, perspective\", which is adopted in various methods [##REF##9520503##23##,##UREF##4##24##]. Let <italic>T </italic>= (<italic>V</italic>, <italic>E</italic>) be a phylogenetic tree on set <italic>χ </italic>of taxa and rooted at node <italic>r</italic>. Each edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) ∈ <italic>E </italic>induces a <italic>cluster </italic>of taxa, denoted <italic>c</italic>_{<italic>e</italic>}, which is the set . The (nontrivial) clusters of tree <italic>T </italic>is the set (<italic>T</italic>) = {<italic>c</italic>_{<italic>e </italic>}: <italic>e </italic>is an internal edge in <italic>E</italic>}. The topology of a tree is a compact graphical representation of its clusters, where the root of the clade that corresponds to cluster <italic>c</italic>_{<italic>e</italic>'}lies on the path from the root of the tree to the root of the clade that corresponds to cluster <italic>c</italic>_{<italic>e </italic>}if and only if <italic>c</italic>_{<italic>e </italic>}⊆ <italic>c</italic>_{<italic>e</italic>'}. Hence, clusters play an important role in phylogenetic tree characterization and reconstruction. A straightforward way to extend this concept to evolutionary networks is to define the set of clusters of evolutionary network <italic>N </italic>as . The clusters of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##0##1##.</p>", "<p>In this form of cluster-based characterization, clusters are unweighted; equivalently, all clusters are weighted equally. One option of weighting the clusters is by considering the fraction of trees in which it appears. In other words, the weight of a cluster <italic>c</italic>_{<italic>e </italic>}can be computed as</p>", "<p></p>", "<p>This weighting scheme informs not only about the clusters of taxa that the network represents, but also how many gene trees in the input share each cluster. It is important to note here that this weighting of a cluster should not be confused with, or used in lieu of, support values of clusters, since a cluster may appear in only one gene tree and have a high support (e.g., by having a high bootstrap value on the edge that defines it) whereas a poorly supported cluster may appear in several trees.</p>", "<p>Nakhleh and colleagues have recently introduced a new characterization of evolutionary networks based on the <italic>tripartitions </italic>of their edges [##REF##17048405##19##]. Let <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) be an edge in an evolutionary network on set <italic>χ </italic>of taxa and rooted at node <italic>r</italic>. We define three disjoint sets <italic>A</italic>_{<italic>e </italic>}= , <italic>B</italic>_{<italic>e </italic>}= , and <italic>C</italic>_{<italic>e </italic>}= . Then, the tripartition induced by edge <italic>e</italic>, denoted <italic>θ</italic>_{<italic>e</italic>}, is the triplet ⟨<italic>A</italic>_{<italic>e</italic>}; <italic>B</italic>_{<italic>e</italic>}; <italic>C</italic>_{<italic>e</italic>}⟩. Roughly speaking, the tripartition induced by an edge is the three sets of taxa reachable from the root only through that edge (<italic>A</italic>_{<italic>e</italic>}), reachable through that edge but not exclusively (<italic>B</italic>_{<italic>e</italic>}), and not reachable through that edge (<italic>C</italic>_{<italic>e</italic>}). The set of (nontrivial) tripartitions induced by a evolutionary network <italic>N</italic>, denoted by <italic>θ</italic>(<italic>N</italic>), is {<italic>θ</italic>_{<italic>e </italic>}: <italic>e </italic>is an internal edge in <italic>E</italic>}. The tripartitions of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##1##2##.</p>", "<p>Tripartition-based characterization of an evolutionary network helps to identify clades across which no genetic transfer occurred. If <italic>A</italic>_{<italic>e </italic>}= <italic>X </italic>and <italic>B</italic>_{<italic>e </italic>}= ∅ for an edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>), this implies that the clade rooted at node <italic>v </italic>has set <italic>X </italic>of leaves, and there does not exist any exchange or transfer of genetic material between any organism in <italic>X </italic>and another organism that is not in <italic>X</italic>. Equivalently, an evolutionary network can be partitioned into a collection {<italic>N</italic>₁, <italic>N</italic>₂,..., <italic>N</italic>_{<italic>k</italic>}} of evolutionary networks that result from <italic>N </italic>by deleting every edge <italic>e </italic>for which <italic>B</italic>_{<italic>e </italic>}= ∅. Such a partition informs about the \"locality\" of reticulation events: each event in <italic>N </italic>is local to one of the <italic>k </italic>components in {<italic>N</italic>₁, <italic>N</italic>₂,..., <italic>N</italic>_{<italic>k</italic>}}. Further, this partition implies that each of the trees in (<italic>N</italic>) has <italic>k </italic>clades that have the sets {<italic>L</italic>(<italic>N</italic>₁), <italic>L</italic>(<italic>N</italic>₂),..., <italic>L</italic>(<italic>N</italic>_{<italic>k</italic>})} of leaves.</p>", "<title>Evolutionary network comparison</title>", "<p>Researchers are often interested in quantifying the similarities and differences between two phylogenies reconstructed either from two different sources of data or from two different reconstruction methods. Such a quantification provides insights into agreements and disagreements among analyses, confidence values for different parts of the phylogenies, and metrics for comparing the performance of phylogenetic reconstruction methods. In the context of phylogenetic trees, this quantification is most commonly done based on one of two criteria:</p>", "<p>• <italic>Topological differences</italic>. The topologies, or shapes, of two phylogenetic trees are compared, and their differences are quantified. Several measures have been introduced to quantify topological differences and similarities between a pair of trees, such as the Robinson-Foulds measure and the SPR distance; see [##UREF##5##25##,##UREF##6##26##] for a description of several such measures.</p>", "<p>• <italic>Fitness to sequence evolution</italic>. When two phylogenies are reconstructed from the same sequence data set, it is common to compare them in terms of how well they model the evolution of the sequences. The most commonly used criteria for measuring such fitness are maximum parsimony, maximum likelihood, and the Bayesian posterior probability; see [##UREF##5##25##] for a detailed discussion of all three criteria.</p>", "<p>In this section, we report on the capabilities in PhyloNet for comparing two evolutionary networks in terms of their topological differences and similarities, as well as in terms of their fitness to sequence evolution based on the maximum parsimony criterion.</p>", "<p>For quantifying the dissimilarity between two evolutionary network topologies <italic>N</italic>₁and <italic>N</italic>₂, we want a measure <italic>m</italic>(·,·) that satisfies three conditions:</p>", "<p><italic>Identity</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) = 0 if and only if <italic>N</italic>₁and <italic>N</italic>₂are <italic>equivalent</italic>;</p>", "<p><italic>Symmetry</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) = <italic>m</italic>(<italic>N</italic>₂, <italic>N</italic>₁); and</p>", "<p><italic>Triangle inequality</italic>: <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₃) + <italic>m</italic>(<italic>N</italic>₃, <italic>N</italic>₂) ≥ <italic>m</italic>(<italic>N</italic>₁, <italic>N</italic>₂) for any evolutionary network <italic>N</italic>₃.</p>", "<p>This issue of evolutionary network equivalence was discussed in [##REF##17048405##19##]. The three characterizations of evolutionary networks that we described above induce three measures which we now define. Let <italic>N</italic>₁and <italic>N</italic>₂be two evolutionary networks on the same set <italic>X </italic>of leaves; we define the three measures as follows.</p>", "<title>Tree-based comparison</title>", "<p>Let (<italic>N</italic>₁) and (<italic>N</italic>₂) be the two sets of all trees induced by the two networks, and let <italic>d</italic>(·,·) be a distance metric on trees (see [##UREF##6##26##] for examples of such metrics). The idea is to compare the two networks based on how similar their corresponding sets of trees are. We formalize this as follows. Construct a weighted complete bipartite graph <italic>G</italic>(<italic>U</italic>₁, <italic>U</italic>₂, <italic>E</italic>), where |<italic>U</italic>_{<italic>i</italic>}| = |(<italic>N</italic>_{<italic>i</italic>})|, and there are two bijections <italic>f</italic>_{<italic>i </italic>}: <italic>U</italic>_{<italic>i </italic>}→ (<italic>N</italic>_{<italic>i</italic>}) for <italic>i </italic>= 1, 2. The weight of an edge <italic>e </italic>= (<italic>u</italic>, <italic>v</italic>) ∈ <italic>E </italic>for <italic>u </italic>∈ <italic>U</italic>₁and <italic>v </italic>∈ <italic>U</italic>₂, <italic>w</italic>(<italic>e</italic>) = <italic>d</italic>(<italic>f</italic>₁(<italic>u</italic>), <italic>f</italic>₂(<italic>v</italic>)). Then, the tree-based measure <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) is defined as the weight of a minimum-weight edge cover of <italic>G </italic>divided by, the number of the edges in the cover. In its current implementation, PhyloNet uses the Robinson-Foulds distance measure [##UREF##7##27##] for <italic>d</italic>. The tree-based measure was first introduced by Nakhleh <italic>et al</italic>. [##UREF##8##28##]. An illustration of tree-based comparison of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## is given in Figure ##FIG##5##6##. Shown on the left of Figure ##FIG##5##6## is the bipartite graph <italic>G </italic>built from the sets (<italic>N</italic>₁) and (<italic>N</italic>₂) of trees induced by the two networks; these two sets are shown in Figure ##FIG##4##5##. The weight of each edge connecting two nodes in <italic>G </italic>is the RF distance between the two trees corresponding to these two nodes. These weights can be normalized by the number of internal edges in the trees. Since each of the eight trees has six internal edges, the weight of each edge in <italic>G </italic>can be divided by six to normalize it.</p>", "<p>Shown on the right of Figure ##FIG##5##6## is the minimum-weight edge cover of <italic>G</italic>, which is the set of edges that satisfies two conditions: (1) each node in <italic>G </italic>must be the endpoint of at least one edge in the set, and (2) the sum of the weights of the edges in the set is minimum among all sets of edges satisfying condition 1. In this case, the four edges shown are a cover, since each node in <italic>G </italic>is \"covered\" by at least one edge (here, each node is covered by exactly one edge). Further, it is of minimum weight, which equals 2, since a simple inspection yields that every other cover has a weight larger than 2. Since the cover has four edges in it, we have <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = (0 + 0 + 1/6 + 1/6)/4 = 1/12. If we use the raw RF values, then <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = (0 + 0 + 1 + 1)/4 = 1/2.</p>", "<title>Cluster-based comparison</title>", "<p>Let <italic>C</italic>₁= (<italic>N</italic>₁) and <italic>C</italic>₂= (<italic>N</italic>₂) be the two sets of all clusters induced by the two networks. We define the measure based on these two sets to be</p>", "<p></p>", "<p>The rationale behind this measure is that it is the sum of the ratios of clusters present in one but not both networks. The cluster-based measure was first introduced by Nakhleh <italic>et al</italic>. [##UREF##9##29##]. The sets <italic>C</italic>₁= (<italic>N</italic>₁) and <italic>C</italic>₂= (<italic>N</italic>₂) of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##0##1##, with |<italic>C</italic>₁| = |<italic>C</italic>₂| = 14. Since |<italic>C</italic>₁- <italic>C</italic>₂| = |<italic>C</italic>₂- <italic>C</italic>₁| = 2 (the two highlighted clusters in Table ##TAB##0##1##), we have <italic>m</italic>^{<italic>cluster</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = 1/7. A similar weighting scheme to that described in the previous section can be used to incorporate the fraction of trees in which a cluster appears into the measure calculation.</p>", "<title>Tripartition-based comparison</title>", "<p>Let <italic>θ</italic>₁= <italic>θ</italic>(<italic>N</italic>₁) and <italic>θ</italic>₂= <italic>θ</italic>(<italic>N</italic>₂) be the two sets of all tripartitions induced by the two networks. We define the measure based on these two sets to be</p>", "<p></p>", "<p>This measure views the two networks in terms of the sets of edges they define (where an edge is in a 1-1 correspondence with a tripartition) and computes the sum of the ratios of edges present in one but not both networks. The tripartition-based measure was devised by Moret <italic>et al</italic>. [##REF##17048405##19##]. The sets <italic>θ</italic>₁= <italic>θ</italic>(<italic>N</italic>₁) and <italic>θ</italic>₂= <italic>θ</italic>(<italic>N</italic>₂) of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure ##FIG##1##2## are listed in Table ##TAB##1##2##, with |<italic>θ</italic>₁| = |<italic>θ</italic>₂| = 12. Since |<italic>θ</italic>₁- <italic>θ</italic>₂| = |<italic>θ</italic>₂- <italic>θ</italic>₁| = 1 (the highlighted tripartition in Table ##TAB##1##2##), we have <italic>m</italic>^{<italic>tripartition</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = 1/12.</p>", "<title>Which measure to use?</title>", "<p>Several distance measures, such as the Robinson-Fould measure and the Subtree Prune and Regraft (SPR) distance, have been introduced over the years to quantify the difference between the topologies of a pair of phylogenetic trees; e.g., see [##UREF##5##25##,##UREF##6##26##] for description of many of these measures. Even though these measures may compute different distance values on the same pair of trees, there has been no consensus as to which measure should be used in general [##UREF##10##30##]. It may be the case that the Robinson-Foulds measure is more commonly used than the others, but this may be a mere reflection of its very low time requirements as compared to the other, more compute-intensive, measures.</p>", "<p>Regarding the three measures for comparing networks, a scenario analogous to that in phylogenetic trees arises here: each measure gives a different quantification of the dissimilarity between two networks based on one of the three ways to characterize a given network. As shown in the examples above, some or all of these measures may compute the same value for a given pair of networks, but that may not always be the case. Tree-based comparison of networks can be viewed as a method to quantify how similar, or dissimilar, two networks are in terms of their quality as a summary of a collection of trees. In some cases, even though two networks \"look different,\" they may be identical in terms of the trees they induce – this is the issue of indistinguishability of networks from a collection of trees that Nakhleh and colleagues discussed in [##REF##17048405##19##]. In such a case, using the tree-based comparison, or equivalently the cluster-based comparison, is most appropriate. However, if the similarity/dissimilarity of two networks means something close to an <italic>isomorphism</italic>, then the tripartition-based measure is more appropriate. However, it is important to note that none of the three measures described here is a metric on the general space of all evolutionary networks labeled by a given set of taxa.</p>", "<p>A practical distinction among the three measures can be derived based on the methods used to infer the evolutionary history of the set of species under study. Methods such as SplitsTree [##REF##9520503##23##] and NeighborNet [##UREF##4##24##] represent the evolutionary history as a set of splits, or clusters, hence making it more natural to use cluster-based comparison to study their performance. Methods such as RIATA-HGT [##UREF##1##16##] and LatTrans [##UREF##0##14##] compute evolutionary networks that are rooted, directed, acylic graphs, where internal nodes have an evolutionary implication in terms of ancestry. For these two methods, all three measures are appropriate. When the evolutionary history of a set of species is represented as a collection of its constituent gene trees, the tree-based measure is most appropriate.</p>", "<p>Finally, a clear distinction can be made among the methods in terms of computational requirements. In their current implementations, the tripartition-based measure is very fast in practice, taking time that is polynomial in the size of the two networks. On the other hand, the tree- and cluster-based measures are much slower, taking time that is exponential in the number of network nodes in the two networks (since these measures compute explicitly all trees inside each of the two networks). In light of recent complexity results that we obtained [##UREF##11##31##], it is very likely that no polynomial-time algorithms exist for computing the tree- and cluster-based measures in general.</p>", "<title>Parsimony of evolutionary networks</title>", "<p>Nakhleh and colleagues have recently formalized a maximum parsimony (MP) criterion for evolutionary networks [##REF##16447967##32##] and demonstrated its utility in reconstructing evolutionary networks on both biological and synthetic data sets [##REF##17068107##33##]. In this section, we describe a PhyloNet utility that allows for comparing two evolutionary networks in terms of their fitness to the evolution of a sequence data set, based on the MP criterion. We first begin with a brief review of the MP criterion, based on the exposition in [##REF##16447967##32##].</p>", "<p>The relationship between an evolutionary network and its constituent trees, as described in the background section, is the basis for the MP extension to evolutionary networks.</p>", "<p><bold>Definition 1 </bold><italic>The Hamming distance between two equal-length sequences x and y, denoted by H</italic>(<italic>x</italic>, <italic>y</italic>)<italic>, is the number of positions j such that x</italic>_{<italic>j </italic>}≠ <italic>y</italic>_{<italic>j</italic>}.</p>", "<p>Given a fully-labeled tree <italic>T</italic>, i.e., a tree in which each node <italic>v </italic>is labeled by a sequence <italic>s</italic>_{<italic>v </italic>}over some alphabet Σ, we define the Hamming distance of an edge <italic>e </italic>∈ <italic>E</italic>(<italic>T</italic>), denoted by <italic>H</italic>(<italic>e</italic>), to be <italic>H</italic>(<italic>s</italic>_{<italic>u</italic>}, <italic>s</italic>_{<italic>v</italic>}), where <italic>u </italic>and <italic>v </italic>are the two endpoints of <italic>e</italic>. We now define the parsimony score of a tree <italic>T</italic>.</p>", "<p><bold>Definition 2 </bold><italic>The parsimony score of a fully-labeled tree T, is Σ</italic>_{<italic>e </italic>∈ <italic>E</italic>(<italic>T</italic>)}<italic>H</italic>(<italic>e</italic>)<italic>. Given a set S of sequences, a maximum parsimony tree for S is a tree leaf-labeled by S and assigned labels for the internal nodes, of minimum parsimony score</italic>.</p>", "<p>The parsimony definitions can be extended in a straightforward manner to incorporate different site substitution matrices, where different substitutions do not necessarily contribute equally to the parsimony score, by simply modifying the formula <italic>H</italic>(<italic>x</italic>, <italic>y</italic>) to reflect the weights. Let Σ be the set of states that the two sequences <italic>x </italic>and <italic>y </italic>can take (e.g., Σ = {<italic>A</italic>, <italic>C</italic>, <italic>T</italic>, <italic>G</italic>} for DNA sequences), and <italic>W </italic>the site substitution matrix such that <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] is the weight of replacing <italic>σ</italic>₁by <italic>σ</italic>₂, for every <italic>σ</italic>₁, <italic>σ</italic>₂∈ Σ. In particular, the <italic>identity </italic>site substitution matrix satisfies <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] = 0 when <italic>σ</italic>₁= <italic>σ</italic>₂, and <italic>W</italic>[<italic>σ</italic>₁, <italic>σ</italic>₂] = 1 otherwise. The weighted Hamming distance between two sequence is <italic>H</italic>(<italic>x</italic>, <italic>y</italic>) = Σ_{1 ≤ <italic>i </italic>≤ <italic>k </italic>}<italic>W</italic>(<italic>x</italic>_{<italic>i</italic>}, <italic>y</italic>_{<italic>i</italic>}), where <italic>k </italic>is the length of the sequences <italic>x </italic>and <italic>y</italic>. The rest of the definitions are identical to the simple Hamming distance case. As described above, the evolutionary history of a single (non-recombining) gene is modeled by one of the trees contained inside the evolutionary network of the species containing that gene. Therefore the evolutionary history of a site <italic>s </italic>is also modeled by a tree contained inside the evolutionary network. A natural way to extend the tree-based parsimony score to fit a dataset that evolved on a network is to define the parsimony score for each site as the minimum parsimony score of that site over all trees contained inside the network.</p>", "<p><bold>Definition 3 </bold><italic>(</italic>[##REF##16447967##32##]<italic>) The parsimony score of a network N leaf-labeled by a set S of taxa, is</italic></p>", "<p></p>", "<p><italic>where TCost</italic>(<italic>T</italic>, <italic>s</italic>_{<italic>i</italic>}) <italic>is the parsimony score of site s</italic>_{<italic>i </italic>}<italic>on tree T</italic>.</p>", "<p>Notice that as usually large segments of DNA, rather than single sites, evolve together, Definition 3 can be extended easily to reflect this fact, by partitioning the sequences <italic>S </italic>into non-overlapping blocks <italic>b</italic>_{<italic>i </italic>}of sites, rather than sites <italic>s</italic>_{<italic>i</italic>}, and replacing <italic>s</italic>_{<italic>i </italic>}by <italic>b</italic>_{<italic>i </italic>}in Definition 3. This extension may be very significant if, for example, the evolutionary history of a gene includes some recombination events, and hence that evolutionary history is not a single tree. In this case, the recombination breakpoint can be detected by experimenting with different block sizes.</p>", "<p>The MP utility in PhyloNet allows the user to specify two evolutionary networks (either or both of which can be a tree) <italic>N</italic>₁and <italic>N</italic>₂and a sequence data set <italic>S</italic>, and computes the parsimony scores <italic>NCost</italic>(<italic>N</italic>₁, <italic>S</italic>) and <italic>NCost</italic>(<italic>N</italic>₂, <italic>S</italic>). The user can then compare the two scores and evaluate the fitness of the networks to the data set <italic>S </italic>based on the difference in the scores. Further, the utility allows the user, for example, to evaluate the significance of each network edge in a network <italic>N </italic>by comparing the parsimony scores of two different versions of <italic>N </italic>that contain different subsets of the network edges in <italic>N</italic>.</p>", "<title>Reconstructing evolutionary networks from species/gene trees</title>", "<p>Assuming incongruence among gene and species trees is the result of HGT events only, the <italic>Phylogeny-based HGT Reconstruction Problem</italic>, or HGT Reconstruction Problem for short, is defined as follows:</p>", "<p><bold>Problem 1 </bold><italic>(HGT Reconstruction Problem)</italic></p>", "<p><bold>Input: </bold><italic>A species tree ST and a set </italic> = {<italic>T</italic>₁,..., <italic>T</italic>_{<italic>p</italic>}}<italic>of gene trees</italic>.</p>", "<p><bold>Output: </bold><italic>An evolutionary network N, obtained by adding a minimal set of edges Ξ to T, such that N contains every tree T</italic>_{<italic>i </italic>}∈ </p>", "<p>The minimization criterion is a reflection of Occam's razor: in the absence of any additional biological knowledge, HGT events should be used sparingly to explain data features otherwise explainable under a tree model. The problem of finding a minimum-cardinality set of HGT events whose occurrence on species tree <italic>ST </italic>would give rise to the gene trees in set is computationally hard [##UREF##12##34##]. In [##UREF##1##16##], Nakhleh <italic>et al</italic>. introduced an accurate, polynomial-time heuristic, RIATA-HGT, for solving the HGT Reconstruction Problem for a pair of species and gene trees (in other words, RIATA-HGT currently handles the case where || = 1). In a nutshell, the method computes the maximum agreement subtree [##UREF##13##35##] of the species tree and each of the gene trees, and adds HGT edges to connect all subtrees that do not appear in the maximum agreement subtree. Theoretically, RIATA-HGT may not compute the minimum-cardinality set of HGT events; nonetheless, experimental results show very good empirical performance on synthetic as well as biological data [##UREF##1##16##].</p>", "<title>Computing multiple solutions and the graphical output</title>", "<p>RIATA-HGT was designed originally to compute a single solution to the problem, and was mainly aimed at binary trees. Later, Than and Nakhleh [##UREF##2##17##] extended the method to compute multiple solutions and to handle non-binary trees. These two features are very significant: the former allows biologists to explore multiple potential HGT scenarios, whereas the latter allows for analyzing trees in which some edges were contracted due to inaccuracies (see [##UREF##14##36##] for example). We have conducted an experimental study to compare the performance of RIATA-HGT with LatTrans [##REF##17572027##18##]. Although RIATA-HGT and LatTrans [##UREF##0##14##] have almost the same performance in terms of the number of HGT solutions and the solution size, the former runs much faster than the latter.</p>", "<p>For a compact representation of multiple solutions, we introduce four terms:</p>", "<p>• An <italic>event</italic>: this is a single HGT edge, written in the form of <italic>X </italic>→ <italic>Y</italic>, where <italic>X </italic>and <italic>Y </italic>are two nodes in the species tree.</p>", "<p>• A <italic>subsolution</italic>: this is an <italic>atomic </italic>set of events, which forms a part of an overall solution. In other words, either all or none of the events of a subsolution are taken in a solution.</p>", "<p>• A <italic>component</italic>: a set of components and/or subsolutions. Two components at the same level of decomposition are independent, in that an element of each component is needed to form a solution.</p>", "<p>• A <italic>solution</italic>: the union of a single element from each component at the highest level.</p>", "<p>To illustrate these concepts, consider species tree (((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>), (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>))) and the gene tree (((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>), ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>)). Observe, that each HGT event required to reconcile the two trees has both endpoints in the subtree ((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>) or both endpoints in the subtree (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>)), and no HGT event has endpoints in both subtrees. In this case, RIATA-HGT divides the pair of trees into two pairs:</p>", "<p>• Pair 1: ((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>) and ((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>)</p>", "<p>• Pair 2: (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>)) and ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>),</p>", "<p>and solves the HGT Reconstruction Problem on each of the two pairs <italic>independently</italic>. The set of solutions of each pair is a component. Notice that for each pair there are three possible ways to reconcile them; each such way is a called a subsolution. Each subsolution is a set of events, which in this case is only one event. Figure ##FIG##6##7(a)## shows the screen captures of two graphical outputs that correspond to two solutions on this pair of trees. Notice that if a component can be further divided into independent components, RIATA-HGT would do so, which will result in components at different levels, with the largest components being at the highest level.</p>", "<p>The compact representation of RIATA-HGT's output in terms of subsolutions and components is especially helpful when the number of solutions is large. RIATA-HGT also has an option to display all complete solutions. RIATA-HGT enumerates all complete solutions that are compactly represented as described in the preceding paragraphs. Each solution, which is a set of HGT events, along with the species tree defines an evolutionary network, which RIATA-HGT displays in the eNewick format. For example, for the trees (((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>), (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>))) and (((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>), ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>)), RIATA-HGT outputs 9 different networks in the eNewick format, if RIATA-HGT's option for displaying complete solutions is on. Figure ##FIG##6##7(b)## shows the corresponding eNewick representations.</p>", "<p>From the multiple comparisons between a species and a set of trees, RIATA-HGT offers a (strict) consensus network. For each pair of species tree and gene tree, RIATA-HGT computes a set of HGT events for reconciling them. To obtain the consensus network, RIATA-HGT retains only HGT events that appear in every set of solutions for every pair of species tree and gene tree. Those events are then added to the species to build the consensus network.</p>", "<p>We note here that while offering a simple summary of solutions, this way of computing consensus networks may not be appropriate in general; work is under way to address this issue more properly.</p>", "<p>Finally, RIATA-HGT may report '[time violation?]' next to an inferred HGT <italic>X </italic>→ <italic>Y</italic>. If this is the case, this indicates that node <italic>X </italic>lies on the path from <italic>Y </italic>to the root of the species tree. Theoretically, this indicates that two nodes that do not co-exist in time, <italic>X </italic>and <italic>Y </italic>in this case, shared genetic material, and hence the warning of 'time violation.' However, this may be the case simply due to incomplete taxon sampling, as discussed in [##REF##17048405##19##]. Therefore, the warning is issued in this case so as to alert that user that this inferred HGT edge is worth further inspection.</p>", "<title>Assessing the support of HGT edges</title>", "<p>In [##UREF##15##37##] we proposed a method for assessing the support of HGT edges. Roughly speaking, the support value of HGT edge <italic>X </italic>→ <italic>Y </italic>in the species tree, where <italic>Y</italic>'is the sibling of <italic>Y</italic>, is derived from the bootstrap values of the gene tree branches that separate the clade under <italic>Y </italic>from the clade under <italic>Y</italic>'. The rationale behind the idea is that if <italic>Y</italic>' and <italic>Y </italic>are well separated in the gene trees (i.e., some branches in the path from <italic>Y </italic>to <italic>Y</italic>' have high bootstrap values), HGT is necessary to move <italic>Y </italic>away from <italic>Y</italic>'). For example, the support of HGT edge <italic>X </italic>→ <italic>Y </italic>in Figure ##FIG##7##8(a)## is calculated based on the bootstrap values of the branches separating <italic>B </italic>from <italic>A </italic>in the gene tree, and it is 80 (which is the maximum bootstrap value of all edges on the path separating <italic>A </italic>and <italic>B </italic>in the gene tree). More technical details can be found in [##UREF##15##37##].</p>", "<p>Than <italic>et al</italic>. [##UREF##15##37##] have studied the reliability of this method for assessing the support of HGT edges on various data sets from [##REF##15598737##38##]. In this paper, we illustrate the output of RIATA-HGT on a pair of species/gene trees from [##REF##15598737##38##], as shown in Figure ##FIG##8##9##. The output of RIATA-HGT on this pair of trees is shown in Figure ##FIG##9##10##. RIATA-HGT computed four solutions, each of which has nine HGT edges. To allow for a compact representation of the solutions, they are divided into two components (which are computed automatically by RIATA-HGT), and each solution is formed by taking one subsolution from each component. HGT edges for the solutions are divided into two components, which means that a complete solution is formed by taking one solution from each component. Each component is labeled by the name of the internal node that is the root of the clade corresponding to that component. In the case of the solutions presented in Figure ##FIG##9##10##, each solution contains nine HGT edges, eight of which form a single subsolution in Component I18 and the ninth is the only edge in the only subsolution in Component I8. The value in parentheses next to each HGT edge is its support value computed from the bootstrap values of the gene tree branches (Figure ##FIG##8##9(b)##). Bergthorsson <italic>et. al</italic>. [##REF##15598737##38##] reported three HGTs involving <italic>Amborella</italic>: one HGT with donor being a species in the <italic>Moss </italic>group (species <italic>Brachythecium</italic>, <italic>Hypnum</italic>, and <italic>Thuidium</italic>, under the internal node I14 in the species tree) and the other two with donors being species in the <italic>Eudicot </italic>group (species <italic>Arabidopsis</italic>, <italic>Beta</italic>, <italic>Brassica</italic>, <italic>Daucus</italic>, <italic>Petunia</italic>, and <italic>Oenothera</italic>, under the internal node I5 in the species tree). The HGT from <italic>Moss </italic>has high SH support value [##UREF##16##39##]. RIATA-HGT finds this event, I14 → <italic>Amborella_H_M</italic>, with bootstrap value 98.0%. The other two HGT events from <italic>Eudicot </italic>do not have significant SH support values. RIATA-HGT also finds these events, I5 → <italic>Amborella_H_E1 </italic>and I2 → <italic>Amborella_H_E2</italic>. However, their support values are 73.0%, much smaller than that of the event from <italic>Moss</italic>. In addition to these three HGT edges, RIATA-HGT identified six more edges, four out of which had support values smaller than 50.0% (RIATA-HGT does not display support values that are smaller than 50.0%). The HGT edge from Component I8, which is shared among all four solutions, has support value of 100.0%. This edge was not reported in [##REF##15598737##38##]. A similar situation arises with the HGT edge I5 → I8, which is part of the three solutions that contain subsolutions 1, 3, and 4 from Component I18: the HGT edge has support of 100.0%, and was not reported in [##REF##15598737##38##], which may be a reflection that the authors focused only on HGT events involving <italic>Amborella</italic>. The ninth HGT edge in Subsolution2 of Component I18 has support value smaller than 50.0%.</p>", "<title>Other utilities</title>", "<p>As evident from the description of the methods above, there are fundamental correlations between phylogenetic trees and networks. Hence, many of the evolutionary network utilities use functionalities from the phylogenetic trees domain, which we have implemented and provide as standalone tools in PhyloNet:</p>", "<p>• A tool for computing the maximum agreement subtree (MAST) of a pair of trees using the algorithm of Steel and Warnow [##UREF##13##35##]. We also extended the algorithm so that it computes <italic>all </italic>MASTs of a pair of tree, and this feature is implemented as well.</p>", "<p>• A tool for computing the Robinson-Foulds distance measure between two phylogenetic trees [##UREF##7##27##].</p>", "<p>• A tool for computing the <italic>last common ancestor </italic>(lca) of a set of nodes in a phylogenetic tree.</p>", "<p>Additionally, PhyloNet provides an implementation of the parsimony-based method RECOMP of Ruths and Nakhleh [##REF##18048130##40##,##UREF##17##41##] for detecting interspecific recombination in a sequence alignment.</p>" ]

[ "<title>Conclusion</title>", "<p>Analyzing and understanding reticulate evolutionary relationships have been hindered by the lack of software tools for conducting these tasks. The proposed software package, PhyloNet, offers an array of utilities to allow for efficient and accurate analysis of such evolutionary relationships. These utilities allow for representing networks in a compact way, characterizing networks in terms of basic building blocks and comparing them based on these characterizations, comparing networks in terms of their fitness to the evolution of a given data set of sequences under the maximum parsimony model, and reconstructing networks from species/gene trees.</p>", "<p>The software package will help significantly in analyzing large data sets, as well as in studying the performance of evolutionary network reconstruction methods. Further, the software package offers the novel eNewick format for compact representation of evolutionary networks, a feature that allows for efficient interoperability of evolutionary network software tools.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Phylogenies, i.e., the evolutionary histories of groups of taxa, play a major role in representing the interrelationships among biological entities. Many software tools for reconstructing and evaluating such phylogenies have been proposed, almost all of which assume the underlying evolutionary history to be a tree. While trees give a satisfactory first-order approximation for many families of organisms, other families exhibit evolutionary mechanisms that cannot be represented by trees. Processes such as horizontal gene transfer (HGT), hybrid speciation, and interspecific recombination, collectively referred to as <italic>reticulate evolutionary events</italic>, result in <italic>networks</italic>, rather than trees, of relationships. Various software tools have been recently developed to analyze reticulate evolutionary relationships, which include SplitsTree4, LatTrans, EEEP, HorizStory, and T-REX.</p>", "<title>Results</title>", "<p>In this paper, we report on the PhyloNet software package, which is a suite of tools for analyzing reticulate evolutionary relationships, or <italic>evolutionary networks</italic>, which are rooted, directed, acyclic graphs, leaf-labeled by a set of taxa. These tools can be classified into four categories: (1) evolutionary network representation: reading/writing evolutionary networks in a newly devised compact form; (2) evolutionary network characterization: analyzing evolutionary networks in terms of three basic building blocks – trees, clusters, and tripartitions; (3) evolutionary network comparison: comparing two evolutionary networks in terms of topological dissimilarities, as well as fitness to sequence evolution under a maximum parsimony criterion; and (4) evolutionary network reconstruction: reconstructing an evolutionary network from a species tree and a set of gene trees.</p>", "<title>Conclusion</title>", "<p>The software package, PhyloNet, offers an array of utilities to allow for efficient and accurate analysis of evolutionary networks. The software package will help significantly in analyzing large data sets, as well as in studying the performance of evolutionary network reconstruction methods. Further, the software package supports the proposed eNewick format for compact representation of evolutionary networks, a feature that allows for efficient interoperability of evolutionary network software tools. Currently, all utilities in PhyloNet are invoked on the command line.</p>" ]

[ "<title>Implementation</title>", "<p>A major goal for the PhyloNet package was to make its functionality platform-independent and accessible both to end users for data analysis and to researchers designing new computational methods and techniques. In order to encompass as many platforms as possible, PhyloNet was implemented in Java. As a result, any system with the Java 2 Platform (Version 5.0 or higher) installed can run PhyloNet.</p>", "<p>PhyloNet can be used in two ways, depending on how the functionality needs to be accessed. A command-line interface exposes all of PhyloNet's tools on a Unix or DOS command-line. Each command accepts input from and writes output to text files. This allows PhyloNet's functionality to be used for manual data analysis or integrated into scripts for performing larger-scale processing. Additionally, a rich and thoroughly documented object model allows the incorporation of any of PhyloNet's functionality into existing Java programs. Also bundled are various programmatic utilities that represent trees, networks, and that read and write these various data structures to and from files.</p>", "<title>The command line interface</title>", "<p>PhyloNet has a consistent and easy-to-use command line interface. A detailed discussion of this interface and all available options is available in the documentation that accompanies a download of the tool. Here we provide a brief overview of the design of the command-line tool and the tools that can be accessed. Table ##TAB##2##3## lists all the commands that are currently available from the command-line. Each of these commands accepts a set of parameters as command-line arguments. All trees, networks, sequences, and other major data structures are read in either from standard in or from text files. Similarly all results can be written either to standard out or to a desired text file. All trees are read and written in Newick format. Networks are read and written in eNewick format. These design features allow the easy use of PhyloNet for manual data analysis or as a tool used within a larger scripted automated analysis.</p>", "<p>With the exception of the RECOMP tool, all the functionality of PhyloNet is independent of other third party tools. Because RECOMP must compute many trees using Maximum Parsimony trees, this tool requires that PAUP* [##UREF##18##42##] be installed on the local system. To run a tool in PhyloNet, invoke the executable <italic>.jar </italic>file downloaded from the PhyloNet project homepage:</p>", "<p>java -jar phylonet.jar charnet -i net.in -m tree</p>", "<p>Here phylonet.jar is the executable jar downloaded from the project homepage (the fle is assumed to be in the current directory where the user invokes this command), charnet is the name of the tool that decomposes the network contained in file net.in into a set of trees. The reference manual included with the executable jar provides very detailed instructions regarding how to run each tool in the PhyloNet package.</p>", "<title>Programmatic interface</title>", "<p>Many phylogenetic methods comprise critical, but intermediate, steps in much larger methods. As a result, there is also a need for the functionality in PhyloNet to be available for incorporation into larger programs. As a result, all of PhyloNet's functionality is exposed through an extensive set of Java classes. Each tool is contained within its own Java class and exposes a carefully constructed set of public methods that will be preserved and maintained even as PhyloNet grows. This modular design allows for the easy addition functionality in the future without effecting existing programs that use PhyloNet as a programmatic library. In addition to exposing a consistent API, PhyloNet also provides implementations of the most common phylogenetic data structures: trees and networks. Utility classes are also included that read and write these data structures to and from files. These classes can accelerate not only incorporation of PhyloNet's functionality, but also the development of new phylogenetic functionality within other applications. As PhyloNet grows, programmatic interfaces will be added to provide access to new functionality and tools. Detailed documentation of these libraries is available in JavaDoc form on the PhyloNet website.</p>", "<title>Availability and requirements</title>", "<p>1. <bold>Project name: </bold>PhyloNet | Phylogenetic Networks Toolkit.</p>", "<p>2. <bold>Project home page: </bold><ext-link ext-link-type=\"uri\" xlink:href=\"http://bioinfo.cs.rice.edu/phylonet/index.html\"/>.</p>", "<p>3. <bold>Operating system: </bold>Platform independent.</p>", "<p>4. <bold>Programming language: </bold>Java.</p>", "<p>5. <bold>Other requirements: </bold>Java 1.5, PAUP* (for some applications).</p>", "<p>6. <bold>License: </bold>GNU GPL.</p>", "<p>7. <bold>Any restrictions to use by non-academics: </bold>The GNU GPL license applies.</p>", "<title>Authors' contributions</title>", "<p>All authors contributed equally to the work described in this manuscript.</p>" ]

[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge the very helpful comments from three anonymous reviewers which helped improve the manuscript, as well as the software tool, significantly. This work is supported in part by the Department of Energy grant DE-FG02-06ER25734, the National Science Foundation grant CCF-0622037, the George R. Brown School of Engineering Roy E. Campbell Faculty Development Award, and the Department of Computer Science at Rice University.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Evolutionary networks and gene trees</bold>. Gene trees <italic>T </italic>and <italic>T</italic>' within species networks <italic>N</italic>. (a) The gene whose tree is depicted with a dashed line is transferred from the genome of species <italic>C </italic>to that of species <italic>B</italic>. (b) Species <italic>B </italic>and <italic>C </italic>exchanged the two genes whose trees are <italic>T </italic>and <italic>T</italic>'. (c) Species <italic>B </italic>is a hybrid whose two parents are species <italic>A </italic>and <italic>C</italic>; each gene in the genome of species <italic>B </italic>has an evolutionary tree that is either <italic>T </italic>or <italic>T</italic>'.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Sample evolutionary networks</bold>. Two evolutionary networks <italic>N</italic>₁and <italic>N</italic>₂, each with eight leaves (labeled <italic>A</italic>,..., <italic>H</italic>) and two network nodes <italic>X </italic>and <italic>Y</italic>. Shown are the orientation of the network edges; all other edges are directed away from the root (toward the leaves) Notice that the difference between the two networks is that node <italic>X </italic>in <italic>N</italic>₁has lineage <italic>G </italic>as one of its parents, whereas node <italic>X </italic>in <italic>N</italic>₂has lineage <italic>H </italic>as one of its parents.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>A modified Newick format</bold>. Three trees, <italic>N</italic>', <italic>X</italic>, and <italic>Y</italic>, along with their Newick representation. These three trees form the tree decomposition of the evolutionary network <italic>N</italic>₁in Figure 2. The eNewick representation of <italic>N </italic>is the triplet ⟨<italic>N</italic>'; <italic>X</italic>; <italic>Y</italic>⟩.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>The eNewick format</bold>. A modified Newick format for representing evolutionary networks. The figure is taken from the paper by Morin <italic>et. al</italic>. [##REF##16717070##22##].</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Trees within networks</bold>. The sets and of all eight trees induced by the two networks <italic>N</italic>₁and <italic>N</italic>₂, respectively, in Figure 2.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Tree-based comparison of networks</bold>. Illustration of the tree-based network comparison measure. (a) The weighted bipartite graph <italic>G </italic>that is constructed from the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure 2. On the left are four nodes that correspond to the four trees in (<italic>N</italic>₁) and on the right are four nodes that correspond to the four trees in (<italic>N</italic>₂). The weight of an edge between and is the values of the Robinson-Foulds (RF) distance between the two trees, which is computed as the number of clusters present in one but not both of the trees, divided by 2. (b) The edges that comprise the minimum-weight edge cover of the bipartite graph <italic>G</italic>. The weight of this cover is 2, which is the sum of the weights of the edges in the cover; therefore, <italic>m</italic>^{<italic>tree</italic>}(<italic>N</italic>₁, <italic>N</italic>₂) = 2.</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p><bold>Screenshot of the graphical output of RIATA-HGT</bold>. (a) Screen captures of the graphical output of RIATA-HGT on the pair of trees (((<italic>a</italic>, <italic>b</italic>), <italic>c</italic>), (<italic>d</italic>, (<italic>e</italic>, <italic>f</italic>))) and (((<italic>a</italic>, <italic>c</italic>), <italic>b</italic>), ((<italic>d</italic>, <italic>f</italic>), <italic>e</italic>)). (b) The eNewick representations of the two selected networks.</p></caption></fig>", "<fig position=\"float\" id=\"F8\"><label>Figure 8</label><caption><p><bold>An illustration of computing the support value of an HGT edge</bold>. An illustration of computing the support value of an HGT edge. In this case, the support of HGT edge <italic>X </italic>→ <italic>Y </italic>added on the species tree (a), is calculated based on the bootstrap of the branches that separate <italic>Y </italic>(or <italic>B</italic>) from <italic>A </italic>in the gene tree (b). The value for the event <italic>X </italic>→ <italic>Y </italic>is 80.</p></caption></fig>", "<fig position=\"float\" id=\"F9\"><label>Figure 9</label><caption><p><bold>The cox2 trees</bold>. The species tree (a): (((Pallavicinia, (Porella, Trichocolea)I15)I16, Marchantia)I17, (Thuidium, Brachythecium, Hypnum)I14, (((Amborella_V, Amborella_H_M, Amborella_H_E1, Amborella_H_E2)I9, ((Eichhornia, (Zea, Oryza)I6)I7, Philodendron, Agave)I8, ((Daucus, Petunia)I4, Beta, (Oenothera, (Brassica, Arabidopsis)I2)I3)I5, ((Piper, Asarum)I10, (Liriodendron, Laurus)I11)I1)I12, (Pinus, Zamia)I13)I0)I18; and gene tree (b): ((((((((Petunia, Amborella_H_E1, (((Arabidopsis, Brassica)I2:99.0, Amborella_H_E2), Oenothera, Daucus)), Beta):73.0, ((Agave, Eichhornia, Philodendron), (Oryza, Zea)I6:100.0)), (Asarum, Piper)I10), (Laurus, Liriodendron)I11), Amborella_V), (Pinus, Zamia)I13:72.0), (((Thuidium, Hypnum, Amborella_H_M):91.0, Brachythecium):98.0, (Marchantia, ((Porella, Trichocolea):97.0, Pallavicinia))I17)); for gene <italic>cox2</italic>. Bootstrap values for the branches in the gene tree that are greater than 50.0% are included in the tree Newick representation. The species tree branches do not have bootstrap values.</p></caption></fig>", "<fig position=\"float\" id=\"F10\"><label>Figure 10</label><caption><p><bold>An example of RIATA-HGT output</bold>. The output of RIATA-HGT on the species tree and <italic>cox2 </italic>gene tree in Figure 9. RIATA-HGT finds 4 solutions, summarized in terms of two components, so that each solution is the union of exactly one subsolution from each component.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>The clusters of the two networks in Figure 2.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Network <italic>N</italic>₁</td><td align=\"left\">Network <italic>N</italic>₂</td></tr></thead><tbody><tr><td align=\"left\">{<italic>B</italic>, <italic>C</italic>}</td><td align=\"left\">{<italic>B</italic>, <italic>C</italic>}</td></tr><tr><td align=\"left\">{<italic>C</italic>, <italic>D</italic>}</td><td align=\"left\">{<italic>C</italic>, <italic>D</italic>}</td></tr><tr><td align=\"left\">{<italic>B</italic>, <italic>C</italic>, <italic>D</italic>}</td><td align=\"left\">{<italic>B</italic>, <italic>C</italic>, <italic>D</italic>}</td></tr><tr><td align=\"left\">{<italic>D</italic>, <italic>E</italic>}</td><td align=\"left\">{<italic>D</italic>, <italic>E</italic>}</td></tr><tr><td align=\"left\">{<italic>E</italic>, <italic>F</italic>}</td><td align=\"left\">{<italic>E</italic>, <italic>F</italic>}</td></tr><tr><td align=\"left\">{<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td><td align=\"left\">{<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td></tr><tr><td align=\"left\">{<italic>B</italic>, <italic>C</italic>, <italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td><td align=\"left\">{<italic>B</italic>, <italic>C</italic>, <italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td></tr><tr><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}</td><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}</td></tr><tr><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>D</italic>}</td><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>D</italic>}</td></tr><tr><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td><td align=\"left\">{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>D</italic>, <italic>E</italic>, <italic>F</italic>}</td></tr><tr><td align=\"left\">{<bold>E</bold>, <bold>F</bold>, <bold>G</bold>}</td><td align=\"left\">{<bold>E</bold>, <bold>F</bold>, <bold>H</bold>}</td></tr><tr><td align=\"left\">{<bold>D</bold>, <bold>E</bold>, <bold>F</bold>, <bold>G</bold>}</td><td align=\"left\">{<bold>D</bold>, <bold>E</bold>, <bold>F</bold>, <bold>H</bold>}</td></tr><tr><td align=\"left\">{<italic>G</italic>, <italic>H</italic>}</td><td align=\"left\">{<italic>G</italic>, <italic>H</italic>}</td></tr><tr><td align=\"left\">{<italic>D</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}</td><td align=\"left\">{<italic>D</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>The tripartitions of the two networks in Figure 2.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\">Edge Label</td><td align=\"left\">Network <italic>N</italic>₁</td><td align=\"left\">Network <italic>N</italic>₂</td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">⟨{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">2</td><td align=\"left\">⟨{<italic>G</italic>, <italic>H</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}⟩</td><td align=\"left\">⟨{<italic>G</italic>, <italic>H</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>}⟩</td></tr><tr><td align=\"left\">3</td><td align=\"left\">⟨{<italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>A</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>, <italic>E</italic>, <italic>F</italic>}, {<italic>A</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\"><bold>4</bold></td><td align=\"left\">⟨{<bold>G</bold>}, {<bold>D</bold>, <bold>E</bold>, <bold>F</bold>}, {<bold>A</bold>, <bold>B</bold>, <bold>C</bold>, <bold>H</bold>}⟩</td><td align=\"left\">⟨{<bold>H</bold>}, {<bold>D</bold>, <bold>E</bold>, <bold>F</bold>}, {<bold>A</bold>, <bold>B</bold>, <bold>C</bold>, <bold>G</bold>}⟩</td></tr><tr><td align=\"left\">5</td><td align=\"left\">⟨{<italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>B</italic>, <italic>C</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">6</td><td align=\"left\">⟨{<italic>C</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>C</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">7</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">8</td><td align=\"left\">⟨{<italic>E</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>E</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">9</td><td align=\"left\">⟨{<italic>D</italic>}, {}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>D</italic>}, {}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">10</td><td align=\"left\">⟨{<italic>D</italic>}, {}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>D</italic>}, {}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>E</italic>, <italic>F</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">11</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr><tr><td align=\"left\">12</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td><td align=\"left\">⟨{<italic>E</italic>, <italic>F</italic>}, {<italic>D</italic>}, {<italic>A</italic>, <italic>B</italic>, <italic>C</italic>, <italic>G</italic>, <italic>H</italic>}⟩</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>List of tools and their description.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Tool name</bold></td><td align=\"left\"><bold>Purpose</bold></td></tr></thead><tbody><tr><td align=\"left\">charnet</td><td align=\"left\">Computing clusters, trees and tripartitions in a network</td></tr><tr><td align=\"left\">cmpnets</td><td align=\"left\">Computing the distance between two networks</td></tr><tr><td align=\"left\">lca</td><td align=\"left\">Finding the last common ancestor of a set of nodes</td></tr><tr><td align=\"left\">mast</td><td align=\"left\">Computing the maximum agreement subtree</td></tr><tr><td align=\"left\">netpars</td><td align=\"left\">Scoring the parsimony of sequences on a pair of networks</td></tr><tr><td align=\"left\">riatahgt</td><td align=\"left\">Reconstructing HGT events from a pair of species/gene trees</td></tr><tr><td align=\"left\">rf</td><td align=\"left\">Computing the Robinson-Foulds tree measure</td></tr></tbody></table></table-wrap>" ]

[ "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1471-2105-9-322-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>u</mml:mi><mml:mo>⇝</mml:mo><mml:mi>v</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\" name=\"1471-2105-9-322-i2\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>u</mml:mi><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>v</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\" name=\"1471-2105-9-322-i3\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>u</mml:mi><mml:mo>/</mml:mo><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>x</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>v</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\" name=\"1471-2105-9-322-i4\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>u</mml:mi><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mover accent=\"true\"><mml:mi>x</mml:mi><mml:mo>ˆ</mml:mo></mml:mover><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>v</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M5\" name=\"1471-2105-9-322-i5\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>Y</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>D</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M6\" name=\"1471-2105-9-322-i6\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>/</mml:mo><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>Y</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>E</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M7\" name=\"1471-2105-9-322-i7\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mover accent=\"true\"><mml:mi>X</mml:mi><mml:mo>ˆ</mml:mo></mml:mover><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>D</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M8\" name=\"1471-2105-9-322-i8\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">F</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M9\" name=\"1471-2105-9-322-i8\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">F</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M10\" name=\"1471-2105-9-322-i9\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mo>∪</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>ℓ</mml:mi></mml:msubsup><mml:mi>L</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>t</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mi>L</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M11\" name=\"1471-2105-9-322-i8\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">F</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M12\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M13\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M14\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M15\" name=\"1471-2105-9-322-i11\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>m</mml:mi><mml:mo>≤</mml:mo><mml:mstyle displaystyle=\"true\"><mml:msubsup><mml:mo>∏</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>ℓ</mml:mi></mml:msubsup><mml:mrow><mml:msub><mml:mi>ρ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M16\" name=\"1471-2105-9-322-i12\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mo>{</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>1</mml:mn><mml:mn>1</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>1</mml:mn><mml:mn>2</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>1</mml:mn><mml:mn>3</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>1</mml:mn><mml:mn>4</mml:mn></mml:msubsup><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M17\" name=\"1471-2105-9-322-i13\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mo>{</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>2</mml:mn><mml:mn>1</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>2</mml:mn><mml:mn>2</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>2</mml:mn><mml:mn>3</mml:mn></mml:msubsup><mml:mo>,</mml:mo><mml:msubsup><mml:mi>T</mml:mi><mml:mn>2</mml:mn><mml:mn>4</mml:mn></mml:msubsup><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M18\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M19\" name=\"1471-2105-9-322-i14\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>∈</mml:mo><mml:mi>χ</mml:mi><mml:mo>:</mml:mo><mml:mi>r</mml:mi><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>v</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M20\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M21\" name=\"1471-2105-9-322-i16\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi mathvariant=\"script\">C</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:msub><mml:mo>∪</mml:mo><mml:mrow><mml:mi>T</mml:mi><mml:mo>∈</mml:mo><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msub><mml:mi mathvariant=\"script\">C</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>T</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M22\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M23\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M24\" name=\"1471-2105-9-322-i17\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>w</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mo>|</mml:mo><mml:mo>{</mml:mo><mml:mi>T</mml:mi><mml:mo>∈</mml:mo><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>:</mml:mo><mml:msub><mml:mi>c</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo>∈</mml:mo><mml:mi mathvariant=\"script\">C</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>T</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>}</mml:mo><mml:mo>|</mml:mo></mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>|</mml:mo></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M25\" name=\"1471-2105-9-322-i14\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>∈</mml:mo><mml:mi>χ</mml:mi><mml:mo>:</mml:mo><mml:mi>r</mml:mi><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>v</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M26\" name=\"1471-2105-9-322-i18\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>∈</mml:mo><mml:mi>χ</mml:mi><mml:mo>:</mml:mo><mml:mi>r</mml:mi><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mover accent=\"true\"><mml:mi>v</mml:mi><mml:mo>ˆ</mml:mo></mml:mover><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M27\" name=\"1471-2105-9-322-i19\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>∈</mml:mo><mml:mi>χ</mml:mi><mml:mo>:</mml:mo><mml:mi>r</mml:mi><mml:mo>/</mml:mo><mml:msup><mml:mo>⇝</mml:mo><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mi>v</mml:mi><mml:mo stretchy=\"false\">]</mml:mo></mml:mrow></mml:msup><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M28\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M29\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M30\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M31\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M32\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M33\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M34\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M35\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M36\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M37\" name=\"1471-2105-9-322-i20\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>T</mml:mi><mml:mn>1</mml:mn><mml:mi>i</mml:mi></mml:msubsup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M38\" name=\"1471-2105-9-322-i21\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msubsup><mml:mi>T</mml:mi><mml:mn>2</mml:mn><mml:mi>j</mml:mi></mml:msubsup></mml:mrow></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M39\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M40\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M41\" name=\"1471-2105-9-322-i22\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mi>m</mml:mi><mml:mrow><mml:mi>c</mml:mi><mml:mi>l</mml:mi><mml:mi>u</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow></mml:mfrac><mml:mo>+</mml:mo><mml:mfrac><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mn>2.</mml:mn></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M42\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M43\" name=\"1471-2105-9-322-i15\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">C</mml:mi></mml:semantics></mml:math></inline-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M44\" name=\"1471-2105-9-322-i23\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:msup><mml:mi>m</mml:mi><mml:mrow><mml:mi>t</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>p</mml:mi><mml:mi>a</mml:mi><mml:mi>r</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>o</mml:mi><mml:mi>n</mml:mi></mml:mrow></mml:msup><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow></mml:mfrac><mml:mo>+</mml:mo><mml:mfrac><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>−</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow><mml:mrow><mml:mo>|</mml:mo><mml:msub><mml:mi>θ</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>|</mml:mo></mml:mrow></mml:mfrac></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mn>2.</mml:mn></mml:mrow></mml:semantics></mml:math></disp-formula>", "<disp-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M45\" name=\"1471-2105-9-322-i24\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>N</mml:mi><mml:mi>C</mml:mi><mml:mi>o</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo>,</mml:mo><mml:mi>S</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mo>:</mml:mo><mml:mo>=</mml:mo><mml:mstyle displaystyle=\"true\"><mml:msub><mml:mo>∑</mml:mo><mml:mrow><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>∈</mml:mo><mml:mi>S</mml:mi></mml:mrow></mml:msub><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mrow><mml:mi>min</mml:mi><mml:mo>⁡</mml:mo></mml:mrow><mml:mrow><mml:mi>T</mml:mi><mml:mo>∈</mml:mo><mml:mi mathvariant=\"script\">T</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:msub><mml:mi>T</mml:mi><mml:mi>C</mml:mi><mml:mi>o</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>T</mml:mi><mml:mo>,</mml:mo><mml:msub><mml:mi>s</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:mstyle></mml:mrow></mml:semantics></mml:math></disp-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M46\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M47\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M48\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>", "<inline-formula><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M49\" name=\"1471-2105-9-322-i10\" overflow=\"scroll\"><mml:semantics><mml:mi mathvariant=\"script\">T</mml:mi></mml:semantics></mml:math></inline-formula>" ]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>A table of the (nontrivial) clusters of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure 2, denoted by (<italic>N</italic>₁) and (<italic>N</italic>₂), respectively, in the text. Highlighted are rows corresponding to clusters that differ between the two networks.</p></table-wrap-foot>", "<table-wrap-foot><p>A table of the (nontrivial) tripartitions of the two networks <italic>N</italic>₁and <italic>N</italic>₂in Figure 2, denoted by <italic>θ</italic>(<italic>N</italic>₁) and <italic>θ</italic>(<italic>N</italic>₂), respectively, in the text. Highlighted are rows corresponding to tripartitions that differ between the two networks.</p></table-wrap-foot>", "<table-wrap-foot><p>A table of the tools currently implemented in PhyloNet. With the exception of the three phylogenetic trees tools lca, mast, and rf, all the other tools are for analyzing reticulate evolutionary relationships.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2105-9-322-1\"/>", "<graphic xlink:href=\"1471-2105-9-322-2\"/>", "<graphic xlink:href=\"1471-2105-9-322-3\"/>", "<graphic xlink:href=\"1471-2105-9-322-4\"/>", "<graphic xlink:href=\"1471-2105-9-322-5\"/>", "<graphic xlink:href=\"1471-2105-9-322-6\"/>", "<graphic xlink:href=\"1471-2105-9-322-7\"/>", "<graphic xlink:href=\"1471-2105-9-322-8\"/>", "<graphic xlink:href=\"1471-2105-9-322-9\"/>", "<graphic xlink:href=\"1471-2105-9-322-10\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Generalized progressive retinal atrophies (gPRAs) in domestic dogs (<italic>Canis familiaris</italic>) are a group of inherited retinal dystrophies that share a similar phenotype. gPRA causes progressive loss of vision, usually leading to blindness. Initially rod photoreceptor vision is affected, causing night blindness followed by progressive loss of cone photoreceptors with deteriorations in daytime vision. gPRAs can be classified by age of onset and rate of progression [##REF##9455155##1##]. Certain breeds show early onset forms, e.g. Collies, Irish Setters, Norwegian Elkhounds and Miniature Schnauzers. In these breeds, the disease results from abnormal or arrested development of the photoreceptor cells in the retina, and gPRA affects pups very early in life. In other breeds (including Miniature Poodles, English and American Cocker Spaniels, Labrador Retrievers) gPRA onset occurs much later. Affected dogs in these latter breeds appear normal when young, but develop gPRA as adults.</p>", "<p>Two X-linked [##REF##11978759##2##] and an autosomal dominantly inherited trait [##REF##11972042##3##,##REF##12692159##4##] have been described, yet most gPRA forms are transmitted in an autosomal recessive (AR) mode. Up to now, causative mutations have been identified only in few breeds of dogs with AR transmitted gPRA [##REF##8387203##5##, ####REF##9714819##6##, ##REF##11124530##7##, ##REF##10393029##8##, ##REF##16806805##9##, ##REF##16859891##10##, ##REF##16938425##11####16938425##11##].</p>", "<p>In addition to the respective pedigree material highly informative polymorphic DNA markers [##REF##12700351##12##,##REF##15363096##13##] are the necessary tools for mapping chromosomal locations of disease gene loci by linkage analysis. In order to determine the molecular basis of canine gPRA, we initiated whole-genome scanning (WGS) using markers spread evenly across the canine genome for linkage in gPRA-informative pedigrees of the Schapendoes breed. Here we demonstrate linkage of the gPRA trait to markers on canine chromosome 20 (CFA20) in Schapendoes. In addition, the critical region was fine mapped, and the novel candidate genes <italic>CACNA2D3</italic>, <italic>HT017</italic>, and <italic>WNT5A</italic> were investigated.</p>" ]

[ "<title>Methods</title>", "<title>Animals</title>", "<p>All dogs were collected from the general breeding population of pure-bred Schapendoes. Five pedigrees, comprising 57 Schapendoes dogs including 13 gPRA-affected animals, were available in which gPRA is transmitted in an AR manner. Ophthalmologically experienced veterinarians confirmed the gPRA status of affected and unaffected dogs by ophthalmoscopy as documented in certificates of eye examinations. gPRA in Schapendoes is characterized by late onset and slow progression as documented by veterinarians of the Dortmunder Ophthalmologenkreis (DOK). Affected Schapendoes dogs appear normal when young, but develop gPRA at an age of onset between 2-5 years. Early in the disease, affected dogs are night-blind, lacking the ability to adjust their vision to dim light; later, their daytime vision also fails. This process of complete photoreceptor degeneration takes up to 2 years.</p>", "<p>Genomic DNA was extracted from peripheral blood according to standard protocols [##REF##3344216##14##]. For isolation of RNA and retina sections we obtained an eye of a gPRA-affected, five year-old Schapendoes with complete loss of night vision yet anecdotally remaining, very limited day-time vision. Retinas of gPRA-free Saarloos/Wolfshounds were used as controls.</p>", "<title>Histology</title>", "<p>The enucleated eyes from a five year old, gPRA-affected Schapendoes dog and control eyes from a gPRA-free Sarloos/Wolfshound were sagittally cut at the level of the optic nerve, immersion-fixed in 100% ethanol and paraffin-embedded. Serial sections, 15 μm thick, were cut over the whole extension of the retina, stained with hematoxylin and eosin and photo-documented.</p>", "<title>Markers and genotyping</title>", "<p>For the WGS highly informative autosomal microsatellite markers were analyzed from the minimal screening set 2 (MSS-2) [##REF##12700351##12##]. Microsatellites for fine mapping (##TAB##0##Table 1##, ##FIG##0##Figure 1##) were identified using published dog markers [##REF##14512627##15##], the dog genome sequence (May 2005) and the Tandem Repeats Finder included in the UCSC Genome Browser. Only microsatellites with a repeat length exceeding 15 units were selected. PCR primers were designed using Primer Express software (PE Biosystems). For PCR we used the \"tailed primer PCR\" as described before [##REF##14968360##16##]. This method requires three oligonucleotides for amplification: 1. tailed forward primer (tailed F), 2. reverse primer and 3. labeled primer (labeled F) corresponding to the 5'-tail sequence of tailed F. PCR conditions were as follows: 1-PCR buffer (Genecraft, Lüdinghausen, Germany), 0.2 mM each dNTP, 1.5 to 3 mM MgCl₂, 0.2 pmol tailed F, 2.5 pmol labeled F, 2.5 pmol reverse primer, 0.5 U BioTherm DNA Polymerase (Genecraft) and 50 ng DNA. PCRs were performed in 96-well microtiter plates (Thermowell Costar Corning, NY). Each well contained a reaction volume of 10 μl. A \"touchdown\" PCR procedure was applied in a thermocycler (Biometra, Göttingen, Germany): initial denaturation (5 min at 95 °C), two initial cycles 6 °C and 3 °C above the annealing temperature, 40 cycles of 95 °C (30 s), annealing temperature of 53 °C (30 s), elongation at 72 °C (30 s) and a final elongation step at 72 °C (3 min).</p>", "<p>Electrophoreses were run using Amersham Biosciences standard protocols for genotyping on the automated capillary DNA sequencer (MegaBACE 1000, Amersham Biosciences, Freiburg, Germany). PCR products of two markers were diluted (each 1:10), pooled and 2 μl of this dilution were mixed with 0.5 μl of MegaBACE^TM ET-R Size Standard and 2.5 μl loading solution (70% formamide, 1 mM EDTA). Raw data were analyzed by the MegaBACE Fragment Profiler software version 1.2 (Amersham Biosciences, Freiburg, Germany) and a table of genotypes was exported. For a few markers no PCR products were obtained for specific dogs.</p>", "<title>Linkage analyses</title>", "<p>Using the LINKAGE package version 5.1 [##REF##6585139##17##], we undertook two-point linkage analyses between the gPRA locus and each marker. The disease trait was coded as being AR transmitted with full penetrance, no phenocopy and a frequency of 0.1 for the disease allele. The data were controlled for Mendelian inheritance using the unknown program, and two-point linkage analyses were performed using mlink program [##REF##6585139##17##]. Marker-allele frequencies were calculated on the basis of genotype data of 10 unrelated individuals of the schapendoes breed.</p>", "<title>Mutation screening of candidate genes <italic>CACNA2D3</italic>, <italic>HT017</italic>, and <italic>WNT5A</italic></title>", "<p>Exon/ intron boundaries of the canine genes <italic>CACNA2D3</italic>, <italic>HT017</italic>, and <italic>WNT5A</italic> were searched for by comparison of the mRNA sequence of the human gene (accession numbers: <italic>CACNA2D3</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_018398\">NM_018398</ext-link>;<italic>HT017</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_065729\">NP_065729</ext-link>;<italic>WNT5A</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_003392\">NM_003392</ext-link>) with the publicly available dog genome sequences in UCSC Genome Browser (assembly: dog May 2005). For sequencing of the coding regions of the three genes, intronic PCR primers flanking the exons were designed in order to amplify at least 50 intronic bases on either end of the exon in order to cover the splice junctions (##TAB##1##Table 2##). PCRs were performed under standard PCR conditions [##REF##12447165##18##] with BioTherm DNA Polymerase (Genecraft) and 1.5 mM MgCl₂ at an annealing temperature of 57 °C.</p>", "<p>For sequencing of the <italic>CACNA2D3</italic> cDNA total RNA of retinal tissue was isolated. For this purpose peqGOLD TriFast reagent (Peqlab, Erlangen, Germany) was added to the frozen tissue samples, the mixture was immediately homogenized and total RNA was then extracted using guanidinium isothiocyanate (RNeasy Mini Kit, Qiagen, Hilden, Germany). cDNA was synthesized by oligo-dT priming with the Sensiscript RT Kit (Qiagen, Hilden, Germany). Overlapping PCR products of the cDNA of the <italic>CACNA2D3</italic> gene were generated using the primers in ##TAB##2##Table 3##.</p>", "<p>All sequencing reactions were carried out by the dideoxy chain termination method using the Dyenamic ET Terminator Kit (Amersham Biosciences, Freiburg, Germany) according to the manufacturer's instructions. Reaction products were run on an automated capillary DNA sequencer (MegaBACE 1000, Amersham Biosciences, Freiburg, Germany).</p>", "<title>Quantitative real-time RT-PCR of candidate gene <italic>CACNA2D3</italic></title>", "<p>Total RNAs from the retinae of a gPRA-affected Schapendoes and an unaffected Saarloos/Wolfshound were subjected to quantitative real-time RT-PCR analysis using the QuantiTect SYBR Green assay (Qiagen, Hilden, Germany) as described by the manufacturer and the iCycler iQ real-time PCR detection system (Bio-Rad, München, Germany). PCR primers were designed using Primer Express software (PE Biosystems). In order to avoid amplification of contaminating genomic DNA, the primers span an intron. <italic>CACNA2D3</italic> mRNA/cDNA was amplified using primers CACNA2D3 Ex9-F (5'-CAC TTC AGG GAG CAT CTG GAC-3') and CACNA2D3 Ex10-R (5'-GGC TGC AGA TGC TTC CTTG-3'). ATP-binding cassette, sub-family A, member 4 gene (<italic>ABCA4</italic>) and guanine nucleotide binding protein, α transducing activity gene (<italic>GNAT1</italic>) are retina specific. They were amplified using primers ABCA4-F (5'-TGG AGG AAA GCT CCC AAT CC-3') and ABCA4-R (5'-GCC TCT CTG GTG ATA GGG CC-3') and GNAT1-F (5'-GCT CGC GTG TCA AGA CCA C-3') and GNAT1-R (5'-ATC CAC TTC TTG CGC TCT GAG-3'). Hypoxanthin phosphoribosyltransferase 1 (HPRT1) served as internal reference and was amplified using primers HPRT1-F (5'-AGC TTG CTG GTG AAA AGG AC-3') and HPRT1-R (5'-TTA TAG TCA AGG GCA TAT CC-3'). One-step PCR cycling was carried out by reverse transcription at 50 °C for 30 min, initial activation step at 95 °C for 15 min x1 cycle, 4-step cycling at 94 °C for 15 s, at 60 °C for 30 s, at 72 °C for 30 s x 40 cycles. As soon as the PCR was completed, baseline and threshold values were set automatically and threshold cycle (CT) values were calculated. CT values were exported to Microsoft Excel for calculating the real copy number. The CT value represents the PCR cycle at which an increase in fluorescence can first be detected above a base line signal level. Signals were quantified by normalizing with GAPDH expression.</p>" ]

[ "<title>Results</title>", "<p>Compared to a normal retina (##FIG##1##Figure 2A##), the gPRA-affected eyes of a five year old Schapendoes displayed typical degeneration signs in peripheral and central areas (##FIG##1##Figure 2B##). The outer retina with the photoreceptor layer and the outer nuclear layer was missing in all retinal parts investigated. The inner retina showed reduced inner nuclear and inner plexiform layers, whereas the ganglion cell layer appeared comparatively preserved.</p>", "<p>A detailed ophthalmological examination was performed on all 57 Schapendoes of five different families revealing 13 dogs with bilateral affection. Evaluation of gPRA in these five families suggested that the disease segregates as an AR trait (##FIG##0##Figure 1##). A case of inbreeding was identified in family SD3. Initially, WGS for linkage was performed in the five pedigrees using markers of the MSS-2 [##REF##12700351##12##]. Having completed the typing of 165 microsatellites (CFA1-20 and 24-26) of 325 MSS-2 markers, the WGS was abbreviated after a two-point lod score of 4.78 at q=0.000 was obtained for marker REN93E07. The high lod score indicated that the gPRA phenotype was linked to a mutation on CFA20. For fine mapping of the gPRA region in the Schapendoes breed nine additional microsatellite markers from CFA20 were genotyped between marker REN100J13 and TL195IIMS (##TAB##0##Table 1##, ##FIG##0##Figure 1##) in the five pedigrees. With one exception all microsatellites represent dinucleotide repeats. Heterozygosity values range around 0.5, and 4-10 different alleles were analyzed in the Schapendoes population. Two-point lod scores for linkage between the gPRA locus and microsatellite markers gave still a maximum lod score of 4.78 with marker REN93E07.</p>", "<p>Genotyping of ten microsatellite markers for all 57 dogs of the five pedigrees revealed that the \"2-2-3-2-2-2-2\" haplotype (marker REN149D23 to TL327MS) segregates with the gPRA trait and has a frequency of 50% in the analyzed pedigrees (##FIG##0##Figure 1##). Analysis of this haplotype placed the gPRA locus in a region between marker FH3358 and TL195IIMS. A potential double recombination event in the dog SD90 of family SD5 may be interpreted to confine the size of the critical haplotype to 5.6 Mb flanked by markers FH3358 and TL336MS. For the \"recombined region\" of dog SD90 no canine gene has been published in the different gene banks so far. Comparison of the canine DNA sequence of the critical region with the human genome in UCSC Genome Browser (assembly: human May 2004) shows homology with chromosome 3p. In man this region comprises candidate genes for retinitis pigmentosa (RP)-and thus also for gPRA in Schapendoes. The marker with the peak lod score REN93E07 is located in intron 7 of candidate gene <italic>CACNA2D3</italic> (##FIG##2##Figure 3##) which spans a genomic region of about 830 kb (kb) and consists of 37 exons. The mRNA of this gene encodes the calcium channel α₂δ₃ subunit, which is mainly expressed in brain [##REF##9880589##19##] and also in the eye <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/UniGene\">UniGene</ext-link>. In intron 26 of the human <italic>CACNA2D3</italic> gene the <italic>HT017/LRTM1</italic> gene is located (##FIG##2##Figure 3##). This gene encodes the leucine-rich repeat and transmembrane domain 1. Upstream of <italic>CACNA2D3</italic> the <italic>WNT5A</italic> gene is situated (##FIG##2##Figure 3##) encoding member 5A of the wingless-type MMTV integration site family. Sequencing of the candidate genes <italic>HT017</italic> and <italic>WNT5A</italic> did not reveal any pathogenic mutations, neither in the coding sequences nor in intron/exon junctions of affected individuals. Five single nucleotide polymorphisms (SNPs) were detected in the <italic>CACNA2D3</italic> gene: IVS16-7T&gt;C, IVS23-51A&gt;T, IVS29+18A&gt;G, IVS29+57C&gt;T, IVS30-57T&gt;C. Yet, these SNPs occur in homozygous state not only in gPRA-affected dogs, but also in healthy Schapendoes (data not shown). Thus these SNPs do not cause gPRA in Schapendoes. Additionally, a thymin-insertion in intron 6 (IVS6-38_-34insT) was identified in comparison to the UCSC dog genome sequence (assembly: dog May 2005). Further investigations revealed that this insertion was present in homozygous state in healthy dogs of other breeds, implying a non-pathogenic polymorphism. Furthermore, sequencing of the <italic>CACNA2D3</italic> cDNA from a diseased Schapendoes eye revealed no sequence deviations, thus excluding \"hidden\" mutations affecting the splicing process. In addition, altogether 25 kb in introns 5, 7 and 8 of the <italic>CACNA2D3</italic> gene comprising evolutionarily conserved sequences were analyzed without any hint on the gPRA mutation in question (data not shown).</p>", "<p>In order to exclude potential transcriptional impact of the elusive gPRA mutation, the expression of <italic>CACNA2D3</italic> mRNA in retinal tissue was determined by real-time RT-PCR (normalized to the level of the housekeeping gene <italic>HPRT</italic>). mRNA expression of two unaffected Saarloos/Wolfshounds was compared to a gPRA-affected Schapendoes. <italic>GNAT1</italic> and <italic>ABCA4</italic> gene expression was substantially reduced in retinal tissue of the affected Schapendoes. In contrast, no reduction was obvious for the <italic>CACNA2D3</italic> mRNA levels (##FIG##3##Figure 4##).</p>" ]

[ "<title>Discussion</title>", "<p>The responsible locus for gPRA in Schapendoes, a canine counterpart for RP in man, maps to the central region of CFA20. Haplotype analyses defined the critical interval between marker FH3358 and TL195IIMS. The haplotype potentially confining a smaller critical interval (between FH3358 and TL336MS) occurred exclusively in individual SD90 of family 5. A caveat remains to accept this confinement: Alleles 3 for markers TL336MS and TL337MS might not represent a recent or ancestral recombination event, but rather be due to non-mendelian inheritance. Yet non-mendelian inheritance appears less likely for two adjacent microsatellites in the absence of any additional slippage mutations of these microsatellites in all the other analyzed meiotic events. Consequently, we concentrated initially on the smaller critical interval between FH3358 and TL336MS, albeit the genomic region between TL337MS and TL195IIMS must not be excluded formally to comprise additional candidate genes.</p>", "<p>An interesting candidate in the critical genomic interval represents the <italic>CACNA2D3</italic> gene. The marker with the highest lod score REN93E07 was located in intron 7. Direct sequencing of all coding exons for homozygously affected and normal SD dogs exclude a gPRA-causing mutation in the coding sequence of the <italic>CACNA2D3</italic> gene. This fact implies that the mutation causing gPRA in Schapendoes may be located intronically in the <italic>CACNA2D3</italic> gene affecting splicing. Yet, extensive sequence analysis of retinal cDNA revealed no splice mutation in the <italic>CACNA2D3</italic> gene. Furthermore, in order to exclude the <italic>CACNA2D3</italic> gene as causative for gPRA in Schapendoes, we analyzed the expression of <italic>CACNA2D3</italic> mRNA in retinal tissue: mRNA levels were nearly identical between a gPRA-affected Schapendoes and an unaffected Saarloos/Wolfshound. In contrast, the expression of the retina-specific genes <italic>GNAT1</italic> and <italic>ABCA4</italic> appeared reduced substantially or even absent. Photoreceptor cells in the retina of the affected Schapendoes have vanished so that an expression of retina-specific genes cannot be demonstrated. Since its mRNA expression is unaltered in a retina without photoreceptor cells, the <italic>CACNA2D3</italic> gene appears expressed mainly in the cell types not affected by gPRA. Yet also photoreceptor cells may well produce small but crucial amounts of <italic>CACNA2D3</italic> transcripts that do not significantly affect the mRNA levels from unseparated retinal extractions. Given the availability of respective tissue samples, we could nevertheless use the haplotype-defined linkage region data to examine obligatorily homozygotic mutation carriers for altered retinal mRNA expression already presymptomatically.</p>", "<p>Since gPRA in Schapendoes is probably not caused by a <italic>CACNA2D3</italic> mutation, mutation analysis of the <italic>HT017</italic> and <italic>WNT5A</italic> genes were performed. Yet, gPRA-causing mutations were excluded in the coding sequence of these two genes. In comparison to the UCSC dog genome sequence (assembly: dog May 2005) the critical region between marker FH3358 and TL336MS comprises further candidate genes, which are be investigated. In case the causative mutation is not identified in this critical interval, additional candidate genes are to be investigated in the region between TL337MS and TL195IIMS. Although the mutation causing gPRA in Schapendoes has not yet been identified, the critical region for the location of the mutation was reduced to 5.6 Mb. Our findings for gPRA in the Schapendoes breed constitute an interesting naturally occurring model for RP, the human counterpart of gPRA.</p>", "<p>Based on linkage analysis data, we established an indirect DNA test for gPRA in this breed. Nearly 600 dogs with a mean age of five years have been tested so far. Based on the age of onset of 2-5 years in the Schapendoes breed, affected dogs among the tested individuals are likely to show initial gPRA symptoms. All 18 phenotypically affected dogs were tested as harbouring the linked haplotype in homozygous state, and all healthy obligatory carriers were typed as being heterozygous. The degree of certainty for a test result depends on the rate of recombination (so far no recombinations were observed) or new mutations. Theoretically small uncalculatable risks remain for false negative and positive results, respectively. Notwithstanding, the established indirect DNA test facilitates the eradication of gPRA among Schapendoes. Known mutation carriers can still produce offspring by selective crossing to dogs with mutation-free haplotypes.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>In order to determine the molecular basis of canine generalized progressive retinal atrophy (gPRA), we initiated whole-genome scanning for linkage in gPRA-informative pedigrees of the Schapendoes breed.</p>", "<title>Methods</title>", "<p>Detailed pedigree and ophthalmological data were assembled in selected Schapendoes pedigrees. A whole-genome scan was initiated by two-point linkage analysis using microsatellite markers in combination with haplotype analyses. Mutation screening was carried out in respective candidate genes by DNA sequencing of amplified products and quantitative real-time reverse transcriptase polymerase chain reaction (RT-PCR).</p>", "<title>Results</title>", "<p>Genotyping data of the microsatellite genome scan evidenced a peak two-point lod score of 4.78 for marker REN93E07 on CFA20. Haplotype analyses inferred the gPRA locus in a 5.6 megabase (Mb) region between markers FH3358 and TL336MS. Mutation screening in the genes <italic>CACNA2D3</italic>, <italic>HT017</italic>, and <italic>WNT5A</italic> revealed no causative sequence deviations. In addition, <italic>CACNA2D3</italic> mRNA levels were equivalent in retinas of affected and healthy dogs.</p>", "<title>Conclusions</title>", "<p>By genome-wide linkage analysis a region for gPRA was identified and fine-localized in Schapendoes dogs. Although the mutation causing gPRA in Schapendoes dogs has not yet been identified, we established indirect DNA testing for gPRA in this breed based on linkage analysis data.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>We thank the owners of the dogs for blood samples, the German and Dutch Schapendoes clubs represented by H. Mohr and G. de Wit-Bazelmans for their support as well as the veterinarians of the Dortmunder Ophthalmologenkreis (DOK), particularly Dr. R. Brahm for the ophthalmologic investigation of the dogs and the enucleation of the eyes. Bouchaib Jamal, Britta Kraczyk, Jörg Rutten and Sonja Vosbeck carried out parts of the linkage analyses initially in the project. Andrea Petzold performed DNA sequencing of the conserved regions. We thank Annegrit Schlichting for excellent technical assistance. These studies were supported by the Gesellschaft für kynologische Forschung, Bonn (Germany).</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Haplotypes of the gPRA Schapendoes families SD1-5 as established by microsatellite markers for chromosome 20. Affected dogs are represented by black, unaffected by white and those with known carrier status are represented by half-filled symbols. Circles represent females and squares represent males. Genotype that could not be ascertained are scored as \"0\". Black bars indicate the affected haplotype. In the box, genotyped markers and the disease haplotype are indicated. The observed recombination events evidence the disease causing locus in the region between markers FH3358 and TL195IIMS.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Hematoxylin-, eosin-stained paraffin sections illustrating normal canine retina and gPRA-affected retina of a Schapendoes dog. <bold>A</bold>: The retina of a Saarloos/Wolfshound exhibited regular nuclear layers with the nerve fiber layer (NF), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), photoreceptor layer (RCL), and the pigment epithelium (PE). <bold>B</bold>: In the degenerated retina of a Schapendoes dog the outer retina with the RCL and ONL was missing, the INL and the IPL reduced, the GCL was comparatively preserved. CH represents choroid. The scale bar in <bold>B</bold> represents 20 μm; same magnification for <bold>A</bold> and <bold>B</bold>.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>Schematic overview of the critical region on chromosome 20 in which the gPRA locus maps in Schapedoes dogs. On the left hand side of the chromosome the analyzed genes and their genomic location are shown, on the right hand side genotyped microsatellite markers are depicted. Location ascertained from UCSC Genome Browser (assembly: dog May 2005).</p></caption></fig>", "<fig id=\"f4\" fig-type=\"figure\" position=\"float\"><label>Figure 4</label><caption><p>Analysis of gene expression by quantitative real-time reverse transcriptase polymerase chain reaction. Real-time RT-PCR was used to determine the expression of the genes <italic>CACNA2D3</italic>, <italic>GNAT1</italic>, and <italic>ABCA4</italic> by calculating the real copy number. Expression levels were normalized to those of the <italic>HPRT1</italic> gene. No differences were obvious between the unaffected Saarloos/Wolfshound (Sa; N=2) and the g-PRA affected Schapendoes (SD; N=1) for <italic>CACNA2D3</italic> mRNA. <italic>GNAT1</italic> and <italic>ABCA4</italic> mRNA expression is substantially reduced or absent in retinal tissue of the affected Schapendoes.</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title>Microsatellite markers for mapping, primers for PCR amplification, their location and PCR products sizes.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"81\" span=\"1\"/><col width=\"56\" span=\"1\"/><col width=\"230\" span=\"1\"/><col width=\"64\" span=\"1\"/><col width=\"32\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Marker</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Microsat type</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Primer sequence (5'-3')</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Location on CFA20</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Size (bp)</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">REN100J131<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGATTGACTCTACTTTACACA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">25,817,177<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">164<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TATATTAGGCGGTTTTCTTCT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">25,817,034<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">FH33582<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">tetra<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CATCACCCAAATTCAAAGGCA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">33,096,985<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">268<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCATCAAGGCCCTAATATTTAAAGATT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">33,097,252<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">REN149D232<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GACAGAAGAGCCCATCGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">37,609,209<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">168<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CATAGTCACACCCACCAATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">37,609,376<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">REN316E232<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAAAAGAGGATGGGATGGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,133,160<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">154<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCAGATAGATCATTTGCTGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,133,313<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">TL335MS<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCCCATAGAAAAGGGACTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,313,482<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">126<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACTTTCTCTCCCCCTCTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,313,607<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">REN93E071<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCCCCCTCACCACTCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,525,708<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">170<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGAGGGCTGCCACTGTAAATA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,525,877<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">TL336MS<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCACTGGTACAGGCATTGTTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,727,171<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">133<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCTTATGTCCATCCCCATC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,727,303<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">TL337MS<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGGCTACTTTTGGGACCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,956,429<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">335<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGAGAGGTGAGAGATGCTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38,956,763<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">TL327MS<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGCTTGTTATGAAGTTGGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">39,812,660<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">167<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGCCCCAGGTGCTATGGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">39,812,826<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">TL195II<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AACTGAGGTTCCCTTGTTCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">47,049,704<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">232<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTAATCGAAAGTGCAGGAGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">47,049,935<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">REN114M191<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">di<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCATACAGCCACACCAAGTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">56,553,756<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">192<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"/><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCTCCCTGACCACAGGTCT</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">56,553,948</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"t2\" position=\"float\"><label>Table 2</label><caption><title>Primers for amplification of exonic regions of <italic>CACNA2D3</italic>, <italic>HT017</italic>, and <italic>WNT5A</italic> including exon/intron boundaries.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"73\" span=\"1\"/><col width=\"49\" span=\"1\"/><col width=\"277\" span=\"1\"/><col width=\"42\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Gene</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Exon</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Sequence (5’-3’)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Size (bp)</bold><hr/></td></tr><tr><td rowspan=\"66\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CACNA2D3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGTGCTGGCAGTTTCTACCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">268<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">1R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATCGCTTCCTGCCACCAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGAGAGGCAGTCCTATTTATTCCTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">329<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAACAACTGAGTCAACTTCACTCTTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGGCTCCAGGTCATAATGCAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">261<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTTACCATTTCTTGTTTGGCAGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">4F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GACACCCTTACCTGGCTTTGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">355<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">4R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGTCCCCCATACCCTCTGTTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">5F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTCATGCTGCTATTGCCAGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">326<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">5R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCATTTTCCCCTATTGGGAGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">6+7F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CAGGGCTGGTCATTGCATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">546<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">6+7R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGGCGGGACATCTAATGCTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">8F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGTACCCCTCAAATGATTAATTGTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">201<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">8R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TAGGTTTGTATCATGACCCTTGATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">9F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCATTCCAGTCTGAGACTCGTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">311<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">9R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCCAAGGCTAACCATAATGCTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">10F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGAAATGCTTATCGTGTAGGTTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">422<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">10R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGAGCCATAGTATTCGGTTTGGTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">11F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCTACAGATGGGAAGCCTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">277<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">11R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTCTTAACTATCCCAACTTGCGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">12F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGAGAGGTGGGTTTATGGTTGAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">394<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">12R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGTTAACACGGTCTTCTGGAATTAAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">13F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTGCCAGTGGTGACCAAATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">208<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">13R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GTACTGAATGCACAAAATCATGGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">14F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACTGGTCTGTTCCCAATGGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">266<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">14R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACCAGAGCTTGAGTCAGAGAATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">15F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAACTTTGAGAAGGCACCAGATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">248<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">15R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGGTATCTTGGACGCTTAGTCCTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">16F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGAATTCACCAGGGAGCCAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">221<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">16R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAACGCTGCTGCAAAAGTGTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">17F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCTTCTCTCCAATATCCCTCCAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">279<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">17R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGCCTCCAGGTACAGAACTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">18+19F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGCATGCTGACTTGGTGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">693<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">18+19R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACTCTTTCCAGCCTTTTGGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">20F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAACCAACACCAACTATAATCAGTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">310<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">20R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCTTTCATTAATCCAATGACTGGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">21+22F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGAGATGCAAGTGAGGAGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">637<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">21+22R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCTGGATTTGATGGGACCG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">23F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGAACTGTTCCATATTTTCAGCTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">406<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">23R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCGAGCTCTTGTGGTTTGGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">24F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTGCATTCTGTGCTTGGTGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">359<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">24R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATCAAGAAACGCAAGCCTCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">25F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCTCCACACTTTCGCCAACAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">484<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">25R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCCAATATTCAACACTGCCTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">26F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACAGCAGCTATGGCGTCAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">410<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">26R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACCAGCTGTCAGAATCTTGAATTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">27F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGCTTGCATCAGCTTCTTGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">251<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">27R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCACTTTTAGGCTCCGGGTAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">28F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TAAGTGGCAATCATAGCAGATGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">232<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">28R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCAGGAGCAATCTGTCAGACAAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">29F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCATGGCCTTAACTCCTAGAGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">381<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">29R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCTGTGACATTTTTAGAGGGATAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">30F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCCTGATTCTTCTCTGGTGCTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">231<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">30R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCTTGCTTTATTTGACCTTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">31F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GACTTTGCATGTTCCTGGTTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">304<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">31R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACAGATAAAGATATGCTCACGCTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">32F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGTATCCAACCATGTTCTTCTTGTAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">373<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">32R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGTCTCAGCTTTCAATATTTCGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">33F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGTAACACAACCAACCATACTGTAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">290<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">33R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGTATGTTTGTCCATCCTTGGTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">34F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAGCGGAACTGGGTTCTGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">352<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">34R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCTAGCGAAGCCAAATGATGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">35+36F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGAGTTTTCCTCAGGATCTTTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">551<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">35+36R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATGAGACTCTCATGGTGAATCTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">37F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGACTTGATTCCTACTTTGGAGAGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">630<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">37R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGTCTCTGCCAACAACCATCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td rowspan=\"8\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">HT017<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCGTTGAAGAAAAGCACAAGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">209<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">1R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGTCCCTTCCTCCCACGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2aF<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATTCCTTGTGACTTCAGAGGGAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">487<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2aR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGAGCTTGATTTGTCATCAAACA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2bF<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCAGACTTTTCCACTCCCTCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">319<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2bR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCTGCGTGTTACCAGCCTAGT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCTGTATATATTCCATCTGCCTGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">605<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GTGAATGCATCAACCCTACTCATATAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td rowspan=\"10\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">WNT5A</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GTAAAGTCTTTTGCACAATCACGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">468<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">1R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAAAAGTGGCGAGCGTCG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AACTCAACGGAGGAGAAGCG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">302<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">2R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AATAAAACAAAGCATATGTACTTAGAAGGAAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACTTTGTCATGAGGACAAGCAGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">440<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">3R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCTTCAGGAGAACACTTGATCCG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">4F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGTCAGAGTGGAGACGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">503<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">4R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTGTCAGGCAGCATCAGGC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">5F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGAGCGGAGCTTTGGTAACC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">599<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">5R</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAATAAGTGGGTCCTGGGAGC</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"t3\" position=\"float\"><label>Table 3</label><caption><title>Primers for amplification of <italic>CACNA2D3</italic> cDNA.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"107\" span=\"1\"/><col width=\"238\" span=\"1\"/><col width=\"96\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Primer</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Sequence (5'-3')</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Size(bp)</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex2 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATGGAAGAGATGTTTCACAAAAAGTC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">605<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex7 R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCAATAATGTTGAAAAAGTCATCATCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex6 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATTAAATGGGAACCAGATGAGAATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">375<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex9 R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ATCACTGAGAATGTTGAAGGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex9 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACTTCAGGGAGCATCTGGAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">728<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex17 R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACTCCACCTCAGAGAGGTCAAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex15 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGATCGAAAGGCATTCTTCTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">624<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex23 R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCATCAAAGAGGACTTCTTGTATC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex20 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGGTGTGGCGCTCTCCAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">752<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex29 R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCAGAATAAACCCATTATTGTCTATGAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex28 F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCCTCTCTGGATGGCAAATG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">762<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">CACNA2D3 Ex37 R</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCACCTTGAGAAGAGCATTAAGAGC</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Location ascertained from UCSC Genome Browser (assembly: dog May 2005).</p></table-wrap-foot>", "<table-wrap-foot><p>The intronic primer sequence for amplification of corresponding exons and 50 intronic bases on either end of the exons and the product sizes are shown.</p></table-wrap-foot>", "<table-wrap-foot><p>The exonic primer sequences for amplification of overlapping polymerase chain reaction products of the cDNA and the product sizes are shown.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-174-f1\"/>", "<graphic xlink:href=\"mv-v13-174-f2\"/>", "<graphic xlink:href=\"mv-v13-174-f3\"/>", "<graphic xlink:href=\"mv-v13-174-f4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Laser in situ keratomileusis (LASIK) has become the most frequently used refractive procedure in the world [##REF##10713222##1##], due to rapid visual recovery and lack of significant pain. More than one million procedures are estimated to have been performed worldwide [##REF##10713222##1##,##REF##9682123##2##]. This procedure represents a combination of previously used techniques in refractive surgery. It involves the use of a microkeratome to create a thin corneal flap, followed by excimer laser ablation of the corneal stroma and repositioning of the flap [##REF##9682123##2##]. Corneal lamellar dissection was first described in 1949 by Barraquer [##UREF##0##3##] as part of keratomileusis surgery, and it was later modified to become an integral component of automated lamellar keratoplasty (ALK). Corneal excimer laser ablation has been used in photorefractive keratectomy (PRK) since 1983. Further advances in excimer laser technology and the development of safer microkeratomes have allowed lamellar refractive surgery to expand from a surgical technique performed by only a few experts to a widespread procedure, now performed by the general ophthalmic surgeon [##REF##9682123##2##,##REF##11333326##4##,##REF##10445711##5##].</p>", "<p>The clinical outcome of laser refractive surgery may be less than ideal for a group of patients because the cornea, as a biological structure, is subject to individual variation in the healing response [##REF##8528917##6##]. Variability in wound healing response among patients is progressively gaining more attention because it affects the degree of prediction and stability of all refractive surgical procedures. With the development of molecular and cellular biology, the understanding of the molecular basis for this variation is becoming increasingly feasible [##REF##8528917##6##,##REF##9109075##7##].</p>", "<p>The stromal cells secrete an extracellular matrix composed mainly of collagen fibrils arranged in orthogonal lamellae, and proteoglycans [##REF##395131##8##]. Maurice [##REF##13429485##9##] attributed the transparency of the cornea to the regular spacing of corneal fibrils, and the corneal proteoglycans play a role in the collagen fibrilogenesis and matrix assembly. There are strong evidences suggesting the involvement of proteoglycans in the development and maintenance of corneal transparency. See reference [##REF##12886457##10##] for a review on corneal collagen and proteoglycans.</p>", "<p>Proteoglycans are macromolecules that have a protein core with covalently linked glycosaminoglycan side chains [##REF##3816423##11##]. In many species, the predominant corneal glycosaminoglycans are dermatan sulfate and keratan sulfate, with smaller amounts of heparan sulfate. The main corneal extracellular matrix proteoglycans belong to the small leucine-rich family of proteins (SLRP). Some members of this family are known to regulate collagen fibrillogenesis [##REF##12886457##10##]. In 1992, a cDNA clone encoding the lumican core protein of a chick corneal keratan sulfate proteoglycan [##REF##1370446##12##] was obtained, and the bovine [##REF##8099356##13##] and human [##REF##7558030##14##] lumican core proteins were cloned later. Two other keratan sulfate proteoglycans, keratocan and mimecan (or osteoglycin), were cloned from the bovine cornea [##REF##8621655##15##]. Although expressed in other tissues, lumican, keratocan, and mimecan are glycosylated only in the cornea with sulfated keratan sulfate chains. The crucial role of lumican in the regulation of collagen assembly into fibrils was established in studies on mice with bilateral corneal opacit that were homozygous for a null mutation in lumican [##REF##9606218##16##]. Furthermore, it was shown that mimecan-deficient mice have thicker collagen fibrils in both corneal and skin preparations [##REF##12432342##17##]. Nonglycosylated core protein of lumican is as effective as the intact proteoglycan in inhibiting fibrillogenesis in vitro [##REF##8595806##18##], but the glycosylation is important to the corneal transparency process [##REF##8125750##19##].</p>", "<p>The main chick corneal dermatan sulfate proteoglycan was identified as decorin [##REF##1605630##20##]. It was shown that synthesis of nonglycosylated decorin in avian cornea leads to disruption in lamellar organization, suggesting that dermatan sulfate proteoglycans are not involved in the regulation of collagen fibril diameter, but are important to fibril-fibril spacing and lamellar cohesiveness [##REF##7592530##21##]. Furthermore, in corneal explants from embryonic chicken, an increased synthesis of keratan sulfate proteoglycan and a decreased synthesis of dermatan sulfate proteoglycan coincided with the onset of tissue transparency, again suggesting a correlation between proteoglycan composition and corneal transparency [##REF##7592530##21##].</p>", "<p>The main heparan sulfate proteoglycans found in cornea are perlecan [##REF##10806439##22##], a basement membrane proteoglycan, and syndecan, a cell surface proteoglycan expressed mainly by epithelial cells [##REF##2029850##23##,##REF##10767393##24##].</p>", "<p>The aim of the present study was to evaluate the effects of LASIK on proteoglycan biosynthesis and collagen organization in human cornea explants, in comparison to paired controls.</p>" ]

[ "<title>Methods</title>", "<title>Materials</title>", "<p>Keratanase (from <italic>Pseudomonas</italic> species) [##REF##2946580##25##], Ham F-12 culture medium, fetal bovine serum, and papain were purchased from Sigma Chemical Co., Inc. (St. Louis, MO). Chondroitinases AC and B, and heparitinase II (from <italic>Flavobacterium heparinum</italic>) were prepared by methods previously described in reference [##REF##12630899##26##]. Agarose (standard, low M_r) was purchased from Bio-Rad Laboratories (Richmond, CA). Acrylamide, N,N-methylenebisacrylamide, N,N,N',N'-tetramethylenediamine, 1,3-diaminopropane, and ethylenediamine were from Aldrich Chemical Co., Inc. (Milwaukee, WI). H₂³⁵SO₄ (carrier free) was purchased from Instituto de Energia Nuclear (São Paulo, SP, Brazil). Ultima Gold liquid scintillation cocktail was purchased from Packard Instruments Co., Inc. (Meriden, CT), and 2,5-diphenyloxazole (PPO) was from Beckman Instruments, Inc. (Fullerton, CA).</p>", "<title>Tissue Source</title>", "<p>We obtained 24 human corneoscleral buttons from 12 donors, aged between 20 and 75 years, from Banco de Olhos do Hospital São Paulo (São Paulo, SP, Brazil). Only eyes from donors who provided specific consent for research purposes and with a contraindication for transplantation were included. The eyes were stored at 4 °C for a maximum of 48 h postmortem, in a wet chamber containing 4 mg/ml gentamycin in phosphate buffered saline (PBS). Detailed information about characteristics of the donors and corneal specimens is provided in ##TAB##0##Table 1##.</p>", "<p>All 24 corneoscleral specimens (LASIK [n=12]; controls [n=12]) were evaluated for gross abnormalities with a slit lamp (BP 900; Haag Streit, Switzerland), using direct and indirect illumination. None of the 12 donors had any history of corneal surgery, and no corneal pathologies were found.</p>", "<p>Methods for obtaining and handling of human tissue were humane, and the tenets of the Declaration of Helsinki were followed. Informed consent was obtained from each donor's family after explanation of the nature and possible consequences of the study.</p>", "<title>Surgical technique: LASIK</title>", "<p>LASIK is a two-step surgical technique for the performance of a refractive corneal surgery. The first step consists of using the microkeratome to create a partial thickness corneal flap. The microkeratome consists of two components: a ring, which is applied to the globe and can harden it by creating a vacuum, and an oscillating blade, which fits onto the vacuum ring and cuts a partial thickness corneal flap. The cut is incomplete, leaving a small hinge, which allows the surgeon to lift the flap, treat the corneal stroma with the excimer laser, and replace the flap without suturing at its original location [##REF##9682123##2##]. The second step uses the excimer laser, in the same manner as in PRK.</p>", "<p>Excimer laser photoablation was performed with a flying-spot laser (LADAR Vision® System; Summit Autonomous Technologies, Orlando, FL), with repetition rate of approximately 55 pulses per second, a spot size of 0.8-0.9 mm, an average fluence of 180-240 mJ/cm², and a pulse energy of 2.4-3.0 mJ. The corneas received a 6.0 mm ablation zone diameter, 6.0 diopter myopic correction to a theoretical stromal ablation depth of 68.3 mm. All surgeries were performed by the same surgeon. For each eye pair, one cornea was submitted to LASIK, and the other was used as a matched control.</p>", "<p>LASIK was performed in 12 corneas from 12 donors. The ocular globes were secured in an ocular globe holder. A hinged flap was created with a microkeratome (Hansatome; B&amp;L, Rochester, NY) with a 160 head and 8.5 ring, and excimer laser photoablation was immediately performed with a flying spot laser (Summit Autonomous Technologies, LADAR Vision® System). The stromal bed was then irrigated with saline solution, and finally the flap was folded back onto the cornea. The other 12 contralateral eyes were kept intact and used as controls.</p>", "<title>Tissue culture and radioisotope labeling of corneas</title>", "<p>After the surgery, the corneas were excised under sterile conditions from the eyes, leaving 1.5 mm scleral rims preserved. The corneas were then washed with 5 ml of a 4 mg/ml gentamycin solution in PBS, and immediately placed in 12 ml of HAM F-12 nutrient mixture supplemented with 10.000 U of penicillin and 100 mg of streptomycin, containing 100 mCi/ml ³⁵S-sulfate for the metabolic labeling of proteoglycans. The corneas were labeled with ³⁵S-sulfate for 24 h at 37 °C in 2.5% CO₂ atmosphere. After ³⁵S-sulfate incorporation, the corneas were trimmed free of the scleral rims, and the proteoglycans were extract and analyzed. The peripheral cornea surrounding the LASIK scar was included in the proteoglycan measurement.</p>", "<title>Extraction, identification, and quantification of proteoglycans and glycosaminoglycans</title>", "<p>After 24 h incubation, the corneal explants were halved. One half was used for proteoglycan extraction, and the other was used for histophatological and birefringence analysis. For proteolgycan extraction, the corneal explant fragments were weighed, cut in small pieces (&lt;0.5 mm), and suspended in 4 M guanidine hydrochloride (GuHCl) in 0.5 sodium acetate buffer, pH 5.8. After overnight incubation at 4 °C with shaking, debris was removed by centrifugation and the proteoglycans were precipitated by the addition of ethanol (3 volumes) to the supernatant. Subsequently, the precipitates formed were collected by centrifugation, washed with 80% ethanol, and dried. The dried material was resuspended in 100 μl of distilled water and analyzed for proteoglycans by a combination of agarose gel electrophoresis and enzymatic degradation with specific glycosaminoglycan lyases, using a technique described in reference [##REF##2116907##27##]. For the analysis of glycosaminoglycans, the proteoglycans were submitted to proteolysis with papain (2 mg/ml in 0.06 M phosphate-cysteine buffer, pH 6.5, containing 20 mM EDTA-1 ml of solution per 100 mg of tissue wet weight) using a previously described technique [##REF##2116907##27##,##REF##11262582##28##]. The proteoglycans and their degradation products were fixed on the gel with cetyltrimethylammonium bromide and stained with toluidine blue. The ³⁵S-sulfate labeled compounds were visualized by exposure of the agarose gel slabs (after fixation, drying, and staining) to a Packard Cyclone^TM Storage Phosphor System by 1-3 days. For quantification, they were scraped off the agarose gels and counted in a Beckman 6800 liquid scintillation spectrophotometer, using Ultima Gold LSC-Cocktail [##REF##8645702##29##]. The quantitative results were always corrected for ³⁵S-decay.</p>", "<title>Histopathology and birefringence microscopy</title>", "<p>Corneal halves were fixed in paraformaldehyde (paraformaldehyde in 0.05 M phosphate-buffered saline-PBS, pH 7.4) for 4 h at room temperature and then rinsed in phosphate buffer. The corneas were dehydrated in graded alcohol washes and embedded in paraffin. Ultra-thin sections were cut on a microtome (5 μm) and stained with hematoxylin-eosin (H&amp;E) for standard morphology [##UREF##1##30##].</p>", "<p>For fluorescence microscopy with DAPI, the fixed tissue fragments were rinsed with PBS, embedded in tissue freezing medium, and stored at -20 °C. Cryostat cross-sections were taken from the corneal central area, air dried and stained with DAPI (1:1000 dilution in PBS) for 5 min to localize cell nuclei. Sections were analyzed under conventional fluorescence microscopy or confocal microscopy [##REF##2205186##31##].</p>", "<p>For birefringence analysis, 8 μm sections of human corneal buttons were used after rehydration. All observations were carried out with transmitted polarized light using a Zeiss microscope (40X). The optical retardation was measured by means of a quarter-wave plate at a wavelength of 546 μm [##REF##4225247##32##]. The corneas were examined with polarized light microscopy 24 h after LASIK. The Sènarmont compensator is connected to the light microscope, so the anisotropic specimen (the human cornea) is oriented in a subtractive position that at some tilt angle extinction occurs, provided the compensator's range is sufficient for the sample. Compensators consist of thin-sections of minerals (e.g., quartz, calcite, gypsum/selenite, mica, etc.), or polymer film equivalents, whose thickness and optical orientation are carefully controlled so as to provide known values of retardation and known direction of high and low refractive indices. When introduced into the light path of a polarizing microscope, these known retardation values and refractive index directions are superimposed on an unknown anisotropic specimen and, by noting the resultant effects (addition or subtraction of retardation, etc.), give valuable identifying characteristics of the sample. The specific axis and magnitude of the cornea collagen fibrils is determined by first imaging the cornea without compensation. However, in uncompensated scans, a nonuniform retardation pattern is present. The statistical significance was calculated using analysis of variance between groups (ANOVA).</p>" ]

[ "<title>Results</title>", "<p>##FIG##0##Figure 1## shows a representative electrophoresis of proteoglycans extracted from control (right, R) and LASIK-treated (left, L) corneal explants, stained with toluidine blue (total proteoglycans) and detected by radioautography of the agarose gel slabs (metabolically labeled ³⁵S-proteoglycans, synthesized during the last 24 h). The main labeled band, observed in all samples, migrated slightly less than the standard heparan sulfate. A minor band of faster migration was observed in some samples (2 and 4 in ##FIG##0##Figure 1##). The total amounts of proteoglycans extracted for each cornea pair were roughly the same, based on toluidine blue staining, indicating that no variations occurred in the extraction yields. The ³⁵S-labeling was found to be greatly decreased in LASIK-treated corneas (see radioautogram, \"R\" versus \"L\" for each pair).</p>", "<p>##FIG##1##Figure 2## shows the individual paired results. A decrease in ³⁵S-sulfate incorporation in proteoglycans was observed in all cases after LASIK.</p>", "<p>In order to check if the biosynthesis of all proteoglycans was affected, the glycosaminoglycan chains were released from the protein cores by proteolysis. They were identified by a combination of agarose gel electrophoresis and enzymatic degradation with specific glycosaminoglycan lyases, as described in Methods.</p>", "<p>The electrophoretic migration of the glycosaminoglycan chains released from the core proteins by proteolysis is shown in ##FIG##2##Figure 3##. Upon incubation of the proteoglycans with papain, the band(s) corresponding to proteoglycans completely disappeared, and one band, migrating as dermatan sulfate and keratan sulfate, appeared upon toluidine blue staining. Nevertheless, on radioautogram, a second band, migrating as heparan sulfate, could also be detected. Chondroitin sulfate was not found.</p>", "<p>To confirm the glycosaminoglycan identification, these compounds were incubated with specific glycosaminoglycan lyases. Upon the action of <italic>F. heparinum</italic> chondroitinase B, dermatan sulfate was degraded to oligosaccharides and disaccharides that were not fixed in the gel [##REF##2158##33##]. The band migrating as heparan sulfate disappeared upon the action of heparitinase II, and upon the action of keratanase, keratan sulfate was digested. <italic>F. heparinum</italic> chondroitinase AC had no effect upon corneal glycosaminoglycan, confirming that chondroitin sulfate was not present and corneal dermatan sulfate is predominantly a L-iduronic acid containing polymer. ##FIG##3##Figure 4## shows the mean±standard error of all the samples (three determinations for each sample), obtained after release of the glycosaminoglycan chains by proteolysis of the ³⁵S-labeled proteoglycans. The synthesis of all glycosaminoglycans decreased after LASIK, but the synthesis of dermatan sulfate decreased more, leading to a decrease in the relative proportion of this glycosaminoglycan. The degradation products formed after the action of the glycosaminoglycan lyases were the same for LASIK-treated and control corneas, indicating that this decrease in ³⁵S-sulfate incorporation is not due to the synthesis of undersulfated proteoglycans.</p>", "<p>##FIG##4##Figure 5## shows a representative polyacrylamide gel electrophoresis of the proteoglycans [##REF##140178##34##] extracted from human corneal explants after LASIK. This analysis was performed for all samples. It showed that only low molecular weight proteoglycans (probably of the decorin/biglycan and lumican/mimecan families) are present in human cornea, both before and after LASIK.</p>", "<p>##FIG##5##Figure 6## shows representative images of H&amp;E and DAPI staining of corneas submitted to LASIK ##FIG##5##Figure 6B,D## and their respective controls ##FIG##5##Figure 6A,C##. H&amp;E analysis did not show any histological alteration after LASIK procedure. DAPI staining showed a reduction in the number of cell nuclei seems to occur after LASIK (quantitative data not yet available).</p>", "<p>##FIG##6##Figure 7## illustrates typical birefringence images of a normal (##FIG##6##Figure 7A,C##) and a LASIK-treated cornea (##FIG##6##Figure 7B,D##), with dark and bright shadows and also some visible irregularities in the intensity. The corneal collagen fibrils were oriented 45° from the polarizer azimuths, allowing maximum shining of the fibrils. Sample ##FIG##6##Figure 7A## represents the control cornea section without compensation. In this human corneal section, collagen fibrils are seen as either parallel aligned linear structures or as hexagonal arranged structures. ##FIG##6##Figure 7C## represents the same corneal micrograph with compensation to allow the measurements of optical retardation values. In birefringence images of human corneal sections after LASIK (##FIG##6##Figure 7B,D##), only minor differences were observed in collagen fibril alignments when compared to the control cornea. These differences are evident after obtaining statistical analysis of the quantitative data of optical retardation (##TAB##1##Table 2##). Eighty-two measurements were performed for each corneal group (Control and LASIK) in different regions of corneal slices. Note that there is a significant decrease in optical values after LASIK, in comparison to the control group.</p>" ]

[ "<title>Discussion</title>", "<p>The relevance of the regular diameter and distribution of collagen fibrils in stroma for corneal transparency is well documented [##REF##13429485##9##] as well as the effects of proteoglycans of the SLRP or \"fibrillar\" family upon the collagen fibrilogenesis and extracellular matrix assembly (review in [##REF##12886457##10##]). This is especially important in processes, such as corneal wound healing, that could lead to corneal haze and opacity, affecting both tissue transparency and biomechanics. These are serious concerns in refractive surgery. The organization of collagen fibrils in corneal stroma may be assessed by birefringence studies [##REF##10590014##35##, ####REF##10590013##36##, ##REF##11070369##37##, ##REF##15629652##38##, ##REF##16505022##39####16505022##39##], and the proteoglycans present are usually identified by immunohistochemical studies [##REF##10445718##40##]. Nevertheless, these latter studies localize all the proteoglycans present in the tissue - not just those synthesized after the surgical procedures - and do not permit the structural characterization of proteoglycans.</p>", "<p>Biochemical analyses of human corneas after LASIK are rare [##REF##10646146##41##]. Most studies have been performed in experimental animals [##REF##10374167##42##, ####REF##8970022##43##, ##REF##115885##44####115885##44##]. The main proteoglycans of human corneal stroma are keratan sulfate and dermatan sulfate [##REF##2946580##25##,##REF##8645702##29##,##REF##1544783##45##]. In our study, the distribution of these compounds was only slightly altered several months after LASIK [##REF##12686254##46##]. Quantock et al. [##REF##12686255##47##] showed that sulfated proteoglycans exist in rabbit corneas healing from lamellar incisions one, two, and three weeks after the surgical procedure. A recent clinico-pathological study of two human corneas that had received successful LASIK treatment reported an active wound-healing response at the flap-bed interface with identification of periodic acid Schiff-positive, electron-dense, material three months postoperative [##REF##11879131##48##].</p>", "<p>Our study used human corneas because morphological investigations have shown that, when this tissue is treated in vitro with LASIK and then maintained in culture for different periods, there are striking clinical similarities in LASIK-treated human and rabbit eyes [##REF##14967288##49##]. As the inflammatory response after LASIK is low and no inflammatory cells usually enter the cornea, the in vivo situation is likely to be independent of systemic factors that are absent in vitro [##REF##10535863##50##,##REF##11019867##51##].</p>", "<p>Although several groups have studied the glycosaminoglycan composition of cornea as well as the biosynthesis of proteoglycans by rabbit and embryonic chicken corneal explants [##REF##12886457##10##,##REF##1370446##12##,##REF##1605630##20##], there are few reports concerning human corneal proteoglycans [##REF##7558030##14##,##REF##2946580##25##,##REF##8645702##29##]. The aim of our study was to investigate the effects of LASIK upon proteoglycan synthesis by corneal human explants.</p>", "<p>We found all human corneal explants were able to incorporate ³⁵S-sulfate in proteoglycans, but variations occurred in the biosynthesis rate among different corneal pairs. These variations could not be attributed to single features, such as donor age or time period between donor death and experiments, but are possibly due to the combined interference of multiple biological conditions.</p>", "<p>Nevertheless, in all cases reported here, a marked decrease in ³⁵S-sulfate incorporation in proteoglycans occurred during the first 24 h after LASIK, in comparison to their respective matched controls. This could be due, at least in part, to the synthesis of undersulfated proteoglycans, but structural analysis with specific glycosaminoglycan lyases revealed no changes in the sulfation degree. This decrease in label incorporation possibly reflects a decrease in the proteoglycan synthesis rate.</p>", "<p>The synthesis of all proteoglycans was disturbed, but dermatan sulfate proteoglycans were the most strongly affected. This is not surprising, since the main proteoglycans synthesized in a 24 h period by human corneal explants are dermatan sulfate proteoglycans [##REF##2946580##25##,##REF##8645702##29##]. Keratan sulfate proteoglycans are synthesized at lower rates, and heparan sulfate proteoglycans are minor components of the cornea. Moreover, only low molecular weight proteoglycans were detected. High molecular weight proteoglycans, such as versican (which could be synthesized as a healing response), could not be detected.</p>", "<p>This conspicuous decrease in proteoglycan synthesis could be due to epithelial lesion induced by the lamellar cut created by the microkeratome as well as to stromal photoablation with excimer laser. However, the 50-60-μm-thick region ablated by LASIK from the 6 mm central area of the cornea corresponds to about 4% of total stromal tissue, and the decrease in ³⁵S-sulfate incorporation in proteoglycans was close to 90%. This clearly indicates that the ablated tissue could not be the only factor responsible for the enormous decrease in proteoglycan synthesis reported here. Keratocyte cell death could possibly be also implicated.</p>", "<p>Light microscopy did not reveal any traces of corneal wound healing. Again, this is not surprising since this is an acute in vitro study. Beneath the flap, corneal collagen bundles seemed to be uniform and regular, but upon birefringence studies, some degree of fiber dearrangements could be observed. There was a decrease in optical retardation values following LASIK, leading to a decreased molecular corneal organization, that may be related to the conspicuous changes in proteoglycan synthesis.</p>", "<p>In conclusion, the data here presented indicate a marked decrease in proteoglycan synthesis and changes in corneal collagen organization 24 h after in vitro LASIK surgery in human cornea.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>To evaluate the acute effects of laser in situ keratomileusis (LASIK) upon the synthesis of proteoglycans (PGs) and collagen fibril organization in human corneal explants.</p>", "<title>Methods</title>", "<p>Human corneas that had been rejected for transplants were obtained at Banco de Olhos of Hospital São Paulo. For each eye pair, one cornea was submitted to refractive surgery, and the other was used as its matched control. After surgery, the corneas were excised from the eyes and immediately placed in a Ham F-12 nutrient mixture containing ³⁵S-sulfate for the metabolic labeling of PGs. After 24 h incubation, PGs were extracted and identified by a combination of agarose gel electrophoresis and enzymatic degradation with protease and specific glycosaminoglycan lyases. Histopathological and birefringence analysis were performed in fixed tissue slices.</p>", "<title>Results</title>", "<p>A marked decrease in ³⁵S-sulfate incorporation in PGs was observed in corneal explants that received LASIK, especially concerning dermatan sulfate-PGs, with keratan sulfate- and heparan sulfate-PG synthesis reduced to a lower degree. Only low molecular weight PGs were present in the corneas, both before and 24 h after LASIK. No sign of wound healing processes were observed, but a marked change in corneal birefringence was seen following LASIK treatment.</p>", "<title>Conclusions</title>", "<p>Laser application led to decreased PG biosynthesis in human corneal explants, with marked changes in the collagen fibril organization, as revealed by changes in the tissue birefringence.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>This work was aided by grants from Conselho Nacional de Desenvolvimento Centífico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa do Estado de São Paulo, and Associação Paulista para o Desenvolvimento da Medicina (SPDM).</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Agarose gel electrophoresis of proteoglycans extracted from human corneal explants. The left (L) cornea of each pair was submitted to LASIK, and the right (R) cornea was its matched control. The corneal explants were maintained under tissue culture conditions for 24 h in the presence of ³⁵S-sulfate for the metabolic labeling of proteoglycans. The proteoglycans were extracted as described in Methods, and aliquots (5 μl) were submitted to agarose gel electrophoresis, as also described in Methods. The proteoglycans were fixed in the gel and stained by toluidine blue (<bold>A</bold>), and the ³⁵S-labeled proteoglycans were localized by radioautography (<bold>B</bold>). In the images, S indicates a mixture of standard glycosaminoglycans containing chondroitin sulfate (CS), dermatan sulfate (DS), and heparan sulfate (HS), 5 μg each. KS indicates keratan sulfate. The numbers 1, 3, 9, and 12 refer to the corneal pairs described in ##TAB##0##Table 1##.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Effect of LASIK upon proteoglycan synthesis by human corneal explants. The experiments were performed as described in ##FIG##0##Figure 1##, except that individual data are presented. The numbers in the insert box refer to the corneal pairs described in ##TAB##0##Table 1##, and each point is the mean value of three determinations.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>Agarose gel electrophoresis of glycosaminoglycans released by proteolysis from proteoglycans extracted from human corneal explants after LASIK. The proteoglycans extracted from pair number 12 (see ##TAB##0##Table 1##) of human corneal explants underwent proteolysis with papain for release of the glycosaminoglycan chains. Aliquots of the incubation mixtures were submitted to agarose gel electrophoresis. Total proteoglycans (PG) and glycosaminoglycans (GAG) were stained by toluidine blue (<bold>A</bold>), and the ³⁵S-labeled glycosaminoglycans (³⁵S-GAG) were localized by radioautography (<bold>B</bold>). S: A mixture of standard glycosaminoglycans containing chondroitin sulfate (CS) dermatan sulfate (DS), and heparan sulfate (HS), 5 μg each; KS, keratan sulfate; PG, intact proteoglycans.</p></caption></fig>", "<fig id=\"f4\" fig-type=\"figure\" position=\"float\"><label>Figure 4</label><caption><p>Effect of LASIK upon the synthesis of ³⁵S-dermatan sulfate, ³⁵S-keratan sulfate, and ³⁵S-heparan sulfate by human corneal explants. Shown are the ³⁵S-sulfate incorporation (<bold>A</bold>; cpm, mean±standard error, three determinations for each sample) and the ratio between LASIK and control (<bold>B</bold>). The identification of each glycosaminoglycan was based on a combination of agarose gel electrophoresis and enzymatic degradation with specific glycosaminoglycan lyases (chondroitinases, keratanase and heparitinase).</p></caption></fig>", "<fig id=\"f5\" fig-type=\"figure\" position=\"float\"><label>Figure 5</label><caption><p>Polyacrylamide gel electrophoresis of proteoglycans extracted from human corneal explants. Aliquots (5 μl) of proteoglycans extracted from pair number 1 (see ##TAB##0##Table 1##) of human corneal explants were submitted to polyacrylamide gel electrophoresis, as described in Methods. The gel was stained with coomassie blue (<bold>A</bold>), and the ³⁵S-labeled compounds were localized by radioautography (<bold>B</bold>). St: molecular weight standard proteins; C: control cornea; L: LASIK submitted cornea.</p></caption></fig>", "<fig id=\"f6\" fig-type=\"figure\" position=\"float\"><label>Figure 6</label><caption><p>Hematoxilin and eosin staining and fluorescence microscopy for nuclei (DAPI) of normal and LASIK-treated corneal explants. The experiment was performed as described in Methods. Ep: epithelium; If: interface after LASIK; St: stroma. The scale bar equals 50 μm.</p></caption></fig>", "<fig id=\"f7\" fig-type=\"figure\" position=\"float\"><label>Figure 7</label><caption><p>Control and LASIK human cornea birefringence images. The experiment was performed as describe in Methods, with (<bold>C</bold>,<bold>D</bold>) and without (<bold>A</bold>,<bold>B</bold>) compensation, for control (<bold>A</bold>,<bold>C</bold>) and LASIK-submitted (<bold>B</bold>,<bold>D</bold>) corneal slices. The samples are positioned 45° from the polarizer azimuth. Ep: epithelium; St: stroma; End: endothelium. The scale bar is equal to 20 μm.</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title>Demographics of LASIK and control corneas.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"87\" span=\"1\"/><col width=\"86\" span=\"1\"/><col width=\"89\" span=\"1\"/><col width=\"91\" span=\"1\"/><col width=\"87\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Cornea samples (pairs)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Cornea type</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Location* (OD/OS)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Donor (Age (y)/Gender)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Time interval (Death-LASIK)</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">61/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">6 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">61/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">6 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">58/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">58/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">20/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">20/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">4<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">47/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">47/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">53/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">6 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">53/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">6 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">6<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">74/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">12 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">74/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">12 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">72/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">24 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">72/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">24 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">66/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">48 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">66/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">48 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">9<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">68/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">68/F<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">75/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">75/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">62/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">62/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">12<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">LASIK<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OS<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">64/M<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"/><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">Control</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">OD</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">64/M</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">10 h</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t2\" position=\"float\"><label>Table 2</label><caption><title>Optical retardation mean values for control cornea and cornea submitted to LASIK, embedded in water.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"112\" span=\"1\"/><col width=\"108\" span=\"1\"/><col width=\"110\" span=\"1\"/><col width=\"112\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Cornea samples</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>N</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>OR</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>p</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Control<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">82<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">24.96<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">&lt;0.0001<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">LASIK</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">82</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">17.92</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>LASIK was performed in 12 corneoscleral buttons from 12 donors. The 12 contralateral corneoscleral buttons were kept intact and used as controls.</p></table-wrap-foot>", "<table-wrap-foot><p>Statistical significance was calculated by analysis of variance between groups (ANOVA), as described in the text. Eighty-two measurements were performed for each corneal group (Control and LASIK) in different regions of corneal slices. In the table, \"N\" indicates the number of measurements for each group, \"OR\" indicates the optical retardation value, and \"p\" denotes the significance level.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-142-f1\"/>", "<graphic xlink:href=\"mv-v13-142-f2\"/>", "<graphic xlink:href=\"mv-v13-142-f3\"/>", "<graphic xlink:href=\"mv-v13-142-f4\"/>", "<graphic xlink:href=\"mv-v13-142-f5\"/>", "<graphic xlink:href=\"mv-v13-142-f6\"/>", "<graphic xlink:href=\"mv-v13-142-f7\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Diabetes mellitus is the most prevalent endocrine disease in developed countries [##REF##9686691##1##], and diabetic retinopathy is the leading cause of blindness in the world [##REF##10051177##2##,##REF##11382558##3##]. Blood-retinal barrier (BRB) breakdown, increased vascular permeability and vascular leakage are early complications of diabetes and a major cause of diabetic macular edema [##REF##9706124##4##, ####REF##10460819##5##, ##UREF##0##6####0##6##]. As there is no satisfactory or noninvasive therapy, diabetic macular edema is a major cause of vision loss in diabetic patients [##REF##9250277##7##].</p>", "<p>An ideal treatment strategy would be to deliver a therapeutic gene with a vector that could confer long-term transgene expression and tissue protection with a single administration. We have previously reported that a recombinant adeno-associated virus vector expressing angiostatin (rAAV-angiostatin) suppressed laser-induced choroidal neovascularization [##REF##11527956##8##]. Recently, an effect of angiostatin in reducing vascular permeability in the retina in diabetic and oxygen-induced retinopathy models was reported [##REF##15094037##9##].</p>", "<p>Angiostatin (Kringles 1 through 4) is a proteolytic fragment of plasminogen [##REF##7525077##10##]. It was identified as a potent angiogenic inhibitor, which blocks neovascularization and suppresses tumor growth and metastases [##REF##7525077##10##,##REF##9576925##11##]. Angiostatin specifically inhibits proliferation, induces apoptosis in vascular endothelial cells [##REF##15150128##12##], and downregulates vascular endothelial growth factor (VEGF), the latter via inactivation of the p42/p44 MAP kinase pathway [##REF##15094037##9##,##REF##8606491##13##,##REF##9519746##14##]. We also noted that some proteolytic fragments of plasminogen can induce upregulation of pigment epithelium-derived factor (PEDF) expression, a potent angiogenic inhibitor in experimental diabetes [##REF##11782462##15##].</p>", "<p>BRB breakdown may be due to disassembly of unique proteins that constitute the functional vascular endothelial tight junction [##REF##10758225##16##, ####REF##10896336##17##, ##REF##15109567##18####15109567##18##]. VEGF is a potent angiogenic factor [##REF##8606491##13##], whose overproduction in the retina has been noted in the development of vascular hyperpermeability in diabetes [##REF##9519746##14##]. Furthermore, VEGF affects the tight junction protein occludin, inducing occludin phosphorylation [##REF##10438525##19##] and redistribution [##REF##11006253##20##]; resultant occludin reduction is associated with BRB breakdown in diabetes [##REF##9836530##21##].</p>", "<p>The present study was designed to examine the transgenic expression of rAAV-angiostatin in the eye and its effect on vascular permeability in the streptozotocin (STZ)-induced diabetic model. Since it has been demonstrated angiostatin can induce the downregulation of VEGF through the blockade of phosphorylation of p42/p44 MAP kinase [##REF##15094037##9##,##REF##8606491##13##,##REF##9519746##14##], we also studied the relationship between rAAV-angiostatin, p42/p44 MAP kinase, occludin, VEGF, and PEDF in this model.</p>" ]

[ "<title>Methods</title>", "<title>Animals</title>", "<p>Male Sprague-Dawley (SD) rats (Charles River Laboratories, WilmingtonMA) weighing approximately 200 g on arrival were used in this study. The animals were cared for in accordance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. All experimental procedures used aseptic sterile techniques and were approved by the Animal Care and Use Committee of the Mackay Memorial Hospital.</p>", "<title>Generation of rAAV-angiostatin</title>", "<p>cDNA coding for angiostatin was amplified by polymerase chain reaction (PCR) according to a published report [##REF##9486976##22##]. rAAV encoding mouse angiostatin cDNA or lacZ were constructed by using a three-plasmid cotransfection system as described previously [##REF##9486976##22##, ####REF##10074195##23##, ##REF##9499080##24####9499080##24##]. Titers of rAAV-angiostatin and rAAV-lacZ were determined by dot blot hybridization using angiostatin cDNA and lacZ as probes [##REF##10693868##25##].</p>", "<title>Intravitreal injections of rAAV-angiostatin</title>", "<p>After being anesthetized, each animal received an intravitreal injection of rAAV- angiostatin (5 μl, 1.5x10¹⁰ viral particles) as described previously [##REF##14961006##26##]. The contralateral eye of each rat was injected with rAAV-lacZ to serve as a control.</p>", "<title>Experimental Diabetes</title>", "<p>Experimental diabetes was induced three weeks after intravitreal injection of rAAV. Diabetes was induced with a single 60 mg/kg intravenous injection of streptozotocin (Sigma-Aldrich, St. Louis, MO) in 10 mM citrate buffer, pH 4.5. Animals that served as nondiabetic controls received an equivalent amount of citrate buffer alone [##REF##9836530##21##] Twenty-four h later, rats with blood glucose levels higher than 250 mg/dl were deemed diabetic. These diabetic rats received 6-8U NPH insulin (Lilly, Indianapolis, IN) once a week to prevent ketoacidosis. Just before experimentation, blood glucose levels were measured again to confirm diabetic status.</p>", "<title>Reverse transcription-polymerase chain reaction</title>", "<p>Expression of rAAV-angiostatin in retina was confirmed by RT-PCR according to a protocol described in reference [##REF##11527956##8##]. Each rat eye that was previously injected with rAAV-angiostatin and rAAV-lacZ was enucleated, and chorioretinal tissues were harvested for RT-PCR at 1, 5, 10, and 15 days after induction of experimental diabetes. The cDNA was synthesized using oligo(dT) primer and 200 IU transcriptase (SuperScript II; Life Technologies, Carlsbad, CA) according to the manufacturer's instructions. PCR amplification was performed with two oligonucleotide primers, 5'-CAG CAA TGC GTG ATC ATG-3' and 5'-TGG AGA TTT TGC CCT CAT AC-3'. As a control, PCR amplification was performed for glyceradehyde-3-phosphate dehydrogenase (GAPDH) with two oligonucleotide primers, 5'-GGA AGG GCT CAT GAC CAC AG-3' and 5'-CCT TTA GTG GGC CCT CGG-3'. To rule out the possibility that gene amplification products were derived from amplification of contaminating angiostatin genomic DNA, we treated the total RNA with RNase free DNase I (Qiagen, Valencia, CA) before RT-PCR.</p>", "<title>Immunofluorescence assay</title>", "<p>Five-μm-thick retinal tissue sections from formalin-fixed, paraffin-embedded blocks were transferred to positively charged slides to be used for staining. Sections were dewaxed in xylene and progressively hydrated [##REF##15331199##27##]. They were then washed three times with PBS and a 1:400 dilution of polyclonal rabbit antihuman albumin antibody (DAKO Diagnostics. Mississauga, ON, Canada) was applied. A fluorescein isothiocyanate (FITC)-conjugated antimouse IgG was used as a secondary antibody. The results were viewed with a fluorescence microscope (Zeiss Axioplan HBO100, Oberkochen, Germany).</p>", "<title>Measurement of leakage with intravascular injected FITC-BSA</title>", "<p>Retinal vascular leakage was measured using the intravascular injected FITC-BSA as previously described [##REF##9836530##21##,##REF##2521787##28##] with some modifications. After induction of anesthesia, the rats received tail vein injections of 100 mg/kg FITC-bovine serum albumin (FITC-BSA, Sigma-Aldrich). The animals were sacrificed 20 min later, and their eyes were removed, embedded in OCT medium, and snap-frozen in liquid nitrogen. The plasma was collected and assayed for fluorescence with an SPEX fluorescence spectrophotometer (Molecular Devices, Sunnyvale, CA) based on standard curves of FITC-BSA in normal rat plasma. Frozen retinal sections (6 μm thick) collected every 60 μm were viewed with a Zeiss Axioplan HBO100 fluorescence microscope. Images from six retinal nonvascular areas (200 μm²) in each section were collected. Quantification of FITC-BSA fluorescence intensity was calculated by computer software Q-win (Leica, Wetzlar, Germany) and normalized to plasma fluorescence intensity for each animal.</p>", "<title>Western blot analysis of VEGF, PEDF, occludin, and p42/p44 MAP kinase</title>", "<p>Rats were sacrificed, and their eyes were removed for western blotting analysis at 1, 5, 10, and 15 days after STZ treatment. The chorioretinal tissue was harvested, and the soluble fractions were prepared by homogenizing the retina in Eppendorf tubes containing RIPA lysis buffer (50 mM Tris, 150 mM NaCl, 10 mM EDTA, 0.1% SDS, 1% NP-40, 0.5% sodium deoxycholate, 1 mM Na₃VO₄, 1 mM NaF, 1 mM EGTA, 1 mM PMSF, 1 mg/ml leupeptin, and 1 mg/ml pepstatin A). Proteins (50 μg) were extracted for electrophoresis on 10% SDS-polyacrylamide gels. The membranes were incubated with antibody specific to VEGF [##REF##15109917##29##,##REF##7583283##30##], PEDF [##REF##11165263##31##], p42/p44 MAP kinase [##REF##9836530##21##] (all from Santa Cruz Biotechnology, Inc., Santa Cruz, CA) and occludin [##REF##11006253##20##] (Zymed, San Francisco, CA). The results were semiquantified by densitometry (Fujifilm LAS3000, Tokyo, Japan) and normalized to actin levels.</p>", "<title>Cell culture and rAAV-angiostatin infection</title>", "<p>To further evaluate whether angiostatin could induce the expression of PEDF in endothelial cells, we infected human umbilical vein endothelial cells (HUVEC-2C, Cascade Biologics, Portland, OR) with rAAV-angiostatin. The HUVEC-2C cells were cultured in medium 200 (Cascade Biologics) containing low serum growth supplement. All cells were supplemented with 1% penicillin-streptomycin and maintained at 37 °C and 5% CO₂. Confluent cells obtained during the fifth passage were used for rAAV-angiostatin infection. The HUVEC-2C cells were infected by rAAV-angiostatin in Dulbeco's modified Eagle's medium for two days. Cell lysates were then prepared and analyzed for PEDF by western blotting as described in the previous paragraph.</p>", "<title>Statistical Analyses</title>", "<p>The results are expressed as the mean±SD. Retinal FITC-BSA fluorescence intensity was analyzed in serial retinal sections from four rats at 5, 10, and 15 days after induction of diabetes. Due to skewed distributions, data were subjected to logarithmic transformation for analysis. Differences of retinal FITC-BSA fluorescence intensity between eyes receiving rAAV-angiostatin and rAAV-lacZ injection at 5, 10, and 15 days after induction of diabetes were analyzed by a paired-sample Student's t test. The retinal expression of VEGF, PEDF, phosporylation of p42/p44 MAPK, and occludin were analyzed by the Wilcoxon signed-rank test. All p-values are two-tailed, and differences were considered to be statistically significant for p&lt;0.05.</p>" ]

[ "<title>Results</title>", "<title>Gene delivery by rAAV-angiostatin</title>", "<p>There was no angiostatin gene expression in normal control eyes (##FIG##0##Figure 1##, lane A) and eyes injected with rAAV-lacZ at 1, 5, 10, and 15 days after induction of diabetes (##FIG##0##Figure 1##, lanes B-E). In the eyes injected with rAAV-angiostatin, angiostatin gene expression was detected at 1, 5, 10, and 15 days after induction of diabetes (##FIG##0##Figure 1##, lanes F-I). As an internal control, expression of GAPDH was detected in normal control eye and eyes receiving both rAAV-angiostatin and rAAV-lacZ injections (##FIG##0##Figure 1##, lanes A-I).</p>", "<title>Induction of experimental diabetes</title>", "<p>Animals (n=12) with a blood glucose exceeding 250 mg/dl were selected for inclusion in the diabetic group. All diabetic animals had higher blood glucose levels and reduced body weight gain at 5, 10, and 15 days after induction of diabetes compared to age-matched, nondiabetic control animals (##TAB##0##Table 1##).</p>", "<title>rAAV-angiostatin influence on vascular permeability</title>", "<p>One week after induction of diabetes, the immunofluorescence assay, using anti-albumin antibody, disclosed staining only inside blood vessels in normal control eyes (##FIG##1##Figure 2A##). Increased extravascular albumin in the retinal parenchyma was seen in the eyes of diabetic animals receiving rAAV-lacZ (##FIG##1##Figure 2B##). In the diabetic animals receiving rAAV- angiostatin, however, albumin staining was observed only inside blood vessels (##FIG##1##Figure 2C##).</p>", "<p>To confirm the effect of rAAV-angiostatin on vascular permeability, we examined animals injected with intravenous FITC-BSA 5, 10, and 15 days after induction of diabetes. ##FIG##2##Figure 3## shows representative micrographs of the eyes of normal control and STZ-induced diabetic rats. FITC-BSA fluorescence is limited to the vasculature in the normal retina (##FIG##2##Figure 3B##) and diffusely increased throughout the retinal parenchyma at 5 days after STZ-induced diabetes in eyes receiving rAAV-lacZ injection (##FIG##2##Figure 3C##). Increased fluorescence intensity throughout the retinal parenchyma is still present at 10 (##FIG##2##Figure 3D##) and 15 (##FIG##2##Figure 3E##) days after STZ-induced diabetes in eyes receiving rAAV-lacZ injection. Little fluorescence was present in the retinal parenchyma in eyes receiving rAAV-angiostatin injection (##FIG##2##Figure 3F##) at 5 days after induction of diabetes. Retinal parenchyma fluorescence at 10 (##FIG##2##Figure 3G##) and 15 (##FIG##2##Figure 3H##) days after induction of diabetes in eyes with rAAV-angiostatin injection was decreased as compared with eyes that received the rAAV-lacZ injection.</p>", "<p>The retinal FITC-BSA fluorescence intensity was calculated and normalized to plasma fluorescence intensity by image analysis of serial sections (##FIG##3##Figure 4##). Four SD rats were represented by the number of sections to be examined at each timepoint. The mean retinal FITC-BSA fluorescence intensity in eyes receiving rAAV-angiostatin injection was 2.99±0.62 pixels at 5 days, 3.42±0.38 pixels at 10 days, and 3.30±0.40 pixels at 15 days after induction of diabetes. The retinal FITC-BSA fluorescence intensity in eyes receiving rAAV-lacZ injection was 3.59±0.31 pixels at 5 days, 3.77±0.51 pixels at 10 days, and 3.71±0.47 pixels at 15 days after induction of diabetes. Quantitative analysis showed that the fluorescence was decreased in eyes receiving rAAV-angiostatin as compared to eyes receiving rAAV-lacZ at 5 days (t=3.67, n=49, p=0.001), 10 days (t=3.94, n=51, p&lt;0.001), and 15 days (t=3.52, n=56, p=0.001) after induction of diabetes.</p>", "<title>rAAV-angiostatin influence on occludin loss</title>", "<p>Rats receiving rAAV-angiostatin in their right eyes and rAAV-lacZ in their left eyes were sacrificed, and their eyes were enucleated for western blotting analysis at 1, 5, 10, and 15 days after induction of diabetes. The retinal occludin content in normal control eye was 42.35±2.67 pixels. No differences in retinal occludin content were detected between eyes receiving rAAV-lacZ and rAAV-angiostatin injection at 1 (rAAV-lacZ: 45.82±3.08 pixels, rAAV-angiostatin: 43.62±2.78) and 5 days (rAAV-lacZ: 38.96±2.22 pixels, rAAV-angiostatin: 40.65±3.46 pixels) after induction of diabetes. Ten days after diabetes induction, retinal occludin content in eyes that received rAAV-lacZ was 11.35±3.57 pixels and 34.73±3.17 pixels in eyes that received rAAV-angiostatin occludin, a statistically significant reduction (n=5, p=0.041, ##FIG##4##Figure 5##). The retinal occludin content in rAAV-lacZ-treted eyes was higher (26.32±3.46 pixels) at 15 days after induction of diabetes than it was at 10 days, and there was no difference in rAAV-angiostatin-treated animals (29.21±2.94 pixels).</p>", "<title>rAAV-angiostatin influence on VEGF expression</title>", "<p>One day after diabetes induction, we observed rAAV-angiostatin-mediated influence of retinal VEGF expression. The retinal VEGF expression in normal control SD rat was 7.56±1.25 pixels. Retinal VEGF was 13.7±3.78 pixels (n=6) in rAAV-lacZ-treated eyes and decreased to 8.69±3.23 pixels (n=6) in rAAV-angiostatin-treated eyes (##FIG##5##Figure 6, p##=0.043). The retinal VEGF expression in eyes receiving rAAV-lacZ was 11.45±2.73 pixels at 5 days, 9.12±3.12 pixels at 10 days, and 10.41±3.36 pixels at 15 days after induction of diabetes. The retinal VEGF expression in rAAV-angiostatin-treated eyes was 9.52±3.96 pixels at 5 days, 8.31±2.67 pixels at 10 days, and 10.16±3.36 pixels at 15 days after induction of diabetes. There was no statistical difference in retinal VEGF expression in rAAV-lacZ- and rAAV-angiostatin-treated eyes at 5, 10, and 15 days after induction of diabetes.</p>", "<title>PEDF expression</title>", "<p>There was no significant difference in retinal PEDF expression between eyes exposed to rAAV-angiostatin and rAAV-lacZ at 1, 5, 10, or 15 days after STZ injection (##FIG##6##Figure 7A##). To further evaluate if rAAV-angiostatin could influence PEDF expression, we infected HUVEC-2C cells with rAAV-angiostatin. No PEDF expression was detected in rAAV-angiostatin-infected HUVEC-2C cells (##FIG##6##Figure 7B##). Western blot analysis of PEDF plasmid-transfected HUVEC-2C cells was used as a positive control.</p>", "<title>rAAV-angiostatin-mediated downregulation of phospho-p42/p44 MAP kinase</title>", "<p>The retinal phosphor-p42/p44 MAP kinase level of normal control SD rat was 7.03±1.22 pixels. At one day after STZ injection, retinal phosphor-p42/p44 MAP kinase levels were 7.43±0.93 pixels (n=5) in eyes receiving rAAV-lacZ, and was decreased to 4.58±1.36 pixels(n=5) in eyes receiving rAAV-angiostatin (##FIG##7##Figure 8, p##=0.043). No effect was observed at 5 days after STZ injection (5.64±1.28 pixels for eyes receiving rAAV-lacZ, and 5.44±1.65 pixels for eyes receiving rAAV-angiostatin), 10 days (5.13±0.92 pixels for eyes receiving rAAV-lacZ, and 5.97±1.87 pixels for eyes receiving rAAV-angiostatin) and 15 days (7.37±1.33 pixels for eyes receiving rAAV-lacZ, and 7.25±2.65 pixels for eyes receiving rAAV-angiostatin)</p>" ]

[ "<title>Discussion</title>", "<p>Retinal vascular leakage is a major cause of macular edema in diabetic retinopathy and other retinal diseases [##REF##9686691##1##, ####REF##10051177##2##, ##REF##11382558##3##, ##REF##9706124##4##, ##REF##10460819##5##, ##UREF##0##6####0##6##]. Traditionally, laser photocoagulation has been used to reduce the vascular leakage induced by diabetes [##REF##7196564##32##,##REF##2866759##33##]. Recently, anti-inflammatory drugs such as triamcinolone [##REF##16205559##34##], or pars-plana vitrectomy with or without internal limiting membrane peeling [##REF##15860282##35##] have been used to attenuate the diabetic macular edema. Due to the duration and severity, an ideal strategy would be to develop an approach involving a single administration of a vector that would result in long-term expression of a suitable therapeutic gene [##REF##11827926##36##].</p>", "<p>rAAV vectors are highly efficient gene delivery systems which can facilitate long-term transduction [##REF##9486976##22##,##REF##10074195##23##]. We have previously reported in several animal models a gene transfer technique based on the use of rAAV vectors [##REF##11527956##8##,##REF##10074195##23##,##REF##10693868##25##,##REF##14961006##26##,##REF##12407159##37##,##REF##11085892##38##]. This gene transfer technique is particularly attractive for treating ocular disease for reasons of accessibility and long term transduction, and potentially because it would enable clinicians to avoid repeated intravitreal injection [##REF##11527956##8##,##REF##12407159##37##]. We previously reported suppression of laser-induced choroidal neovascularization by an rAAV vector expressing angiostatin [##REF##11527956##8##]. Here, we report that vascular leakage in experimental diabetic rats can be reduced by angiostatin delivery via an rAAV vector. These results suggest that rAAV-angiostatin could be beneficial in the treatment of diabetic macular edema.</p>", "<p>Angiostatin is a proteolytic fragment of plasminogen and contains kringle domains 1 through 4 [##REF##7525077##10##]. It has been determined that angiostatin is a potent anti-angiogenic factor [##REF##9576925##11##] that can inhibit endothelial cell migration and induce apoptosis in these cells [##REF##15150128##12##]. Recently, intravitreal injection of angiostatin was found to reduce vascular leakage in a rat model of experimental diabetes and in oxygen induced retinopathy [##REF##15094037##9##]. In the same report, the expression of VEGF was found to be downregulated by angiostatin.</p>", "<p>VEGF is a potent angiogenic factor, expression of which is increased in eyes with diabetic retinopathy [##REF##8606491##13##,##REF##9519746##14##]. VEGF, which is also known as vascular permeability factor (VPF) [##REF##9134347##39##], increases microvascular permeability at very low concentrations [##REF##9134347##39##], and may be important in the pathogenesis of vascular leakage induced by diabetes [##REF##2155059##40##]. Angiostatin-induced reduction of vascular leakage occurs through blockade of VEGF expression [##REF##11782462##15##]. In our study, retinal VEGF expression decreased in eyes receiving rAAV-angiostatin as compared to rAAV-lacZ treated eyes at one and five days after induction of diabetes. Vascular leakage was also decreased in eyes receiving intravitreal injection of rAAV-angiostatin compared to the contralateral eyes receiving rAAV-lacZ injection at 5, 10, and 15 days after induction of diabetes.These results are consistent with previous reports that angiostatin reduces the vascular leakage via blockade of VEGF [##REF##8606491##13##, ####REF##9519746##14##, ##REF##11782462##15####11782462##15##,##REF##9134347##39##,##REF##2155059##40##]. How angiostatin reduces vascular leakage through inhibition of VEGF production is still under investigation.</p>", "<p>It is known that p42/p44 MAP kinase phosphorylation is induced by hypoxia [##REF##16106912##41##]. This phosphorylation is diminished by angiostatin in microvascular endothelial cells [##REF##10050071##42##]. Phosphorylation of p42/p44 MAP kinase promotes VEGF expression by activating its transcription via recruitment of the AP-2/Sp1 (activator protein-2) complex of the VEGF promoter [##REF##10865838##43##]. It is therefore plausible that inhibition of phosphorylation of p42/p44 MAP kinase by angiostatin suppresses VEGF expression under conditions of hypoxia. In our study, retinal phosphorylation of p42/p44 MAP kinase decreased in eyes receiving rAAV-angiostatin at one day after induction of diabetes (##FIG##7##Figure 8##). Our results in STZ-induced diabetic rats suggest that angiostatin suppresses VEGF expression by inhibition of phosphorylation of the p42/p44 MAP kinase.</p>", "<p>BRB breakdown is a hallmark of vascular leakage in diabetic retinopathy and other retinal vascular diseases [##REF##5919260##44##,##REF##655916##45##]. The tight junctions between the retinal vascular endothelial cells constitute an essential structured component of BRB [##REF##15109567##18##]. This barrier limits diffusion of molecules from vessel lumen to the tissue, and thereby maintains the microenvironment of the retina [##REF##15106951##46##]. The barrier protein occludin is decreased in experimental diabetes [##REF##9836530##21##]. VEGF stimulates phosphorylation and redistribution of occludin [##REF##10438525##19##], which is subsequently endocytosed and degraded [##REF##8276896##47##,##REF##9443899##48##]. This process is closely related to the elevated vascular permeability in experimental diabetes [##REF##15109567##18##]. In our study, retinal occludin content in STZ-induced diabetic rats was preserved in eyes receiving rAAV-angiostatin as compared to eyes receiving rAAV-lacZ. The rAAV-angiostatin-induced inhibition of VEGF may therefore suppress vascular leakage by preserving retinal occludin content in STZ-induced diabetic rats</p>", "<p>PEDF is a potent angiogenic inhibitor that is counter balanced by the angiogenic effect of VEGF [##REF##9255066##49##, ####REF##10398599##50##, ##REF##11434719##51####11434719##51##]. Decreased expression of PEDF in retina is associated with ischemia-induced retinal neovascularization and proliferative diabetic retinopathy [##REF##10398599##50##]. Recently, another proteolytic fragment of plasminogen-kringle 5 (K5) was noted to upregulate PEDF expression in a dose-dependent manner in vascular endothelial cells and in the retina [##REF##11782462##15##]. In our study, there was no statistically significant difference between PEDF expression in eyes receiving rAAV-angiostatin and the contralateral eyes receiving rAAV-lacZ. Our results also revealed that rAAV-angiostatin did not upregulate PEDF expression in HUVEC-2C cells. However, PEDF expression has been shown to be induced at both the mRNA and protein level following injury in the eye [##REF##16384991##52##]. Further research is warranted to explore the effect of rAAV-angiostatin on PEDF expression.</p>", "<p>Our study showed that transgenic expression of rAAV-angiostatin can reduce retinal vascular leakage in STZ-induced diabetic rats. This effect is associated with downregulation of retinal VEGF and phospho-p42/p44 MAP kinase expression, and a reduction in the retinal occludin loss induced by diabetes. However, the vascular leakage and VEGF expression after induction of diabetes in the SD rat model was demonstrated to be a short-term effect [##REF##15632023##53##]. Gene-based therapies can be as effective and viable as real treatment if long-term expression can be achieved. To demonstrate the long-term effect of rAAV-angiostatin on vascular leakage induced by diabetes, an alternative animal model such as the Brown-Norway rat could be used in a future study.</p>", "<p>Diabetic macular edema is a major cause of vision loss in diabetic patients [##REF##9250277##7##]. On the basis of these findings, we believe that a similar vector and therapeutic gene could eventually be a useful strategy for long-term preventive or adjunctive therapy for macular edema induced by diabetes. It could serve as the basis for an alternative treatment for patients who are suffering from diabetic macular edema as well as a potentially preventive therapeutic modality for diabetic patients who are at risk for development of macular edema.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>To evaluate the efficacy of recombinant adeno-associated virus (rAAV) vector expressing mouse angiostatin (Kringle domains 1 to 4) in reducing retinal vascular leakage in an experimental diabetic rat model.</p>", "<title>Methods</title>", "<p>rAAV-angiostatin was delivered by intravitreal injection to the right eyes of Sprague-Dawley rats. As a control, the contralateral eye received an intravitreal injection of rAAV-lacZ. Gene delivery was confirmed by reverse-transcriptase polymerase chain reaction (RT-PCR). Diabetes was induced by intravenous injection of streptozotocin (STZ). Vascular permeability changes were evaluated by extravascular albumin accumulation and leakage of intravenous-injected fluorescein isothiocynate-bovine serum albumin (FITC-BSA). Effects of rAAV-angiostatin on expression of vascular endothelial growth factor (VEGF), pigment epithelium-derived factor (PEDF), occludin, and phospho-p42/p44 MAP kinase in retina tissue were analyzed by western blotting.</p>", "<title>Results</title>", "<p>The rAAV-angiostatin injections led to sustained angiostatin gene expression in retina as confirmed by RT-PCR, and reduced extravascular albumin accumulation in STZ-induced diabetic retina. Further, rAAV-angiostatin significantly decreased intravascularly injected FITC-BSA leakage at 5 days (p=0.001), 10 days (p&lt;0.001), and 15 days (p=0.001) after STZ-induced diabetes, as compared to the control eyes receiving rAAV-lacZ. Expression of VEGF and phosphorylation of p42/p44 MAP kinase in retina was reduced by rAAV-angiostatin at day 1 (p=0.043 for both VEGF and phospho-p42/p44 MAP kinase) after STZ-induced diabetes compared with rAAV-lacZ eyes. rAAV-angiostatin reduced retinal occludin loss at 10 days after STZ-induced diabetes (n=5, p=0.041). There was no significant difference in retinal PEDF expression between eyes injected with rAAV-angiostatin and rAAV-lacZ.</p>", "<title>Conclusions</title>", "<p>Intravitreal delivery of rAAV-angiostatin reduces vascular leakage in an STZ-induced diabetic model. This effect is associated with a reduction in the retinal occludin loss induced by diabetes and downregulation of retinal VEGF and phosphor-p42/p44 MAP kinase expression. This gene transfer approach may reduce diabetic macular edema, providing protection in diabetic patients at risk for macular edema.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>The authors thank Hong-Kong Chen, Ju-Yun Wu, and I-Pin Choung for excellent technical support. This study was supported by grants from National Science Council, Taiwan (NSC 94-2314-B-95-002, NSC 95-3112-B-195-001) and from the Mackay Memorial Hospital (MMH-E-95006, MMH-9501).</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>RT-PCR analysis of angiostatin cDNA in chorioretinal tissue. The eyes previously injected with rAAV-lacZ (lanes B to E) and rAAV-angiostatin (lanes F to I) were enucleated and chorioretinal tissues were harvested for RT-PCR at 1, 5, 10, and 15 days after induction of experimental diabetes. Lane A is the control eye. Lanes B and F are 1 day after diabetes induction. Lanes C and G are 5 days after diabetes induction. Lanes D and H are 10 days after diabetes induction. Lanes E and I are 15 days after diabetes induction. There was no angiostatin gene expression in the control eye (lane A) and eyes injected with rAAV-lacZ (lanes B to E). In the eyes injected with rAAV-angiostatin, angiostatin gene expression was detected (lanes F to I). As an internal control, expression of GAPDH was detected in normal control eye and eyes receiving both rAAV-angiostatin and rAAV-lacZ injections (lanes A to I). \"M\" indicates molecular weight markers.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Representative retinal sections following immunostaining for albumin. Increased immunostaining was present throughout the retina one week after STZ-induction of diabetes in eyes receiving rAAV-lacZ injection (<bold>B</bold>) compared to the normal Sprague-Dawley rat (<bold>A</bold>) where staining was restircted to blood vessels. <bold>C</bold>: Intravitreal injection of rAAV-angiostatin decreased immunostaining in the retina one week after induction of diabetes. Magnification X200. IPL denotes the inner plexiform layer, INL indicates the inner nuclear layer, and ONL marks the outer nuclear layer.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>FITC-BSA fluorescence in normal and streptozotocin (STZ)-induced diabetic rat retina. <bold>A</bold>: Hematoxylin and eosin staining of control retina. <bold>B</bold>: FITC-BSA fluorescence is limited to the vasculature in the normal retina and in <bold>C</bold> is diffusely increased throughout the retinal parenchyma at 5 days after STZ-induced diabetes in eyes receiving rAAV-lacZ injection. Increased fluorescence intensity throughout the retinal parenchyma is still present at 10 (<bold>D</bold>) and 15 (<bold>E</bold>) days after STZ-induced diabetes in eyes receiving rAAV-lacZ injection. <bold>F</bold>: Little fluorescence was present in the retinal parenchyma in eyes receiving rAAV-angiostatin injection at 5 days after induction of diabetes. Retinal parenchyma fluorescence at 10 (<bold>G</bold>) and 15 (<bold>H</bold>) days after induction of diabetes in eyes with rAAV-angiostatin injection was decreased as compared with eyes with rAAV-lacZ injection. Original magnification was 200X.</p></caption></fig>", "<fig id=\"f4\" fig-type=\"figure\" position=\"float\"><label>Figure 4</label><caption><p>Quantification of vascular leakage in experimental diabetes. FITC-BSA fluorescence intensity was measured by image analysis in serial retinal sections. Rats each received an intravenous injection of FITC-BSA were sacrificed at 5, 10, and 15 days after induction of diabetes. The average retinal FITC-BSA fluorescence intensity was calculated and normalized to plasma fluorescence intensity. The retinal FITC-BSA fluorescence intensity in eyes receiving rAAV-angiostatin injection was 2.99±0.62 pixels at 5 days, 3.42±0.38 pixels at 10 days and 3.30±0.40 pixels at 15 days after induction of diabetes. The retinal FITC-BSA fluorescence intensity in eyes receiving rAAV-lacZ injection was 3.59±0.31 pixels at 5 days, 3.77±0.51 pixels at 10 days and 3.71±0.47 pixels at 15 days after induction of diabetes. The normalized FITC-BSA fluorescence intensity in eyes receiving rAAV-angiostatin was decreased as compared to eyes receiving rAAV-lacZ at 5 days (t=3.67, n=49, p=0.001), 10 days (t=3.94, n=51, p&lt;0.001), and 15 days (t=3.52, n=56, p=0.001) after STZ-induction of diabetes. The asterisk indicates a p less than or equal to 0.001. Four SD rats were represented by the number of sections (n) to be examined.</p></caption></fig>", "<fig id=\"f5\" fig-type=\"figure\" position=\"float\"><label>Figure 5</label><caption><p>The effect of rAAV-angiostatin gene transfer on retinal occludin expression 10 days after STZ-induction of diabetes The rats received intravitreal injection of rAAV-angiostatin in the right eyes and rAAV-lacZ in left eyes, and diabetes was induced three weeks after injection. <bold>A</bold>: Each blot is a representative of the results from five rats. <bold>B</bold>: Occludin levels were semi-quantified by densitometry, and normalized to actin. The rAAV-angiostatin significantly decreased retinal occludin loss as compared to eyes receiving rAAV-lacZ injection at 10 days after induction of diabetes (the asterisk indicates significance using the Wilcoxon signed rank test, n=5, p=0.041).</p></caption></fig>", "<fig id=\"f6\" fig-type=\"figure\" position=\"float\"><label>Figure 6</label><caption><p>The effect of rAAV-angiostatin gene transfer on retinal VEGF expression at 1 day after STZ-induction of diabetes <bold>A</bold>: The blots show representative of results from six rats. <bold>B</bold>: VEGF levels were semiquantified by densitometry and normalized by actin levels. rAAV-angiostatin decreased the expression of VEGF as compared to eyes with rAAV-lacZ injection (the asterisk indicates significance using the Wilcoxon signed rank test, n=6, p=0.043).</p></caption></fig>", "<fig id=\"f7\" fig-type=\"figure\" position=\"float\"><label>Figure 7</label><caption><p>The effect of rAAV-angiostatin gene transfer on retinal PEDF expression <bold>A</bold>: There was no apparent difference in retinal PEDF expression between eyes exposed to rAAV-angiostatin and rAAV-lacZ. at 1, 5, 10, or 15 days after STZ injection. <bold>B</bold>: There was no increase in PEDF expression in HUVEC-2C cells receiving rAAVangiostatin compared to control HUVEC-2C cells. Western blotting of the PEDF plasmid-transfected HUVEC-2C cells was used as a positive control.</p></caption></fig>", "<fig id=\"f8\" fig-type=\"figure\" position=\"float\"><label>Figure 8</label><caption><p>The effect of rAAV-angiostatin gene transfer on retinal phosphorylation of p42/p44 MAP kinases at 1 day after STZ-based induction of diabetes <bold>A</bold>: Representative blots show retinal phospho-p42/44 MAP kinase and total p42/44 MAP kinase in normal control eyes and in eyes injected with rAAV-lacZ or rAAV-angiostatin. <bold>B</bold>: Retinal levels of phosphor-p42/p44 MAP kinase one day after STZ-based induction of diabetes was reduced by rAAV-angiostatin (the asterisk indicates significance using the Wilcoxon signed rank test, n=5, p=0.043).</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title>Animal physiological variables.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"51\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"48\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"54\" span=\"1\"/><col width=\"48\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"54\" span=\"1\"/><col width=\"48\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"54\" span=\"1\"/><col width=\"48\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><hr/></td><td colspan=\"9\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>After streptozotocin induction of diabetes</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>Baseline (n=4)</bold><hr/></td><td colspan=\"3\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>5 days (n=4</bold><hr/></td><td colspan=\"3\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>10 Days (n=4)</bold><hr/></td><td colspan=\"3\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>15 Days (n=4)</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>sample</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>BW (g)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Blood sugar (mg/dl)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>BW (g)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Increase in body weight (%)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Blood sugar (mg/dl)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>BW (g)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Increase in body weight (%)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Blood sugar (mg/dl)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>BW (g)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Increase in body weight (%)</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Blood sugar (mg/dl)</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Age-matched control rat<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">248+14<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">139+13<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">260+13<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">4.8<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">141+11<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">294+10<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">18.5<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">154+12<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">312+9<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">25.8<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">143+11<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">STZ-induced diabetic rat</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">254+11</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">143+9</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">257+10</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2.4</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">352+15</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">270+14</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">7.7</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">377+13</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">280+11</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">11.6</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">396+15</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Animals were made diabetic by a single streptozocin (STZ) injection (65 mg/kg) in 1 mmol/l sodium citrate buffer, pH 4.5. All diabetic animals had higher blood glucose levels and reduced body weight gain compared to age matched, non-diabetic control animals.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-133-f1\"/>", "<graphic xlink:href=\"mv-v13-133-f2\"/>", "<graphic xlink:href=\"mv-v13-133-f3\"/>", "<graphic xlink:href=\"mv-v13-133-f4\"/>", "<graphic xlink:href=\"mv-v13-133-f5\"/>", "<graphic xlink:href=\"mv-v13-133-f6\"/>", "<graphic xlink:href=\"mv-v13-133-f7\"/>", "<graphic xlink:href=\"mv-v13-133-f8\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>The optic neuropathy called glaucoma is the second most common cause of bilateral blindness in the world [##REF##8695555##1##]. The most frequent form of glaucoma is open-angle glaucoma (OAG), which can occur as adult-onset primary open-angle glaucoma (POAG) or juvenile-onset primary open-angle glaucoma (JOAG). Prevalence of OAG has been measured at higher frequencies in individuals of African ancestry than in those of European or Asian ancestry [##REF##2056646##2##]. Although the most common form of OAG in the US involves elevated intraocular pressure (IOP), OAG also develops in individuals whose IOP is never observed outside of the normal range (normal tension glaucoma, NTG). Associated risk factors for OAG include race (i.e., population genetic factors, particularly ethnic ancestry), a family history of glaucoma, increasing age, and an IOP elevated above the normal range.</p>", "<p>During the last decade, genetic mapping and cloning experiments have demonstrated that glaucoma has substantial genetic components [##REF##16124852##3##]. Among the more than one dozen mapped glaucoma loci, 11 GLC1 loci cause OAG [##REF##16124852##3##], two GLC3 loci cause congenital glaucoma [##REF##8586416##4##,##REF##8842741##5##], and the remaining known loci are responsible for secondary and developmental forms of glaucoma [##REF##16124852##3##]. Additional genetic risk factors for differential severity of OAG have been reported [##REF##16124852##3##].</p>", "<p>Mutations in the myocilin (<italic>MYOC</italic>) gene at the GLC1A locus are found in 2.6-4.3% of POAG cases [##REF##10196380##6##] and up to one-third of the familial JOAG cases [##REF##11004290##7##]. There has not yet been a follow-up on a recent report that mutations in WD repeat domain 36 (WDR36) that occur in cases of POAG that map to the GLC1G locus on chromosome 5 [##REF##15677485##8##].</p>", "<p>Rezaie et al. [##REF##11834836##9##] described mutations in the <italic>optineurin</italic> (<italic>OPTN</italic>) gene, located within the GLC1E interval at 10p15-p14 [##REF##9497264##10##], in 16.7% of families from a predominantly NTG population. The original report of <italic>OPTN</italic> involvement in glaucoma presented three likely disease-causing variants designated E50K, 691_692insAG, and R545Q, and one proposed risk factor M98K [##REF##11834836##9##]. Further studies find association of some <italic>OPTN</italic> alleles with OAG, but others report no evidence of association of OAG with those same alleles [##REF##14597044##11##, ####REF##12920093##12##, ##REF##15498064##13##, ##REF##15312511##14##, ##REF##16148883##15##, ##REF##15557444##16##, ##REF##15226658##17##, ##REF##14627677##18##, ##REF##16205626##19##, ##REF##12811537##20##, ##REF##15370540##21##, ##REF##15851979##22##, ##REF##12912697##23##, ##REF##15326130##24####15326130##24##].</p>", "<p>In this paper, we present new data on our <italic>OPTN</italic> mutation screening of 314 open-angle glaucoma patients who have either POAG, JOAG, or NTG, from populations of Caucasian, Asian, Hispanic, and African ancestry. We present case reports of individuals with E50K and 691_692insAG mutations and discuss findings from more than a dozen studies that have carried out <italic>OPTN</italic> mutation screening.</p>" ]

[ "<title>Methods</title>", "<title>Subjects</title>", "<p>Informed consent was obtained from each participant according to a HIPAA-compliant study protocol approved by The University of Michigan Institutional Review Board for review of human subjects studies. Ophthalmologic examinations included slit-lamp biomicroscopy, optic disk examination, IOP by applanation, gonioscopy, and refraction. Individuals with known surgical or pharmacologic risk factors for glaucoma, such as steroid use, were excluded from this study.</p>", "<p>OAG was diagnosed based on the presence of open filtration angles, glaucomatous optic discs and glaucomatous visual field changes. Individuals with elevated IOP, greater than or equal to 22 mmHg, were considered to have POAG if they showed adult-onset at 35 years of age or older, and to have JOAG if they showed onset prior to 35 years of age. They were deemed to have NTG if their highest known IOP never exceeded 21 mmHg.</p>", "<p>##TAB##0##Table 1## lists our study case and control subjects by their diagnosis and ancestry. Our 314 OAG subjects included 51 JOAG, 230 POAG, and 33 NTG cases. Our control samples came from 371 unrelated individuals. Normal control samples were matched for race to the cases, so that a sequence variant found in a particular case population had control screening carried out only in the control population of the same ancestry. In most cases, the sample screened was the proband of the family, but sometimes a different case from that family had to be used, such as when the proband was someone with an ambiguous diagnosis. For some families in which the proband had a sequence variant of interest, additional relatives were also screened. The group of normal control samples included samples from 48 individuals of African ancestry (Corielle Institute, Camden, NJ), 19 individuals of Hispanic ancestry, and 99 individuals of Asian ancestry (Corielle Institute) who had not been characterized for ophthalmologic phenotype. These uncharacterized population controls were used in a subset of experiments as detailed in Results.</p>", "<title>Mutation Screening</title>", "<p><italic>OPTN</italic> was screened via sequencing of polymerase chain reaction (PCR) amplified DNA. Genomic DNA was extracted from peripheral blood samples using Puregene DNA Isolation kits (Gentra Systems, Minneapolis, MN) following the manufacurer's protocol. <italic>OPTN</italic> coding exons were amplified by PCR in a 20 μl reaction containing 50 ng of genomic DNA, 1.5 mmol/l MgCl₂, 0.5 μmol/l of each primer, 0.125 mmol/l of each dNTP, and 0.5 units of Amplitaq Gold (PE Applied Biosystems, Foster City, CA) in 1X final concentration of the PCR buffer. Primers used for exon amplification are listed in ##TAB##1##Table 2##. PCR conditions were 10 min at 95 °C followed by 36 cycles of 1 min at 95 °C, 1 min at 55 °C, and 1 min at 72 °C with a final extension for 10 min at 72 °C. Sequencing of PCR-amplified DNA was used to screen all 314 OAG cases for mutations in the coding sequences (i.e., exons 4 through 16) and splice sites flanking <italic>OPTN</italic> exons. When a sequence variant was detected in a patient, we screened for that specific mutation in the control population samples of the same ancestry.</p>", "<p>Individuals with E50K and 691_692insAG mutations who are presented in the case reports were screened for mutations in <italic>MYOC</italic>. PCR amplification of the three <italic>MYOC</italic> exons was conducted as described in reference [##REF##11004290##7##] with some modified primers as listed in ##TAB##2##Table 3##. PCR products were purified with a QIAquick PCR purification kit (Qiagen, Santa Clarita, CA). Sequenced PCR products were analyzed on an ABI 377 sequencer or at the University of Michigan DNA Sequencing Core facility on either an ABI 3730 or 3700 sequencer.</p>", "<title>Statistical Analysis</title>", "<p>Published reports on the frequency of OAG mutations were compared using several different statistical tests. Because some studies contained expected frequencies of less than 5, Fisher's exact test was chosen to examine the 2x2 contingency tables of individual studies. In tandem with Fisher's exact test, odds ratios and 95% confidence intervals for the odds ratio were calculated. To estimate odds ratios for whole populations based on multiple studies, fixed effect estimates were calculated using a Mantel-Haenszel (MH) model [##UREF##0##25##]. Homogeneity was evaluated with the Woolf test, in which the p value allows a determination of the appropriateness of combining studies by testing for evidence of effect modification by study group (i.e., testing whether the odds ratios are the same in all studies). For a case-control study, an odds ratio greater than 1 indicates that OAG cases are more likely to have the gene of interest than controls. For 2x2 contingency tables, independence is equivalent to an odds ratio of 1. All statistics were computed using the open source statistical program R 2.3.1 with the packages rmeta 2.12, meta 0.5, and vcd 0.9-7 [##UREF##1##26##, ####UREF##2##27##, ##UREF##3##28##, ##UREF##4##29####4##29##].</p>" ]

[ "<title>Results</title>", "<title>E50K <italic>OPTN</italic> mutation in a case with normal tension glaucoma</title>", "<p>Case 1, a 52 year old Chilean female (III:1; ##FIG##0##Figure 1##), was diagnosed with NTG at age 42 years and her highest pretreatment IOP was 18 mmHg in both eyes. After bilateral trabeculectomies and betaxolol treatment, her IOPs were 6 mmHg in the right eye and 10 mmHg in the left eye. Gonioscopic exam revealed open angles in both eyes, with iris processes noted circumferentially in both eyes. A dilated funduscopic exam demonstrated advanced glaucomatous cupping with cup-to-disc ratios of 1.0 in both eyes and absence of hemorrhage. Sequence changes were absent in the <italic>MYOC</italic> gene coding sequence and splice sites. Her family history showed evidence of autosomal dominant inheritance (##FIG##0##Figure 1##). The E50K mutation was found in three of the proband's four affected relatives that were in the study (II:1, III:2, and III:7; ##FIG##0##Figure 1##). The E50K mutation was absent in the proband's affected aunt (II:3; ##FIG##0##Figure 1##) as well as five unaffected relatives that were screened (##FIG##0##Figure 1##).</p>", "<title>691_692insAG <italic>OPTN</italic> mutation in a case with primary open-angle glaucoma</title>", "<p>Case 2 was a female Russian Ashkenazi Jewish immigrant diagnosed with POAG at 80 years of age. Her ocular history was significant for high myopia (right eye -17.75 diopters, left eye -19.00 diopters) and myopic retinal degeneration in both eyes. The patient had a childhood history of measles, a disease that has been identified as a possible contributor to high myopia [##REF##13435338##30##,##REF##1483402##31##]. At the time of the POAG diagnosis, the patient already had dense, 4-quadrant visual field defects in both eyes, attributable to the retinal degeneration, or a long-standing undiagnosed glaucoma, or both. She had cup-to-disc ratios of 0.5 in both eyes and diffuse chorioretinal atrophy. Her IOPs were 22 mmHg in the right eye and 21 mmHg in the left eye. Her IOPs decreased to 17 mmHg in the right eye and 16 mmHg in the left eye at one month after treatment with betaxolol, dipivefrin, and pilocarpine. Over the next several years, her IOPs fluctuated between the low teens and mid-twenties while she underwent treatment with medication, laser treatments, and multiple trabeculectomies. Screening of the <italic>OPTN</italic> gene revealed an insertion of AG at positions 691 and 692 (691_692insAG) in one copy of the <italic>OPTN</italic> gene. There were no other sequence variants in the coding sequence or splice sites of either <italic>OPTN</italic> or <italic>MYOC.</italic> Little family history information was available. She had a maternal grandfather affected by high myopia, but she didn't know of any other cases of glaucoma in her small family. Her only living relative, a reportedly unaffected son, declined to participate in the study.</p>", "<title>R545Q and M98K <italic>OPTN</italic> sequence variants</title>", "<p>The R545Q sequence variant was found in two individuals with OAG. One woman with Filipino ancestry had JOAG diagnosed at 24 years of age and had a maximum known pretreatment IOP of 50 mmHg. Her mother also had POAG and her brother is unaffected. She did not know the diagnostic status of the rest of her relatives in the Philippines. The second case, a Korean woman diagnosed at 55 years of age, had a maximum known IOP of 29 mmHg and an unknown family history of glaucoma.</p>", "<p>Among 36 OAG cases with the M98K mutation, the 26 for whom we have historical IOP data had known maximum IOPs between 16 mmHg and 55 mmHg (mean=29.6 mmHg). Out of the 283 OAG cases who lacked the M98K mutation, 253 had historical IOP data available, with the maximum recorded IOPs ranging from 14 mmHg up to 77 mmHg (mean=29.9 mmHg).</p>", "<title><italic>OPTN</italic> sequence variants in the whole study cohort</title>", "<p>Among the 314 OAG cases, we found a total of four (1.2%) individuals who possessed any of the three sequence variants reported by Rezaie and colleagues [##REF##11834836##9##] to be disease-causing variants (##TAB##3##Table 4##).</p>", "<p>The E50K mutation in Case 1 was the only instance of E50K among the 314 OAG cases (1/314, 0.3%) and in none of 371 controls (&lt;2.7%), and was one of only 11 Hispanic cases screened (1/11, 9.1%; ##TAB##3##Table 4##). E50K was identified in one of the 33 NTG cases (3.0%), but was not present in the 230 POAG or 51 JOAG cases. This mutation was present in 1/11 (9.1%) Hispanic cases and none of 50 Hispanic controls. It was also absent from 86 Caucasian normal controls.</p>", "<p>The single instance of 691_692insAG in Case 2 was found among the 314 OAG cases (1/314, 0.3%), and was one of 217 Caucasian OAG cases screened (0.5%; ##TAB##3##Table 4##). This was one of 230 POAG cases (0.4%) and was not present in 116 Caucasian controls, including seven samples that share Ashkenazi Jewish ancestry with the case having the mutation. In addition, 691_692insAG was present in one case in the original report by Rezeai [##REF##11834836##9##] but that report did not provide information on ancestry of that case, so we could not tell whether their case and our case shared ancestral origins. This mutation was also previously reported as being absent from 200 normal control chromosomes of Caucasian origin [##REF##11834836##9##].</p>", "<p>R545Q was present in two of the 314 OAG cases (0.6%; ##TAB##3##Table 4##). It was found once among the 51 JOAG cases (1.9%) and once among the 33 NTG cases (3.0%). Both instances of R545Q were found in individuals of Asian ancestry (2/5, 40.0%). R545Q was also present in 11 of 117 (9.4%) controls of Asian ancestry. The absence of this allele from our Caucasian cases or controls (0/333, &lt;0.3%) concords with previous reports that failed to find it in either cases or controls of European ancestry (0/1457), suggesting that the allele frequency in European populations may be less than 0.1% [##REF##11834836##9##,##REF##14597044##11##,##REF##15498064##13##,##REF##15851979##22##,##REF##12912697##23##,##REF##16020311##32##,##REF##16358725##33##]. Based on our data, we suggest that R545Q may be of low prevalence in African (&lt;0.6%) or Hispanic populations (&lt;1.6%), but our ability to estimate frequencies in these populations is limited because of sample size.</p>", "<p>The M98K sequence variant was found in JOAG, POAG, NTG, and control populations (##TAB##4##Table 5## and ##TAB##5##Table 6##). We observed statistically insignificant differences in the frequencies between cases and controls for Africans and Caucasians, the two large sample sets in the study (##TAB##4##Table 5##). Frequencies in Asian samples (32/122, 26.2%) resembled values for African samples (18/81, 22.2%), while frequencies for Hispanic samples (2/62, 3.2%) seemed more similar to frequencies for Caucasian samples (8/116, 6.9%), but sample sizes were small. Additionally, the Asian samples showed no difference between cases and controls (p value=0.112), but the sample size was small and the use of a predominantly Chinese population to control for findings from a mixed Asian case set was problematic when looking at an allele that showed considerable variation among populations. Thus, although our overall study population showed M98K in 36 of 314 OAG individuals (11.5%) and 58 of 371 controls (15.6%), such pooling of data from different racial/ethnic groups is invalid where population frequencies vary so greatly.</p>", "<p>Screening identified two instances of E322K in both cases and controls - a change previously reported to be associated with glaucoma [##REF##11834836##9##] (##TAB##3##Table 4##). We also found silent <italic>OPTN</italic> coding sequence polymorphisms, including L32L, T34T, L41L, E63E, A134A, and S321S, as well as previously reported intronic sequence variants [##REF##8586416##4##,##REF##9497264##10##,##REF##14597044##11##,##REF##12811537##20##,##REF##15326130##24##,##REF##12789137##34##,##REF##12939304##35##]. We did not find Ile88Val or Ala99Ser in our case populations, but did observe them among our controls (##TAB##3##Table 4##).</p>", "<title>Pooled data on R545Q</title>", "<p>R545Q was present in our Asian data set, but absent from the other three populations we screened. We found no significant differences in allele frequencies between cases and controls for R545Q. This agrees with many of the other published studies, although it should be noted that Mukhopadhyay et al. [##REF##16205626##19##] did report the case-control difference to be significant (##TAB##5##Table 6##). Evaluation of odds ratios and frequencies for each of the Asian studies showed no statistically significant differences between case and control values for any of the Asian data sets (##FIG##1##Figure 2##, ##TAB##5##Table 6##). With the exception of the Rezaie study [##REF##11834836##9##], R545Q has been reported only in Chinese, Japanese, Korean, Filipino, Indian, and mixed-ancestry populations (##TAB##5##Table 6##).</p>", "<p>Our Asian data set is small, so we examined the possibility of pooling data from multiple studies. Because of observed variation in allele frequencies among studies (0.6-6.8%; ##TAB##5##Table 6##), we questioned whether the data could be validly combined. Using the Woolf test for heterogeneity to address this question, we found no statistically significant study-based stratification within the individual populations for R545Q (##TAB##6##Table 7##). This means that it is reasonable to take data from the studies in ##TAB##5##Table 6## and pool them for a given population from multiple studies under a model of homogeneity. When pooled, we found no statistically significant difference between case and control values for the combined Asian data set (p value=0.541), nor for the separate Chinese (p value=0.89) or Japanese (p value=0.43) subsets (##TAB##6##Table 7##). The same lack of difference was true when considering only NTG cases.</p>", "<title>Pooled data on M98K</title>", "<p>We found no evidence of significant difference between case and control frequencies for M98K in our Asian, African, Hispanic, or Caucasian populations (##TAB##7##Table 8##). Fuse and Alward reported statistically significant evidence of association of M98K with OAG in the Japanese population, although Alward indicated that this difference becomes nonsignificant when adjusted for testing multiple times [##REF##14597044##11##,##REF##15226658##17##]. Other studies do not report a significant case-control difference [##REF##14597044##11##, ####REF##12920093##12##, ##REF##15498064##13##, ##REF##15312511##14##, ##REF##16148883##15##, ##REF##15557444##16##, ##REF##15226658##17##, ##REF##14627677##18##, ##REF##16205626##19##, ##REF##12811537##20##, ##REF##15370540##21##, ##REF##15851979##22##, ##REF##12912697##23##, ##REF##15326130##24####15326130##24##].</p>", "<p>Previous studies supported our finding that M98K allele frequences are much higher in populations of Asian (555/2818, 19.7%) or African (38/169, 22.5%) ancestries than in Caucasian (179/3149, 5.7%) or Hispanic (2/61, 3.3%) populations (##TAB##7##Table 8## and ##TAB##8##Table 9##). Thus, ancestry would be a significant confounding variable when attempting to analyze data pooled from different populations.</p>", "<p>If we consider specific defined subpopulations, where there should be less concern about ancestry serving as a confounding variable, then we are left with concerns about differences observed not just between but also within populations. When we compared the different Asian studies using odds ratios (##FIG##2##Figure 3##), the aggregate Asian data, the aggregate Japanese data, the data produced by our study, and by the individual studies of Umeda et al. [##REF##15370540##21##], Fuse et al. [##REF##15226658##17##], and Alward et al. [##REF##14597044##11##], we found each showed significant evidence of a difference between cases and controls. When we evaluated allele frequencies for the various Asian data sets, we saw dramatic differences in allele frequencies among the different studies (##FIG##2##Figure 3##, ##TAB##7##Table 8##). Also, the control values showed much greater variation among studies than the case values. The control values from some studies are higher than the case values from other studies, even though within each separate study the case frequencies are always higher than control frequencies (##FIG##2##Figure 3##). With regard to our study, in which a small number of samples came from diverse Asian regions, the observed difference could be due to the limited case sample size, differential representation of M98K within the Asian population, case versus control status, or some combination of the three.</p>", "<p>The results of the Woolf test for heterogeneity indicated that there was something noncomparable about the M98K findings from a number of the studies that reported results for the same populations (##TAB##8##Table 9##). In the case of the Japanese data set, pooled data showed M98K frequencies of 18.2% (220/1208) in cases versus 11.6% (77/661) in controls (p value=0.0002), but results of the Woolf test led us to suspect that we may be combining noncomparable data sets (p value=0.046). In the case of the European data set, Fisher's exact test indicated that there was a statistically significant difference between cases and controls (p value=0.001), but again the Woolf test identified heterogeneity among the data sets (p value=0.005; ##TAB##8##Table 9##). When we pooled the worldwide data from the entire set of published studies, we saw a significant difference between cases and controls (p value=0.00000004), but again, testing for heterogeneity indicated that it may be invalid to pool these studies (##TAB##8##Table 9##; p value=0.0018). Interestingly, if we removed data from the Rezaie study [##REF##11834836##9##], which indicated Caucasian controls but did not specify its case population composition, the remaining Caucasian data sets appeared to be homogeneous (p value=0.512) and Fisher's exact test indicated no significant difference between case and control values (##TAB##8##Table 9##; p value=0.072). Fewer studies distinguish observations for NTG only. For those studies that provided data for NTG frequencies, we saw that both the Japanese and European populations showed homogeneity across studies. However, Fisher's exact testing of pooled studies showed opposing results between Japanese (p value=0.00002) and European (p value=0.58) populations.</p>", "<p>The case versus control difference for the Hispanic data are also intriguing, with M98K case values of 1/11 (9.1%) and control values of 1/50 (2.0%). Our small Hispanic data set was not well-powered for statistical testing, but this represented an initial view of a population under represented in previous studies (##TAB##7##Table 8##). Given that our Hispanic data set represented cross-continental cases from North, Central, and South America, we have to wonder whether the apparent differences in M98K allele frequences was simply due to small sample size, or rather might be attributed to differential allele frequencies correlated with geographic origins of samples rather than case-control status.</p>" ]

[ "<title>Discussion</title>", "<p>In our study of 314 individuals with OAG, we found 42 individuals with sequence variants predicted to alter the protein coding sequence. This included three <italic>OPTN</italic> variants previously reported to be disease-causing variants-E50K, 691_692insAG, and R545Q, as well as the M98K variant previously reported as a risk factor [##REF##11834836##9##].</p>", "<p>This is the second time the 691_692insAG mutation has been reported. Both times it has been identified in case populations but not seen in controls. It is the first report of 691_692insAG in an individual of Russian Ashkenazi Jewish ancestry, and ancestry is unavailable for the previously reported case. Although <italic>OPTN</italic> defects were originally reported in a population of primarily NTG cases, we found this variant in an individual with modestly elevated IOP (22 mmHg). The shift in the reading frame that it causes and the fact that it is seen among cases but not controls suggests that it could be a causative variant. However, if we combine data from all studies, we see it in 2/3677 cases (0.0005%) in the studies that used protocols that would have detected it (all studies in ##TAB##7##Table 8## except Aung [##REF##12920093##12##], Melki [##REF##14627677##18##], and Wiggs [##REF##12912697##23##]). Only a fraction of the 2,270 controls from those studies screened the whole sequence from all controls, so they would not have been highly likely to detect this variant among the controls even if the control frequency were equal to the case frequency. Thus, while it is tempting to say that a variant seen only in two cases might be causative, the available numbers can only support the conclusion that 691_692insAG event is a rare occurence.</p>", "<p>We report here the first observation of the E50K change in a Caucasian Hispanic individual. The observation of E50K at a frequency of 0.3% in our cases is consistent with reports of frequencies in OAG populations of 0.1% by Alward et al. [##REF##14597044##11##], 0.6% by Aung et al. [##REF##12920093##12##], and 0.6% by Hauser et al. [##REF##16988596##36##]. The NTG subset is reported to have E50K at a higher prevalence of 13.5% (7/52),1.5% (2/132), 1.5% (1/67), and 2.9% (1/34) in studies by Rezaie et al. [##REF##11834836##9##], Aung et al. [##REF##12920093##12##], Hauser et al. [##REF##16988596##36##], and ourselves, respectively. Many other studies found no evidence of this mutation, including reports of its absence from 237 cases with Chinese ancestry [##REF##15312511##14##,##REF##12939304##35##] and 961 cases with Japanese ancestry [##REF##14597044##11##,##REF##15312511##14##,##REF##15557444##16##,##REF##15226658##17##,##REF##12811537##20##,##REF##15370540##21##,##REF##12939304##35##,##REF##14755458##37##], which supports the supposition that this is a polymorphism private to the Caucasian and Hispanic populations. Variation in frequencies observed among studies may be affected by the ancestry of the population, the fraction of the cohort with familial glaucoma, and differences in specific diagnoses included in the study. Failure to see complete cosegregation of E50K with glaucoma (i.e., we have one OAG case in a family lacking the E50K mutation) raises questions about whether we are observing a phenocopy or whether E50K is not the cause of the glaucoma in this family.</p>", "<p>Our data and the compiled evidence from more than a dozen other studies support the idea that R545Q may be a private polymorphism of Asian populations. Although our Asian data set provides marginal evidence for a difference in R545Q allele frequency between cases and controls, it is a small population and the results are not statistically significant. When we pooled our data with data from other studies there did not appear to be any evidence to support a role for R545Q as a disease causing variant.</p>", "<p>We found the M98K variant in all four populations screened, but evaluation of all of the published studies leaves unresolved the issue of whether or not M98K is a risk factor for glaucoma. A similar conclusion was drawn by Craig et al. [##REF##16885188##38##] but they did not analyze the population (ancestry) structure of the data for the allele. Several studies find evidence for association, while others do not. Evaluation of the published data in addition to our own indicates that there is considerable variation in allele frequencies, not only among populations, but also within populations. This variant is found in Asian and African populations at more than twice the frequency seen in Caucasian and Hispanic populations. Comparison of findings from different studies indicates large variations in allele frequencies in different study populations within Japanese (MH p value=0.00038) and Chinese (MH p value=0.118) populations (##TAB##8##Table 9##). The case-control difference is much smaller within Caucasian or African populations (##FIG##2##Figure 3##), and data on Caucasian populations show less variation between studies than the data on Japanese and Chinese populations (##TAB##8##Table 9##, ##FIG##2##Figure 3##).</p>", "<p>There are a number of confounding factors that might contribute to the observed variability of allele frequency between Asian populations. Differential allele frequencies within a population could result from founder effects. At this point, there is not enough information available regarding origins of the different subpopulations (##TAB##9##Table 10##) to allow for evaluation of the likelihood of a founder effect. There appears to be a correlation between total sample size and the difference between case and control frequencies (##FIG##1##Figure 2##), although the published studies seem to be adequately powered (for Fisher's exact test, the power, or probability to reject the null hypothesis when it is true, is 0.76 for the parameters π₁=0.2, π₂=0.1, where each sample size is 200 and α=0.05). An alternative confounding factor could be the result of the different screening techniques applied (##TAB##9##Table 10##); however, there is no obvious correlation of high allele frequencies with one screening approach and low allele frequencies with a different technique. Selective under-representation of an allele in a data set relative to the actual allele frequency could result if M98K were in linkage disequilibrium with a neighboring polymorphism contained within the sequence of a primer used in amplification or sequencing in some studies, but not others. Some of the papers do not present the primer sequences and the available primer sequence data do not provide support for this idea. Additional contributions to variability between studies could include differences in diagnostic inclusion and exclusion criteria and fraction of familial glaucoma within each cohort. Thus, the extant data do not allow us to distinguish between technical, ascertainment and demographic models for the observed differences in M98K allele frequencies between different studies of the same population.</p>", "<p>An alternative approach to evaluation of whether the M98K allele is involved in glaucoma is through the study of cosegregation in families. Wiggs et al. [##REF##12912697##23##] reported lack of cosegregation in families. An accompanying population-based portion of that study [##REF##12912697##23##] also failed to find association of M98K with glaucoma in a population of mostly European ancestry.</p>", "<p>One alternative explanation for why some studies find association, yet others do not, might be that there is a valid statistical difference between the case and control populations but that the M98K allele is actually associated with some other variable that differs between cases and controls, or has been excluded from cases but not controls. An obvious example of this would be IOP. The Rezaie et al. study [##REF##11834836##9##] looked at mostly NTG families, while there was a lot of variation in the extent to which NTG was represented in the different populations in the other studies. If M98K is actually responsible for reducing IOP, or for preventing the rise of IOP, but is not actually causing glaucoma, then we would expect exclusion of individuals with elevated IOP from the cases would bias the M98K frequency in the cases as compared to the controls even if M98K were not actually causing glaucoma. Melki et al. [##REF##14627677##18##] offered the view that M98K is associated with lower IOP. In our data set we found that cases with the M98K mutation had known maximum IOP values ranging from 16 mmHg to 55 mmHg (mean=29.6 mmHg) while those who lacked the M98K mutation had maximum recorded IOP values ranging from 14 mmHg in an NTG case up to 77 mmHg (mean=29.9 mmHg). Thus, in our data set there was no obvious difference in maximum known IOP between those with and those without M98K.</p>", "<p>The original report by Rezaie provided apparently compelling statistical evidence that M98K is a glaucoma risk factor with a p value of 2.18x10^-7. The other studies that found any support for M98K association with glaucoma found only weak evidence of this association. It remains unclear what the differences are between the studies that could account for the differences in study outcome. One key issue for M98K appears to be the great variability of allele frequency reported in different studies and different populations. This would be a problem if the case population in the Rezaie et al. study [##REF##11834836##9##] contained multiple populations or an admixed population that self-identified as Caucasian. In the Rezaie et al. study [##REF##11834836##9##], both E50K, an apparently private Caucasian polymorphism, and R545Q, an apparently private Asian polymorphism, were in the same study cohort. While this could mean that their undescribed case population was a mixed race group, it is also the kind of thing that can happen in a fairly admixed urban population when using self identification as the basis for applying racial/ethnic classification, even when setting out to identify a relatively homogeneous population. Thus, there is the possibility that the Rezaie et al. study [##REF##11834836##9##] outcome differs from the others because of differences in diagnostic inclusion and exclusion criteria or other unidentified factors, but it could also be the result of studying an allele that varies significantly between and within populations - something that can happen even when making efforts to carry out adequate matching of cases and controls.</p>", "<p>Thus the findings on M98K are currently contradictory, with some studies finding association and other studies finding no support for association, and with the differences in study outcome not assorting according to population or technology used. Because there are such substantial differences in allele frequencies between the different studies and between and within populations, it is likely that a final resolution of this question will require the following: The screening to take place by technologies selected for precision rather than high throughput; the study be adequately powered; matching of cases and controls for ancestry be highly rigorous and matched for subpopulations rather than simply matching for one of a handful of racial or ethnic categories; inclusion and exclusion criteria be carefully defined, that tests for association with associated variables such as IOP be carried out in addition to tests for association with the primary glaucoma status variable; and population substructure analysis be included in the analysis to help deal with apparent differences within populations that can be difficult to control.</p>", "<p>This study has contibuted additional evidence of association of <italic>OPTN</italic> E50K with glaucoma, and reported an additional instance of the 691_692insAG sequence variant. We have also provided new information on <italic>OPTN</italic> in populations of African and Hispanic ancestry. Evaluation of data from more than a dozen studies indicated no association of R545Q with glaucoma in most populations. Combined analysis of more than a dozen studies suggests that M98K is associated with NTG in Asian, but not Caucasian study populations, but these results must be interpreted with great caution because of the large differences in allele frequencies between and within populations.</p>" ]

[]

[ "<p>The first two authors contributed equally to this publication.</p>", "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>To evaluate the extent to which mutations in the <italic>optineurin</italic> (<italic>OPTN</italic>) glaucoma gene play a role in glaucoma in different populations.</p>", "<title>Methods</title>", "<p>Case-controlled study of <italic>OPTN</italic> sequence variants in individuals with or without glaucoma in populations of different ancestral origins and evaluate previous <italic>OPTN</italic> reports. We analyzed 314 subjects with African, Asian, Caucasian and Hispanic ancestries included 229 cases of primary open-angle glaucoma, 51 cases of juvenile-onset open-angle glaucoma, 33 cases of normal tension glaucoma, and 371 controls. Polymerase chain reaction-amplified <italic>OPTN</italic> coding exons were resequenced and case frequencies were compared to frequencies in controls matched for ancestry.</p>", "<title>Results</title>", "<p>The E50K sequence variant was identified in one individual from Chile with normal tension glaucoma, and the 691_692insAG variant was found in one Ashkenazi Jewish individual from Russia. The R545Q variant was found in two Asian individuals with primary open-angle glaucoma; one of Filipino ancestry and one of Korean ancestry. In addition to presenting <italic>OPTN</italic> allele frequencies for Caucasian and Asian populations that have been the subject of previous reports, we also present information for populations of Hispanic and black African ancestries.</p>", "<title>Conclusions</title>", "<p>Our study contributes additional evidence to support the previously reported association of the <italic>OPTN</italic> E50K mutation with glaucoma. After finding an additional 691_692insAG <italic>OPTN</italic> variant, we can still only conclude that this variant is rare. Combined analysis of our data with data from more than a dozen other studies indicates no association of R545Q with glaucoma in most populations. Those same studies disagree in their conclusions regarding the role of M98K in glaucoma. Our analysis of the combined data provides statistically significant evidence of association of M98K with normal tension glaucoma in Asian populations, but not in Caucasian populations; however, the validity of this conclusion is questionable because of large differences in allele frequencies between and within populations. It is currently not possible to tell how much of the underlying cause of the allele frequency difference is attributable to demographic, technical, or ascertainment differences among the studies.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>The authors thank Dr. Alfonzo Mendoza A. for his contributions to this paper. Financial support came from NIH EY07003 (Core grant, Kellogg Eye Center), NIH EY09580 (J.E.R.), and NIH EY11671 (J.E.R.) from the National Institutes of Health, Bethesda, MD, a fellowship from the Pan American Association of Ophthalmology, Arlington, TX, (R.A-L.), an unrestricted grant from Research to Prevent Blindness, Inc., New York, NY, to the Kellogg Eye Center, and by the Van Arnam Glaucoma Research Fund of the University of Michigan Department of Ophthalmology and Visual Sciences, Ann Arbor, MI. The authors have no financial or proprietary conflicts relevant to the content of this paper.</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Lack of complete cosegregation of E50K with glaucoma in the pedigree of a Chilean family. The arrow indicates the proband (Case 1). Filled symbols are affected individuals with NTG, open symbols are individuals who are unaffected or reported to be unaffected. Symbols with a cross indicate individuals who are glaucoma-suspect, symbols with a center dot indicate glaucoma-affected individuals according to family report, and partially filled symbols denote individuals affected with POAG. Diagonal lines mark deceased individuals. Individuals denoted with ++ have E50 alleles on both chromosomes and ones with M+ carry the E50K heterozygous change. Members of generation four are young enough that they are not expected to be affected yet.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>R545Q log odds ratios and allele frequences in Asian population studies. <bold>A</bold> shows the odds ratios with 95% confidence interval bars for individual Asian studies, and pooled results for Japan, China, and both in open angle glaucoma (OAG) cases versus controls. Odds ratios and confidence intervals are fixed effect estimates resulting from the Mantel-Haenszel method. <bold>B</bold> shows the case (OAG, filled circle) and control (open circle) proportion observed for each study. Total sample sizes are listed along the right-hand margin. None of the differences between case and control frequencies are statistically significant in a comparison of the odds ratios (as readily observed from the odds ratio confidence intervals) and frequencies of R545Q mutations in any of the Asian populations studied.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>Studywise differences appear in Japanese populations when odds ratios and frequencies of M98K mutations are compared. The left-hand graph (<bold>A</bold>) shows the odds ratios with 95% confidence interval bars for individual Asian studies and pooled results for Japan, China, and both in open angle glaucoma (OAG) cases versus controls. Odds ratios and confidence intervals are fixed effect estimates resulting from the Mantel-Haenszel method. The right-hand graph (<bold>B</bold>) shows the case (OAG, filled circle) and control (open circle) proportions observed for each study. Total sample sizes are listed along the right-hand margin. Larger samples have both narrower confidence intervals and shorter distance between fractions observed for cases and controls. Studies inconsistently estimate the odds of OAG versus controls carrying an M98K mutation, with larger studies (more than 400 total cases and controls) estimating no statistically significant difference. Other population estimates are not shown, because, among the European population-based studies, only Rezaie's study [##REF##11834836##9##] showed a statistically significant difference. The single study on India yielded a significant odds ratio, but no other comparable populations have been reported [##REF##16205626##19##].</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title>Ancestry and diagnosis of subjects.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"221\" span=\"1\"/><col width=\"63\" span=\"1\"/><col width=\"54\" span=\"1\"/><col width=\"45\" span=\"1\"/><col width=\"54\" span=\"1\"/><col width=\"52\" span=\"1\"/><col width=\"38\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Population</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>JOAG</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>POAG</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>NTG</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Total OAG</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Control</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">African (U.S., Ghana, Nigeria, and the Caribbean)<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">14<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">63<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">4<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">81<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">88<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">169<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Asian (Korea, China, and the Philippines)<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">117<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">122<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Caucasian (Europe and the Middle East)<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">32<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">159<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">26<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">217<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">116<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">333<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Hispanic (Mexico, Puerto Rico, Chile, Panama, and Colombia)<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">50<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">61<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Totals</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">51</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">230</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">33</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">314</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">371</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">685</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t2\" position=\"float\"><label>Table 2</label><caption><title>Primers used for sequencing the <italic>OPTN</italic> gene.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"39\" span=\"1\"/><col width=\"201\" span=\"1\"/><col width=\"201\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Exon</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Forward primer sequence (5'-3')</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Reverse primer sequence (5'-3')</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGAGAGAAAGTGGGCAACT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACCAGCTACCACCTATGGA<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCATCTTTCAATTCAGAGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GACACGTAAGATTCCACTGC<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCCCAGAGCTCTGCGATTAA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCTACACTGGAATTTCCTCA<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCTGAGCCACCCCGTTTAAA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GACCTCCGGTGACAAG<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGAGAATGTTCTGGAAAGCAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGTGAACTGTATGGTATCT<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCCCTGATCCTTTATCCCAA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AATTCAGTGGCTGGACTAC<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGTTCAGCCTGTTTTCTCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCCCCCATCTTACAAGTATTTC<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGCCAGGTCTAGTGAAGAA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTTATCCCCCTCTCTGAGAG<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">12<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAAATGCTAGTAGGTCGTGG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCCTGACCATAGGACATTCA<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">13<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CCGGCCAGAGCTGATAAT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGATCCACTGAGCACTTTCC<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">14<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTAGCAGGATTGTGCATCGT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GTGGCGCGAACACAGCTATT<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">15<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTTCCCCTACTTCTGTGGAC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAGACTGACGGGTGCTATAT<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">16</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCATGTCCCACTACGTGTTG</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGTGCCCGGCCTGTTTTCTT</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t3\" position=\"float\"><label>Table 3</label><caption><title>Primers used for sequencing the <italic>MYOC</italic> gene.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"41\" span=\"1\"/><col width=\"234\" span=\"1\"/><col width=\"234\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Exon</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Forward primer sequence (5'-3')</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Reverse primer sequence (5'-3')</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">1A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCTGGCTCCCCAGTATATA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTGCTGAACTCAGAGTCCCC<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">1B<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGGCCAATGTCAAGTCATCCAT<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTCCAGAACTGACTTGTCTC<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACATAGTCAATCCTTGGGCC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TAAAGACCACGTGGCACA<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">3A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTGGCTCTGCCAAGCTTCCGCATGA<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGCTGGCTCTCCCTTCAGCCTGCT<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">3B</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAGCTGAATACCGAGACAGTGAA</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GAGGCCTGCTTCATCCACAGCCAAC</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t4\" position=\"float\"><label>Table 4</label><caption><title>Frequency of sequence variants that alter the <italic>OPTN</italic> protein sequence.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"83\" span=\"1\"/><col width=\"85\" span=\"1\"/><col width=\"64\" span=\"1\"/><col width=\"73\" span=\"1\"/><col width=\"65\" span=\"1\"/><col width=\"71\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Protein change</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>DNA change</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Exon</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Ancestry</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Cases</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Controls</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">E50K<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.458 G&gt;A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Hispanic<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/50<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">I88V<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.572 A&gt;G<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/116<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">A99S<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.605 G&gt;T<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">African<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2/88<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">E322K<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.1274 G&gt;A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">African<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6/88<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">E322K<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.1274 G&gt;A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/90<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">691Frameshift<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">691_692insAG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/116<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">R545Q</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.1944 G&gt;A</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">16</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Asian</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2/5</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11/117</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t5\" position=\"float\"><label>Table 5</label><caption><title>Frequency of M98K in four populations within our cohort.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"66\" span=\"1\"/><col width=\"66\" span=\"1\"/><col width=\"50\" span=\"1\"/><col width=\"51\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"50\" span=\"1\"/><col width=\"55\" span=\"1\"/><col width=\"54\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Ancestry</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Whole population</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>JOAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>POAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>NTG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total OAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Controls</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Fisher’s exact test p value</bold><hr/></td></tr><tr><td colspan=\"8\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Frequency of mutation in screened samples by population<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">African<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">38/169<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3/14<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14/63<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">18/81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">20/88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.0<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Asian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">32/122<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3/5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">29/117<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.112<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Hispanic<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2/62<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1/50<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.331<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22/336<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3/32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11/159<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0/26<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14/217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8/116<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.0<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Total<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">94/690<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7/51<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">27/230<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2/33<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">36/314<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">58/371<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"8\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Percent of mutation in screened samples by population<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">African<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">21.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">25.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Asian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">26.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">50.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">50.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">60.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">24.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Hispanic<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Total</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.6</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.7</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.7</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.1</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.5</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.6</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"t6\" position=\"float\"><label>Table 6</label><caption><title>Comparison of R545Q frequency in different populations.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"46\" span=\"1\"/><col width=\"46\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"46\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"55\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"44\" span=\"1\"/><col width=\"49\" span=\"1\"/><col width=\"51\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Source</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>OAG</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Controls</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Percent</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Odds ratio</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>95%CI bounds</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Fisher's exact test p value</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>R545Q</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>R545Q</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>OAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Controls</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Lower</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Upper</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">China<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15312511##14##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">118<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">150<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.28<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.36<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.54<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.753<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16148883##15##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">400<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">19<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">262<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.92<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.50<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.70<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.876<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Japan<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">12<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">247<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">89<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.46<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.40<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.31<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.767<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15557444##16##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">26<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">411<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">218<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.62<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.62<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.596<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15226658##17##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">154<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.96*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.08<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">48.69*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12811537##20##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">20<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">313<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">196<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.58<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.77<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.700<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15370540##21##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">83<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">58<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.51<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.35<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.446<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Asia<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">117<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">33.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.82<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.79<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">29.36<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.122<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Europe<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">650<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">162<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15498064##13##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">94<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##11834836##9##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">46<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.63*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">.26*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">165.80*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.315<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15851979##22##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">112<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Africa<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">90<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">India<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16205626##19##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">13.40*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.75*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">239.49*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.030<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Mixed<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12912697##23##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">86<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">80<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15326130##24##]</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">114</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">187</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.9</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.6</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.54</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.06</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.28</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t7\" position=\"float\"><label>Table 7</label><caption><title>Aggregate statistical summaries in Asian populations screened for R545Q.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"56\" span=\"1\"/><col width=\"46\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"46\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"50\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"44\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"42\" span=\"1\"/><col width=\"52\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Ancestry</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Cases</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Controls</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Percent</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Odds ratio</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>95% CI bounds</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Woolf test p value</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Fisher’s exact test p value</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>R545Q</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>R545Q</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>OAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Control</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Lower</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Upper</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">China<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">518<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">24<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">412<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.98<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.57<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.70<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.648<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.89<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Japan<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">62<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1208<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">28<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">661<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.20<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.76<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.90<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.838<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.43<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Asia<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">94<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1726<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">52<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1073<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.12<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.78<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.58<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.925<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.541<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">China-NTG<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">106<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">150<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.04<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.54<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8.41<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">-<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.244<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Japan-NTG</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">40</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">705</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">28</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">661</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.7</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.2</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.40</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.33</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.848</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.263</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t8\" position=\"float\"><label>Table 8</label><caption><title>Frequency of M98K in individuals from different populations.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"46\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"50\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"44\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"52\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Source</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Cases</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Controls</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>Percent</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Odds ratio</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"left\" rowspan=\"1\"><bold>95% CI bounds</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Fisher’s exact test p value</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>M98K</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>M98K</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>OAG</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Control</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Lower</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Upper</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">China<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15312511##14##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">26<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">118<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">150<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.64<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.08<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.148<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16148883##15##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">129<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">400<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">281<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">32.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">28.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.18<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.84<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.64<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.355<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Japan<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">51<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">247<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">89<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">20.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.63<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.20<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.80<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.014<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15557444##16##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">411<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">36<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">218<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">19.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">16.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.24<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.91<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.389<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15226658##17##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">25<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">154<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">16.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.68<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.36<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.97<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.009<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12811537##20##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">51<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">313<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">196<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">16.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">13.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.22<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.74<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.02<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.527<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15370540##21##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">12<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">83<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">58<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.63<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.22<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">76.31<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.149<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Asia<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">29<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">117<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">60.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">24.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.55<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.72<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">28.60<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.112<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Europe<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">13<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">217<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">116<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.86<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.34<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.14<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.814<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">46<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">650<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">162<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.16<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.57<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.35<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12920093##12##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">315<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">95<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.30<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.67<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.87<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.224<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15498064##13##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">94<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.43<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.38<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">15.33<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.310<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16020311##32##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.90<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.36<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.25<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14627677##18##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">237<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">110<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.02<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.35<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.02<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16358725##33##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">170<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.85<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.87<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">53.87<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.036<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##11834836##9##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">23<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">169<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">422<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">13.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.23<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.27<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">15.98<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15851979##22##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">105<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">93<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">6.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Hispanic<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">50<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.90<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.28<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">85.05<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.331<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Africa<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">18<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">81<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">20<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.97<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.47<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.00<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">India<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16205626##19##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">22<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">200<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">11.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.12<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.00<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.51<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.068<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16885925##39##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">220<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">inf<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.04<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">inf<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.034<hr/></td></tr><tr><td colspan=\"11\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Mixed<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16885188##38##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">28<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">498<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">17<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">218<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">5.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">7.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.70<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.38<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.315<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16988596##36##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">14<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">153<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">100<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.02<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.42<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.45<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12912697##23##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">86<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">80<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10.0<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.92<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.33<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.59<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">1.000<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15326130##24##]</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">115</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">101</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">10.4</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">4.0</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.83</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.88</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">9.06</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.116</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t9\" position=\"float\"><label>Table 9</label><caption><title>Aggregate statistical summaries for populations screened for M98K.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"56\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"55\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"44\" span=\"1\"/><col width=\"43\" span=\"1\"/><col width=\"42\" span=\"1\"/><col width=\"51\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Ancestry</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>OAG</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>Controls</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>Percent</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Odds ratio</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>95% CI bounds</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Woolf test p value</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Fisher's exact test p value</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>M98K</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>M98K</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Total</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>OAG</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Controls</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Lower</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Upper</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">China<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">155<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">518<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">103<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">431<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">29.9<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">23.9<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.26<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.94<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.70<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.354<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.04<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Japan<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">220<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1208<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">77<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">661<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">18.2<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">11.6<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.65<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.25<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2.19<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.046<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Asia<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">375<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1726<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">180<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1092<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">21.7<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">16.5<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.46<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.19<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.79<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.075<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.0006<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Europe<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">131<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1873<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">48<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1276<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">7<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">3.8<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.87<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.31<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2.66<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.005<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td colspan=\"12\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Total<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">600<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">4871<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">277<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">3167<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">12.3<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8.7<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.51<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.29<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.77<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.002<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">-<hr/></td></tr><tr><td colspan=\"12\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Japan-NTG<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">142<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">705<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">77<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">661<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">20.1<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">11.6<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.91<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.40<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2.62<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.240<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2E-05<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Europe-NTG<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">28<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">371<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">24<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">544<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">7.5<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">4.4<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.77<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.97<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">3.24<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.149<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.58<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">Total-NTG</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">170</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1076</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">101</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1205</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">15.8</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">8.4</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.75</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">1.33</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">2.31</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">0.177</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">6E-08</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t10\" position=\"float\"><label>Table 10</label><caption><title>M98K population data sources and screening methods ordered by ancestry.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"82\" span=\"1\"/><col width=\"167\" span=\"1\"/><col width=\"116\" span=\"1\"/><col width=\"116\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Source</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Recruitment locations (population)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Methodology</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Notes</bold><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">China<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15312511##14##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">China-Beijing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16148883##15##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">China-Hong Kong<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR and HTCSGE-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Japan<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Japan-Gifu<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15557444##16##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Japan-Tokyo, Kumamoto, Hamamatsu, Hiroshima, Niigata<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15226658##17##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Japan-Miyagi<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12811537##20##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Japan-Yamanashi<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15370540##21##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Japan-Okayama City<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Asia (other than China and Japan)<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Michigan (Korean, Chinese, Filipino)<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Europe<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Michigan<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14597044##11##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Australia-Melbourne, Adelaide, USA-Iowa<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Australian samples Are Caucasian (D. Mackey, personal report), Iowa population &gt;91% Caucasian according to the State Data Center of Iowa<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12920093##12##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">England-London<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Caucasian<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15498064##13##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Australia-New South Wales<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">mostly Caucasian<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16020311##32##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Sweden-Uppsala and Tierps<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">DHPLC, PCR, SNaPshot<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##14627677##18##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">France-Paris<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">French and Moroccan Caucasians<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16358725##33##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Russia-St. Petersburg<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP, PCR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##11834836##9##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Chicago, Connecticut, New Haven, UK-London, Canada-Toronto<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing and SSCP-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Unspecified cases with Caucasian controls<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15851979##22##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Germany-Tuebingen, Wuerzburg<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP, DHPLC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Hispanic<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Michigan, Florida, Mexico, Panama, Peru, Chile, Paraguay<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Africa<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">[This study]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Michigan, Ghana- Acra, Sunyani<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">African American and African<hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">India<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16205626##19##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">India-Hyperabad, Kolkata<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">SSCP-&gt;sequencing, DHPLC, PCR--RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16885925##39##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">India-Chennai<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing, RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td colspan=\"4\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\">Mixed<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16885188##38##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Australia/Tasmania<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##16988596##36##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-New England area<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing, DHPLC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">about 90% Caucasian<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##12912697##23##]<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">USA-Massachusetts, North Carolina<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-&gt;sequencing<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">about 90% Caucasian<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"> [##REF##15326130##24##]</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Canada-Toronto</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">PCR-RFLP</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>The frequency distribution of cases and controls according to open-angle glaucoma (OAG) condition and ancestry (national) in our analysis included 314 cases with juvenile onset OAG (JOAG), primary open-angle glaucoma (POAG), and normal tension glaucoma (NTG).</p></table-wrap-foot>", "<table-wrap-foot><p>Primers used in amplification of <italic>OPTN</italic> exons were also used in sequencing reactions. Primers located in introns were placed far enough away from the exon boundaries to allow visualization of the sequence of the splice sites. Exons 4 through 16 are the exons that contain coding sequence.</p></table-wrap-foot>", "<table-wrap-foot><p>Primers used in amplification of <italic>MYOC</italic> exons were also used in sequencing reactions. Primers located in introns were placed far enough away from the exon boundaries to allow visualization of the sequence of the splice sites. Primer pairs 1A, 2, and 3A were used for PCR amplification and sequencing of exons 1, 2, and 3, respectively. Primers 1B and 3B are internal primers that were used for sequencing purposes only.</p></table-wrap-foot>", "<table-wrap-foot><p>All case samples were screened and scored for each mutation listed. Absence of a listing for one of the four control groups does not imply that it was screened. Data for M98K appear in ##TAB##4##Table 5##.</p></table-wrap-foot>", "<table-wrap-foot><p>The total enumeration of both cases and controls is listed in the whole population column. Cases are subdivided according to OAG type, either JOAG, POAG, or NTG. A two-sided Fisher's exact test p value indicated no statistical significance for association between cases and controls in each ancestry category. Woolf's test for homogeneity among the ancestry frequencies yielded a p value of 0.312, indicating that the ancestral subdivisions are statistically similar.</p></table-wrap-foot>", "<table-wrap-foot><p>The asterisks denote a calculation based on adding 0.5 to each cell in cases with a zero cell frequency, otherwise the value is nonexistent. Lower and upper bounds refer to the individual study 95% confidence interval around the odds ratio for a fixed effects Mantel-Haenszel model. Information from Leung et al. [##REF##12939304##35##] were omitted because it duplicated that contained in Fan et al. [##REF##16148883##15##]. Data from Toda et al. [##REF##14755458##37##] were omitted because it duplicated information contained in Tang et al. [##REF##12811537##20##]. In the Europe category, only the data regarding Caucasians (Iowa and Australia) in Alward et al. [##REF##14597044##11##] were enumerated, while the reported cases with pigmentary, developmental, and exfoliative data were omitted.</p></table-wrap-foot>", "<table-wrap-foot><p>Results from computing the upper and lower 95% confidence interval bounds around the odds ratio indicate that none of the Asian divisions are statistically different from an odds ratio of 1. The Woolf test for homogeneity indicates that across studies within each ancestry group the odds ratios are statistically equivalent (i.e., homogeneous, because a p value less than 0.05 would indicate heterogeneity [##UREF##0##25##]). A two-sided Fisher's exact test on the pooled frequencies was computed for those instances when the Woolf test indicated homogeneity at the 0.05 level. The ancestry groups are collated for China from Chen et al. [##REF##15312511##14##] and Fan et al. [##REF##16148883##15##]; and for Japan from Alward et al. [##REF##14597044##11##], Funayama et al. [##REF##15557444##16##], Fuse et al. [##REF##15226658##17##], Tang et al. [##REF##12811537##20##], and Umeda et al. [##REF##15370540##21##]. The Asia listing includes data pooled from the China and Japan categories. Only Fan et al. [##REF##16148883##15##] report on NTG for China.</p></table-wrap-foot>", "<table-wrap-foot><p>Under the fixed effects Mantel-Haenszel model, individual study 95% confidence interval bounds around the odds ratio are given. For compatibility with much of the published literature the two-sided Fisher's exact test p values are given for each study. Although the presence of M98K mutations in OAG cases appears to be statistically significant relative to controls, Alward et al. [##REF##14597044##11##] reported that when multi-testing is taken into account their result becomes nonsignificant. Information from Leung et al. [##REF##12939304##35##] was omitted because it duplicated the information contained in Fan et al. [##REF##16148883##15##]. Data from Toda et al. [##REF##14755458##37##] were omitted because they duplicated the observations contained in Tang et al. [##REF##12811537##20##]. Pigmentary and exfoliative data were omitted from the Europe (Caucasians living in Iowa and Australia) samples reported by Alward et al. [##REF##14597044##11##]. Rezaie et al. [##REF##11834836##9##] reported a p value=2.18^-7.</p></table-wrap-foot>", "<table-wrap-foot><p>The ancestry groups are collated for China: Chen et al. [##REF##15312511##14##] and Fan et al. [##REF##16148883##15##]; Japan: Alward et al. [##REF##14597044##11##], Funayama et al. [##REF##15557444##16##], Fuse et al. [##REF##15226658##17##], Tang et al. [##REF##12811537##20##], and Umeda et al. [##REF##15370540##21##]; Europe: Alward et al. [##REF##14597044##11##], Aung et al. [##REF##12920093##12##], Baird et al. [##REF##15498064##13##], Jansson et al. [##REF##16020311##32##], Melki et al. [##REF##14627677##18##], Rakhmanov et al. [##REF##16358725##33##], Rezaie et al. [##REF##11834836##9##], and Weisschuh et al. [##REF##15851979##22##]. Asia is the pooling of the China and Japan categories. The total combines all published studies from the lines above with the addition of Craig et al. [##REF##16885188##38##], Hauser et al. [##REF##16988596##36##], Mukhopadhyay et al. [##REF##16205626##19##], Sripriya et al. [##REF##16885925##39##], Wiggs et al. [##REF##12912697##23##], and Willoughby et al. [##REF##15326130##24##]. The Europe-NTG group consists of the data from Alward et al. [##REF##14597044##11##], Aung et al. [##REF##12920093##12##], Baird et al. [##REF##15498064##13##], Rakhmanov et al. [##REF##16358725##33##], and Weisschuh et al. [##REF##15851979##22##]. Results from computing the upper and lower 95% confidence interval bounds around the odds ratio indicate that some studies are statistically different than an odds ratio of 1. The Woolf test for homogeneity indicated that across studies within each ancestry group which of the odds ratios were statistically equivalent (i.e., heterogeneity is indicated by a p value less than 0.05 [##UREF##0##25##]). A two-sided Fisher's exact test on the pooled frequencies is given for those instances when the Woolf test indicated homogeneity at the 0.05 level. When Rezaie et al. [##REF##11834836##9##] data are excluded the Europe group, then the odds ratio becomes 1.33 with a 95% confidence interval of (0.90, 1.98), Woolf p value of 0.512, and a Fisher's exact test p value of 0.072.</p></table-wrap-foot>", "<table-wrap-foot><p>The following methodologies were used to screen samples for variants. We omitted two studies: Wang et al. [##REF##15547491##40##], a Filipino population, and Forsman et al. [##REF##12789137##34##], a population from south Finland, because they are small family-based studies without population data. SSCP: single-strand conformation polymorphism. DHPLC: denaturing high-performance liquid chromatography. HTCSGE: High throughput conformation sensitive gel electrophoresis. RFLP: Restriction Fragment Length Polymorphisms.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-151-f1\"/>", "<graphic xlink:href=\"mv-v13-151-f2\"/>", "<graphic xlink:href=\"mv-v13-151-f3\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Primary hereditary cataracts are common in purebred dogs, affecting over 120 breeds. Cataracts frequently cause visual impairment and are a major cause of blindness in dogs [##UREF##0##1##, ####UREF##1##2##, ##UREF##2##3##, ##UREF##3##4##, ##UREF##4##5##, ##REF##15762923##6####15762923##6##]. Inheritance of noncongenital cataracts has been demonstrated in several dog breeds, e.g., the golden and labrador retrievers [##REF##4423543##7##,##UREF##5##8##], German shepherd [##UREF##6##9##], West Highland white terrier [##REF##7289590##10##], American cocker spaniel [##UREF##7##11##], Tibetan terrier [##REF##15301763##12##], Afghan hound [##REF##5014602##13##], standard poodle [##REF##5036188##14##,##REF##4024442##15##], and the Entlebucher mountain dog [##REF##15910366##16##]. As the dachshund is a breed predisposed to primary noncongenital cataract (CAT), it is assumed that these cataracts are also hereditary [##UREF##1##2##,##UREF##3##4##].</p>", "<p>Dachshunds are bred in three coat varieties (long-haired, smooth-haired, and wire-haired) and three different sizes (standard, dwarf, and rabbit). Dwarf- and rabbit-sized dachshunds are referred to in this investigation as miniature dachshunds. The prevalence of CAT in the long-haired dachshund in North America is 2.10% [##REF##15762923##6##]. In Germany, the prevalence has been estimated to be 3.21% for the long-haired, 1.87% for the smooth-haired, and 4.80% for the wire-haired dachshund [##UREF##8##17##]. In an animal threshold model, the heritabilities for CAT were 0.39±0.06 (wire-haired), 0.08±011 (long-haired), and 0.72±0.28 (short-haired) [##UREF##8##17##].</p>", "<p>The transparency and high refractive index of the eye lens is achieved by a regular arrangement of the lens fiber cells and by a high concentration and the supramolecular organization of the lens-specific proteins, the crystallins, within each fiber cell [##UREF##9##18##].</p>", "<p>The crystallin proteins are the major structural components of the eye lens that constitute 80-90% of its soluble proteins. These proteins are divided into three classes, α-, β-, and γ-crystallins, which form two protein superfamilies: the α-crystallin superfamily and the β-/γ-crystallin superfamily [##REF##6548413##19##,##REF##9497271##20##]. The common characteristic of the β-/γ-superfamily is a unique folding structure, the Greek-key motif. Each of the β- and γ-crystallins has two domains, with each domain being composed of two extremely stable protein structures, the so-called Greek-key structural motifs. These structures allow a dense packing of proteins in the ocular lens [##REF##9426193##21##,##REF##10627816##22##]. Any structural alterations of these proteins can disturb the highly ordered tissue architecture and can lead to opacity. Because of that, the genes that encode these proteins are obvious candidate genes for cataracts.</p>", "<p>The γ-crystallins are encoded by the <italic>CRYG</italic> genes. Six members of the <italic>CRYG</italic> family (<italic>CRYGA</italic>-<italic>CRYGF</italic>) are located in a cluster on mouse chromosome 1 [##REF##3242494##23##, ####REF##3248380##24##, ##REF##1358796##25####1358796##25##] and on human chromosome 2, respectively [##REF##2991114##26##, ####UREF##10##27##, ##REF##3011643##28####3011643##28##]. The seventh <italic>CRYG</italic> gene, <italic>CRYGS</italic>, maps to mouse chromosome 16 and human chromosome 3 [##UREF##11##29##,##REF##9565648##30##]. Also in the dog, the <italic>CRYG</italic> genes are located in a cluster on dog chromosome (CFA) 37 with the exception of <italic>CRYGS</italic>, which maps to CFA34 [##REF##16760895##31##]. In mice, mutations identified in different <italic>CRYG</italic> genes are known to cause dominant or recessive cataracts [##REF##1303247##32##, ####REF##10704279##33##, ##REF##11133865##34##, ##REF##11121426##35##, ##REF##12079281##36##, ##REF##12202521##37##, ##REF##11773036##38####11773036##38##]. Also in humans, several hereditary cataracts have been shown to be caused by mutations in the <italic>CRYG</italic> genes [##REF##10521291##39##, ####REF##9927684##40##, ##REF##10915766##41##, ##REF##10914683##42##, ##REF##12011157##43####12011157##43##]. In this report, we provide the complete sequence and the genomic sequences of all exons of <italic>CRYGB</italic>, <italic>CRYGC,</italic> and <italic>CRYGS.</italic> In addition, we test single nucleotide polymorphisms for linkage and association in dachshunds and compare expression of mRNA in lenses of dogs affected by primary cataract and an unaffected control dog.</p>" ]

[ "<title>Methods</title>", "<title>Animals, phenotypic data, and DNA specimens</title>", "<p>Ophthalmological data for the dachshunds were provided by the Dortmunder Kreis (DOK), which is the German panel of the European Eye Scheme for diagnosis of inherited eye diseases in animals. The German Dachshund Club 1888 e.V. (DTK) supplied pedigree data and we identified pedigrees with multiple CAT-affected dogs. For the present analysis, we chose 24 dogs from four different dachshund families. Most of the animals (14 dogs) came from a standard-sized wire-haired family, whereas seven wire-haired miniature dachshunds were from two different families. The other three dogs were smooth-haired standard-sized dachshunds. Altogether, this study included 17 CAT-affected dachshunds. The signs of CAT in these dogs differed in regard to stage. In seven dogs an immature cataract was diagnosed, in eight dogs an incipient cataract, and in two dogs a mature cataract. Most of the affected dogs included in the analysis had an opacification localized in the cortex of the lens (82.4%). Lens opacity was additionally found in the capsule (one dog) and the nucleus (five dogs). In one dog only the nucleus was affected; two dogs showed only capsular opacifications. Both eyes were affected in ten animals, while alterations were found only in the lens of the left eye in the other seven. Most of the dogs (about 70%) were examined two to three times. CAT was first diagnosed at a mean age of 3.67±2.14 years. At least one unaffected dog was investigated from each family. The seven unaffected dogs were between 5.1 and 9.7 years old at the last ophthalmological examination.</p>", "<p>We also tested four unaffected dogs from other breeds (dalmatian, German shepherd mix, Hanoverian hound, great dane) as control animals.</p>", "<p>Two milliliters of heparinized blood were obtained from each dog, and DNA was extracted using QIAamp 96 DNA Blood kit (Qiagen, Hilden, Germany).</p>", "<p>For cDNA analysis of the three genes, we used lens tissue of seven dogs of six different breeds (mixed breed, German shepherd dog, dachshund mix, Jack Russell terrier, Tibetan terrier, and Yorkshire terrier). Six of the seven dogs underwent cataract surgery; one dog (mixed breed) with normal lenses was used as reference. The cataract surgery was done using the phacoemulsification method with ultrasound. After removal from eye, the lens tissue was conserved using RNA-later solution (Qiagen). The RNA was extracted from dog lens tissue using the Nucleospin RNA II-Kit (Machery-Nagel, Düren, Germany) and transcribed into cDNA using SuperScript III Reverse Transcriptase (Invitrogen, Karlsruhe, Germany).</p>", "<title>Structural analysis of the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> gene</title>", "<p>We searched the dog-expressed sequence tag (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/genome/seq/BlastGen/BlastGen.cgi?taxid=9615\">EST</ext-link>) archive for ESTs by cross-species BLAST searches with the corresponding human reference mRNA sequences for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_005210\">NM_005210</ext-link>), <italic>CRYGC</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_020989\">NM_020989</ext-link>), and <italic>CRYGS</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_017541\">NM_017541</ext-link>). We found a canine EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>) isolated from dog lens tissue with 88% identity to the human <italic>CRYGB</italic> mRNA sequence. A significant match to this canine EST was identified on canine chromosome 37 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876304.1\">NW_876304.1</ext-link>|Cfa37_WGA83_2) by means of BLASTN searches of this canine EST against the dog genome assembly (Dog genome assembly 2.1).</p>", "<p>For <italic>CRYGC</italic> we found a canine EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>) with 87% identity to the human mRNA sequence. A significant match to this canine EST was identified on canine chromosome 37 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876304.1\">NW_876304.1</ext-link>|Cfa37_WGA83_2) [##REF##16879363##44##].</p>", "<p>We also found a canine EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) isolated from beagle lens tissue with 90% identity to the human <italic>CRYGS</italic> mRNA sequence. A significant match to this canine EST was identified on canine chromosome 34 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876301.1\">NW_876301.1</ext-link>|Cfa34_WGA80_2) by means of BLASTN searches of this canine EST against the dog genome assembly (Dog genome assembly 2.1). The genomic structure of the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes were determined with the <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/IEB/Research/Ostell/Spidey/index.html\">Spidey</ext-link> mRNA-to-genomic alignment program. We verified the canine ESTs by sequencing the cDNA of all three genes isolated from the lens of seven dogs. The primers were designed in such a way that the open reading frames of the three genes were amplified. All reverse primers were located downstream from the stop codons of the three genes. The forward primers included the start codon (<italic>CRYGB</italic> and <italic>CRYGS</italic>) or were located a few bases upstream of the start codon (<italic>CRYGC</italic>; ##TAB##0##Table 1##).</p>", "<title>Mutation analysis</title>", "<p>For evaluation of <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> as candidate genes for CAT in the dachshund, we sequenced all exons and their flanking intronic regions of the three genes for the animals mentioned above (##TAB##0##Table 1##). All PCRs were performed in 50 μl reactions using 50 pmol of each primer, 100 μM dNTPs, 2 U <italic>Taq</italic>-DNA-Polymerase (Q-BIOgene, Heidelberg, Germany) in the reaction buffer supplied by the manufacturer, and 10X PCR Enhancer (Invitrogen, Karlsruhe, Germany) for 2 μl template DNA or cDNA, respectively. The PCR conditions were as follows: 95 °C for 4 min followed by 34 cycles of 94 °C for 30 s, annealing temperature of 58 °C for 45 s, 72 °C for 45 s, and 4 °C for 10 min. All PCR products were cleaned using the Nucleo-Fast PCR purification kit (Machery-Nagel) and directly sequenced with the DYEnamic ET Terminator kit (Amersham Biosciences, Freiburg, Germany) and a MegaBACE 1000-capillary sequencer (Amersham Biosciences). PCR primers were generated with the <ext-link ext-link-type=\"uri\" xlink:href=\"http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi\">Primer3</ext-link> program based on the canine ESTs (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) and the canine genomic sequences (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876304.1\">NW_876304.1</ext-link>|Cfa37_WGA83_2, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876304.1\">NW_876304.1</ext-link>|Cfa37_WGA83_2, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NW_876301.1\">NW_876301.1</ext-link>|Cfa34_WGA80_2). Sequence data were analyzed with Sequencher 4.7 (GeneCodes, Ann Arbor, MI).</p>", "<title>Nonparametric linkage and association analyses</title>", "<p>A nonparametric multipoint linkage analysis was employed for the four dachshund families. This analysis was based on allele sharing by identical-by-descent methods and the MERLIN 1.0.1 software [##REF##11731797##45##]. Haplotypes were estimated using MERLIN 1.0.1 using the option \"best\". A case-control analysis based on χ² tests for genotypes, alleles, and trends of the most prevalent allele was also performed for the dachshund families. The CASECONTROL and ALLELE procedures of <ext-link ext-link-type=\"uri\" xlink:href=\"http://support.sas.com/software/91x/geneugwhatsnew900.htm\">SAS</ext-link> were used for association tests, tests for Hardy-Weinberg equilibrium of genotype frequencies, and the estimation of allele frequencies.</p>" ]

[ "<title>Results &amp; Discussion</title>", "<title>Position of <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> on canine chromosomes</title>", "<p>The canine ESTs for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>) and <italic>CRYGS</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>), which were found by cross-species BLAST searches with the corresponding human reference mRNA sequences, mapped to the same positions as the annotated canine genes for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) and <italic>CRYGS</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC607506\">LOC607506</ext-link>; ##TAB##1##Table 2##). For <italic>CRYGC</italic>, no annotated canine gene is available but the <italic>CRYGC</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>) mapped between canine <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) and <italic>CRYGD</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488495\">LOC488495</ext-link>). This assumed position of <italic>CRYGC</italic> in dogs agrees with all other investigated species [##REF##3242494##23##, ####REF##3248380##24##, ##REF##1358796##25####1358796##25##]. A recent study tried to obtain sequence tagged sites (STS) for <italic>CRYGB</italic> and other candidate genes for primary cataracts in the dog [##REF##16760895##31##]. The putative canine <italic>CRYGB</italic> amplicon was located at 20,124,535-20,124,930 on CFA37 in this previous study. This location is close to <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC609894\">LOC609894</ext-link>, similar to <italic>CRYGE</italic>. However, the canine <italic>CRYGB</italic> gene (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) as verified in our study is located on CFA37 at 19.440-19.445 Mb. Comparisons between the primer sequence of the <italic>CRYGB</italic> amplicon (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link>) used by Hunter et al. [##REF##16760895##31##] and the predicted canine mRNA sequences for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) and <italic>CRYGE</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_847242.1\">XM_847242.1</ext-link>) showed that the canine mRNA sequence for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) had less homology (95%) to the sequence under accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link> than the canine mRNA sequence for <italic>CRYGE</italic> (97%). Homology between the predicted canine mRNA sequences for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) and the human <italic>CRYGB</italic> mRNA sequence (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_005210\">NM_005210</ext-link>) was 88%, but only 81% between predicted canine <italic>CRYGE</italic> mRNA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_847242.1\">XM_847242.1</ext-link>) and human <italic>CRYGB</italic> mRNA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_005210\">NM_005210</ext-link>). The canine EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN86603\">DN86603</ext-link>) we used to determine the genomic structure of the canine <italic>CRYGB</italic> gene mapped to the same position as the annotated canine locus for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>). The <italic>CRYGB</italic> cDNA sequences of all seven dogs analyzed in the present study perfectly matched the sequence of the canine <italic>CRYGB</italic> EST.</p>", "<p>The crystallin genes are similar genes that show high sequence homologies to each other. We assume that the problems of the previous study to place the putative <italic>CRYGB</italic> amplicon to the predicted canine <italic>CRYGB</italic> location was due to assortment of the wrong sequence (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link>) for primer design of the <italic>CRYGB</italic> amplicon.</p>", "<title>Genomic organization of canine <italic>CRYGB</italic></title>", "<p>The canine <italic>CRYGB</italic> gene was found to contain all three exons and two introns that are present in the orthologous human gene, and the canine exon/intron boundaries conformed perfectly to the GT/AG rule. The sizes of all three exons of the canine <italic>CRYGB</italic> gene were identical to those of the human <italic>CRYGB</italic> gene. Analysis of the 648 bp of the canine <italic>CRYGB</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>) revealed an open reading frame of 528 bp predicting a protein of 175 amino acids. The canine CRYGB protein displayed 84.6% similarity to the human CRYGB protein and 91.4% similarity to the mouse CRYGB protein (##FIG##0##Figure 1##).</p>", "<p>The canine EST contained 29 nucleotides before the start codon in exon 1, and 91 nucleotides after the stop codon in exon 3. The polyadenylation signal AAUAAA was located 37 bp downstream of the stop codon.</p>", "<p>The cDNA sequences of lens tissue of the seven dogs perfectly matched the sequences of the canine ESTs. Only the 5' and the 3' ends were shorter due to primer position.</p>", "<p>The gene structure described here is in contrast to the annotated structure of the canine <italic>CRYGB</italic> gene (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>), which was derived by automated computational analysis (Dog genome assembly 2.1). Under this accession number, the canine <italic>CRYGB</italic> gene has five exons, with exon 3 corresponding to human exon 1, exon 4 corresponding to human exon 2, and exon 5 corresponding to human exon 3. The canine EST and our sequenced <italic>CRYGB</italic> cDNA contained only the predicted canine exons 3, 4, and 5. No canine EST was found for the predicted exons 1 and 2.</p>", "<p>The γ-crystallin genes are considered to be highly conserved genes, which are similar among the different species. In all mammals examined to date, the γ-crystallin genes have a three-exon-structure: a short first exon, which encodes the start codon, and the short NH₂-terminal \"arm\". The other two exons encode the two structural domains, each of which contains two Greek key motifs [##REF##9426193##21##,##REF##10627816##22##,##REF##3052280##46##]. We could not verify the predicted canine exons 1 and 2 as described in <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>. Due to the fact that the gene structure of <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link> was derived by automated computational analysis, it is possible that the predicted exons 1 and 2 do not exist.</p>", "<title>Genomic organization of canine <italic>CRYGC</italic></title>", "<p>The canine <italic>CRYGC</italic> gene contained all three exons and two introns that are present in the orthologous human gene. The sizes of all three exons of the canine <italic>CRYGC</italic> gene were identical to the human <italic>CRYGC</italic> gene. The analysis of the 669 bp of the canine <italic>CRYGC</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>) revealed an open reading frame of 525 bp, predicting a protein of 174 amino acids. As the canine EST contained 89 nucleotides before the start codon in exon 1 and 55 nucleotides after the stop codon in exon 3, we assumed that the 5'- and 3'-UTR of the canine <italic>CRYGC</italic> were included [##REF##16879363##44##]. The canine CRYGC protein displayed 87.4% similarity to the mouse CRYGC and 87.9% similarity to the human CRYGC protein (##FIG##0##Figure 1##).</p>", "<title>Genomic organization of canine <italic>CRYGS</italic></title>", "<p>The canine <italic>CRYGS</italic> gene also had three exons interrupted by two introns as does the orthologous human gene. The canine exon/intron boundaries conformed perfectly to the GT/AG rule, and the sizes of all three exons of the canine <italic>CRYGS</italic> gene were identical to those of the human <italic>CRYGS</italic> gene. Analysis of the 680 bp of the canine <italic>CRYGS</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) revealed an open reading frame of 537 bp, predicting a protein of 178 amino acids. The canine CRYGS protein displayed 93.3% similarity to the human CRYGS protein and 87.1% similarity to the mouse CRYGS protein (##FIG##0##Figure 1##). The canine EST contained 39 nucleotides before the start codon in exon 1 and 104 nucleotides after the stop codon in exon 3. The polyadenylation signal AAUAAA was located 76 bp downstream of the stop codon.</p>", "<p> <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC607506\">LOC607506</ext-link> lists seven isoforms of the canine <italic>CRYGS</italic> gene which were derived by automated computational analysis (Dog genome assembly 2.1). The isoform with the transcript ID <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_844792\">XM_844792</ext-link>.1 agrees with the results of our study. The other isoforms have additional exons, which were not confirmed in our analysis, or have different exon sizes that do not fit into the canine EST.</p>", "<p>To confirm the results of the structure analyses of the three genes, it would be necessary to produce a full-length cDNA using RACE methods. For this purpose it is necessary to obtain complete RNA with intact 3' and 5' ends. It was possible to gain the cDNA sequence of all three genes without the 5' ends. The cDNA sequences of all dogs perfectly matched to the sequences of the canine ESTs. Our sequenced cDNA of the three genes contained all exons corresponding to the ESTs described (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) and a few bases upstream from the start codons and downstream from the stop codons, respectively. ##FIG##1##Figure 2## shows the cDNAs from the lens of two CAT-affected dogs and an unaffected dog for each gene on an agarose gel. The cDNAs of the other four dogs did not differ in sequence and product size. However, even after several attempts, it was not possible to receive full-length cDNAs of the investigated genes.</p>", "<title>Polymorphisms within the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> gene</title>", "<p>The search for sequence variations within the three genes revealed a total of five SNPs as shown in ##TAB##2##Table 3##. Of these five SNPs, two were located in the exon sequence of <italic>CRYGC</italic> while another was located in the exon sequence of <italic>CRYGB</italic>. The exonic SNP of <italic>CRYGB</italic> was a T&gt;C transition in exon 3, which changes a GTT triplet to a GTC triplet. Both triplets code for valine and thus do not alter the amino acid sequence of <italic>CRYGB</italic>. In the <italic>CRYGC</italic> gene, a C/T transition at position 112 of exon 3 was observed only in the wire-haired dachshunds. This transition changes a CGC triplet into a TGC triplet and thus causes an amino acid change from arginine (R) to cysteine (C). This means a change from a charged alkaline amino acid to a neutral amino acid with a nonpolar side chain. Multi species protein sequence comparisons between human (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_066269\">NP_066269</ext-link>), mice (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_031801\">NP_031801</ext-link>), rat (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XP_343583\">XP_343583</ext-link>), and cattle (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_001013613\">NP_001013613</ext-link>) showed that this position was not variable between the known orthologous <italic>CRYGC</italic> proteins.</p>", "<p>The second exonic SNP of <italic>CRYGC</italic> was found at position 127 of exon 3. This C/T SNP changes a CTG triplet to a TTG triplet, which has no effect on the amino acid sequence of <italic>CRYGC</italic>. Except for <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>:c.364C&gt;T, all other SNPs were polymorphic in all six examined breeds (##TAB##2##Table 3##). None of the polymorphisms affected the splice sites in the investigated genes.</p>", "<title>Linkage and association analyses for <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic></title>", "<p>##TAB##1##Table 2## shows the results of the nonparametric multipoint linkage analysis in the dachshunds. All SNP alleles were in Hardy-Weinberg equilibrium. The highest Z-mean value was 0.32 and the highest LOD score was 0.16, while the error probabilities ranged from 0.2 to 0.4. The maximum achievable Z-mean was 29.85 and the corresponding value for the LOD score was 5.52. These values indicated that the pedigrees used had enough power to detect significant linkage. There were also no significant results from the case-control χ²-tests for the dachshund families. The χ² test statistics for allelic distributions between cases and controls ranged from 0.02 to 0.52 and their error probabilities from 0.88 to 0.47. Similar results were obtained for the distributions of genotypes between cases and controls (χ² from 0.50 to 3.17 with error probabilities from 0.78 to 0.20).</p>", "<p>Therefore, it is unlikely that the <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes are involved in the pathogenesis of CAT in these wire- and smooth-haired dachshunds.</p>", "<p>None of the five polymorphisms identified in this study proved to be a causal mutation for CAT in canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> exons and exon/intron junctions in the CAT-affected wire- and smooth-haired dachshunds from our pedigrees. In addition, expression analysis of these genes in six affected dogs and a control dog did not reveal any differences in the bands on an agarose gel. So it seems unlikely that a mutation outside of the genomic regions analyzed here possibly affects <italic>CRYGB</italic>, <italic>CRYGC</italic> or <italic>CRYGS</italic> expression. However, the SNPs identified here may be useful to test <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> as candidate genes in other dog breeds.</p>" ]

[ "<title>Results &amp; Discussion</title>", "<title>Position of <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> on canine chromosomes</title>", "<p>The canine ESTs for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>) and <italic>CRYGS</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>), which were found by cross-species BLAST searches with the corresponding human reference mRNA sequences, mapped to the same positions as the annotated canine genes for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) and <italic>CRYGS</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC607506\">LOC607506</ext-link>; ##TAB##1##Table 2##). For <italic>CRYGC</italic>, no annotated canine gene is available but the <italic>CRYGC</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>) mapped between canine <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) and <italic>CRYGD</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488495\">LOC488495</ext-link>). This assumed position of <italic>CRYGC</italic> in dogs agrees with all other investigated species [##REF##3242494##23##, ####REF##3248380##24##, ##REF##1358796##25####1358796##25##]. A recent study tried to obtain sequence tagged sites (STS) for <italic>CRYGB</italic> and other candidate genes for primary cataracts in the dog [##REF##16760895##31##]. The putative canine <italic>CRYGB</italic> amplicon was located at 20,124,535-20,124,930 on CFA37 in this previous study. This location is close to <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC609894\">LOC609894</ext-link>, similar to <italic>CRYGE</italic>. However, the canine <italic>CRYGB</italic> gene (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>) as verified in our study is located on CFA37 at 19.440-19.445 Mb. Comparisons between the primer sequence of the <italic>CRYGB</italic> amplicon (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link>) used by Hunter et al. [##REF##16760895##31##] and the predicted canine mRNA sequences for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) and <italic>CRYGE</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_847242.1\">XM_847242.1</ext-link>) showed that the canine mRNA sequence for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) had less homology (95%) to the sequence under accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link> than the canine mRNA sequence for <italic>CRYGE</italic> (97%). Homology between the predicted canine mRNA sequences for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_545618.2\">XM_545618.2</ext-link>) and the human <italic>CRYGB</italic> mRNA sequence (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_005210\">NM_005210</ext-link>) was 88%, but only 81% between predicted canine <italic>CRYGE</italic> mRNA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_847242.1\">XM_847242.1</ext-link>) and human <italic>CRYGB</italic> mRNA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_005210\">NM_005210</ext-link>). The canine EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN86603\">DN86603</ext-link>) we used to determine the genomic structure of the canine <italic>CRYGB</italic> gene mapped to the same position as the annotated canine locus for <italic>CRYGB</italic> (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>). The <italic>CRYGB</italic> cDNA sequences of all seven dogs analyzed in the present study perfectly matched the sequence of the canine <italic>CRYGB</italic> EST.</p>", "<p>The crystallin genes are similar genes that show high sequence homologies to each other. We assume that the problems of the previous study to place the putative <italic>CRYGB</italic> amplicon to the predicted canine <italic>CRYGB</italic> location was due to assortment of the wrong sequence (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=AACN010184836\">AACN010184836</ext-link>) for primer design of the <italic>CRYGB</italic> amplicon.</p>", "<title>Genomic organization of canine <italic>CRYGB</italic></title>", "<p>The canine <italic>CRYGB</italic> gene was found to contain all three exons and two introns that are present in the orthologous human gene, and the canine exon/intron boundaries conformed perfectly to the GT/AG rule. The sizes of all three exons of the canine <italic>CRYGB</italic> gene were identical to those of the human <italic>CRYGB</italic> gene. Analysis of the 648 bp of the canine <italic>CRYGB</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>) revealed an open reading frame of 528 bp predicting a protein of 175 amino acids. The canine CRYGB protein displayed 84.6% similarity to the human CRYGB protein and 91.4% similarity to the mouse CRYGB protein (##FIG##0##Figure 1##).</p>", "<p>The canine EST contained 29 nucleotides before the start codon in exon 1, and 91 nucleotides after the stop codon in exon 3. The polyadenylation signal AAUAAA was located 37 bp downstream of the stop codon.</p>", "<p>The cDNA sequences of lens tissue of the seven dogs perfectly matched the sequences of the canine ESTs. Only the 5' and the 3' ends were shorter due to primer position.</p>", "<p>The gene structure described here is in contrast to the annotated structure of the canine <italic>CRYGB</italic> gene (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>), which was derived by automated computational analysis (Dog genome assembly 2.1). Under this accession number, the canine <italic>CRYGB</italic> gene has five exons, with exon 3 corresponding to human exon 1, exon 4 corresponding to human exon 2, and exon 5 corresponding to human exon 3. The canine EST and our sequenced <italic>CRYGB</italic> cDNA contained only the predicted canine exons 3, 4, and 5. No canine EST was found for the predicted exons 1 and 2.</p>", "<p>The γ-crystallin genes are considered to be highly conserved genes, which are similar among the different species. In all mammals examined to date, the γ-crystallin genes have a three-exon-structure: a short first exon, which encodes the start codon, and the short NH₂-terminal \"arm\". The other two exons encode the two structural domains, each of which contains two Greek key motifs [##REF##9426193##21##,##REF##10627816##22##,##REF##3052280##46##]. We could not verify the predicted canine exons 1 and 2 as described in <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link>. Due to the fact that the gene structure of <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC488497\">LOC488497</ext-link> was derived by automated computational analysis, it is possible that the predicted exons 1 and 2 do not exist.</p>", "<title>Genomic organization of canine <italic>CRYGC</italic></title>", "<p>The canine <italic>CRYGC</italic> gene contained all three exons and two introns that are present in the orthologous human gene. The sizes of all three exons of the canine <italic>CRYGC</italic> gene were identical to the human <italic>CRYGC</italic> gene. The analysis of the 669 bp of the canine <italic>CRYGC</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>) revealed an open reading frame of 525 bp, predicting a protein of 174 amino acids. As the canine EST contained 89 nucleotides before the start codon in exon 1 and 55 nucleotides after the stop codon in exon 3, we assumed that the 5'- and 3'-UTR of the canine <italic>CRYGC</italic> were included [##REF##16879363##44##]. The canine CRYGC protein displayed 87.4% similarity to the mouse CRYGC and 87.9% similarity to the human CRYGC protein (##FIG##0##Figure 1##).</p>", "<title>Genomic organization of canine <italic>CRYGS</italic></title>", "<p>The canine <italic>CRYGS</italic> gene also had three exons interrupted by two introns as does the orthologous human gene. The canine exon/intron boundaries conformed perfectly to the GT/AG rule, and the sizes of all three exons of the canine <italic>CRYGS</italic> gene were identical to those of the human <italic>CRYGS</italic> gene. Analysis of the 680 bp of the canine <italic>CRYGS</italic> EST (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) revealed an open reading frame of 537 bp, predicting a protein of 178 amino acids. The canine CRYGS protein displayed 93.3% similarity to the human CRYGS protein and 87.1% similarity to the mouse CRYGS protein (##FIG##0##Figure 1##). The canine EST contained 39 nucleotides before the start codon in exon 1 and 104 nucleotides after the stop codon in exon 3. The polyadenylation signal AAUAAA was located 76 bp downstream of the stop codon.</p>", "<p> <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=LOC607506\">LOC607506</ext-link> lists seven isoforms of the canine <italic>CRYGS</italic> gene which were derived by automated computational analysis (Dog genome assembly 2.1). The isoform with the transcript ID <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XM_844792\">XM_844792</ext-link>.1 agrees with the results of our study. The other isoforms have additional exons, which were not confirmed in our analysis, or have different exon sizes that do not fit into the canine EST.</p>", "<p>To confirm the results of the structure analyses of the three genes, it would be necessary to produce a full-length cDNA using RACE methods. For this purpose it is necessary to obtain complete RNA with intact 3' and 5' ends. It was possible to gain the cDNA sequence of all three genes without the 5' ends. The cDNA sequences of all dogs perfectly matched to the sequences of the canine ESTs. Our sequenced cDNA of the three genes contained all exons corresponding to the ESTs described (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN866034\">DN866034</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867380\">DN867380</ext-link>) and a few bases upstream from the start codons and downstream from the stop codons, respectively. ##FIG##1##Figure 2## shows the cDNAs from the lens of two CAT-affected dogs and an unaffected dog for each gene on an agarose gel. The cDNAs of the other four dogs did not differ in sequence and product size. However, even after several attempts, it was not possible to receive full-length cDNAs of the investigated genes.</p>", "<title>Polymorphisms within the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> gene</title>", "<p>The search for sequence variations within the three genes revealed a total of five SNPs as shown in ##TAB##2##Table 3##. Of these five SNPs, two were located in the exon sequence of <italic>CRYGC</italic> while another was located in the exon sequence of <italic>CRYGB</italic>. The exonic SNP of <italic>CRYGB</italic> was a T&gt;C transition in exon 3, which changes a GTT triplet to a GTC triplet. Both triplets code for valine and thus do not alter the amino acid sequence of <italic>CRYGB</italic>. In the <italic>CRYGC</italic> gene, a C/T transition at position 112 of exon 3 was observed only in the wire-haired dachshunds. This transition changes a CGC triplet into a TGC triplet and thus causes an amino acid change from arginine (R) to cysteine (C). This means a change from a charged alkaline amino acid to a neutral amino acid with a nonpolar side chain. Multi species protein sequence comparisons between human (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_066269\">NP_066269</ext-link>), mice (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_031801\">NP_031801</ext-link>), rat (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=XP_343583\">XP_343583</ext-link>), and cattle (R; accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_001013613\">NP_001013613</ext-link>) showed that this position was not variable between the known orthologous <italic>CRYGC</italic> proteins.</p>", "<p>The second exonic SNP of <italic>CRYGC</italic> was found at position 127 of exon 3. This C/T SNP changes a CTG triplet to a TTG triplet, which has no effect on the amino acid sequence of <italic>CRYGC</italic>. Except for <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=DN867687\">DN867687</ext-link>:c.364C&gt;T, all other SNPs were polymorphic in all six examined breeds (##TAB##2##Table 3##). None of the polymorphisms affected the splice sites in the investigated genes.</p>", "<title>Linkage and association analyses for <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic></title>", "<p>##TAB##1##Table 2## shows the results of the nonparametric multipoint linkage analysis in the dachshunds. All SNP alleles were in Hardy-Weinberg equilibrium. The highest Z-mean value was 0.32 and the highest LOD score was 0.16, while the error probabilities ranged from 0.2 to 0.4. The maximum achievable Z-mean was 29.85 and the corresponding value for the LOD score was 5.52. These values indicated that the pedigrees used had enough power to detect significant linkage. There were also no significant results from the case-control χ²-tests for the dachshund families. The χ² test statistics for allelic distributions between cases and controls ranged from 0.02 to 0.52 and their error probabilities from 0.88 to 0.47. Similar results were obtained for the distributions of genotypes between cases and controls (χ² from 0.50 to 3.17 with error probabilities from 0.78 to 0.20).</p>", "<p>Therefore, it is unlikely that the <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes are involved in the pathogenesis of CAT in these wire- and smooth-haired dachshunds.</p>", "<p>None of the five polymorphisms identified in this study proved to be a causal mutation for CAT in canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> exons and exon/intron junctions in the CAT-affected wire- and smooth-haired dachshunds from our pedigrees. In addition, expression analysis of these genes in six affected dogs and a control dog did not reveal any differences in the bands on an agarose gel. So it seems unlikely that a mutation outside of the genomic regions analyzed here possibly affects <italic>CRYGB</italic>, <italic>CRYGC</italic> or <italic>CRYGS</italic> expression. However, the SNPs identified here may be useful to test <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> as candidate genes in other dog breeds.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>We analyzed the γ-crystallin genes <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> in the dog and tested single nucleotide polymorphisms (SNPs) for linkage and association with primary noncongenital cataract (CAT) in the dachshund, a popular dog breed. The crystallin genes may be involved in the pathogenesis of canine CAT as shown in humans and mice.</p>", "<title>Methods</title>", "<p>We sequenced all exons and their flanking intronic regions of the <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes and in addition, the complete cDNA of these three genes using lens tissue from CAT-affected and unaffected dogs of several breeds. After examining BLASTN analyses, we compared the gene structure with the predicted genes in the current dog genome assembly and the orthologs of humans and mice.</p>", "<title>Results</title>", "<p>The search for SNPs within these crystallin genes revealed a total of five polymorphisms. As both CAT-affected and unaffected dogs shared identical haplotypes, there was no cosegregation of the SNP alleles with the affected animals. Expression did not differ among CAT-affected and unaffected dogs.</p>", "<title>Conclusions</title>", "<p>The polymorphisms reported for <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> can be excluded as causative mutations for the CAT phenotype in the wire- and smooth-haired dachshund. The canine cataract gene orthologs described here may serve as a valuable resource for further studies in other dog breeds to develop a canine model. Many different dog breeds are affected by CAT. The use of the SNPs presented in this paper can facilitate the screening of more dog breeds.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>The authors express their gratitude to the German Dachshund Club 1888 e.V. (DTK) for providing the pedigree data and the blood samples as well as for the financial support of this study. The authors thank the veterinary ophthalomologists of the Dortmunder Kreis (DOK) for providing the ophthalmological data. We particularly thank the veterinary ophthalomologists Dr. I. Allgoewer, Dr. R. Brahm, Dr. H. Grußendorf, S. Hertslet, Dr. J. Linek. and Prof. Dr. A. Meyer-Lindenberg for providing lens tissue of dogs. We also thank Heike Klippert-Hasberg for expert technical assistance.</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>γ-Crystallin protein alignment. Shown are the alignment of the canine CRYGB protein (175 amino acids), the canine CRYGC protein (174 amino acids), and the canine CRYGS protein (178 amino acids) derived from our sequenced cDNA with the known orthologous protein sequences. The sequences were derived from GenBank entries with the following accession numbers: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_005201\">NP_005201</ext-link> (human CRYGB), <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_658906\">NP_658906</ext-link> (mouse CRYGB), <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_066269\">NP_066269</ext-link> (human CRYGC), <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_031801\">NP_031801</ext-link> (mouse CRYGC), <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_060011\">NP_060011</ext-link> (human CRYGS) and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NP_034097\">NP_034097</ext-link> (mouse CRYGS). Residues identical to the dog are indicated by asterisks. The three exons are labeled by different colors. All exons included only complete triplets.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>γ-Crystallin cDNA analysis. Bands of cDNA PCR products of the lens tissue of two dogs affected by CAT and an unaffected dog for each gene (<italic>CRYGB</italic>, 567 bp; <italic>CRYGC</italic>, 603 bp; and <italic>CRYGS</italic>, 645 bp) on an agarose gel. In the gel, band 1=mixed breed, unaffected; band 2=dachshund mix, affected; band 3=German shepherd, affected. The cDNAs of the other four dogs did not differ in sequence and product size.</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title>γ-Crystallin PCR primers.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"52\" span=\"1\"/><col width=\"64\" span=\"1\"/><col width=\"116\" span=\"1\"/><col width=\"219\" span=\"1\"/><col width=\"74\" span=\"1\"/><col width=\"52\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Gene</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Target</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Primer</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Sequence (5'-3') of primers</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Annealing temperature (°C)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Product size (bp)</bold><hr/></td></tr><tr><td rowspan=\"4\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGB<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">Exon 1 and Exon 2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGB_Ex1_Ex2_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TGGTTTAATTGCCTTTGAGG<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">929<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGB_Ex1_Ex2_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGCAAGCACCACAGAGTTC<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\">Exon 3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGB_Ex3_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTGGAAGCAAACCTAGACTCC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">577<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGB_Ex3_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCCCCCTTAGAAGACAGTATTTC<hr/></td></tr><tr><td rowspan=\"6\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">Exon 1 and 5' UTR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGC_Ex1_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CACTAAGAATCCAAATAAAAGCAAC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">390<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGC_Ex1_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CGTAGAAGGTGATCTGCAAAG<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\">Exon2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGC_Ex2_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AAGGTGAGCGGGATACAAG<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">494<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGC_Ex2_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CTGGCTTTGTGCATTTGTC<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\">Exon 3 and 3' UTR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGC_Ex3_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACACACAGCCATCTCAGAGTC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">577<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGC_Ex3_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CATTTCACTTTGCAGAGCTTC<hr/></td></tr><tr><td rowspan=\"6\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGS<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">Exon 1 and 5' UTR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGS_Ex1_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TCAATAGCCTCTAAATGACTGACTC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">290<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGS_Ex1_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GTACATTGGAAAAGAGGAAACG<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\">Exon2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGS_Ex2_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCCAGAGGATAGGTGTTGTG<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">495<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGS_Ex2_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GGGAGGGAGTAGGGAAAAG<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\">Exon 3 and 3' UTR<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGS_Ex3_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CATGCTGTTCTCGGAGTTG<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">468<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGS_Ex3_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">AGGCATTACAGTCAACACTGG<hr/></td></tr><tr><td colspan=\"6\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGB<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">cDNA CRYGB*<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGB_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CATGGGAAAGATCACCTTCTAC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">567<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGB_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTGGATTCTAAAGGACAAAAGTG<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">cDNA CRYGC**<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGC_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCCAGTCGCACTGAACTC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">603<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGC_R<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">TTAGGTTCCAAACTGAGAAAATG<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\">CRYGS</td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">cDNA CRYGS^#</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">CRYGS_F<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">ACCAATCTATGCAACAAAATGTC<hr/></td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">58</td><td rowspan=\"2\" valign=\"top\" align=\"left\" colspan=\"1\">645</td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">CRYGS_R</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">GCCAATTGTTTTATTTATGATGC</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t2\" position=\"float\"><label>Table 2</label><caption><title>SNP analysis.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"52\" span=\"1\"/><col width=\"130\" span=\"1\"/><col width=\"36\" span=\"1\"/><col width=\"31\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"38\" span=\"1\"/><col width=\"39\" span=\"1\"/><col width=\"39\" span=\"1\"/><col width=\"37\" span=\"1\"/><col width=\"37\" span=\"1\"/><col width=\"56\" span=\"1\"/><col width=\"56\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Position of gene (Mb)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>SNP</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>HET (%)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>PIC (%)</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Z-mean</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>P Z-mean</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>LOD Score</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>P LOD Score</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>χ² allele</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>P allele</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>χ² genotype</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>P genotype</bold><hr/></td></tr><tr><td colspan=\"12\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><italic>CRYGB</italic> on CFA37 19.440-19.442<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><italic>LOC488497:g.2537C&gt;A</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">45.8<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">31.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.16<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.02<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3.17<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.20<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><italic>LOC488497:g.4348T&gt;C</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">26.1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">24.6<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.16<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.23<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.63<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.83<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.24<hr/></td></tr><tr><td colspan=\"12\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><italic>CRYGC</italic> on CFA37 19.431-19.433<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><italic>DN867687:c.364C&gt;T</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">16.7<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">19.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.16<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.52<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.47<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.5<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.78<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><italic>DN867687:c.379C&gt;T</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">25<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">23.9<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.4<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.16<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.2<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.32<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.57<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.88<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.24<hr/></td></tr><tr><td colspan=\"12\" valign=\"top\" align=\"left\" scope=\"col\" rowspan=\"1\"><italic>CRYGS</italic> on CFA34 22.166-22.172<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"/><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><italic>DN867380:c.*7G&gt;A</italic></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">33.3</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">30.5</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.4</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.15</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.2</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.13</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.71</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">2.91</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.23</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t3\" position=\"float\"><label>Table 3</label><caption><title>Nucleotide polymorphisms within the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"64\" span=\"1\"/><col width=\"82\" span=\"1\"/><col width=\"138\" span=\"1\"/><col width=\"78\" span=\"1\"/><col width=\"78\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Gene</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Location of polymorphic site</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Position and nucleotide polymorphism</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Allele frequencies</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Genotype frequencies</bold><hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\"><italic>CRYGB</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Intron 1<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">NC_006619.2:g.2537C&gt;A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.71<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">50/43/7<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">Exon 3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">NC_006619.2:g.4348T&gt;C<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.80<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">67/26/7<hr/></td></tr><tr><td rowspan=\"2\" valign=\"top\" align=\"left\" scope=\"row\" colspan=\"1\"><italic>CRYGC</italic><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Exon 3^#<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">DN867687:c.364C&gt;T<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.89<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">82/14/4<hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"left\" scope=\"row\" rowspan=\"1\">Exon 3<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">DN867687:c.379C&gt;T<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.86<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">75/21/4<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><italic>CRYGS</italic></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">3'UTR</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">DN867380:c.*7G&gt;A</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">0.75</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">61/29/11</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Shown are the PCR primers for the amplification of genomic canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> exons with their flanking intronic regions and PCR primers for the amplification of the cDNA of the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes. The asterisk indicates that the forward primer is located 1 bp upstream of the start codon and the reverse primer is located 38 bp downstream of the stop codon. The double asterisk indicates that the forward primer is located 39 bp upstream of the start codon and the reverse primer is located 39 bp downstream of the stop codon. The sharp (hash mark) indicates that the forward primer is located 8 bp upstream of the start codon and the reverse primer is located 90 bp downstream of the stop codon.</p></table-wrap-foot>", "<table-wrap-foot><p>Shown are heterozygosity (HET), polymorphism information content (PIC), chromosome-wide multipoint test statistics Z-mean and LOD Score, their error probabilities (p Z-mean, p LOD Score), χ²-tests for allele and genotype distribution of the case-control analysis and their corresponding error probabilities (P) for the SNPs in the dachshund families. According to the SNP nomenclature, the asterik indicates the position of a changed nucleotide 3' of the translation stop codon.</p></table-wrap-foot>", "<table-wrap-foot><p>Shown are the locations of nucleotide polymorphisms within the canine <italic>CRYGB</italic>, <italic>CRYGC</italic>, and <italic>CRYGS</italic> genes, their positions in the canine sequence used for the respective gene and SNP allele frequencies for the wild-type allele and distribution of SNP genotypes as percent of animals (homozygous for allele 1, and heterozygous and homozygous for allele 2). According to the SNP nomenclature, the asterik indicates the position of a changed nucleotide 3' of the translation stop codon. The sharp (hash mark) indicates that this SNP showed only a polymorphism in the wire-haired dachshunds.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-125-f1\"/>", "<graphic xlink:href=\"mv-v13-125-f2\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Usher Syndrome type 1 (USH1) is the most severe form of Usher syndrome [##REF##8160750##1##] and is characterized by congenital profound deafness, vestibular areflexia, and (generally) early onset of retinitis pigmentosa (RP). Six loci have been mapped and five genes have been identified: myosin VIIa (<italic>MYO7A</italic>), cadherin-23 (<italic>CDH23</italic>), protocadherin-15 (<italic>PCDH15</italic>), harmonin (<italic>USH1C</italic>), and SANS (<italic>USH1G</italic>) [##REF##11700295##2##,##REF##12786748##3##]. <italic>MYO7A</italic> appears to be the most frequently involved, and mutations have been reported in 29-54 [##REF##10930322##4##,##REF##9382091##5##] percent of cases but there have been few systematic studies on a cohort of patients [##REF##15660226##6##,##REF##16679490##7##].</p>", "<p>The USH1F locus was mapped about ten years ago to chromosome 10q21-22, and the <italic>PCDH15</italic> gene was cloned in 2001 [##REF##11487575##8##]. Several USH1F transcripts have been identified in humans, and the longest isoform (isoform A), consisting of 1 noncoding and 32 protein-coding exons, encodes a 1955 amino acid transmembrane protein that is predicted to contain 11 cadherin repeats, one transmembrane domain, and a cytoplasmic domain containing two proline-rich regions [##REF##11487575##8##, ####REF##11398101##9##, ##REF##14570705##10####14570705##10##]. Recently, multiple alternative protocadherin-15 transcripts were characterized in the mouse inner ear. These transcripts define four major isoform classes alternatively spliced, and two of them encode new cytoplasmic domains, raising the number of exons to 39. Three of these isoforms have different spatiotemporal expression patterns in developing and mature hair cells, suggesting a specific role for each protocadherin-15 isoform in the sensory hair bundle [##REF##16807332##11##]. These alternatively spliced exons encoding the two novel cytoplasmic domains were also detected in human retina, indicating that the organization of the human gene could be more complex than was initially thought [##REF##16807332##11##]. Together with other USH1 proteins protocadherin-15 ensures hair bundle morphogenesis [##REF##16219682##12##] via its binding to harmonin [##REF##15590703##13##,##REF##15928608##14##] and myosin VIIa [##REF##16481439##15##].</p>", "<p>Around 25 mutations have been documented, nearly all predicted to lead to premature termination of the proteins (6-10). Ouyang et al. [##REF##15660226##6##] studied <italic>PCDH15</italic> together with other USH1 genes in a cohort of patients and found <italic>PCDH15</italic> mutations in five patients but identified both causative mutations in only one of them.</p>", "<p>We present in this study an exhaustive analysis of the deletions that were detected in three different families [##REF##16679490##7##]. We show that not only are all deletions different, they also account for a significant proportion of <italic>PCDH15</italic> mutations, probably because of the genomic structure of this gene. We suggest that deletion screening should be part of the molecular analysis for <italic>PCDH15</italic> and any other genes that have such an unusual genomic structure.</p>" ]

[ "<title>Methods</title>", "<title>Patients</title>", "<p>The project was approved by the local ethics committee. Consent to genetic testing was obtained from adult probands or parents of minors. Patients meeting the diagnostic criteria for USH1 were previously described [##REF##16679490##7##]. USH1 was diagnosed on the basis of congenital profound sensorineural deafness, vestibular dysfunction, and retinal degeneration.</p>", "<p>U153 and U297 were sporadic cases whereas two affected siblings were available for family U382. All patients underwent audiological examination and all presented with profound deafness. The age of walking was delayed and ranged from 18 months (U153) to 36 months (U297). Electroretinograms (ERG) and fundus examinations were altered in all cases when diagnoses were made at 9 years old (U153 and U297). The ERG was already extinguished at 4 years old in both siblings in family U382.</p>", "<title>Sequencing analysis of <italic>PCDH15</italic></title>", "<p>PCR amplification and sequencing of the <italic>PCDH15</italic> gene, corresponding to isoform A as described by Ahmed et al. [##REF##14570705##10##] (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_033056\">NM_033056</ext-link>), has already been reported [##REF##16679490##7##]. PCR parameters and primers have already been published in the study from Roux et al. [##REF##16679490##7##].</p>", "<title>Haplotypes</title>", "<p>Haplotypes were constructed from a combination of intragenic single nucleotide polymorphisms (SNPs) and seven microsatellite markers: D10S1124-D10S2522-<italic>PCDH15</italic>(IVS3-(CA)-D10S2536-D10S546)-D10S1643- D10S1762. The location of the markers is reported in ##FIG##0##Figure 1A##. Sequences of the microsatellite primers are available on <ext-link ext-link-type=\"uri\" xlink:href=\"http://gdbwww.gdb.org\">gdb</ext-link> with the exception of IVS3-(CA)-IVS3-F: 5'-GTA TGT ACA GTT AAT TGG TAG-3'; IVS3-R: 5'-GAT GCA GGT ATG GTT TCA G-3'.</p>", "<p>Microsatellites were analyzed on an ABI 3100 Avant genetic analyzer (Applied Biosystems, Applera France, France) whereas the SNPs were analyzed by direct sequencing.</p>", "<title>Semiquantitative assays</title>", "<p>Two semiquantitative approaches were used in parallel: the quantitative multiplex PCR of short fluorescent fragments (QMPSF) and semiquantitative nonfluorescent multiplex PCR. QMPSF containing multiplex PCR of 3-9 amplicons were analyzed on an ABI310 (Applied Biosystems). We applied to the PCDH15 gene the stategy used by Audrezet et al. for the CFTR gene [##REF##15024729##16##]. Semiquantitative nonfluorescent multiplex PCR products were separated under nondenaturing conditions on a liquid chromatography system (3500 Wave HS system coupled to an HSD system, Transgenomic, Elancourt, France) then quantified by fluorescent detection using a post column intercalation dye, based on guidelines described by Dehainault et al. [##REF##15477586##17##]. One advantage of the semiquantitative nonfluorescent multiplex PCR analyzed on the 3500 Wave HS system is that the primers used for routine sequencing can also be used to determine if a particular exon has been deleted.</p>", "<p>To narrow down the deletion breakpoints, we used PCR walking methods that included laboratory-designed amplicons localized in a first step every 50 kb both upstream and downstream of the identified deletions. The primers were chosen according to the sequence of the bacterial artificial chromosome (BAC) clones (their accession number is given in ##FIG##0##Figure 1A##). Once a breakpoint was localized between two adjacent amplicons, further primers were designed for new amplicons until this initial 50 kb distance was reduced to a maximum 4 kb interval. Each breakpoint interval thus characterized by PCR walking is positioned on the BAC clones (##FIG##1##Figure 2A##).</p>", "<title>Identification of the junction fragment in patient U297</title>", "<p>Once proximal and distal amplicons were identified within 4 kb intervals, a junction fragment of 1.3 kb was obtained using the forward primer of the proximal amplicon with the reverse primer of the distal amplicon. Further internal primers (U297-bkp-prox-F: 5'-TGA AGA AAC CAC TAA GAC TGA G-3' and U297-bkp-dist-R: 5'-GTA GCC ATT GCA GGC ACA G-3') enabled the sequencing of a 360 bp junction fragment.</p>", "<title>Analysis of control DNA</title>", "<p>Guthrie cards were obtained from the neonatal screening center GREPAM in Montpellier. All samples were anonymously referenced and neither phenotypic nor ethnic origin data were available. DNA was extracted using standard procedures. A total of 172 control DNAs were amplified for the noncoding exon 1 and exon 2. We tested 88 DNAs using primers U297-bkp-prox-F and U297-bkp-dist-R.</p>" ]

[ "<title>Results</title>", "<title>Haplotype analyses and evidence of the deletions</title>", "<p>We have previously reported the screening for mutations in <italic>MYO7A</italic>, <italic>CDH23</italic>, <italic>PCDH15, USH1C</italic>, and <italic>SANS</italic> in a cohort of 31 USH1 families [##REF##16679490##7##]. While conducting a preliminary linkage analysis using microsatellites surrounding each USH1 gene, we detected apparent noninheritance of some markers or failure of amplification among the USH1F panel (D10S1124; D10S2522; IVS3-(CA); D10S2536; D10S546; D10S1643 and D10S1762) in two families (U153, and U382) as shown on ##FIG##0##Figure 1B##. These results were confirmed by amplification in neighboring regions. Microsatellite analysis was not informative in patient U297 but a deletion was suggested after an apparently homozygous p.Arg290X mutation, localized in exon 8, was identified. This novel mutation appeared to be carried on different haplotypes as revealed by heterozygous intronic SNPs in the 3' end of the gene (##FIG##0##Figure 1B##).</p>", "<p>The resulting haplotypes of the three pedigrees are presented in ##FIG##0##Figure 1B## together with SNPs analyses when informative. Sequencing of the entire coding region of <italic>PCDH15</italic> revealed that the patients were compound heterozygotes for premature truncating mutations p.Ser144LeufsX15 (c.423_430dup) and p.Arg290X (c.868A&gt;T) in trans to the two deletions identified in U153 and U297. A third homozygous deletion was identified in family U382 with a known history of consanguinity.</p>", "<title>Narrowing of the breakpoints</title>", "<p>To narrow down the deletion breakpoints of the two compound heterozygous patients, we used two semiquantitative PCR walking methods. The narrowing of the deletion breakpoint in patient U382 was performed by simple PCR walking, looking at the amplification or nonamplification of each amplicon.</p>", "<p>When each breakpoint was localized within an interval below 4 kb, PCR was performed to identify the precise deletion breakpoints. One breakpoint was identified (U297; see ##FIG##1##Figure 2B##). Unfortunately, several other attempts using different long-range PCR kits failed to identify a junction fragment in the other two patients, suggesting that the deletions may be more complex than anticipated.</p>", "<p>PCR walking in patient U382 narrowed the deletion to a proximal breakpoint localized within a 1.6 kb interval in the 5' region of the <italic>PCDH15</italic> gene and to a distal breakpoint lying in IVS1 within an 1.4 kb interval. The size of the deletion is estimated as 190 kb (##FIG##0##Figure 1## and ##FIG##1##Figure 2##). None of the 172 control DNAs showed an absence of amplification of exon 1 excluding a similar homozygous deletion in these controls.</p>", "<p>The deletion in patient U153 was originally characterized as spanning exons 3-5 by means of the intragenic marker D10S2536 and SNP. However this deletion was further characterized as extending from a proximal breakpoint within IVS1, within an interval of 3.5 kb, to a distal breakpoint within an 0.8 kb interval of IVS5 (##FIG##0##Figure 1## and ##FIG##1##Figure 2##). The size of the deletion is about 341 kb. None of the 172 control DNAs showed an absence of amplification of exon 2, excluding an homozygous deletion spanning at least this exon in these controls.</p>", "<p>The deletion in patient U297 was narrowed down by semiquantitative PCR then further characterized by amplification of a junction fragment (##FIG##1##Figure 2B##). The deletion spans about 684 kb, includes exon 8, and is in trans to the p.Arg290X mutation (##FIG##0##Figure 1## and ##FIG##1##Figure 2##). The proximal breakpoint, lies within 2.4 kb of U382 breakpoint, but is not identical. This junction fragment was not detected in 176 alleles (i.e., 88 control DNAs).</p>" ]

[ "<title>Discussion</title>", "<p>None of the deletions described in this paper have been found in normal controls, and they would all result in nonfunctional protein. Recent data has shown that multiple isoforms exist. No exon is present in all identified so far alternative transcripts [##REF##16807332##11##]. However, no isoform has been observed to containing deletions extending from exon 2 to exon 5 or 8. In addition, an Arg3X mutation in the second exon has been observed in two patients, providing evidence that the presence of the first few exons is necessary [##REF##11487575##8##,##REF##11398101##9##]. Recently, an alternatively spliced isoform (lacking exons 3-15) was found to circumvent the effect of the mutant allele IVS14-2A&gt;G in the homozygous <italic>Pcdh^15av-5J</italic> mice [##REF##16799054##18##]. Such a mechanism is not likely to be involved here as the patients described in this study are affected with typical USH1.</p>", "<p>The six intervals surrounding the breakpoints were placed on the BAC clones (NCBI Accession numbers given in ##FIG##0##Figure 1A## and ##FIG##1##Figure 2A##) and analyzed through repeat masker (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.repeatmasker.org/\">repeatmasker</ext-link>). Although short interspersed elements (SINE), long interspersed elements (LINE), and long terminal repeats (LTR) were found in all cases (##FIG##1##Figure 2A##), there is no evidence for direct repeats or duplicons as found in some other cases of recurrent deletion or duplication. In patient U297 the only obvious feature at the breakpoint is a repetition of GAA (##FIG##1##Figure 2B##). This is in line with the findings in studies of deletions of the dystrophin gene in DMD [##REF##16439068##19##] and duplications of <italic>PLP1</italic> in Pelizaeus-Merzbacher disease [##REF##16380909##20##].</p>", "<p>A detailed analysis of the gene structure provides a likely explanation for the high rate of such deletions. The gene spans nearly 1 Mb for a corresponding ORF of 7,021 bp. The intron size of <italic>PCDH15</italic> is up to 150 kb, and the first three exons of the gene cover 0.42 Mb. The six breakpoint intervals lie in introns ranging from 22 to 140 kb in size localized in the first third of the gene.</p>", "<p>Because of the large size of <italic>PCDH15</italic> and, in particular, the low proportion which is coding, predominantly in the 5' end of the gene, it is not surprising that large deletions, with differing breakpoints, form a significant proportion of <italic>PCDH15</italic> mutations (30% in our cohort) which represents nearly 10% of all USH1 patients [##REF##16679490##7##]. The situation is reminiscent of the high frequency of deletions within the dystrophin gene found in patients with Duchenne Muscular Dystrophy. The dystrophin gene coding region of 11 kb is encoded over 2.4 Mb of genomic DNA. Around 60% of mutations are large deletions [##REF##2491009##21##], and many occur within the two large introns 7 and 44 [##REF##1363782##22##].</p>", "<p>This observation has several implications. First, although an initial linkage analysis approach was incorporated to target which gene was the best candidate for mutation screening, it may also identify apparent noninheritance of markers. Second, these results show that restricting the molecular analysis of <italic>PCDH15</italic> in USH1F to sequencing is not sufficient, and testing for large genomic rearrangements is recommended. A previous study has described only one <italic>PCDH15</italic> mutation in patients [##REF##15660226##6##]. It is possible that either a large genomic deletion or a mutation lying in the additional exons [##REF##16807332##11##] accounts for the second pathogenic mutation in these patients. Detection of large genomic rearrangements is becoming easier and more routine with the development of methods such as multiplex ligation-dependent probe amplification (MLPA) and multiplex amplifiable probe hybridization (MAPH) [##REF##15603451##23##] and should be considered, particularly for genes with an extended genomic structure. Third, large genomic rearrangement analysis cannot be routinely achieved by PCR of junction fragments as each deletion appears to be different and is likely to be ineffective across breakpoints involving complex rearrangements. PCR may still be customized by semiquantitative PCR, or other methods, such as MLPA, may be developed.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>Protocadherin-15 (<italic>PCDH15</italic>) is one of the five genes currently identified as being mutated in Usher 1 syndrome and defines Usher syndrome type 1F (USH1F). When <italic>PCDH15</italic> was systematically analyzed for mutations in a cohort of USH1 patients, a number of deletions were found. Here we characterize these deletions as to extent, position, and breakpoints.</p>", "<title>Methods</title>", "<p>Microsatellite and single nucleotide polymorphism (SNP) analyses, used in a preliminary survey of an Usher cohort of 31 patients, revealed large deletions in three patients. These deletions were further characterized by semiquantitative PCR assays to narrow down the breakpoints.</p>", "<title>Results</title>", "<p>The analysis of the three large deletions revealed that all six breakpoints are different. The breakpoint junction was identified in one patient and the four other breakpoints were mapped to 4 kb. There were no specific distinguishing features of the isolated breakpoints.</p>", "<title>Conclusions</title>", "<p>A complete screen of <italic>PCDH15</italic> should include a search for large deletions. Failure to screen for gross genomic rearrangements is likely to significantly lower the mutation detection rate. A likely explanation for the high rate of such deletions is the unusual gene structure. <italic>PCDH15</italic> gene spans nearly 1 Mb for a corresponding open reading frame (ORF) of 7,021 bp. The intron sizes of <italic>PCDH15</italic> are up to 150 kb, and the first three exons of the gene cover 0.42 Mb. The genomic structure of any gene should be taken into consideration when designing a mutation screening strategy.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>We are grateful to Dr. Sandrine Marlin and Pr. Brigitte Gilbert who referred the patients and to the families who participated in this study. We thank SOS Rétinite for generous support (S.L.G.). This work was supported in part by le Ministère de la Recherche \"PHRC National 2004.\"</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Pedigrees at the USH1F locus. <bold>A</bold>: Genomic organization of the <italic>PCDH15</italic> isoform A with numbering of the exons as described by Ahmed et al. [##REF##14570705##10##] <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_033056\">NM_033056</ext-link>. The noncoding exon 1 is represented in grey. Positions of the BAC clones and the microsatellite markers are indicated. <bold>B</bold>: Representation of the three pedigrees with haplotypes. (-) represents lack of amplification; N represents normal. In the first pedigree \"Ins\" stands for the c.423_430dup mutation (insertion of 7 bp). The different haplotypes are indicated by rectangles with various fillings.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Schematic localization of the deletion breakpoints on the <italic>PCDH15</italic> gene and their analysis. <bold>A</bold>: Localization of the six deletion breakpoints on the bacterial artificial chromosome (BAC) clones. <bold>B</bold>: The breakpoint junction fragment identified in patient U297 is aligned with the wild-type sequences spanning the 5' and 3' breakpoints. The deleted sequences are crossed out.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"mv-v13-102-f1\"/>", "<graphic xlink:href=\"mv-v13-102-f2\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Blepharophimosis-ptosis-epicanthus inversus syndrome (BPES, OMIM <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?omim=110100\">110100</ext-link>) is a rare autosomal dominant disease with a prevalence of about 1 in 50,000 [##REF##3270326##1##]. Clinically, BPES has been divided into two subsets depending on the association of ocular malformation with (type I) or without (type II) premature ovarian failure (POF) [##REF##6613996##2##]. Genetically, however, both types are caused by mutations in <italic>FOXL2</italic>, and a genotype-phenotype correlation has been described in some cases [##REF##11175783##3##,##REF##11468277##4##].</p>", "<p>The human <italic>FOXL2</italic> gene (OMIM <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?omim=605597\">605597</ext-link>), located at 3q23, is a member of winged/forkhead transcription factor gene family [##REF##12297093##5##]. This single-exon gene codes a protein with 376 residues, which consists of a DNA-binding forkhead domain (resudes 52-152) and a polyalanine domain (residues 221-234) [##REF##11175783##3##,##REF##11401404##6##,##REF##8798505##7##]. A number of mutations in <italic>FOXL2</italic> have been identified [##REF##15300845##8##], including six novel mutations in the Chinese population [##REF##16454982##9##, ####REF##16394030##10##, ##REF##15450400##11####15450400##11##].</p>", "<p>Here, we report four mutations identified in six Chinese families with BPES. Two novel missense mutations were associated with BPES type II.</p>" ]

[ "<title>Methods</title>", "<title>Patients</title>", "<p>Thirteen probands with BPES from unrelated families were collected from the Zhongshan Ophthalmic Center. Informed consent conforming to the tenets of the Declaration of Helsinki and following the Guidance of Sample Collection of Human Genetic Diseases (863-Plan) by the Ministry of Public Health of China was obtained from all participated individuals or their guardians prior to the study. The diagnosis of BPES was based on criteria previously established [##REF##5538320##12##] with exclusion of microphthalmia.</p>", "<title>Mutation Analysis</title>", "<p>Genomic DNA was prepared from leucocytes of peripheral venous blood [##REF##2776474##13##]. Amplification of the genomic fragments encompassing <italic>FOXL2</italic> coding regions (NCBI human genome build 35.1, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NC_000003\">NC_000003</ext-link> for gDNA, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_023067\">NM_023067</ext-link> for mRNA, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=NP_075555\">NP_075555</ext-link> for protein) was carried out by PCR using primers as follows: AF: 5'-CAG CGC CTG GAG CGG AGA G-3', AR: 5'-CTT GCC GGG CTG GAA GTG C-3', BF: 5'-GAC CCG GCC TGC GAA GAC A-3', BR: 5'-GGC CGC GTG CAG ATG GTG T-3', CF: 5'-CGC GGC CGC TGT GGT CAA G-3', CR: 5'-GCT GGC GGC GGC GTC GTC-3'. The sizes of the amplified DNA fragments are 545 bp, 517 bp, and 500 bp, respectively.</p>", "<p>PCR amplification was carried out initially at 95 °C for 8 min, followed by 5 cycles at 94 °C for 40 s, at 68 °C for 40 s, at 72 °C for 40 s, then 5 cycles at 94 °C for 40 s, at 66 °C for 40 s, at 72 °C for 40 s, and a further 30 cycles at 94 °C for 40 s, at 64 °C for 40 s, at 72 °C for 40 s, and finally an elongation step at 72 °C for 5 min. Due to the high GC-rich nature of <italic>FOXL2</italic>, an additional 10% dimethylsulfoxide and 10% glycerol were added to the PCR mixture in order to successfully amplify the genomic fragments.</p>", "<p>Direct sequencing of the PCR products was performed with an ABI BigDye Terminator Cycle Sequencing Kit v3.1 (ABI Applied Biosystem, Foster City, CA), using an ABI 3100 Genetic Analyzer. Sequencing results from patients as well as the <italic>FOXL2</italic> consensus sequences from the NCBI Human Genome Database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NC_000003\">NC_000003</ext-link>) were imported into the SeqManII program of the Lasergene package (DNAStar Inc., Madison, WI) and then aligned to identify variations. Each mutation was confirmed by bidirectional sequencing. Mutation description followed the nomenclature recommended by the Human Genomic Variation Society (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.hgvs.org/mutnomen/\">HGVS</ext-link>).</p>", "<p>Any variation detected in <italic>FOXL2</italic> was further evaluated in available family members as well as in 100 normal controls by heteroduplex-SSCP analysis as described previously [##REF##8739504##14##]. Two additional pairs of primers were used for heteroduplex-SSCP analysis. The sequence of these primers were: DF: 5'- CCG TAA GCG GAC TCG TGC-3', DR: 5'- AGT AGT TGC CCT TGC GCT C-3', EF: 5'- CGC ACT TCC AGC CCG GCA A-3', and ER: 5'- TGT GTA CGG CCC GTA CGA-3'.</p>", "<p>In addition, one variation of insertions with multiple nucleotides that was found in three families was further analyzed by cloning sequencing. PCR products harboring this mutation were subcloned to pMD18-T Simple Vector (TaKaRa BIO, Japan) according to the manufacture's instructions. Clones with the mutant allele as well as the normal allele were selected by using heteroduplex-SSCP analysis. Sequence of the cloned fragment was identified by cycle sequencing as described above. Mutations were confirmed by sequencing three positive clones from each family. One mutation, c.241T&gt;C, was further analyzed by PCR-RFLP analysis since the mutation creates a new <italic>FOK</italic>I site.</p>" ]

[ "<title>Results</title>", "<p>All patients demonstrated typical features of BPES, including small palpebral fissures, ptosis of the eyelids, and epicanthus inversus (##FIG##0##Figure 1##). Upon complete sequencing analysis of <italic>FOXL2</italic> for 13 probands with BPES, four heterozygous mutations were found in six probands, including c.241T&gt;C, c.650C&gt;G, c.804dupC, and c.672_701dup (##FIG##1##Figure 2##; ##TAB##0##Table 1##). Of the four, c.241T&gt;C and c.650C&gt;G are novel. All four heterozygous mutations were further detected by heteroduplex-SSCP analysis, and one (c.241T&gt;C) was further detected by <italic>FOK</italic>I digestion (##FIG##2##Figure 3##). These mutations were also present in affected patients from corresponding families but neither in unaffected individuals nor in 100 controls.</p>", "<p>The c.241T&gt;C (p.Tyr81His) mutation results in substitution of a charge-free tyrosine with a charge-positive basic hydrophilic histidine within the forkhead domain. The c.650C&gt;G (p.Ser217Cys) mutation is located immediately upstream of the polyalanine domain. The tyrosine at position 81 and the serine at position 217 are well conserved in <italic>FOXL2</italic> by ClustalW analysis of 11 orthologs from related vertebrate species (##FIG##3##Figure 4##).</p>" ]

[ "<title>Discussion</title>", "<p><italic>FOXL2</italic> encodes a forkhead transcription factor containing a forkhead domain for DNA-binding and a polyalanine domain of uncertain function. Strong expression of <italic>FOXL2</italic> has been found in eyelids [##REF##11175783##3##,##REF##7795600##15##], developing periocular muscles, and surrounding tissues [##REF##14684984##16##,##REF##12630957##17##]. Of the four mutations identified in this study, the c.241T&gt;C affected the forkhead domain, while the other three (c.650C&gt;G, c.804dupC, and c.672_701dup) were located upstream, within, and downstream of the polyalanine domain, respectively.</p>", "<p>Missense mutations in <italic>FOXL2</italic> reported so far usually occurred at the forkhead domain [##REF##16454982##9##,##REF##12630957##17##, ####REF##12938087##18##, ##REF##12529855##19####12529855##19##], except two, such as c.650C&gt;T in a Belgian family [##REF##11468277##4##] and c.644A&gt;G in a five-generation family from south-India [##REF##15257268##20##]. The clinical subtypes of the patients with the c.650C&gt;T and c.644A&gt;G mutations were unknown. The novel c.650C&gt;G (p. Ser217Cys) mutation identified in Chinese family B occurred at the same site as that found in the Belgian family, which is located immediately upstream of the polyalanine domain. The serine at position 217 is well conserved in 11 orthologs (##FIG##3##Figure 4##). It has been shown that mutations affecting the polyalanine domain induce extensive nuclear and cytoplasmic protein aggregation [##REF##15591279##21##,##REF##16219626##22##]. Missense changes have been suggested to act as null allele leading to BPES phenotype due to haploinsufficiency [##REF##11468277##4##] or dominant-negative effect [##REF##15257268##20##,##REF##12149404##23##].</p>", "<p>It has been suggested that <italic>FOXL2</italic> mutations truncating the protein led to BPES type I while those extending the mutant protein were associated with type II [##REF##11175783##3##,##REF##11468277##4##]. However, intra- and inter-family phenotypic variations have been found [##REF##11175783##3##,##REF##11468277##4##,##REF##12529855##19##,##REF##12567411##24##,##REF##11910558##25##] so that this genotype-phenotype correlation might not be general [##REF##12938087##18##,##REF##12529855##19##,##REF##11960581##26##]. The c.804dupC mutation has been shown to cause both types of BPES [##REF##11468277##4##,##REF##12529855##19##,##REF##11910558##25##], and the c.672_701dup causing polyalanine expansion most likely leads to BPES type II [##REF##12529855##19##]. Missense mutations have been associated with both BPES type I [##REF##12630957##17##] and II [##REF##11175783##3##,##REF##12529855##19##]. The patients from families A and B in this study, with novel c.241T&gt;C and c.650C&gt;G mutations, respectively, had type II BPES. The c.650C&gt;G mutation is the first mutation described that occurs immediately upstream of the polyalanine domain and associated with type II BPES. This may raise a possibility that the region containing the c.650C&gt;G mutation is of importance for <italic>FOXL2</italic> function.</p>", "<p>The c.672_701dup (p.Ala224_Ala234dup) was found in families D, E, and F (##TAB##0##Table 1##), consistent with a mutation hotspot. To check the origin of the c.672_701dup mutation in three families (families D, E, and F in ##FIG##2##Figure 3##), six SNPs (including <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs13325788\">rs13325788</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs2291252\">rs2291252</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs28937885\">rs28937885</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs7432551\">rs7432551</ext-link>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs28937884\">rs28937884</ext-link>, and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs11924939\">rs11924939</ext-link>) were analyzed (##TAB##1##Table 2##). The SNP at <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs2291252\">rs2291252</ext-link> is different between patient II:1 from family D and patient III:1 from family E, which may suggest a different origin of the mutant allele. The mutation in family F is most likely a de novo event as BPES was not present in the patients' parents although the SNPs in the patient II:1 in family F were the same as that of II:1 in family D. It has been reported that 30% of the <italic>FOXL2</italic> mutations lead to polyalanine expansion [##REF##12529855##19##]. The c.672_701dup has been found in BPES families of Caucasian [##REF##11468277##4##,##REF##12529855##19##,##REF##12400065##27##,##REF##16283882##28##] and Asian origin [##REF##16394030##10##,##REF##14986827##29##].</p>", "<p>In summary, we identified two novel and two known mutations in <italic>FOXL2</italic> of six Chinese families with BPES. The two novel mutations are the first reported instances that were associated with BPES type II. Our results expanded the spectrum of <italic>FOXL2</italic> mutations and confirmed the mutation hotspot in <italic>FOXL2</italic>.</p>" ]

[]

[ "<p>(The first two authors contributed equally to this publication)</p>", "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>Blepharophimosis-ptosis-epicanthus inversus syndrome (BPES) is an autosomal dominant disorder where eyelid malformation associated with (type I) or without (type II) premature ovarian failure (POF). It is ascribed to mutations in the forkhead transcriptional factor2 (<italic>FOXL2</italic>) gene. The purpose of this study is to identify mutations in <italic>FOXL2</italic> of Chinese patients with BPES.</p>", "<title>Methods</title>", "<p>Genomic DNA was prepared from leucocytes of peripheral venous blood. The coding regions and nearby intron sequences of <italic>FOXL2</italic> were analyzed by cycle and cloning sequencing.</p>", "<title>Results</title>", "<p>Four mutations in <italic>FOXL2</italic> were identified in six families, including c.241T&gt;C, c.650C&gt;G, c.804dupC, and c.672_701dup. Of the four, the c.241T&gt;C and c.650C&gt;G were novel and would result in missense changes of the encoded proteins, i.e., p.Tyr81His and p.Ser217Cys, respectively. The c.672_701dup (p.Ala224_Ala234dup) was detected in three families, indicating a mutation hotspot. The c.804dupC (p.Gly269ArgfsX265) mutation was found in one family.</p>", "<title>Conclusions</title>", "<p>Our results expand the spectrum of <italic>FOXL2</italic> mutations and confirm the mutation hotspot in <italic>FOXL2</italic>.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>The authors thank all patients and family members for their participation. This study was supported in part by the National 863 Plan of China (Z19-01-04-02 to QZ), National Natural Science Foundation of China (30572006 to QZ), and Foundation from the Ministry of Education of China (20050558073 to QZ).</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Clinical phenotype of a Chinese patient with BPES. A photo of the eyelid area from a 40 years old man (III:1 from family E in ##FIG##2##Figure 3##) demonstrated typical phenotype of BPES. The horizontal diameter of his cornea was 11.5 mm for both eyes. Ultrasound A-scan recorded an axial length of 24.19 mm/OD and 24.43 mm/OS. His refractive measurement was -3.00DCX180°/OD and -4.50DCX180°/OS.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Sequencing results of the two novel mutations in <italic>FOXL2.</italic> Sequence chromatograms of Family A (<bold>A</bold>) and family B (<bold>B</bold>), and their corresponding normal sequences. The underline below each sequence highlights the codon containing the mutation.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>Pedigrees and heteroduplex-SSCP analysis. Pedigrees of the different families (A, B, C, D, E, and F) are shown. Black filled symbols indicated patients affected with BPES in each family. The \"+/+\" or \"+/-\" sign indicated individuals analyzed with normal sequences or heterozygous mutation in <italic>FOXL2</italic>, respectively. The \"M\" under each lane indicated mutation, the \"N\" represented normal individuals, and \"N+M\" represented a mixture of PCR products resulted from normal and mutant clones. In addition, results of FOKI digestion for family A were present at the bottom of ##FIG##0##Figure 1A##. The c.241T&gt;C mutation in family A creates an additional <italic>FOK</italic>I site. By <italic>FOK</italic>I digestion of the 545 bp PCR product, normal allele yielded two fragments (340 bp and 205 bp), but the mutant allele yielded three fragments (275 bp, 205 bp, and 65 bp). Patients with the heterozygous c.241T&gt;C mutation had four bands (only three bands were shown in the figure) as compared to normal individuals with two bands.</p></caption></fig>", "<fig id=\"f4\" fig-type=\"figure\" position=\"float\"><label>Figure 4</label><caption><p>Multiple alignment of 11 FOXL2 orthologs. This demonstrated high conservation of residues involved by the p.Tyr81His and p.Ser217Cys mutation. The resource for the 11 FOXL2 orthologs was as follows: human (<italic>Homo sapiens</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=NP_075555\">NP_075555</ext-link>), mouse (<italic>Mus musculus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=NP_036150\">NP_036150</ext-link>), pig (<italic>Sus scrofa</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=AAQ91845\">AAQ91845</ext-link>), rabbit (<italic>Oryctolagus cuniculus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=AAQ91846\">AAQ91846</ext-link>), rat (<italic>Rattus norvegicus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=XP_345976\">XP_345976</ext-link>), mole vole (<italic>Ellobius lutescens</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=AAV30684\">AAV30684</ext-link>), cow (<italic>Bos taurus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=NP_001026920\">NP_001026920</ext-link>), goat (<italic>Capra hircus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=AAM52099\">AAM52099</ext-link>), chicken (<italic>Gallus gallus</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=NP_001012630\">NP_001012630</ext-link>), zebrafish (<italic>Danio rerio</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=XP_698915\">XP_698915</ext-link>), and salmon trout (<italic>Oncorhynchus mykiss</italic>, <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbprot=AAS87040\">AAS87040</ext-link>).</p></caption></fig>" ]

[ "<table-wrap id=\"t1\" position=\"float\"><label>Table 1</label><caption><title><italic>FOXL2</italic> mutations detected in Chinese patients with BPES.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"52\" span=\"1\"/><col width=\"79\" span=\"1\"/><col width=\"69\" span=\"1\"/><col width=\"73\" span=\"1\"/><col width=\"105\" span=\"1\"/><col width=\"61\" span=\"1\"/><tbody><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\"><bold>Family</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>DNA change</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Mutation type</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Location</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>Protein change</bold><hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\"><bold>BPES</bold><hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">A<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.241T&gt;C<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Missense<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Forkhead<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Tyr81His<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Type II<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">B<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.650C&gt;G<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Missense<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Immediately upstream polyalanine<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Ser21Cys<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Type II<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">C<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.804dupC<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Insertion<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Downstream of polyalanine<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Gly269ArgfsX265<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Unknown<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">D<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.672_701dup<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Duplication<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Polyalanine domain<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Ala224_Ala234dup<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Unknown<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">E<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.672_701dup<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Duplication<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Polyalanine domain<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Ala224_Ala234dup<hr/></td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Type II<hr/></td></tr><tr><td valign=\"top\" align=\"left\" scope=\"row\" rowspan=\"1\" colspan=\"1\">F</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">c.672_701dup</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Duplication</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Polyalanine domain</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Ala224_Ala234dup</td><td valign=\"top\" align=\"left\" rowspan=\"1\" colspan=\"1\">Unknown</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"t2\" position=\"float\"><label>Table 2</label><caption><title>Results of SNPs analysis of the three families with the c.672_701dup mutation.</title></caption><table frame=\"hsides\" rules=\"groups\"><col width=\"56\" span=\"1\"/><col width=\"47\" span=\"1\"/><col width=\"33\" span=\"1\"/><col width=\"81\" span=\"1\"/><col width=\"74\" span=\"1\"/><col width=\"63\" span=\"1\"/><col width=\"72\" span=\"1\"/><col width=\"71\" span=\"1\"/><col width=\"72\" span=\"1\"/><tbody><tr><td rowspan=\"2\" valign=\"top\" align=\"center\" scope=\"row\" colspan=\"1\"><bold>Family</bold><hr/></td><td rowspan=\"2\" colspan=\"2\" valign=\"top\" align=\"center\"><bold>Patient</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>Upstream of FOXL2</bold><hr/></td><td colspan=\"3\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>Inside FOXL2</bold><hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\"><bold>Downstream of FOXL2</bold><hr/></td></tr><tr><td valign=\"top\" colspan=\"1\" align=\"center\" scope=\"row\" rowspan=\"1\"><bold>rs11924939</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>rs28937885</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>rs7432551</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>rs28937884</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>rs13325788</bold><hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\"><bold>rs2291252</bold><hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">d<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">II:1<hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\">C<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">C<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">G<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">C<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">e<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">III:1<hr/></td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\">C<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">C<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">G<hr/></td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T<hr/></td></tr><tr><td valign=\"top\" align=\"center\" scope=\"row\" rowspan=\"1\" colspan=\"1\">f</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">II:1</td><td colspan=\"2\" valign=\"top\" align=\"center\" rowspan=\"1\">C</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">C</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">T</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">G</td><td valign=\"top\" align=\"center\" rowspan=\"1\" colspan=\"1\">C</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Subtypes of BPES in families C, D, and F are unknown, as there were no female patients (families C and F) or the female patients were too young (family D, where the two female patients were only 4 or 2 years old, respectively).</p></table-wrap-foot>", "<table-wrap-foot><p>The origin of the c.672_701dup mutation in family D is different from family E as they have different SNP at <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?snp=rs2291252\">rs2291252</ext-link>. This mutation in family F is a de novo event, although patient II:1 in family F shares the same haplogroup of the six SNPs with that of family D.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"mv-v13-108-f1\"/>", "<graphic xlink:href=\"mv-v13-108-f2\"/>", "<graphic xlink:href=\"mv-v13-108-f3\"/>", "<graphic xlink:href=\"mv-v13-108-f4\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>The lens is composed of two types of epithelial cells: A sheet of cuboidal cells, the lens epithelium, covers its anterior surface, and post-mitotic, elongated fiber cells comprise the bulk of the lens (##FIG##0##Figure 1##). Stimulation by factors present in the vitreous body causes epithelial cells near the lens equator to withdraw from the cell cycle and differentiate into lens fiber cells. Differentiating fiber cells elongate and initiate the transcription of genes that encode a distinct array of abundant membrane, cytoskeletal, and cytoplasmic proteins. The accumulation of high concentrations of cytoplasmic proteins (crystallins) in fiber cells is important for the transparency and refractive power of the lens. Some crystallins, cytoskeletal, and membrane proteins are found primarily in lens cells, or are present only at very low levels in non-lens tissues [##REF##15302206##1##, ####REF##7035467##2##, ##REF##7587300##3##, ##REF##1932094##4##, ##REF##9565648##5##, ##REF##3371069##6##, ##REF##15452068##7####15452068##7##].</p>", "<p>Lens fiber cells undergo remarkable morphological changes during their differentiation. Fiber cells first elongate to many times their original length, extending to over 140 μm per day in the chicken embryo [##REF##12573658##8##]. As they elongate, the anterior and posterior ends of the fiber cells extend beneath the lens epithelium and along the posterior lens capsule toward the optical axis. When the ends of these cells approach the anterior and posterior poles of the lens, they meet elongating fiber cells extending from the other side, resulting in the formation of the anterior and posterior sutures (##FIG##0##Figure 1##). Once the cells stop elongating, they become buried beneath the next group of elongating fiber cells. Soon after the fiber cells detach from the posterior capsule, the composition of their cell-cell adhesion proteins changes [##REF##11222534##9##], their lateral membranes become interdigitated [##REF##12573658##8##] and partially fuse with the membranes of neighboring fiber cells [##REF##12573658##8##,##REF##10806102##10##], and all intracellular, membrane-bound organelles are degraded [##REF##1421526##11##, ####REF##4430579##12##, ##REF##1855541##13##, ##REF##7635654##14##, ##REF##9286256##15##, ##REF##9105035##16##, ##REF##11878813##17####11878813##17##]. Mature fiber cells persist in this state for the life of the organism.</p>", "<p>Many of the genes that are preferentially expressed in lens fiber cells have been identified, cloned, and sequenced, and their promoters used to express foreign genes in the lenses of transgenic animals [##REF##3865198##18##,##REF##8817455##19##]. The products of all these \"fiber-specific\" genes are detected at or soon after the initiation of fiber cell differentiation. To date, only a few transcripts have been identified that are preferentially expressed late in fiber cell differentiation [##REF##11222534##9##,##REF##15710416##20##], and no mRNAs have been identified that are expressed only at this stage.</p>", "<p>To identify molecules that might regulate or be required for the final stages of fiber cell differentiation, we used subtractive hybridization between cDNA libraries created from chicken embryo lens fiber cells before and after they detached from the lens capsule. The open reading frame of one of the transcripts that was selectively expressed after fiber cells detached from the capsule consisted of 73 amino acids, 60 of which had strong sequence similarity to the homeodomain consensus. This gene was previously named <italic>Hop</italic>, for \"homeodomain-only protein\" [##REF##12297045##21##,##REF##12297046##22##].</p>" ]

[ "<title>Methods</title>", "<title>Animals and surgical procedures</title>", "<p>Animals were treated in accordance with the guidelines of the U.S. Public Health Service under a protocol approved by the Washington University Animal Studies Committee. Mice were maintained in an animal facility accredited by the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC). Fertile chicken eggs were obtained from CBT Farms (Chestertown, MD) and incubated in a humidified, forced-draft incubator at 38 °C. Embryos at different stages of development were removed, their lensers were fixed, and sectioned at 500 μm with a tissue slicer (OTS-4000; Electron Microscopy Sciences, Warrington, PA), and examined for the distribution of <italic>Hop</italic> mRNA by in situ hybridization. Mice in which the <italic>Hop</italic> coding sequence was replaced with DNA encoding a nuclear-targeted form of <italic>E. coli</italic> β-galactosidase [##REF##12297046##22##] were genotyped by PCR. Whole lenses were stained for β-galactosidase activity according to directions described in reference [##REF##12556399##23##], embedded in glycol methacrylate, and sectioned at 1 μm. <italic>Hop</italic> knockout mice were mated with TgN(GFPU)5Nagy strain of mice, which express green fluorescent protein (GFP) in a mosaic pattern, to determine whether lens cells lacking Hop fused with their neighbors during fiber cell maturation [##REF##12953070##24##]. Lenses lacking Hop were fixed in 10% formalin and sectioned perpendicular to the long axis of the fiber cells. GFP fluorescence was viewed with a Zeiss LSM 510 confocal microscope.</p>", "<title>Overview of the subtractive hybridization method</title>", "<p>The procedures used were modified from previous reports [##REF##9449464##25##,##REF##1353734##26##]. RNA was prepared from microdissected regions of the lens fiber cells and region-specific cDNA pools were synthesized. The cDNAs were amplified by PCR, made single-stranded (tester), and annealed with excess biotinylated, single-stranded cDNA prepared from a different region of the lens (driver). The biotinylated complex was removed with magnetic streptavidin beads and the remaining cDNA was cloned into a bacterial plasmid. Bacterial clones were screened with labeled probes prepared from both regions of the lens to confirm the effectiveness of the subtraction.</p>", "<title>Preparation of region-specific libraries</title>", "<p>In chicken embryos, organelle degradation in the central fiber cells begins at E12 [##REF##1421526##11##]. After this age, lenses contain elongating fiber cells, fiber cells that have stopped elongating and detached from the capsule but not yet degraded their organelles, and mature fiber cells with no organelles (##FIG##0##Figure 1##). To isolate mRNA from these populations, we removed E15-16 lenses from the eye, embedded them in 4% agar, and cut 500 μm slices parallel to the optic axis with a tissue slicer. Slices that included the center of the lens were dissected into three regions: \"cortex,\" which contained elongating fiber cells, \"middle,\" which contained fiber cells that had detached from the capsule yet still contained organelles, and \"core,\" which contained the fiber cells that had already lost their organelles (##FIG##0##Figure 1##). The following primer sequences for PCR reactions were used: T primer: 5'-GTG CCT CTA GAT TTT TTT TTT-3'; TC primer: 5'-GTG CCT CTA GAT TTT TTT TTT GGA TCC CCC CCC CC-3'; C primer: 5'-TTT TCA CGG ATC CCC CCC CCC-3'; X primer: 5'-GTC CGG CCA ACG GTA TGG TG-3'; XT primer: 5'-GTC CGG CCA ACG GTA TGG TGC CTC TAG ATT TTT TTT TT-3'; and XC primer: 5'-GTC CGG CCA ACG GTA TGG TGC ACG GAT CCC CCC CCC C-3'.</p>", "<p>Total RNA from these regions was extracted using the standard guanidine thiocyanate procedure as described in reference [##REF##2440339##27##]. Total RNA (0.25-1 μg) was heat-denatured at 65 °C for 5 min and annealed at room temperature for 5 min with 5 pM of T-primer in a total volume of 20 μl containing 1X RT buffer (50 mM Tris-HCl, pH 8.3, 6 mM MgCl₂, 75 mM KCl, 1 mM dithiothreitol, 1 mM of each dATP, dTTP, dCTP, and dGTP), and 1 U RNase inhibitor (Promega, Madison, WI). After addition of 200 units of Moloney murine leukemia virus reverse transcriptase (SuperScript II; Life Technologies, Gaithersburg, MD), incubation was continued at 42 °C for 1 h, followed by 94 °C for 5 min, using a programmable thermal cycler (PTC-100TM; MJ Research, Watertown, MA). The tube was spun briefly and the cDNA was purified from the T-primer and dNTPs by ultrafiltration through a Microcon-100 concentrator (Millipore, Billerica, MA). Purified cDNA (5 μl aliquots) was oligo-dG-tailed at 37 °C for 0.5-1.5 h in a total reaction volume of 15 μl containing 1X terminal deoxynucleotidyl transferase (TdT) buffer (50 mM sodium cacodylate, pH 7.2, 0.1 mM 2-mercaptoethanol, 1 mM CoCl₂), 400 mM dGTP and 2 U TdT. Higher TdT concentration (5-20 U) as well as longer time of incubation can significantly reduce the amount of DNA available for subsequent amplification with TC- and T-primers. For this reason, 4 μl aliquots of DNA were removed every 30 min of incubation and submitted to 18 cycles of \"hot-start\" PCR in 50 μl of 1X PCR buffer (40 mM Tricine-KOH, pH 9.2, at 20 °C; 10 mM potassium acetate, 3 mM MgCl₂; 50 mg/ml BSA, 200 mM of each dATP, dTTP, dCTP, and dGTP), 5 pM TC primer, 20 pM T primer and 1.5 U Taq Polymerase. The first cycle of PCR was 94 °C for 30 s, 52 °C for 1 min, 72 °C for 1.5 min, followed by 16 cycles (94 °C for 10 s, 56 °C for 20 s, and 71 °C for 1.5 min). The final cycle had 5 steps: 94 °C for 10 s, 56 °C for 20 s, 71 °C for 2 min, 56 °C for 20 s, and 71 °C for 2 min. The five-step PCR was used during the last cycle for converting single-stranded \"pan-like\" DNA to double-stranded products. Full-length TC-T cDNA was prepared using the same conditions and cycle parameters except the elongation time was extended to 5 min and 0.05 U of Pfu polymerase was added to the PCR mix [##REF##8134376##28##].</p>", "<title>Preparation of biotinylated T-C cDNA</title>", "<p>To obtain biotinylated \"middle\" and \"cortex\" T-C cDNA, 10 ng of the original TC-T cDNA was amplified through 10 cycles of PCR with 5'-end biotinylated T- and C-primers (Integrated DNA Technologies), the product purified from the primers and unincorporated nucleotides with a PCR purification kit (Promega), ethanol precipitated and resuspended in 12 μl of deionized water.</p>", "<title>Driver preparation</title>", "<p>About 7 μg of sense and antisense cDNA (driver) were prepared from 5 μl (2 μg) of biotinylated T-C cDNA (Integrated DNA Technologies) by five cycles of asymmetric amplification with 100 pM of biotinylated C-primer (for sense) or biotinylated T-primer (for antisense) in five tubes with a total volume 250 μl. The PCR reaction was stopped by the addition of 2 μl of 0.5 M EDTA, pH 8.0, and frozen at -20 °C.</p>", "<title>Tester (tracer) preparation</title>", "<p>Sense and antisense tracer cDNA were prepared from 1 μl of biotinylated T-C cDNA by additional 5 cycles of asymmetric PCR with 20 pM of un-biotinylated XC-primer (for sense) or XT-primer (for antisense) in 50 ml of PCR buffer. The PCR reaction was stopped by addition 1 μl of 0.5 M EDTA pH 8.0 and frozen at -20 °C.</p>", "<title>Subtractive hybridization</title>", "<p>For each subtraction, two samples were prepared: one containing 5 μg of sense driver and 250 ng of antisense tracer and the second containing antisense driver and sense tracer. After undergoing phenol-chloroform extraction and precipitation with ethanol, each cDNA sample was dissolved in 400 μl of deionized water and purified from the primers by 5X filtration with Microcon-100 filters. Purified cDNA was precipitated with ethanol and resuspended in 4 μl of hybridization buffer (50 mM HEPES, pH 8.3; 0.5 M NaCl; 0.05 mM EDTA, pH 8.0), overlaid with mineral oil, heated 2 min at 95 °C and incubated overnight at 68 °C. The hybridization mix was diluted in 400 μl of NTE buffer (10 mM Tris-HCl, pH 8.0, 0.5 M NaCl, and 1 mM EDTA) and the aqueous phase was transferred to a fresh tube with 100 μl of streptavidin-beads (Dynal Biotech, Lake Success, NY) in NTE buffer (the beads were washed 3X in NTE buffer before use). After 5 min incubation at room temperature, the beads and bound DNA were removed with a magnet, and the remaining cDNAs were subjected to a second round of purification with streptavidin beads. After purification, the two samples were combined, mixed with 1 μg of each sense and antisense driver, precipitated with ethanol, dissolved in 4 μl of hybridization buffer and used for second step of hybridization at 68 °C, overnight. The second hybridization mix was purified twice with streptavidin beads. PCR was performed with 2 μl of the remaining cDNA in 50 μl of PCR buffer containing 10 pM of X-primer using the following parameters: 72 °C for 3 min, then 25-30 cycles of 94 °C for 12 s; 56 °C for 20 s; 72 °C for 2 min. The PCR reaction mixture was diluted 500 times and subjected to additional 15-17 rounds of PCR with T- and C-primers. Purified product of this secondary PCR was digested with <italic>Xba</italic> I and <italic>Bam</italic> HI endonuclease (Roche Applied Science, Indianapolis, IN) and inserted into a pcDNA3.1(-) vector (Invitrogen, Carlsbad, CA). For differential screening, 96 individual clones from the subtracted \"middle\" library were replicated and hybridized with DIG-labeled probes synthesized by PCR from \"cortex\" and \"middle\" subtracted cDNA. Plasmids from clones that reacted only or preferentially with the \"middle\" library were sequenced.</p>", "<title>Genomic sequencing</title>", "<p>Sequencing of the region upstream of the <italic>Hop</italic> translation start site was accomplished by genomic walking. Chicken genomic DNA was extracted and digested with one of several restriction enzymes that generate 5' overhangs. The genomic fragments were ligated to double-stranded anchor primers with the appropriate 3' overhangs using the Rapid DNA Ligation Kit (Roche Applied Science), and PCR products were amplified with primers designed against the <italic>Hop</italic> coding sequence and the sequence of the anchor primer. The longest PCR fragments were cloned and sequenced using standard methods. Potential transcription factor binding sites in the genomic sequence upstream of the translation start site were identified with P-Match, a public version of <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.gene-regulation.com/cgi-bin/pub/programs/pmatch/bin/p-match.cgi\">Match</ext-link> (Biologische Datenbanken GmbH, Wolfenbüttel, Germany), using the stringency cutoff selection to minimize the identification of false positive matches.</p>", "<title>Tests of Hop DNA binding</title>", "<p>Electrophoretic mobility shift assays (EMSA) were performed as described [##REF##11602361##29##]. Radiolabeled Hop protein was synthesized in vitro using TNT Quick Coupled rabbit reticulocyte lysate reagents (Promega, Madison, WI) and ³⁵S-methionine (Amersham Pharmacia, Piscataway, NJ). Substrate DNA was 0.5 mg of a plasmid containing <italic>Hop</italic> cDNA. ³²P-labeled oligonucleotides representing binding sites for transcription factors were as follows: LHX3 LIM-class homeodomain site, 5'-GAT CCC AGA AAA TTA ATT AAT TGT AA-3' (LBC) [##REF##11602361##29##]; paired-class homeodomain site, 5'-TCC GAC TAA TTG AAT TAG CGA GA-3' (PRD) [##REF##7901121##30##]; bicoid-class homeodomain site, 5'-GAT CCG CAC GGC CCA TCT AAT CCC GTG GGA TC-3' (BIC) [##REF##11301317##31##]; Pit-1 POU-class homeodomain site, 5'-GAT CCT ATG TGC TCA AAG TTC AGG TAT GAA TAT AAA GGA TC-3' (PIT) [##REF##8504933##32##]; and a MyoD basic helix-loop-helix site, 5'-GGG AAA GGA TCT GAC AGG TGG CCC CAG CCC TCG G-3' (MD).</p>", "<title>Amplification of <italic>Hop</italic> sequences using degenerate PCR primers</title>", "<p>cDNA prepared from the lenses of several species was amplified with degenerate primers based on the sequence of chicken <italic>Hop</italic>. The primers were: 5'-GAT TCC ACC ACG CTG TGY CTN ATY GC-3' and 5'-CCA CTT BGC CAG NCG YTG YTT-3' where Y is C or T, N is A,G,T or C and B is C, G, or T. PCR products were cloned and sequenced by standard methods.</p>", "<title>Northern blotting</title>", "<p>Total RNA from E15 lens fiber masses was separated by agarose gel electrophoresis, transferred to nylon membranes (Roche Applied Science, Indianapolis, IN), and probed with digoxigenin-labeled antisense riboprobes derived from the chicken <italic>Hop</italic> sequence by following directions given in the manual provided with the riboprobe kit. Bands were visualized with a peroxidase-labeled antibody to digoxigenin and chemiluminescent detection (Roche Applied Science).</p>", "<p>In situ hybridization was performed using standard techniques for whole mount staining [##UREF##0##33##] on whole lenses (E6-E8) or about 500 μm-thick sections of formaldehyde fixed lenses (&gt;E8). Lenses were fixed for about 1 h, washed in PBS, and stained whole or sectioned using an OTS-4000 tissue slicer. Sections were stained with antisense or sense digoxigenin-labeled riboprobes derived from the full length chicken <italic>Hop</italic> cDNA sequence. An alkaline phosphatase-conjugated antibody to digoxigenin and 5-bromo-4-chloro-3-indolyl phosphate/Nitro blue tetrazolium were used for color development (Roche Applied Science).</p>" ]

[ "<title>Results</title>", "<p>To identify genes expressed late in fiber cell maturation we used a PCR-based method to prepare cDNA libraries from microdissected regions of E15-16 chicken lenses (##FIG##0##Figure 1##) and performed subtractive hybridization to identify cDNAs that are selectively expressed in fiber cells that had detached from the lens capsule, yet still contained organelles. Several clones were identified that were enriched or were expressed exclusively in mature fiber cells. One of these cDNAs encoded vinculin (GenBank <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_205441\">NM_205441</ext-link>), a transcript that we had previously found to increase after fiber cells detach from the lens capsule [##REF##11222534##9##]. Most other clones from this library encoded genes that were differentially, but not exclusively, expressed in mature fiber cells. One clone encoded a sequence that was expressed selectively in detached fiber cells but at low levels. A few ESTs for this transcript have been identified, the longest being GenBank accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=CN228064\">CN228064</ext-link>. Since this transcript was expressed at a low level in the lens, it was not examined further. Another transcript was expressed at high levels only in fiber cells that had detached from the capsule. It contained a short open reading frame encoding 73 amino acids with sequence similarity to the homeodomain transcription factors (GenBank <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=NM_204556\">NM_204556</ext-link>). The mouse ortholog of this gene (<italic>Hop</italic>) was recently shown to be expressed in heart development and to modulate the activity of other transcription factors [##REF##12297045##21##,##REF##12297046##22##,##REF##12617835##34##].</p>", "<p>Sequence analysis and database searches revealed that chicken <italic>Hop</italic> differs at several locations from the homeodomain consensus and is not sufficiently similar to any of the known homeodomain sequences to be grouped in one of the homeodomain \"superclasses\" [##UREF##1##35##]. The greatest similarity of <italic>Hop</italic> to a characterized homeodomain is 47% amino acid identity with the Pitx homeoprotein of the cephalochordate <italic>Branchiostoma belcheri</italic> [##REF##10654612##36##], although it is nearly as closely related to many other homeodomains of the \"paired\" superclass. The Hop homeodomain is 61 amino acids, containing a valine between the first and second helix, a characteristic sometimes present in diverged homeodomains [##UREF##1##35##].</p>", "<p>Because amino acids thought to be critical for DNA binding are altered in the <italic>Hop</italic> sequence, Hop protein was tested for its ability to bind DNA by electrophoretic mobility shift assay (EMSA). ³⁵S-radiolabeled Hop protein was synthesized by in vitro transcription/translation and then incubated with ³²P-radiolabeled DNA probes representing LIM-, paired- bicoid-, and POU-class homeodomain binding sites, or a MyoD basic helix-loop-helix protein binding site. In a parallel positive control, the LIM class site was bound by M2-LHX3 [##REF##11470784##37##]. In agreement with other studies on mouse Hop [##REF##12297045##21##,##REF##12297046##22##], interaction between chicken Hop and DNA was not observed (##FIG##1##Figure 2##). DNA binding also was not observed in similar experiments using bacterially expressed Hop protein (data not shown).</p>", "<p>Sequencing <italic>Hop</italic> PCR products and over 6 kb of the chicken <italic>Hop</italic> genomic locus identified a 226 bp intron in the 5' untranslated region and a second intron of about 2,000 bp located between the regions coding for the first and second alpha helical regions of the Hop homeodomain. This is consistent with our northern blot analysis of lens RNA, which detected two transcripts of about 1 and 1.2 kb (##FIG##2##Figure 3A##). Sequencing of several <italic>Hop</italic> clones revealed that some <italic>Hop</italic> transcripts lack the first intron, while others may be initiated within the first intron. However, it is possible that these clones represent unspliced transcripts that did not extend to the 5' end of the cDNA. Alternative splicing of the first intron was later confirmed by examination of the chicken genomic sequence using the <ext-link ext-link-type=\"uri\" xlink:href=\"http://genome.ucsc.edu\">UCSC genome browser</ext-link>, which shows that some <italic>Hop</italic> ESTs from the chicken genome initiative include the first intron while others do not [##REF##15592404##38##]. This analysis also demonstrates that <italic>Hop</italic> maps to chicken chromosome 4 [##REF##15592404##38##]. The structure of the chicken <italic>Hop</italic> locus is shown in ##FIG##2##Figure 3B##.</p>", "<p>The genomic sequence of <italic>Hop</italic> was analyzed using a search program that identifies putative transcription factor binding sites (P-Match). The sites upstream of the translation start site that were identified in this search are shown in ##FIG##3##Figure 4A##.</p>", "<p>To determine whether <italic>Hop</italic> was expressed in the lenses of other species, we used specific or degenerate PCR primers to amplify cDNA prepared from human, mouse, rat, rabbit, and bovine lens fiber cells. The PCR products were sequenced to confirm that <italic>Hop</italic> transcripts were detected in the lenses of each of the species examined. <italic>Hop</italic> cDNA or genomic DNA has not previously been sequenced from rabbits. The sequence of partial <italic>Hop</italic> transcripts from the rabbit lens was submitted to GenBank (accession number <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.molvis.org/molvis/external.cgi?gbdna=EF154428\">EF154428</ext-link>). An alignment of all known Hop protein sequences is shown in ##FIG##3##Figure 4B##.</p>", "<p>The expression and distribution of <italic>Hop</italic> transcripts in the chicken embryo lens were examined using RT-PCR and in situ hybridization. <italic>Hop</italic> sequences were first detected by PCR in cDNA prepared from E6 (Hamburger-Hamilton Stage 28-30) lenses and were readily detected in the fiber cells from older lenses (##FIG##4##Figure 5A##). A previous study found that primary fiber cells detach from the lens capsule between E5 and E6 [##REF##10711704##39##]. <italic>Hop</italic> mRNA was first detected by situ hybridization at E7.5 in the central fiber cells (##FIG##4##Figure 5B##). After E7, an increasing number of cells in the central region of the fiber mass expressed <italic>Hop</italic> mRNA. Examination of lens sections suggested that, independent of the age of the lens, <italic>Hop</italic> transcripts were first detected in fiber cells soon after they detached from the lens capsule (##FIG##4##Figure 5B##).</p>", "<p>Mouse lenses in which both alleles of <italic>Hop</italic> had been disrupted by insertion of a nuclear-targeted lacZ sequence appeared normal in size (##FIG##5##Figure 6A##) and were transparent throughout adult life (not shown). When stained for β-galactosidase activity, these lenses revealed a similar pattern of Hop expression as seen in chicken embryo lenses. β-Galactosidase staining was not present in superficial fiber cell nuclei, but was detected in the nuclei of fiber cells that were deep in the fiber mass (##FIG##5##Figure 6B-D##). β-Galactosidase continued to be present in these nuclei until they were degraded during organelle deletion.</p>", "<p>The TgN(GFPU)5Nagy strain of transgenic mice was used to determine whether, during their maturation, fiber cells fused with their neighbors. Mice of this strain express GFP in a mosaic pattern in superficial, elongating fiber cells [##REF##12953070##24##]. When fiber cells fuse during maturation, all cells become uniformly fluorescent, since GFP can now diffuse between neighboring cells. Our results demonstrated that elongating fiber cells of <italic>Hop</italic> knockout lenses showed mosaic expression of GFP, but fiber cells deeper in the lens were uniformly fluorescent (##FIG##6##Figure 7##). This indicates that the maturing fiber cells of <italic>Hop</italic> null lenses fused with their neighbors during their maturation in a manner that closely resembled that seen in lenses that contained both wild type <italic>Hop</italic> alleles (##FIG##6##Figure 7##) [##REF##12953070##24##].</p>" ]

[ "<title>Discussion</title>", "<p>We postulated that the proteins that are encoded by transcripts that first appear after lens fiber cells detach from the capsule might be important for fiber cell maturation as well as denucleation. We and others identified transcripts that are differentially accumulated late in fiber cell differentiation [##REF##11222534##9##,##REF##15710416##20##]. It is not known whether these transcripts change in abundance due to increased rates of synthesis or decreased degradation. Vinculin and paxillin mRNAs increase markedly in fiber cells after they detach from the capsule, compared to fiber cells that were still elongating and were attached to the capsule [##REF##11222534##9##]. However, the expression of vinculin and paxillin is not unique to mature fiber cells; these transcripts are expressed at lower levels in elongating fiber cells.</p>", "<p>To identify transcripts that are expressed only in fiber cells that have detached from the capsule, we prepared libraries from microdissected lens regions and performed subtractive hybridization. One of the transcripts detected in this screen encoded chicken Hop, an unusual homeodomain-containing protein. Other labs found that <italic>Hop</italic> is prominently expressed in the heart [##REF##12297045##21##,##REF##12297046##22##,##REF##12617835##34##]. Based on its unusual coding sequence, these groups named it \"homeodomain only protein\" (<italic>Hop</italic>) [##REF##12297045##21##,##REF##12297046##22##] or \"odd box\" (<italic>OB1</italic>) [##REF##12617835##34##]. <italic>Hop</italic> is the first gene to be identified that is not expressed in elongating fiber cells but is transcribed after fiber cells detach from the lens capsule. This pattern of gene expression demonstrates that there are mechanisms to initiate transcription at this critical stage of lens fiber cell differentiation and raises the possibility that other genes may be similarly regulated.</p>", "<p><italic>Hop</italic> transcripts appear in fiber cells soon after they detach from their basal lamina, the lens capsule. There is ample precedent for the activation of a new gene expression program in other types of epithelial cells after they separate from their basal laminae. For example, when keratinocytes detach from the epidermal basal lamina and move out of the germinative layer of the epidermis, they initiate a complex program of differentiation that is related to the ability of superficial keratinocytes to protect the body surface from desiccation, injury and infection [##REF##11132762##40##]. Thus, <italic>Hop</italic> expression in maturing fiber cells may be regulated by signals from integrins or other matrix-binding proteins [##REF##9599291##41##,##REF##10954416##42##] that are altered following detachment from the capsule.</p>", "<p>Previous studies found that Hop positively and negatively modulates gene expression in the heart and lung. In heart muscle [##REF##12617835##34##], Hop reduces transcriptional activation by serum response factor by recruiting histone deacetylases (HDACs) to the promoters of several heart muscle-specific genes [##REF##12297045##21##,##REF##12297046##22##,##REF##12975471##43##]. Hop also functions prominently in the atrium and in the cardiac conduction system, where loss of Hop function results in an abnormal electrocardiogram, associated with a marked and selective reduction in the expression of connexin40 [##REF##15790958##44##]. In the airway epithelium, Hop suppresses surfactant production in type II pneumocytes, again by recruiting HDACs to surfactant protein genes [##REF##16510470##45##]. Hop may function in a similar manner in the lens, perhaps by regulating the expression of crystallin or connexin genes.</p>", "<p>In the heart and lung, the expression of <italic>Hop</italic> is regulated by members of the Nkx2.x and GATA families of transcription factors [##REF##12297045##21##,##REF##12297046##22##,##REF##16510470##45##]. Of the several members of these families, none was detectable in whole, adult mouse lens fibers by microarray analysis (Vasiliev, Wang, and Beebe, unpublished). Whether these proteins are expressed at sufficient levels to contribute to Hop expression in the lens remains to be tested.</p>", "<p>Analysis of the genomic sequence upstream of the <italic>Hop</italic> coding sequence identified few potential binding sites for transcription factors considered to be key for regulating gene expression during lens fiber cell differentiation (Pax6, c-maf, L-maf, Prox1, Sox1-3, RAR/RXR) [##REF##15558471##46##, ####REF##9651402##47##, ##REF##12081646##48##, ##REF##10080188##49####10080188##49##]. There is a potential Pax6 binding element 3.4 kb upstream of the translation start site. However, Pax6 levels decline sharply during fiber cell differentiation [##REF##15452066##50##,##REF##9710641##51##], making it unlikely that Pax6 contributes to the regulation of <italic>Hop</italic> late in fiber cell differentiation. Since <italic>Hop</italic> is the first gene known to be expressed exclusively during the latest phase of fiber cell differentiation, it is not surprising that it may not be regulated in the same manner as genes expressed early in fiber cell formation.</p>", "<p>In spite of the paucity of binding sites for these \"core\" lens fiber cell transcription factors, a CP2 binding site is located at position -2876. CP2 is a ubiquitous factor that was shown to be essential for lens-specific expression of α-crystallin in the chicken [##REF##9753426##52##]. Similarly, USF1, which is expressed in lens cells and regulates the expression of the chicken and mouse αA-crystallin genes [##REF##7935450##53##,##REF##9055817##54##], may regulate <italic>Hop</italic> expression by binding the USF site at -2042. The HAND1/E47 E2 boxes at -559 and -2352 bind basic helix-loop-helix transcription factors and might be negatively regulated by the δ-crystallin enhancer-binding protein, δEF1, which competes for E2 sites [##REF##8065305##55##]. In addition, there are two CHOP10 (C/EBP homologous protein 10) binding sites beginning at position -5184. These are of interest because CHOP10 dimerizes with other members of the C/EBP family of transcription factors to inhibit their activity. C/EBP family members can heterodimerize with ATF4 (CREB2), which is required for the differentiation of secondary lens fiber cells [##REF##10096021##56##]. In a preliminary microarray study, CHOP10 transcripts were decreased tenfold in <italic>Hop</italic> knockout mice, compared to wild type (Vasiliev, Wang, and Beebe, unpublished). This raises the possibility that CHOP10 and Hop are mutual regulators of their respective genes. Since CHOP10 is most often a negative regulator of transcription, it may serve as a feedback regulator of <italic>Hop</italic> expression. The importance of these cis-binding elements in regulating <italic>Hop</italic> expression in the lens and the basis of CHOP10 regulation by Hop will have to be evaluated in future experiments.</p>", "<p>Examination of EST databases and staining with specific antibodies showed that, in addition to the cardiac and pulmonary systems, Hop is expressed in many tissues [##REF##12617835##34##,##REF##15967424##57##]. However, other than in the heart and lungs, no defects have been described in <italic>Hop</italic> knockout mice. We observed no obvious phenotype in the lenses of <italic>Hop</italic> null mice. <italic>Hop</italic> null lenses were clear and of normal size and their cellular morphology appeared normal. Fiber cells lacking <italic>Hop</italic> fused with their neighbors and degraded their nuclei in a manner that was morphologically indistinguishable from wild-type lenses. Although <italic>Hop</italic> does not appear to have an essential function in maturing lens fiber cells, it may be possible to use <italic>Hop</italic> regulatory sequences to target the expression of exogenous genes to fiber cells at the stage just before they fuse and degrade their nuclei.</p>" ]

[]

[ "<p>This is an open-access article distributed under the terms of the\n Creative Commons Attribution License, which permits unrestricted use,\n distribution, and reproduction in any medium, provided the original\n work is properly cited.</p>", "<title>Purpose</title>", "<p>To identify transcripts expressed late in lens fiber cell maturation that might regulate fiber cell fusion, organelle degradation, or other events associated with the maturation of lens fiber cells.</p>", "<title>Methods</title>", "<p>cDNA libraries were prepared from microdissected regions of chicken embryo lenses using a PCR-based method. Subtractive hybridization was used to identify transcripts expressed exclusively in fiber cells that had detached from the lens capsule. Database searches and PCR amplification with degenerate primers were used to identify human, mouse, rat, rabbit, and bovine orthologs of one such sequence and to confirm its expression in the lenses of these animals. The ability of in vitro-transcribed and translated protein to bind DNA was assessed by mobility shift assays. The locus encoding this transcript and an area about 6 kb upstream of the translation start site were sequenced. The microscopic morphology of lenses from mice in which the locus encoding this protein had been disrupted by the insertion of a nuclear-targeted bacterial lacZ sequence were analyzed. Gene expression was analyzed by PCR, in situ hybridization, and by staining for β-galactosidase activity in lenses expressing <italic>lacZ</italic> in place of the coding sequence. Knockout lenses expressing green fluorescent protein in a mosaic pattern were sectioned in the equatorial plane and viewed with a confocal microscope to assess the presence of cell-cell fusions during fiber cell maturation.</p>", "<title>Results</title>", "<p>Subtractive hybridization identified transcripts encoding Hop, a short, atypical homeodomain-containing protein that had previously been shown to be an important regulator of gene expression in the heart and lung. Chicken Hop did not bind to known homeodomain-binding sequences in DNA. In chicken embryos, <italic>Hop</italic> transcripts were first detected at E6. At all stages analyzed, <italic>Hop</italic> mRNA was only detected in cells that had detached from the lens capsule. Mice in which the <italic>Hop</italic> coding sequence was replaced with nuclear-targeted β-galactosidase showed that Hop was expressed in the mouse lens in a similar pattern to the chicken lens. Characterization of lenses from mice lacking <italic>Hop</italic> revealed no morphological phenotype and no apparent defects in the degradation of nuclei or fiber cell fusion during fiber cell maturation.</p>", "<title>Conclusions</title>", "<p>The expression pattern of <italic>Hop</italic> provides the first evidence that new transcription is initiated in lens fiber cells after they detach from the capsule. <italic>Hop</italic> may be the first of a class of genes with this pattern of expression. Although lens abnormalities have yet to be identified in mice lacking <italic>Hop</italic>, the genomic sequences that regulate Hop expression in the lens may be useful for expressing exogenous transcripts selectively in fiber cells just before they fuse with their neighbors and degrade their organelles.</p>" ]

[]

[ "<title>Acknowledgements</title>", "<p>The authors thank Dr. Eric Olson, Department of Molecular Biology, University of Texas Southwestern Medical Center at Dallas for providing the <italic>Hop</italic> knockout mice, Dr. Rashmi Hegde, Department of Pediatrics, University of Cincinnati, for confirmation that the secondary structure of Hop conformed to that of the consensus homeodomain, Dr. Steven Bassnett for the gift of the TgN(GFPU)5Nagy mice, and Cheryl Shomo for generating ##FIG##0##Figure 1##. The work described was supported in part by grants from the National Science Foundation (IBN-0131702 to S.J.R.), the National Institutes of Health (EY04853 and EY09179 to D.C.B. and HD42024 to S.J.R.), an unrestricted grant from Research to Prevent Blindness, and a core grant (EY02687) to the Department of Ophthalmology and Visual Sciences.</p>" ]

[ "<fig id=\"f1\" fig-type=\"figure\" position=\"float\"><label>Figure 1</label><caption><p>Diagram of lens regions. Diagram representing a section through the center of a lens showing the regions of the fiber mass that were dissected to produce region-specific cDNA libraries. Fiber cells in the cortex region are still in the process of elongation and are attached at their basal ends to the lens capsule, the lens basement membrane. Cells in the middle region have completed the process of elongation and have detached from the capsule. The apical and basal ends of these cells abut the ends of fiber cells from the other side of the lens at the anterior and posterior sutures. Cells in the core region have degraded their nuclei and other membrane-bound organelles.</p></caption></fig>", "<fig id=\"f2\" fig-type=\"figure\" position=\"float\"><label>Figure 2</label><caption><p>Hop does not bind to homeobox sequences. Electrophoretic mobility shift assay using radiolabeled oligonucleotide probes representing transcription factor binding sites. Probes were incubated with the indicated ³⁵S-labeled in vitro translated proteins, and the bound complexes (B) were separated from the free probe (F) by electrophoresis. Unprogrammed lysate was used as a negative control (lysate). Bacterially expressed M2-LHX3 was used as a positive control [##REF##11470784##37##]. Abbreviations: LBC=LHX3 LIM-class homeodomain site, PRD=paired-class homeodomain site, BIC=bicoid-class homeodomain site, PIT=Pit-1 POU-class homeodomain site, MD=MyoD basic helix-loop-helix site. The upper panel shows the input Hop protein (³⁵S-labeled); the lower panel shows the migration of ³²P-labeled DNA.</p></caption></fig>", "<fig id=\"f3\" fig-type=\"figure\" position=\"float\"><label>Figure 3</label><caption><p>Splicing of <italic>Hop</italic> transcripts in the lens. <bold>A</bold>: Northern blot of total RNA extracted from E15-E16 lens fiber masses and probed with a digoxigenin-labeled <italic>Hop</italic> riboprobe. Two bands were detected that were the approximate predicted size of the <italic>Hop</italic> mRNA, with or without the inclusion of the first intron. <bold>B</bold>: Diagram showing the chicken <italic>Hop</italic> gene structure. The dimensions of the different regions of the gene are not to scale. The numerals above the line diagram mark the number of nucleotide pairs in each region. Introns are represented by thin solid lines and exons by boxes. Filled boxes represent translated regions of the mRNA and unfilled boxes are the untranslated regions.</p></caption></fig>", "<fig id=\"f4\" fig-type=\"figure\" position=\"float\"><label>Figure 4</label><caption><p>Analysis of the <italic>Hop</italic> gene and protein. The upstream genomic sequence of <italic>Hop</italic> and alignment of the Hop protein sequences from several species. <bold>A</bold>: About 6 kb of DNA sequence upstream of the Hop protein coding sequence, including the first intron (lower case, light blue letters), was annotated with potential transcription factor binding sites, as determined using the <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.gene-regulation.com/cgi-bin/pub/programs/pmatch/bin/p-match.cgi\">P-Match</ext-link> search tool. Settings for the search were adjusted to reveal only the most conservative matches (to minimize false positives). Because Nkx2.x factors regulate Hop expression in the heart and lung, we also show potential Nkx2.x binding sequences (in red), although these motifs were not detected by <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.gene-regulation.com/cgi-bin/pub/programs/pmatch/bin/p-match.cgi\">P-Match</ext-link> when set to minimize false positive matches. The transcription start site of the longest spliced form of Hop mRNA is marked by a vertical bar followed by an arrow. The initial methionine codon is shown in green. <bold>B</bold>: Alignment of the Hop protein sequences from several species. GenBank accession numbers are shown after each sequence. The chicken protein sequence obtained by conceptual translation of the cDNAs sequenced in this study was identical to that in GenBank. The partial rabbit sequence was determined using degenerate PCR primers, since this sequence was not determined previously.</p></caption></fig>", "<fig id=\"f5\" fig-type=\"figure\" position=\"float\"><label>Figure 5</label><caption><p><italic>Hop</italic> expression during lens development. <bold>A</bold>: PCR amplification of <italic>Hop</italic> sequences in RNA extracted from chicken lenses from E5 through E10. <italic>Hop</italic> transcripts were first detectable at E6. Transcript levels increased at later stages. <bold>B</bold>: <italic>Hop</italic> is expressed soon after primary and secondary fiber cells detach from the capsule. In situ hybridization showing the distribution of <italic>Hop</italic> transcripts during lens development in chicken embryos. Sections are from lenses at E7.5, E8.5, E12, and E19. The decreased staining in the center of lenses at E12 and E19 probably reflects a decrease in probe penetration, not a decrease in <italic>Hop</italic> transcripts, because PCR analysis of microdissected lens cores from lenses at these stages revealed no obvious decrease in <italic>Hop</italic> sequences.</p></caption></fig>", "<fig id=\"f6\" fig-type=\"figure\" position=\"float\"><label>Figure 6</label><caption><p>Appearance of <italic>Hop</italic> knockout lenses. <italic>Hop</italic> is expressed in maturing secondary fiber cells in the mouse lens. <bold>A</bold>: <italic>Hop</italic> wild type and null lenses from P3 mice. Both lenses have cold cataracts, as expected of lenses at this age. No consistent variations were detected in the size of the wild type and knockout lenses or in the extent of the cold cataracts. <bold>B</bold>: Polar view of a whole, <italic>Hop</italic> null lens stained for β-galactosidase activity. The superficial zone of the lens has no stained nuclei. The \"trefoil\" pattern of stained nuclei in the deeper fiber cells is due to the displacement of the nuclei in a more anterior or posterior direction as a result of differences in the extension of the fiber cells toward the anterior and posterior sutures [##REF##15558480##58##]. <bold>C</bold>: The displacement of β-galactosidase-stained nuclei as viewed from the lens equator. <bold>D</bold>: A 1 μm plastic section of the equatorial region of a mouse lens in which both <italic>Hop</italic> alleles were disrupted by the insertion of the sequence encoding nuclear-targeted β-galactosidase [##REF##12297046##22##]. The lens was stained for β-galactosidase activity, embedded in glycol methacrylate, and sectioned. The section was viewed using differential interference contrast optics to show the location of the nuclei of the fiber cells. Only the nuclei of the deeper fiber cells are stained blue, indicating that <italic>Hop</italic> expression is initiated late in fiber cell maturation. β-Galactosidase activity was still present in the fragments of nuclei remaining after organelle loss. The morphology of the cells of the <italic>Hop</italic> knockout lenses appears similar to wild type.</p></caption></fig>", "<fig id=\"f7\" fig-type=\"figure\" position=\"float\"><label>Figure 7</label><caption><p>Fiber cell fusion in a <italic>Hop</italic> null lens. During their maturation in <italic>Hop</italic> knockout lenses, fiber cells fuse with their neighbors. This section of a TgN(GFPU)5Nagy; Hop^-/- lens is cut perpendicular to the long axis of the fiber cells. GFP fluorescence is seen in a mosaic pattern in the peripheral fiber cells, similar to the pattern described previously for TgN(GFPU)5Nagy lenses that are wild type for <italic>Hop</italic> [##REF##12953070##24##]. Deeper in the fiber mass, GFP fluorescence abruptly spreads to all cells, an indication of fiber cell fusion. This result shows that Hop is not required for the cell-cell fusion of fiber cells during their maturation.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"mv-v13-114-f1\"/>", "<graphic xlink:href=\"mv-v13-114-f2\"/>", "<graphic xlink:href=\"mv-v13-114-f3\"/>", "<graphic xlink:href=\"mv-v13-114-f4\"/>", "<graphic xlink:href=\"mv-v13-114-f5\"/>", "<graphic xlink:href=\"mv-v13-114-f6\"/>", "<graphic xlink:href=\"mv-v13-114-f7\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[]

[]

[]

[]

[]

[ "<p>As <italic>PLoS Pathogens</italic> turns three, we are pleased to say that the publication is flourishing. A journal's overall health can be measured in numerous ways: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plospathogens.org/static/information.action\">high quality and breadth of the research</ext-link>; high citation counts of individual papers; solid submission numbers; rising <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plospathogens.org/static/information.action\">impact factor</ext-link>; <ext-link ext-link-type=\"uri\" xlink:href=\"http://news.google.com/news?hl=en&amp;ned=us&amp;q=%22PLoS+Pathogens%22+OR+%22Public+Library+of+Science+Pathogens%22&amp;btnG=Search+News\">wide influence</ext-link> and robust <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plospathogens.org/static/commentGuidelines.action\">discussion</ext-link> within the community; strong <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plospathogens.org/static/edboard.action\">editorial leadership</ext-link>; rapid publishing speed; accessibility of research; and, in our case especially, an unwavering commitment to creativity and new facets of <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plos.org/oa/index.html\">open-access (OA) publishing</ext-link>. In all of these areas, the journal has grown and gained strength in the past three years through the collaborative effort of the community, editorial board, and PLoS staff to produce a publication that is both innovative and integrative.</p>", "<p>The crux of <italic>PLoS Pathogens'</italic> strength lies in its vision and commitment to publish “outstanding original articles that significantly advance the understanding of pathogens and how they interact with their host organisms” and to make those articles immediately and widely available. By publishing a broad range of topics, including viruses, bacteria, prions, yeast and fungi, and parasites, readers can cross-reference methodologies and findings across various disciplines that traditionally have been segregated into specialist journals. This provides not only a breadth of information but also unique interdisciplinary consultations among outstanding editors whose expertise crosses both pathogens research efforts and the various scientific communities.</p>", "<p>As the journal completes its first three-year editorial term, we especially thank the editorial board for their willingness to make a sustained commitment to <italic>PLoS Pathogens</italic> and the quality of work we strive to publish. We also thank the pathogens community for their groundswell of support, as evidenced in a trend of record manuscript submissions each month. This support in turn drives the need to continue to build a diverse editorial board that is integrated with its members' imperative to publish research of the highest caliber with significance across pathogens.</p>", "<p>\n<italic>PLoS Pathogens</italic> is committed to OA publishing, making all of our content freely available to read, download, and reuse. The business model for and opportunities available through OA publishing are still evolving, but as funding agencies and academic institutions around the world advance laws, mandate actions, and launch <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plos.org/cms/openaccess\">key initiatives</ext-link> to support full access to published scientific articles, <italic>PLoS Pathogens'</italic> reach will only continue to expand.</p>", "<p>This year <italic>PLoS Pathogens</italic> also provides a unique outlet among pathogens research journals with its transition to a new Web publishing platform, known as Topaz. Accepted manuscripts are now published more rapidly, and the online functionality enables members of the community to interact with the science and each other through erudite discourse on the published articles. This<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.plospathogens.org/static/commentGuidelines.action\"> discussion</ext-link> is overseen by our new team of Community Editors, who encourage and review responses to the published articles—fostering a new method of increasing the journal's utility, accessibility, value, and ultimate impact on the field.</p>", "<p>Thus, in three years, <italic>PLoS Pathogens</italic> has established itself as a leading journal that is poised to grow further. We are proud of what has been achieved so far, in such a short period of time, and we welcome the opportunity to publish your best research on pathogens and their host interactions.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<fn-group><fn fn-type=\"COI-statement\"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p>The authors received no specific funding for this article.</p></fn></fn-group>" ]

[]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Head and Neck Squamous Cell Carcinoma (HNSCC), ranked the 6th common cancer worldwide, has long been recognized with a heterogeneous clinical presentation and a poor prognosis in advanced stages ##REF##15761078##[3]##. Historically, decisions to pursue aggressive treatments such as chemoradiotherapy (CRT) or neck dissection, to a very large extent, depended on clinical staging. Many patients suffered from treatment failure due to local recurrence, distant metastases, or the development of second primary HNSCC, even with the utilization of multi-modality treatment options ##REF##17327856##[4]##. Nevertheless, understanding mechanisms of tumorigenesis and metastatic progression remains as the most urgent call for future remedy of HNSCC.</p>", "<p>Recent advance in using microarray technology to investigate HNSCC cancer biology has attracted significant research interest. Choi and colleagues ##REF##16092115##[5]##, who took the lead in systematically summarizing the HNSCC transcriptome, discovered such significant biological pathways as cell cycle regulation, inflammatory response, mevalonate pathway, and down-regulation of genes encoding cytoplasmic ribosomal proteins. These reconfirmed or newly discovered pathways shed light on the pathophysiology of HNSCC.</p>", "<p>Graphical presentations of biological networks become a common platform to demonstrate gene–gene interplays and to model human diseases at systems-level ##REF##17483841##[6]##. Integrative meta-methods, which utilize genomic, proteomic and phenotypic information from various sources, have been shown reliable in generating novel experimental hypotheses ##REF##15920529##[7]##, ##REF##17922014##[8]##. However, an integrative approach of network analysis and systems biology has not been applied to HNSCC.</p>", "<p>We recently developed a knowledge-based network approach to conduct genomic meta-analysis of HNSCC ##UREF##0##[9]##. This article, aiming to depict the evolving transcriptome of HNSCC via comparisons of gene expression profiles, sought to dissect the progressive states of HNSCC by examining the following three comparisons: <italic>Pre</italic>, premalignant lesions v.s. normal; <italic>TvN</italic>, primary tumors v.s. normal; and <italic>Meta</italic>, disseminated (regional lymph node involvement, distant metastases, or local recurrence) v.s. primary localized tumors. Results in the original articles were demonstrated to identify patterns of etiologic or metastatic processes of HNSCC in terms of <italic>Pre</italic>, <italic>TvN</italic>, or <italic>Meta</italic>. Here, we synthesized results of differential gene expression profiles into knowledge-based interacting networks. It was designated that the evolving nature of HNSCC could be read out from the topological characteristics, the prismatic visualization of three staged interacting networks, and the probabilities of reporting differential gene activities across the genome.</p>" ]

[ "<title>Methods</title>", "<title>Search Strategy</title>", "<p>We conducted this meta-analysis in accordance with the standard protocol recommended by the Quality of Reporting of Meta-analyses group ##REF##10584742##[10]##. A systematic search in the PubMed database (Jan 1994 to Apr 2008) was performed using a complex query, consisted of keywords “head and neck neoplasm”, “gene expression profiling”, “oligonucleotide array sequence analysis”, “microarray” and “carcinoma, squamous cell”. Details of the complex query were provided in ##SUPPL##3##Text S1##. A total of 410 potentially relevant articles were identified. First, we excluded studies examining lesions located in thyroid glands (n = 82), salivary glands (n = 16), nasopharynx (n = 23), eyes or elsewhere (n = 5). Studies were further excluded if the primary data reported was not differential gene expression profiling (n = 118), or if the samples used in the experiment were not human tumor tissue (n = 96). Of the remaining 70 studies, six were examining HPV-related or smoking-related transcriptional profiles and one was unavailable. Sixty-three studies of transcriptional profiles of HNSCC were included in the meta-analysis and classified into three specific comparisons: <italic>Pre</italic>, premalignant lesions <italic>v.s.</italic> normal (n = 5); <italic>TvN</italic>, primary tumors <italic>v.s.</italic> normal (n = 41); and <italic>Meta</italic>, disseminated (regional lymph node involvement, distant metastases, or local recurrence) <italic>v.</italic>s. primary localized tumors (n = 26). ##FIG##0##Figure 1## demonstrated the QUOROM flow diagram of screening microarray-based HNSCC transcriptional profiles.</p>", "<title>Data extraction, processing and parsing</title>", "<p>For each study, reported genes were extracted from tables, text or supplements. We converted various kinds of gene or sequence identifiers, such as UniGene cluster IDs, Genbank accession numbers, gene symbols, or Affymetrix probe sets, into the universal Entrez GeneIDs. GeneIDs conversion was done by the web-based program of DAVID2007–2008 (Database for Annotation Visualization and Integrated Discovery, NIH) ##REF##12734009##[11]##. Then, for each article, we compiled information of the PubMed ID, the original identifiers, the converted Entrez GeneIDs, and the values or directions of fold changes into a standard format (##SUPPL##3##Text S1##). Program scripts were developed for the use of ActivePerl and R statistical software (version 2.6.1) in text processing, parsing networks (svg files), analyzing and comparing the gene lists, linking gene-specific information and chromosomal coordinates, and transforming gene-gene interactions into matrices for networks topological analyses. Cytoscape software (version 2.5.1) was used for the illustration of networks ##REF##14597658##[12]##.</p>", "<title>Quantitative data synthesis: bounded fold changes</title>", "<p>In order to synthesize the original information of fold changes, a novel method was developed to overcome differences in multiple microarray platforms. This method based on the assumption that different transcriptional measurements of the same target gene, i.e. different sequence or gene identifiers converted into the same Entrez GeneID, were indeed representing the same functional entity. For each study, if fold changes, <italic>θ</italic>, were reported, the standardized bounded fold changes would be |<italic>θ</italic>′| = <italic>θ</italic>/(maximum of <italic>θ</italic>) with regard to up- and down-regulated genes separately; alternatively, if only directions of up- or down-regulation were reported, the bounded fold changes would be translated into 1 for up and −1 for down, respectively. For each of the <italic>Pre</italic>, <italic>TvN</italic> or <italic>Meta</italic> stages, consensus of gene expression was computed as the averaged mean of the bounded fold changes if studies reported values of fold changes; else, the median was computed instead if at least one study reported only directions of gene regulation. Genes without such information were coded with 0 as the bounded fold changes in the analysis.</p>", "<title>Validity assessment</title>", "<p>Owing to the underlying heterogeneity among included studies, such as differences in the tumor of origins (oral, pharynx, or larynx), multiple microarray platforms, different analytical approaches taken, and diverse endpoints, we sought to examine the validity of three staged classification of the HNSCC transcriptome. First, we systematically computed the frequency of reporting the same Entrez GeneID within each stage of comparison. If a gene was reported more than once, this gene was regarded as verified. Subsequently, the validity of <italic>TvN and Meta</italic> was tested through comparisons of ratios of internal consistency, defining as the percentage of verified genes for each study within the groups of interest, i.e. studies of lesions in different subsites, studies using different microarray platforms, studies investigating different endpoints, or the proposed classification. <italic>C</italic>lassifying studies in <italic>TvN</italic> or <italic>Meta</italic> would be considered reasonable if the ratios of consistency were higher than those within the subgroups of interest. For instance, of the 121 differentially expressed genes by Ibrahim and colleagues, 74 genes (61%) were verified when classified in <italic>TvN</italic>; 38 genes (32%) verified among the 23 studies using cDNA microarrays in <italic>TvN</italic>; as well as 32 genes (27%) verified among the 19 studies examining tumors located exclusively in the oral cavity.</p>", "<title>Knowledge-based network analyses and identification of enriched canonical pathways</title>", "<p>The bounded fold changes of the full gene lists and the verified gene lists of three comparisons, <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic>, were imported into the Ingenuity Pathways Analysis (IPA) Software (Ingenuity Systems, Redwood City, CA, USA) to obtain six sets of networks for further analyses. We used IPA to identify the top 10 enriched canonical pathways for each stage of comparison (##FIG##1##Fig. 2##). The enriched canonical pathways were ranked by the p-values of the Fisher's exact test, which indicated the probabilities of the input genes to be associated with genes in the canonical pathways expected by chance.</p>", "<p>Networks generated from the IPA consisted of identified focus genes from the user input and other correlated molecules or genes from the knowledge base ##REF##16136080##[13]##. Networks were scored and ranked according to the probabilities of having more focus genes than expected by chance. To gain a comprehensive perspective of the HNSCC transcriptome, three sets of networks generated from the IPA analyses with the full gene lists as inputs were parsed and merged into three staged interacting networks, representing the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> progressive states of HNSCC. Only networks of scoring higher than 10 (log p-value) were included in the analysis.</p>", "<title>Network topological analyses</title>", "<p>Based on findings in model organisms, indicating that network structure such as dynamic modularity ##REF##15190252##[14]## and topological cartography ##REF##15729348##[15]## determined the key aspects of regulation and functionality, we developed a new framework of network topological analyses to estimate the implied pathological effect for each gene in the HNSCC transcriptome. The idea was to evaluate the functional significance of a gene based on the concept of connectivity. An inter-modular hub-designated as a cut node in the graph - would cause the original component breaking down into different blocks upon removal of itself, leading to the blockade of signaling crosstalk. If an inter-modular hub <italic>i</italic> was disrupted, i.e. removed in the interacting network, we estimated the potential for pathophysiological perturbation by the informational score <italic>(f_i</italic>), computed by the number of blocked out paths divided by the number of breaking down components. The informational score (<italic>f_i</italic>) was calculated as equation (1), where <italic>m</italic> denoted the number of broken-down components after removing a node <italic>i,</italic> N_cp denoted the total number of nodes in this component where node <italic>i</italic> was located, <italic>S</italic> was the size of each broken-down component, and <italic>m.lg</italic> was the iterating counter part for each <italic>S</italic> to calculate the blocked-out paths.Rest of the genes were grouped into the periphery genes or the intra-modular hubs, whose interactions were equal or greater than two and whose removal would NOT cause the breakdown of networks. We did not consider the pathophysiological effects of these two groups of genes based on the topological properties.</p>", "<p>Sub-networks of enriched canonical pathways were extracted from each of the three progressive stages of the HNSCC transcriptome for independent topological analyses (##FIG##2##Fig. 3a–i##). Prominent connecting hubs were identified by the topological characteristics, changes in the transcriptional profiles, or the participation among different stages of the HNSCC transcriptome.</p>", "<title>Probabilities of reporting differentially expressed genes within each cytoband along the chromosomal coordinates</title>", "<p>Across the genome, we computed the accumulative probabilities (PB) of reporting genes within the chromosomal segments for each stage of comparisons. For instance, in the <italic>TvN</italic> comparison consisted of 41 papers, the cumulative probability of a cytoband with <italic>k</italic> genes reported would be , where fq_g was the number of articles reporting gene <italic>g</italic> in <italic>TvN</italic>. In order to compare across three progressive stages, we standardized PB of the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> to be within 0∼1 by dividing the maximum probability of each stage. We plotted PBs of three progressive stages along the chromosomal coordinates to identify hot-spot regions. For the identified hot-spots, differential gene activities (bounded fold changes) were illustrated on the resolution of a single gene for each stage of comparison.</p>" ]

[ "<title>Results</title>", "<title>Consensus among genes reported in each stage of comparison</title>", "<p>There were 1822, 4311, and 2293 genes, respectively, reported from 5, 41, and 26 papers in the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> comparisons. Eighty-two genes out of 1822, 1260 out of 4311, and 321 out of 2293 were found reported at least twice in the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> comparisons. With regard to the direction of fold changes of the verified genes, we found the least contradiction in <italic>TvN</italic> (217/1260 = 17.2%), less in <italic>Meta</italic> (117/321 = 36.5%), and the most, in <italic>Pre</italic> (42/82 = 51.2%). There were few genes overlapped between <italic>Pre</italic> and <italic>Meta</italic>, whereas many overlapped between any other pairs of comparisons. In ##TAB##0##Table 1##, reported genes were listed according to the number of reporting studies for each stage of comparison. Notably, MMP1, reported 13 times in <italic>TvN</italic> with a bounded fold change of 1, was found consistently highly up-regulated, albeit that tumors were harvested from different anatomical subsites; whereas in the <italic>Meta</italic> comparison, we found MMP1 with three studies reporting induced ##REF##12866027##[16]##, ##REF##17156469##[17]##, ##REF##17504990##[18]## and one repressed ##REF##15144956##[19]##. We speculated that the contradictory regulation of MMP1 in <italic>Meta</italic> might stem from differences in prognostic endpoints investigated rather than the lesion sites.</p>", "<title>Validity of the <italic>TvN</italic> and <italic>Meta</italic> progressive stages of the HNSCC transcriptome</title>", "<p>We found a higher internal consistency, i.e. having a higher ratio of the verified genes, among studies in <italic>TvN</italic> (mean ratio = 71%), secondly in <italic>Meta</italic> (31%), and lastly in <italic>Pre</italic> (26%) (##TAB##1##Table 2##). In <italic>TvN,</italic> we further investigated ratios of consistency within subgroups of studies examining tumors from distinct anatomical subsites (p, pharynx; L, larynx; and o, oral cavity) or tumors from unspecified locations (mix). Nineteen papers procured specimens located exclusively within the oral cavity. Unexpectedly, we found a significant decrease of the internal consistency within this subgroup (mean ratio = 37%). Gene lists reported from distinct anatomical subsites were examined in details (##SUPPL##3##Text S1##). The majority of genes reported from tumors of distinct oral cavity (63%), pharynx or larynx (74%) overlapped with those from unspecified locations. There were 94 genes reported in common from distinct and mix groups; 58 genes specific to pharynx or larynx; and 376 genes specific to oral cavity. Particularly, 98 genes, accounting for 9.6% from oral cavity as well as 41% from pharynx or larynx, overlapped and suggested that some similarities existed among the distinct groups. We also noted decreases of internal consistencies within subgroups of studies using similar microarray platforms. In general, studies using Affymetrix Genechips demonstrated higher internal consistencies. Three studies using Affymetrix HG-U95A and 4 studies using Affymetrix HG-U133 held with more overlap in the findings; however, another four studies using Affymetrix HG-U95Av.2 did not. Taken cDNA microarrays as a single category, four studies remained at the same level of consistency while the rest showed considerable decreases (data not shown). It was of importance to be reminded that the size of the reported gene lists would certainly affect the ratio of consistency. Details of the numbers and anatomical subsites of procured tumor samples, microarray platforms used, analytical methods conducted, original identifiers reported, information regarding fold changes, and the availability of datasets were provided in ##SUPPL##0##Table S1##.</p>", "<p>With regard to differences of prognostic outcomes investigated in <italic>Meta</italic>, we classified studies into 4 subgroups (<italic>pN</italic>, positive lymph nodes; <italic>recur</italic>, recurrence; <italic>dM</italic>, distant metastasis; and <italic>surv</italic>, survival). Similar to the results in <italic>TvN</italic>, ratios of internal consistencies within each subgroup dropped significantly, especially in the <italic>dM</italic> and <italic>surv</italic> group (mean ratio = 23%, 5%, 5% for <italic>pN</italic>, <italic>dM</italic>, and <italic>surv</italic> subgroups, respectively). Overall, we believed that classification of three progressive stages, <italic>Pre</italic>, <italic>TvN</italic> and <italic>Meta</italic>, of the HNSCC transcriptome was sufficient for the purpose of this meta-analysis.</p>", "<title>The global HNSCC transcriptome in Pre, TvN, and Meta</title>", "<p>For reasons of the inherent noise in the HNSCC transcriptome, we developed a strategy to capture the essential themes by focusing on the enriched signaling pathways as well as the topological properties of the interacting networks. In the verified gene lists, findings were more stably shown in HNSCC but the scope might be too limited. In contrast, using the full gene lists might facilitate findings of significant modules, which might be obscure when data were scarce. Therefore, the bounded fold changes of the full gene lists and the verified gene lists of <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> were first imported into IPA to obtain six sets of networks. We compared these two levels of analyses to come up a consensus of the enriched signaling pathways. The interacting networks of the HNSCC transcriptome were ultimately built on those generated by the full gene lists. Networks of scoring higher than 10 (log p-value) were parsed and merged into three staged interacting networks, representing the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> progressive states of HNSCC.</p>", "<p>\n##TAB##2##Table 3## described statistics of three staged interacting networks. A total of 65, 100 and 64 networks were merged into the <italic>Pre</italic>, <italic>TvN</italic> and <italic>Meta</italic> interacting networks, respectively. The density (average degree) of the networks was similar for each stage, and all of them contained a major component (a connected subset) of the size around 2000 genes. We did network topological analyses and identified significant inter-modular hubs with the highest informational scores. Likewise, intra-modular hubs of the highest connectivity for each stage of comparison were also listed in ##TAB##2##Table 3##.</p>", "<title>Consensus of the enriched canonical signaling pathways</title>", "<p>Top 10 enriched canonical pathways resulted from the IPA analysis using the verified gene lists were quite different from those using the full gene lists. The −log(p-values) of the canonical pathways analyzed with the verified genes list were more significant than those with the full gene lists. ##FIG##1##Figure 2## demonstrated the percentage of the up- and down-regulated genes in each pathway and the −log (p-value) of each pathway was plotted in decreasing orders. The embedded table in ##FIG##1##Figure 2## showed eight canonical pathways in consensus across three progressive stages. Antigen presentation, calcium signaling and integrin signaling pathways were highlighted as the top ranked.</p>", "<title>Enriched antigen presentation and integrin signaling pathways</title>", "<p>We sought to explore the global HNSCC transcriptome by looking into the enriched antigen presentation and integrin signaling pathways (##FIG##2##Figure 3##). Emergent view of cancers as an equilibrium state of the adaptive immunity confirmed the long obscuring roles of immunoediting in tumorigenesis and metastasis ##REF##18026089##[20]##. In the sub-networks of the antigen presentation pathway, we identified three components, representing three major complexes–proteasome, MHC class I, and MHC class II. Significant repression of the transcriptional profiles in <italic>Meta</italic> was noted, particularly <italic>HLA</italic>-G in MHC I <italic>and HLA-DRB1</italic> in MHC II. <italic>CALR</italic>, the endoplasmic reticulum-residing chaperone, calreticulin, was found differentially expressed in <italic>Pre</italic> and <italic>Meta</italic>; and presented itself as the hub connecting MHC I, the complement system, and <italic>THBS1</italic>.</p>", "<p>Network-based approach to address the complex mechanisms underlying the integrin adhesome has been sought out by researchers ##REF##17671451##[21]##. In the integrin signaling networks of the HNSCC transcriptome, we identified several repressed inter-modular hubs: <italic>ACTN2, CAPN3</italic> and <italic>TTN</italic> in <italic>Pre</italic> and <italic>TvN</italic>; and <italic>ILK</italic>, <italic>RHO-G</italic> and <italic>VCL</italic> in <italic>Meta</italic>. <italic>GRB2</italic>, <italic>ITGA5</italic>, <italic>ITGB6</italic>, <italic>ITGB7</italic> and <italic>MAPK8</italic> were distinguished as topologically significant hubs in the <italic>TvN</italic> interacting networks. ##SUPPL##1##Table S2## provided details of the topologically significant genes in the enriched antigen presentation and integrin signaling networks.</p>", "<title>Invasiveness of HNSCC implied from the disruption of integrin signaling pathways</title>", "<p>Gaggioli and colleagues ##REF##18037882##[1]## established a new model to visualize the collective invasion of co-cultured stromal fibroblasts and oral carcinoma cells (SCC12). <italic>ITGA3</italic>, <italic>ITGA5</italic>, and the RhoGTPases were required in the force-mediated matrix remodeling, by which the leading stromal fibroblasts were able to generate tracks to support SCC invasion. To exploit the biological significance of the interacting networks in the enriched pathways, we compared the topological informational scores of the integrin family with the percentage of matrix contraction due to knockdown of integrins by siRNA in stromal fibroblasts (##TAB##3##Table 4##). With regard to eight integrins, <italic>ITGA1, ITGA2, ITGA3</italic>, <italic>ITGA5, ITGAV, ITGA6, ITGB1</italic> and <italic>ITGB4</italic>, the correlation between the topological informational scores in <italic>TvN</italic> and the matrix contraction after the knockdown was −0.867 (Pearson correlation test, p-value = 0.005). The informational scores derived from the topology of interacting networks were developed to estimate the perturbed pathological effects, i.e. blocked signaling information. Not all of the integrins were differentially expressed across three stages; hence, we could not correlate the estimated pathological effects beyond the <italic>TvN</italic> networks. Nonetheless, based on the strong association between the estimated biological significance and the experimental findings, we are convinced that network-based meta-analyses of the evolving HNSCC transcriptome could indeed recapitulate the underlying nature of disease progression.</p>", "<title>Genome-wide probabilities of reporting differential gene activities in the evolving HNSCC transcriptome</title>", "<p>In ##FIG##3##Figure 4##, we plotted the standardized accumulative probabilities (PBs) of reporting differentially expressed genes within each chromosomal segment for the HNSCC transcriptome. Several significantly reported regions were identified: 1p36, 1q21, 5q31, 6p21, 9q34, 11p15, 11q13, 12p13, 12q13, 16p13, 17q21, 19p13, 19q13 and 22q13. Hot-spot loci, for instances, 1q21, where resided <italic>S100As, CD48,</italic> and <italic>ECM1</italic>, as well as 6p21, 19p13 and 19q13 were highlighted. It was of interest to know if genes co-localized in a hot-spot would interact with those within another hot-spot. In the antigen presentation pathway, <italic>MHC</italic> complex, <italic>TAP1</italic> and <italic>TNF</italic> were located in 6p21, whereas another interacting gene, <italic>CALR</italic>, was in the other hot-spot of 19p13. We compared hot-spots of differential gene activities to those of genomic alterations reported by Weber and colleagues ##REF##17213402##[2]##. Correspondingly, 19p13 region was demonstrated to have loss of heterozygosity in both the stroma and the epithelium compartments of HNSCC; and 19q13–a stroma-specific locus - was correlated to the clinical nodal status. ##SUPPL##2##Table S3## listed highly reported genes within the hot-spots of 6p21, 19p13, and 19q13. Bounded fold changes of the differential gene expression profiles within 6p21 (167 genes) and 19q13 (189 genes) were illustrated across three progressive stages in ##FIG##3##Figure 4 c,d##. In 6p21.3, <italic>HIST1H4s</italic> were found repressed in <italic>Pre</italic> and <italic>TvN</italic>; <italic>HIST1H2s</italic> induced in <italic>TvN</italic>; and <italic>HIST1H3s</italic> repressed in <italic>TvN</italic>.</p>" ]

[ "<title>Discussion</title>", "<p>In order to fully utilize the powerful gene expression profiling, challenges remained in data integration and in gaining meaningful insights. The purpose of this meta-analysis aimed at investigating the transcriptional profiles of HNSCC via a systems-level and knowledge-based network approach by means of synthesizing previous research efforts. We showed that gene-gene interplays in the interacting networks, which were quantitatively analyzed with topological informational scores and qualitatively visualized with bounded fold changes, illuminated the underlying biological events in three progressive stages of HNSCC. To date, we conducted for the first time a genome-wide meta-analysis in the context of knowledge-based networks and systematic reviews. We took the first step to unravel the pathophysiology of HNSCC via a systems-biology approach. Moreover, we provided a platform for the HNSCC research community to make strides in advancing our knowledge and future progress.</p>", "<p>We demonstrated that the perturbation of genes in the interacting networks could be estimated by the topological properties. In the enriched antigen presentation and integrin signaling pathways, we recognized significant roles of <italic>CALR</italic>, <italic>TAP1</italic>, <italic>HLA-DQB2, PTEN, HRAS, RHOA, ITGA3</italic> and <italic>IT GA5</italic> from the topological scorings and the differential gene activities in the evolving HNSCC transcriptome. Remarkably, the estimated informational scores derived from the integrin signaling networks not only supported previous findings of Gaggioli et al. ##REF##18037882##[1]##, but also extended the functional implication <italic>in vivo</italic>. Most of the differentially expressed genes in the antigen presentation and integrin signaling pathways fell into hot-spot regions of 6p21 and 17q21. Moreover, several highlighted hot-spots of differential gene activities, such as 19p13 and 19q13, co-localized to previous implicated regions of genomic alterations by Weber et al. ##REF##17213402##[2]##. Thus, we supported and further extended findings from genomic instabilities to genome-wide differential gene expression profiles. Disrupted genes exclusively found in each stage of the HNSCC trascriptome might serve as candidate targets for future cancer prevention, targeted treatment, or drug discovery. Altogether, we hope the effort in putting systematic information into perspective will lead to the medical advancement of HNSCC.</p>", "<p>It is of importance to acknowledge that the approach taken in this meta-analysis, including converting identifiers, standardizing bounded fold changes, and analyzing the topology of knowledge-based networks, are innovative but primitive. Therefore, further experimental efforts to consolidate the demonstrated findings are crucial. Nonetheless, applying a standard template for each study, so that the subsequent meta-analyses could be feasible, was indeed painstaking. Currently, we do not have a standard guideline to report genome-wide experiments in functional context. As ‘gene’ has become a vague definition and new ‘genon’ concept been proposed ##REF##17353929##[22]##, the work presented here might bring about the initiative to come up with a standard functional format in reporting genome-wide experiments for future systematic integration. Furthermore, the limited access to most of the datasets deserves the HNSCC research community to address issues in data-sharing and public access. Collectively, the integrative transcriptome, which orchestrated differential gene expression profiles, functional annotations, chromosomal coordinates, knowledge-based interactome, and enriched signaling pathways, elucidated the evolving nature of HNSCC. As benefits of conducting systems-level meta-reviews become clear while future research advances, we hope to see a more common practice applying the same strategy in other research areas.</p>" ]

[]

[ "<p>Conceived and designed the experiments: YHY HKK KWC. Performed the experiments: YHY. Analyzed the data: YHY. Contributed reagents/materials/analysis tools: YHY. Wrote the paper: YHY HKK KWC.</p>", "<title>Background</title>", "<p>Numerous studies were performed to illuminate mechanisms of tumorigenesis and metastases from gene expression profiles of Head and Neck Squamous Cell Carcinoma (HNSCC). The objective of this review is to conduct a network-based meta-analysis to identify the underlying biological signatures of the HNSCC transcriptome.</p>", "<title>Methods and Findings</title>", "<p>We included 63 HNSCC transcriptomic studies into three specific categories of comparisons: <italic>Pre</italic>, premalignant lesions v.s. normal; <italic>TvN</italic>, primary tumors v.s. normal; and <italic>Meta</italic>, metastatic or invasive v.s. primary tumors. Reported genes extracted from the literature were systematically analyzed. Participation of differential gene activities across three progressive stages deciphered the evolving nature of HNSCC. In total, 1442 genes were verified, i.e. reported at least twice, with <italic>ECM1</italic>, <italic>EMP1, CXCL10 and POSTN</italic> shown to be highly reported across all three stages. Knowledge-based networks of the HNSCC transcriptome were constructed, demonstrating integrin signaling and antigen presentation pathways as highly enriched. Notably, functional estimates derived from topological characteristics of integrin signaling networks identified such important genes as <italic>ITGA3</italic> and <italic>ITGA5</italic>, which were supported by findings of invasiveness <italic>in vitro</italic>\n##REF##18037882##[1]##. Moreover, we computed genome-wide probabilities of reporting differential gene activities for the <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic> stages, respectively. Results highlighted chromosomal regions of 6p21, 19p13 and 19q13, where genomic alterations were shown to be correlated with the nodal status of HNSCC ##REF##17213402##[2]##.</p>", "<title>Conclusions</title>", "<p>By means of a systems-biology approach via network-based meta-analyses, we provided a deeper insight into the evolving nature of the HNSCC transcriptome. Enriched canonical signaling pathways, hot-spots of transcriptional profiles across the genome, as well as topologically significant genes derived from network analyses were highlighted for each of the three progressive stages, <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic>, respectively.</p>" ]

[ "<title>Supporting Information</title>" ]

[]

[ "<fig id=\"pone-0003215-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.g001</object-id><label>Figure 1</label><caption><title>QUOROM flow diagram of the systematic reviews and meta-analysis.</title><p>The diagram summarized the search strategy. In order to be included, studies had to examine the HNSCC tumor samples by means of microarray-based gene expression profiling.</p></caption></fig>", "<fig id=\"pone-0003215-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.g002</object-id><label>Figure 2</label><caption><title>Ranking of the enriched canonical pathways.</title><p>Eight canonical pathways were found in consensus in IPA with the full gene lists (all) or the verified gene lists (fq2) as inputs. Embedded table showed rankings of the canonical pathways in different analyses. Antigen presentation, calcium signaling, and integrin signaling pathways were highlighted as highly enriched across three progressive stages. For each stage of the HNSCC transcriptome, figure panels demonstrated the enriched canonical pathways ranked by the −log (p-values) (right y-axis), that is, the orange line with square data points. Colored bars were indicating the percentage (left y-axis) of the up- or down-regulated genes within each canonical pathway. The numbers on top of the colored bars were the number of total genes in the canonical pathways.</p></caption></fig>", "<fig id=\"pone-0003215-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.g003</object-id><label>Figure 3</label><caption><title>Enriched antigen presentation and integrin signaling pathways in each stage of comparison of the HNSCC transcriptome.</title><p>Genes were represented by nodes and functional associations by edges. Node coloring was scaled to the bounded fold changes–red: up-regulated; green: down-regulated. Node size was proportional to the number of papers reporting this gene in the HNSCC transriptome. Edges were colored according to the stage of the HNSCC transcriptome–red: <italic>Meta</italic>; blue: <italic>TvN</italic>; and green: <italic>Pre</italic>. a–c. Merged networks of the antigen presentation pathways with nodes colored according to the bounded fold changes in <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta</italic>, respectively. d–f. Merged networks of the integrin signaling networks with nodes colored according to the bounded fold changes in <italic>Pre</italic>, <italic>TvN</italic>, and <italic>Meta,</italic> respectively. g–i. Sub-networks of the integrin signaling pathway in the <italic>Pre</italic>, <italic>TvN</italic> and <italic>Meta</italic> stages of the HNSCC transcriptome. (For details, please see ##SUPPL##4##Figure S1##, ##SUPPL##5##S2##, ##SUPPL##6##S3##, ##SUPPL##7##S4## and ##SUPPL##8##S5##).</p></caption></fig>", "<fig id=\"pone-0003215-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.g004</object-id><label>Figure 4</label><caption><title>Genome-wide probabilities of the evolving HNSCC transcriptome.</title><p>a. We computed the accumulative probabilities of reporting differentially expressed genes within each cytoband along the chromosomal coordinates. Hot-spots of differential gene activities, 1p21, 6p21, 19p13 and 19q13, were highlighted. The standardized accumulative probability for each cytoband was plotted across the genome. The color schemes represented three progressive stages of the HNSCC transcriptome–red circles: <italic>Meta</italic>; blue squares: <italic>TvN</italic>; and green triangles: <italic>Pre</italic>. b. Co-localization between hot-spots of differential gene activities and previously implicated regions of genomic alterations by Weber et al. ##REF##17213402##[2]##. c–d. Differential gene expression profiles–bounded fold changes - of 167 genes in 6p21 and 189 genes in 19q13 were plotted along the chromosomal coordinates for the <italic>Pre</italic>, <italic>TvN</italic> and <italic>Meta</italic> stages, respectively.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003215-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.t001</object-id><label>Table 1</label><caption><title>Highly reported genes with bounded fold changes in each stage of comparison.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"4\" align=\"left\" rowspan=\"1\">Pre</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">TvN</td><td colspan=\"4\" align=\"left\" rowspan=\"1\">Meta</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">gene</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fq</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">chr</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gene</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fq</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">chr</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gene</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fq</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">chr</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>NR2F2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15q26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TNC</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9q33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.03</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>EMP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12p12.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.72</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PI3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TAP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6p21.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PLAU</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10q24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>SFRP4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7p14.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.19</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL6A3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>FN1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PLEC1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8q24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.51</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>GPRC5A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12p13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MAL</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2cen-q13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TRIM22</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11p15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.46</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>DPYSL3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL1A2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7q22.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>SERPINB2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18q21.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.32</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CRIP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14q32.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>SPARC</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q31.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>FN1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.44</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CXCL10</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>POSTN</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q13.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>POSTN</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q13.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.71</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>IGJ</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.82</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>IFI6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1p35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>DSG3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">18q12.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.44</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>RBP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3q23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TGM3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20q11.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.86</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>FGFBP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4p16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.19</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>IFI44</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1p31.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>SPP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4q21-q25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.79</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>EGFR</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7p12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.29</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CA2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8q22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.56</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ITGA6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q31.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TGM3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20q11.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.89</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ADH7</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4q23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT13</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q12-q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PLAU</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10q24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL4A1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>EMP1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12p12.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ITGB4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.32</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL6A1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ECM1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CHPT1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12q</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.11</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>LOX</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q23.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>TNC</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9q33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CDH3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16q22.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.32</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>FKBP1A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20p13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP10</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT16</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>SEC23A</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14q21.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP3</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>PHC2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1p34.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.23</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CTNND1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP12</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>RAC2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">22q13.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>CLINT1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q23.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>LAMC2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1q25-q31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>GREM1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15q13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>THY1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11q22.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>IL8</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4q13-q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>GPC5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL4A2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT17</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT14</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>AK2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1p34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL5A2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q14-q32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>MMP2</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16q13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>KRT10</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>COL4A1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13q34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>LGALS1</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">22q13.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003215-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.t002</object-id><label>Table 2</label><caption><title>Ratios of internal consistency of selected studies in each stage of comparison.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Articles in TvN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ratio</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ratio</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">site</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Articles in Pre</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ratio</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ratio</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">site</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ye et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">289/316</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.91</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kondoh et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9/27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Suhr et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">92/175l</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Banerjee et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">69/1348</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Braakhuis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">44/59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Odani et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11/18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ziober et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">68/76</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Carinci et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21/159</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kainumai et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8/10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ha et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59/357</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gottschlich et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12/22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Tomioka et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">32/46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>Articles in Meta</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ratio</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>ratio</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>site</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>category</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Dysvik et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29/50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mendez et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28/180</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Jarvinen et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16/40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">L</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Pramana et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9/40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">r</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Roesch Ely et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5/5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Carinci et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9/38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">L</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Belbin et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">107/208</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chung et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17/44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">s</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Schlingemann et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">46/63</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Vachani et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">53/92</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kornberg et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">91/113</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Zhou et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16/48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Carinci et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7/27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Nguyen et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16/68</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Laytragoon-Lewin et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8/12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kato et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3/19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chin et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26/44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Roepman et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">167/742</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Shimada et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2/9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Carinci et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20/125</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Irie et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6/10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Belbin et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">53/208</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cromer et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">119/125</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">O'Donnell et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6/29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Schmalbach et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">48/57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Roepman et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71/96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.74</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ginos et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">902/2126</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Irie et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13/20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Marcus et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">45/60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Chung et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">70/180</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p,s</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Toruner et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">43/54</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Schmalbach et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28/57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.49</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kuriakose et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40/40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Warner et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0/15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Tsai et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">48/62</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Nagata et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14/20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Whipple et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">44/47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.94</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Braakhuis et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10/41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ha et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">875/2041</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">oL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Giri et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8/39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Banerjee et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5/5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Talbot et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14/65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Nagata et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">31/35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cromer et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9/36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">d</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Sok et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">195/231</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ginos et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">22/59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">r</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gonzalez et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5/7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.71</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ganly et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4/16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">s</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Leethanakul et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26/37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Winter et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30/154</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">s</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Kuo et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2/9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Belbin et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29/260</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">s</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ibrahim et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">74/121</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hwang et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">38/43l</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">El-Naggar et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8/11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.73</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mendez et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">244/305</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">op</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Squire et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11/13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.85</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Alevizos et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41/42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">o</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Leethanakul et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33/57</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Villaret et al</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10/13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">mix</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003215-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.t003</object-id><label>Table 3</label><caption><title>Network Statistics.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Stage</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Pre</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TvN</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Meta</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Number of nodes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2084</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3383</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2101</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Number of edges</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3484</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5401</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3266</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ave. degrees</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ave deg of top25%</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.09</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.82</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7.56</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">size of the major component</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1911</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2155</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2025</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">% of IPA focus genes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">71%</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">76%</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75%</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>Significant hubs (inter)</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MUC1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CSF2RB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DSG3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">MARK2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DKK2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HLA-DQB2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">CYP1A1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NCF4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TAF11</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">CYP3A5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NEDD9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RHOG</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">PRKCB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RUNX1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">BLVRB</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>Significant hubs (intra)</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TNF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TGFB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TNC</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">TGFB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MYC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PI3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">MYC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IFNG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PLAU</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">TP53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NFkB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FN1</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">NFkB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TP53</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">MMP1</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003215-t004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003215.t004</object-id><label>Table 4</label><caption><title>Functional estimates of integrins in the integrin signaling networks.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gene</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">geneID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">chr</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">siRNA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold.pre</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold.tvn</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">fold.meta</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">info.score.tvn<xref ref-type=\"table-fn\" rid=\"nt106\">*</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGA1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3672</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q11.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29.6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.20619</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGA2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3673</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5q23-q31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28.9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.52905</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGA3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3675</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q21.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.19046</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.27718</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGA5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3678</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">12q11-q13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.56625</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">26.3</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGAV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3685</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q31-q32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.15233</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGA6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3655</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2q31.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3295</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.25694</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.54636</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3688</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10p11.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">22.7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.15638</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITGB4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3691</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17q25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16508</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.31686</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr></tbody></table></alternatives></table-wrap>" ]

[ "<disp-formula><label>(1)</label></disp-formula>", "<inline-formula></inline-formula>" ]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s001\"><label>Table S1</label><caption><p>Included studies of microarray based differential gene expression profiles of HNSCC.</p><p>(0.18 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s002\"><label>Table S2</label><caption><p>Topologically significant genes in enriched canonical pathways.</p><p>(0.06 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s003\"><label>Table S3</label><caption><p>Most frequently reported genes in 6p21, 19p13, and 19q13.</p><p>(0.09 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s004\"><label>Text S1</label><caption><p>Details of the PubMed Query, compiled format for each study, and details of the anatomical-site-specific genes in TvN.</p><p>(0.11 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s005\"><label>Figure S1</label><caption><p>Detailed Figure of the Integrin Signaling Networks in Pre.</p><p>(0.26 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s006\"><label>Figure S2</label><caption><p>Detailed Figure of the Integrin Signaling Networks in TvN.</p><p>(0.38 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s007\"><label>Figure S3</label><caption><p>Detailed Figure of the Integrin Signaling Networks in Meta.</p><p>(0.24 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s008\"><label>Figure S4</label><caption><p>Detailed Figure of the Merged Integrin Signaling Networks, with node coloring of the differential gene expression profiles of the Meta stage.</p><p>(0.56 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003215.s009\"><label>Figure S5</label><caption><p>Detailed Figure of the Merge Networks of the Antigen Presentation Pathway, with node coloring of the differential gene expression profiles of the Meta stage.</p><p>(0.16 MB PDF)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><p>\n<bold>Abbreviations:</bold> fq, the number of papers reporting a gene; chr, the chromosomal coordinate; fold, the consensus of the bounded fold changes.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt102\"><p>\n<bold>Abbreviations:</bold> o, oral; p, pharynx; L, larynx; op, oral and pharynx; oL, oral and larynx ; pL, pharynx and larynx; mix, multiple tumor of origins; p, positive lymph node; r, recurrence; d, distant metastasis; s, survival.</p></fn><fn id=\"nt103\"><p>\n<bold>Note:</bold> detailed references were provided in ##SUPPL##0##Table S1##.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt104\"><p>Functional estimates of integrins in the integrin signaling networks of the HNSCC transcriptome were highly correlated to the percentage of matrix contraction due to knockdown of integrins with siRNA in stromal fibroblasts, which in turn should promote the invasion of the co-cultured oral cancer cells, SCC12. The percentages of matrix contraction due to siRNA depletion were formerly reported by Gaggioli and colleagues ##REF##18037882##[1]##. The higher the informational score, i.e. the lower percentage of matrix contraction due to knockdown of siRNA, indicated a more significant role in the invasion process.</p></fn><fn id=\"nt105\"><p>Pearson correlation coefficient = −0.86 <italic>P</italic>-value = 0.005.</p></fn><fn id=\"nt106\"><label>*</label><p>Informational scores were derived from the topological analysis of the integrin signaling networks of the HNSCC transcriptome in <italic>TvN</italic>.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>Dr. Yu was supported by a grant from Ministry of Education, Aim for the Top University Plan, Taiwan. Dr. Kuo was supported by the National Health and Research Institutes (Project code: GE-095-CP0).</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003215.g001\"/>", "<graphic xlink:href=\"pone.0003215.g002\"/>", "<graphic xlink:href=\"pone.0003215.e001.jpg\" mimetype=\"image\" position=\"float\"/>", "<graphic xlink:href=\"pone.0003215.g003\"/>", "<inline-graphic xlink:href=\"pone.0003215.e002.jpg\" mimetype=\"image\"/>", "<graphic id=\"pone-0003215-t001-1\" xlink:href=\"pone.0003215.t001\"/>", "<graphic id=\"pone-0003215-t002-2\" xlink:href=\"pone.0003215.t002\"/>", "<graphic id=\"pone-0003215-t003-3\" xlink:href=\"pone.0003215.t003\"/>", "<graphic id=\"pone-0003215-t004-4\" xlink:href=\"pone.0003215.t004\"/>", "<graphic xlink:href=\"pone.0003215.g004\"/>" ]

[ "<media xlink:href=\"pone.0003215.s001.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s002.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s003.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s004.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s005.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s006.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s007.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s008.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003215.s009.pdf\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Molecular motors generally are thought to be recruited to vesicles or organelles to provide directional movement; however, this perspective is complicated by evidence showing that multiple motors, using multiple cytoskeletal substrates, are found on individual vesicles and organelles [##REF##9930703##1##, ####REF##10611957##2##, ##REF##12928328##3##, ##REF##11864991##4##, ##REF##17369356##5##, ##REF##16214870##6##, ##REF##15556858##7####15556858##7##]. While kinesins and dyneins clearly transport cargo for long distances <italic>in vivo</italic>, there is surprisingly little evidence for such a role for unconventional myosins in higher eukaryotes [##REF##11470781##8##]. Biophysical studies have shown that many myosin head domains bind more tightly to actin in response to loading [##REF##9485324##9##, ####REF##15014434##10##, ##REF##16100513##11##, ##REF##16150709##12####16150709##12##], but these adaptations usually are interpreted as promoting processive transport of cargo over long distances. However, the biophysical data also are consistent with adaptation to function as dynamic tethers or tensioners between actin filaments and other cytoplasmic structures. In this context, tethering is distinct from docking, in that it may simply represent a net balance of forces, movements, and/or positions. Accordingly, retention (and active transport) within cortical actin might prevent endosomes from encountering microtubules, so tethering may represent an effect rather than a distinct molecular mechanism. Actual point-to-point transport of cargo by unconventional myosins in a cellular context might be relatively rare; for example, to reposition the myosin in the absence or reduction of load, halting as a new load is sensed.</p>", "<p>Myosin-Vb, originally named myr 6 [##REF##8855265##13##], is a member of one of the most ancient divisions of the myosin superfamily [##REF##16121172##14##], with diverse cellular functions. It interacts with the brain-expressed RING finger protein BERP, Rab11a, Rab11a-FIP2, Rab11b, Rab25, and Rab8a [##REF##10391919##15##, ####REF##11408590##16##, ##REF##11994279##17##, ##REF##15772161##18##, ##REF##17507647##19####17507647##19##]. It has been implicated in recycling of transferrin and its receptor [##REF##11408590##16##,##REF##15772161##18##,##REF##14766983##20##], the chemokine receptor CXC2 [##REF##12411301##21##], HIV Vpu [##REF##16497224##22##], acetylcholine receptors [##REF##12427833##23##], the polymeric IgA receptor [##REF##11408590##16##,##REF##10869360##24##], and the alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA)-type glutamate receptor subunit GluR1 [##REF##16338934##25##]. It also has been implicated in formation of bile canaliculi [##REF##16214890##26##].</p>", "<p>Overexpression of tail fragments of unconventional myosins has been the standard technique for their inhibition, and data from these experiments are usually interpreted in the context of point-to-point transport. For myosin-Vb in transferrin trafficking, overexpression of a tail fragment in HeLa cells caused accumulation of transferrin in perinuclear compartments, suggesting that myosin-Vb functions in the transport of vesicles between perinuclear recycling endosomes and the plasma membrane [##REF##11408590##16##]. By contrast, we adapted a chemical-genetic method pioneered by Shokat and colleagues for kinases [##REF##11891113##27##,##REF##17289560##28##] to unconventional myosins, allowing us to acutely and specifically induce tight binding of a sensitized mutant myosin to actin by microinjection or dialysis of an ADP analog [##REF##10531338##29##, ####REF##11853671##30##, ##REF##16102537##31##, ##REF##17951722##32####17951722##32##]. When we inhibited the sensitized mutant myosin-Vb (also dominant-negative inhibition), it prevented accumulation of transferrin-positive vesicles and organelles in the perinuclear region [##REF##14766983##20##]. This result was inconsistent with the transport hypothesis, because if myosin-Vb is required for transport between perinuclear compartments and the plasma membrane, induction of tight binding to actin should have caused transferrin to accumulate in perinuclear compartments.</p>", "<p>These apparently contradictory results could be reconciled if myosin-Vb acts peripherally as a dynamic tether that antagonizes the retrograde transport of transferrin to perinuclear compartments, possibly by holding the parental organelle in the periphery during fission. We also observed an increase in plasma-membrane transferrin receptor upon myosin-Vb inhibition [##REF##14766983##20##], suggesting that chemical-genetic inhibition had shunted trafficking to the rapid peripheral pathway [##REF##10809763##33##]. The tail-fragment overexpression data can be explained as release of the peripheral endocytic compartments from actin, allowing entire peripheral endosomes to be transported to the perinuclear region.</p>", "<p>Our hypothesis is illustrated in Fig. ##FIG##0##1##. Peripheral endosomes are retained in the periphery by multiple myosin-Vb motors whose heads periodically detach from actin (green) as they go through the ATPase cycle, but usually rapidly reattach, as suggested by biophysical data (Fig. ##FIG##0##1A##). In Fig. ##FIG##0##1B##, dynein (or a minus-end-directed kinesin; its head domain is shown as the letter \"D\") attaches to a microtubule and exerts retrograde force. Occasionally, adjacent myosin-Vb detaches from actin (dotted circle) and cannot reattach because dynein has pulled it away from the actin filament. The remaining myosins hold the bulk of the endosome in place. In Fig. ##FIG##0##1C##, fission has occurred, and the daughter vesicle moves retrogradely; after the switch to microtubules, myosin-Vb is carried along as a passenger. Although we hypothesize that myosin-Vb primarily functions as a dynamic tether, our model does not preclude myosin-Vb-dependent meandering within the peripheral actin network. We have diagrammed two different means of binding myosin-Vb to the endosome as cyan and purple circles, since two different means have been demonstrated experimentally: Rab11a [##REF##11408590##16##] and the CART complex [##REF##15772161##18##].</p>", "<p>In this study, we have employed three different perturbations of myosin-Vb function to further test the dynamic tethering hypothesis, which makes clear predictions: first, overexpression of full-length, functional myosin-Vb will prevent transferrin from reaching perinuclear compartments; second, chemical-genetic inhibition of sensitized mutant myosin-Vb in cells <bold>after </bold>transferrin loading (in our previous study, it was done <bold>before </bold>transferrin loading) will neither cause accumulation of transferrin in perinuclear compartments nor prevent transferrin from moving from perinuclear compartments to the plasma membrane; and third, overexpression of the myosin-Vb tail fragment will cause at least some peripheral endocytic markers to assume more perinuclear distributions. The new data generally contradict the transport hypothesis. In addition, our data suggest that members of the myosin-V family may play a ubiquitous function in modulating vesicle transport along microtubules, as they are available to interact with passing actin filaments as passengers. Applied more broadly, our data suggest that identifying endocytic compartments by their positions within the cytoplasm may be unreliable in the context of significant experimental disruptions.</p>" ]

[ "<title>Methods</title>", "<title>Expression Constructs</title>", "<p>The full-length eGFP-wild-type myosin-Vb, eGFP-myosin-Vb tail, mRFP-Rab4a, mRFP-Rab5a, mRFP-Rab8a and mRFP-Rab11a expression constructs were gifts from Jim Goldenring and are based on the peGFP-C2 expression vector (Clontech). The sensitized Y119G mutant eGFP myosin-Vb was created by shuttling a 989-bp <italic>Cla</italic>I/<italic>Bst</italic>EII fragment from pEcho/pcDNA3.1 Y119G myosin-Vb [##REF##14766983##20##]. The control eGFP-tagged myosin-Vb 1IQ expression vector was created by amplifying the eGFP-tagged, wild-type myosin-Vb sequence for the head domain through the first IQ domain and cloning into pYY8.</p>", "<title>Cells and transfection</title>", "<p>HeLa cells were cultured as described [##REF##14766983##20##]. For transfections, 1 μg of Lipofectamine 2000 (Invitrogen) was added to 40 μl of OptiMEM (Invitrogen), then mixed with 0.5 μg of DNA diluted into 40 μl of OptiMEM according to manufacturer's instructions. HeLa cells were trypsinized, collected and resuspended in complete medium at a concentration of 1 × 10⁶cells/ml. The cell suspension (80 μl) was added to the DNA/liposome mixture and plated as 40-μl dots in live-cell chambers (Bioptechs, Butler, PA) or glass coverslips, incubated for 1–2 h and then flooded with complete medium. Cells were used in experiments 24–48 h after transfection.</p>", "<title>Immunofluorescence</title>", "<p>EEA1 was detected using a monoclonal antibody (BD Transduction Laboratories 610456). The primary antibody was detected with Alexa-546- or Alexa-647-labeled goat anti-mouse secondary (Invitrogen). For cell outlines, actin was stained with Alexa-647-labeled phallacidin (Invitrogen).</p>", "<title>Transferrin trafficking, microinjection, and latrunculin treatment</title>", "<p>Transfected cells were incubated in serum-free medium for 60 min, then exposed to 10 μg/ml Alexa 546-labeled transferrin (Invitrogen) for 1 min, washed 3 times with PBS and incubated in pre-equilibrated complete medium for the duration of live-cell experiments. For concomitant labeling with transferrin before expression of exogenous eGFP-myosin-Vb (Fig. ##FIG##1##2D,E,F##), fluorescent transferrin (10 μg/ml) was added to the complete medium used to flood the coverslips during transfection as described above. During live-cell experiments, stage positions of individual transfected cells were stored using MetaMorph (Molecular Devices) and a motorized stage (Prior). To inhibit Y119G myosin-Vb, HeLa cells were injected in the nucleus with 10 mM PE-ADP, 100 mM KCl, 8 mM K-phosphate (pH 7.0), 0.05 mg/ml fixable Alexa 647-labeled dextran (Invitrogen), and 10 mM Mg-ATP using a Harvard Apparatus PLI-100 at 8–15 kilopascals; negative control injections contained the same solution lacking PE-ADP. Assuming an injection volume of ~3% cell volume, the final concentration of PE-ADP was ~300 μM. To inhibit actin polymerization, latrunculin A (Molecular Probes) was added to medium at 2.5 μg/ml.</p>", "<title>Imaging and Quantitation</title>", "<p>All images were obtained using a Nikon TE2000E equipped with a Q57 12-bit CCD camera (Roper Scientific) controlled by MetaMorph software. Images were obtained through a 60× (1.2 NA) water-immersion lens that was maintained at 37°C using an objective heater (Bioptechs). For time-lapse movies, images were obtained at a rate of 1 frame/sec over a 1-min time course. Fluorescence imaging of the dextran to identify injected cells was performed following the time-lapse imaging. Instantaneous speeds of individual particles were measured by observers (blindly with respect to experimental conditions) using the Track Points package of MetaMorph and the data were exported to Microsoft Excel. Measurements were obtained from 5–10 cells per condition, and numbers of particles are provided in the Figure ##FIG##2##3## legend. Since pixel size produced submicron/sec speed measurement errors, speeds were separated into 3 bins: 0–0.15 μm/sec (stationary and actin-based), 0.16–0.70 μm/sec (both actin- and microtubule-based), and 0.71–1.0 μm/sec (microtubule-based).</p>" ]

[ "<title>Results and Discussion</title>", "<p>We have shown that expression of low levels of exogenous myosin-Vb (25–40% of endogenous levels) does not alter the trafficking of transferrin [##REF##14766983##20##]. However, the dynamic tethering hypothesis predicts that exceeding endogenous levels with wild-type exogenous myosin-Vb will alter the balance of forces, reducing the extent and/or rate of retrograde movement from peripheral to perinuclear compartments. To test this prediction, we increased the amount of myosin-Vb associated with those compartments by transiently transfecting HeLa cells with a full-length, wild-type myosin-Vb construct. To allow imaging of live cells, we used a construct with an N-terminal eGFP tag [##REF##11408590##16##]. We compared the distribution of eGFP-tagged myosin-Vb with that of our C-terminal -tagged (V5 and 6x-His) version [##REF##14766983##20##], and observed no significant differences (data not shown). At low levels of eGFP-myosin-Vb expression, we observed only occasional, highly dynamic, colocalization of myosin-Vb and transferrin (arrows, Fig. ##FIG##0##1D,E,F##; Additional file ##SUPPL##0##1##).</p>", "<p>Figure ##FIG##1##2## and Additional files ##SUPPL##1##2##, ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5##, ##SUPPL##5##6##, ##SUPPL##6##7##, ##SUPPL##7##8## show transferrin accumulation in peripheral compartments as a function of the overexpression level of eGFP-myosin-Vb, which the dynamic tethering hypothesis predicts will cause the coalescence and caging of peripheral endosomes by actin (Fig. ##FIG##1##2A##). A coalescence of actin around the enlarged peripheral endosomes is shown by the colocalization of myosin-Vb and actin (Fig. ##FIG##1##2B,C##).</p>", "<p>HeLa cells that endocytosed fluorescent transferrin <bold>before and during </bold>overexpression of eGFP-myosin-Vb sequestered transferrin in large peripheral compartments decorated with myosin-Vb (Fig. ##FIG##1##2D,E,F##; Additional file ##SUPPL##1##2##), suggesting that fission of the compartments in which myosin-Vb and transferrin normally transiently colocalize (arrow, Fig. ##FIG##0##1D,E,F##; Additional file ##SUPPL##0##1##) was inhibited. By contrast, when transferrin was introduced <bold>after </bold>overexpression of myosin-Vb, transferrin was not colocalized with myosin-Vb in the enlarged peripheral compartments (arrows, Fig. ##FIG##1##2F–K##; Additional files ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5##). In addition, transferrin failed to accumulate in perinuclear compartments. As a negative control, we expressed a truncated myosin-Vb consisting of the head domain and first IQ domain, which had no effect on transferrin localization (data not shown). These data suggest that that overexpression of myosin-Vb prevents transferrin from both entering into and exiting from a normally dynamic, short-lived endocytic compartment.</p>", "<p>In isolation, the static images shown in Figure ##FIG##1##2## can be fit to the anterograde transport model if overexpression caused rapid transport of transferrin from perinuclear compartments while delaying its passage through cortical actin. However, Additional files ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5## show that transferrin is not reaching perinuclear compartments.</p>", "<p>As these data suggest that fission of vesicles from peripheral endocytic compartments and/or their transport to perinuclear compartments had been prevented by increased tethering to cortical actin, we examined the distribution of the endocytic markers Rab11a, Rab4, and Rab5. Cotransfections with eGFP-myosin-Vb and the recycling endosome marker mRFP-Rab11a showed virtually complete colocalization at high levels of myosin-Vb expression (Additional file ##SUPPL##5##6##). By contrast, little colocalization was observed in cells cotransfected with eGFP-myosin-Vb and the early endosome markers mRFP-Rab4 (Additional file ##SUPPL##6##7##) and mRFP-Rab5 (Additional file ##SUPPL##7##8##), suggesting that trafficking through early endosomes was not prevented. The videos also show that the enlarged endosomes are relatively static, consistent with increased tethering forces and caging by actin.</p>", "<p>In a previous study, we used a chemical-genetic approach to show that induction of tight binding of sensitized myosin-Vb to actin, <bold>before </bold>addition of transferrin, prevented transferrin from accumulating in perinuclear compartments [##REF##14766983##20##]. Our hypothesis is diagrammed in Fig. ##FIG##2##3A##, and the effect of inhibition before transferrin uptake, demonstrated previously, is shown in Fig. ##FIG##2##3B##. If myosin-Vb is required for transport from perinuclear compartments to the plasma membrane, then inducing tight binding of myosin-Vb to actin <bold>after </bold>transferrin loading should increase transferrin accumulation in perinuclear compartments, just as myosin-Vb tail overexpression does. We therefore transfected HeLa cells with Y119G sensitized mutant (Fig. ##FIG##2##3##) and wild-type control (not shown) myosin-Vb, loaded them with fluorescent transferrin, and microinjected the specific inhibitor of Y119G myosin-Vb, <bold><italic>N</italic></bold>⁶-(2-phenylethyl)-ADP (PE-ADP) [##REF##14766983##20##]. Only cells with a punctate eGFP localization, representing lower expression levels, were chosen for microinjection. When PE-ADP was injected 10 min (data not shown) and 30 min (Fig. ##FIG##2##3D,E,F##) following the addition of transferrin, we still observed a decrease in fluorescence intensity in the perinuclear region of the transfected and injected cells (Fig. ##FIG##2##3D,E,F##) as well as rapid movement of transferrin when it did not colocalize with myosin-Vb (Additional file ##SUPPL##8##9##). These data, as well as the limited colocalization between transferrin and myosin-Vb, indicate that myosin-Vb activity is not required to transport transferrin from perinuclear compartments to the plasma membrane. These data are much more consistent with the peripheral tethering hypothesis, because the peripheral site of myosin-Vb function has been bypassed by loading with transferrin before induction of tight binding of myosin-Vb to actin.</p>", "<p>While the inhibition of the Y119G sensitized mutant myosin-Vb in preloaded cells did not cause transferrin accumulation in perinuclear compartments, the data were not as simple as they were predicted to be by the dynamic tethering hypothesis, as myosin-Vb inhibition retarded the depletion of transferrin from perinuclear compartments relative to control cells (Fig. ##FIG##2##3G,H##). Upon closer examination, our induction of binding of myosin-Vb to actin had the general effect of halting nearly all motion of myosin-Vb-decorated structures within the cell (Fig. ##FIG##3##4A##). The motility of eGFP-myosin-Vb before and after microinjection was analyzed using kymographs (Fig. ##FIG##3##4B,C## for the cells shown in Fig. ##FIG##3##4A##, Fig. ##FIG##3##4D,E## for additional negative control cells; also see Additional files ##SUPPL##9##10##, ##SUPPL##10##11##, ##SUPPL##11##12##). Binned measurements of instantaneous particle speeds in the presence and absence of PE-ADP (Fig. ##FIG##3##4F##, Additional files ##SUPPL##9##10## and ##SUPPL##10##11##) show that not only was slower actin-based motility (0.15 – 0.3 μm/s) inhibited, but higher-speed movements of myosin-Vb-decorated particles caused by microtubule-based motors (&gt; 0.7 μm/s) were halted as well. No such inhibition was observed under control conditions, which included cells expressing Y119G myosin-Vb after injection of vehicle plus fluorescent Dextran without PE-ADP (data not shown), as well as cells expressing wild-type myosin-Vb after PE-ADP injection (Fig. ##FIG##3##4G##, Additional file ##SUPPL##11##12##).</p>", "<p>The arrest of microtubule-based motility of myosin-Vb-decorated particles was unexpected, and we initially suspected that it might have been an artifact of high effective ADP concentration in the form of the microinjected PE-ADP analog. To test the hypothesis that myosin-Vb interacts transiently with actin filaments during microtubule-based transport under normal conditions, we measured the speeds of particles decorated with wild-type eGFP-tagged myosin-Vb before and after the addition of latrunculin A. If myosin-Vb (or other myosins) normally interacts with actin filaments, latrunculin A treatment should increase both mean speed and the proportion of vesicles moving at 0.7–1.0 μm/sec. This prediction was confirmed, as latrunculin treatment nearly doubled the proportion of particles exhibiting rapid movement (Figure ##FIG##3##4H##), in contrast with results from melanosome transport in fish melanophores [##REF##14588239##34##]. The modification of the dynamic tethering hypothesis to account for these data is diagrammed in Fig. ##FIG##3##4I## and ##FIG##3##4J##.</p>", "<p>The dynamic tethering hypothesis further predicts that some markers found in peripheral endocytic compartments are likely to be shifted to a more perinuclear distribution by myosin-Vb tail overexpression (Fig. ##FIG##4##5A##). We tested this prediction for early endosomal antigen-1 (EEA1), which had a dispersed pattern in control cells (Fig. ##FIG##4##5B,C,D##, arrowhead), while in cells expressing the eGFP/myosin-Vb tail chimera [##REF##11408590##16##], EEA1 was much more concentrated, in an asymmetric pattern primarily on one side of the nucleus (Fig. ##FIG##4##5B,C,D##, arrows).</p>", "<p>Based on the change in distribution of EEA1 coupled with its failure to colocalize with the myosin-Vb tail, we hypothesize that in the presence of the tail, endosomes still are transported to more perinuclear regions of the cytoplasm, but the fission between their domains that normally occurs in peripheral regions occurs in a more perinuclear location. We then confirmed the effect of the myosin-Vb tail on Rab11a redistribution. As observed by Lapierre et al., the dispersed pattern observed in untransfected control cells (Fig. ##FIG##4##5E,F,G##, arrowheads) was changed to a more perinuclear pattern by overexpression of the eGFP/myosin-Vb tail (arrows).</p>", "<p>We next examined Rab8a, which has been shown to interact <italic>in vitro </italic>with myosin-Vb [##REF##17507647##19##]. We observed a nearly normal distribution of Rab8a despite the overexpression of the myosin-Vb tail (Fig. ##FIG##4##5H,I,J##). These results are consistent with the differences between Rab11a and Rab8a compartments and pathways observed by Roland et al., and indicate that the affinity of the myosin-Vb tail domain for Rab8a is much lower than its affinity for Rab11a. This result also is consistent with their inability to observe interaction between myosin-Vb and Rab8a in a cellular context.</p>", "<p>Since mosaic endosomes have been observed with every possible combination of Rab4, Rab5, and Rab11a [##REF##10811830##35##], we examined Rab4 and Rab5 distribution. Overexpression of the myosin-Vb tail produced a slight alteration in the distribution of Rab4 (Fig. ##FIG##5##6A,B,C,D##), but no significant effect on Rab5 distribution (Fig. ##FIG##5##6F,G,H##), which is puzzling given the association between EEA1 and Rab5 [##REF##7768953##36##].</p>", "<p>To summarize our model, myosin-Vb is associated with multiple compartments, of which only some are involved in transferrin trafficking. Myosin-Vb primarily tethers a subset of peripheral, Rab11a-positive endocytic compartments to cortical actin, opposing forces from dynein or minus-end-directed kinesins and retaining the compartment in the actin-rich periphery. This is analogous to the mechanism of Velcro™, except that instead of hooks bending, the myosin-Vb heads are going through the ATPase cycle and periodically releasing from actin. In this analogy, overexpression of full-length, wild-type myosin-Vb (Fig. ##FIG##1##2##) causes greater retention of normally endocytic compartments in the periphery, leading to their coalescence, because the increase in number of myosins outweighs their individual cycling off and back onto actin. These data strongly suggest that while this compartment is normally rare and transient (Fig. ##FIG##0##1##), all transferrin still must pass through it to reach perinuclear compartments. Both our overexpression of myosin-Vb and overexpression of the myosin-Vb tail create artifacts. In the former case (Fig. ##FIG##1##2##), caging by actin causes coalescence and blockage of both entry and exit; while in the latter case [##REF##11408590##16##], release from actin causes what we believe to be virtually the same compartment to collapse to a perinuclear location. Chemical-genetic inhibition is analogous to preventing individual Velcro™ hooks from bending, but does not prevent entry and exit into this compartment via the peripheral pathway [##REF##14766983##20##].</p>", "<p>Myosin-Va, the founding member of this myosin family, appears to have a similar function, albeit involving different compartments. In melanocytes, we first suggested a peripheral tethering function for myosin-Va based on the mutant phenotype, a perinuclear accumulation of melanosomes [##REF##8962090##37##]. The best-characterized system for melanosome transport has been Xenopus melanophores [##REF##11864991##4##,##REF##17369356##5##,##REF##9443916##38##,##REF##10541038##39##], with similar, but less dynamic, results from murine melanocytes [##REF##9864363##40##]. In both cases, myosin-Va function was hypothesized to provide not only peripheral capture, but transport within the periphery as well. While pauses in microtubule-based movement attributed to myosin-Va have been observed [##REF##10477758##41##,##REF##11553713##42##], these studies represent the first such observation for myosin-Vb. In general, myosin-Vb appears to perform the same function in the endocytic pathway as myosin-Va performs in exocytic pathways, and our future experiments will test the validity of our generalization. In a technical context, our results suggest that membrane compartments cannot necessarily be reliably identified by their locations within the cytoplasm in cells in which trafficking has been grossly perturbed by manipulation, particularly overexpression, of any relevant component.</p>" ]

[ "<title>Results and Discussion</title>", "<p>We have shown that expression of low levels of exogenous myosin-Vb (25–40% of endogenous levels) does not alter the trafficking of transferrin [##REF##14766983##20##]. However, the dynamic tethering hypothesis predicts that exceeding endogenous levels with wild-type exogenous myosin-Vb will alter the balance of forces, reducing the extent and/or rate of retrograde movement from peripheral to perinuclear compartments. To test this prediction, we increased the amount of myosin-Vb associated with those compartments by transiently transfecting HeLa cells with a full-length, wild-type myosin-Vb construct. To allow imaging of live cells, we used a construct with an N-terminal eGFP tag [##REF##11408590##16##]. We compared the distribution of eGFP-tagged myosin-Vb with that of our C-terminal -tagged (V5 and 6x-His) version [##REF##14766983##20##], and observed no significant differences (data not shown). At low levels of eGFP-myosin-Vb expression, we observed only occasional, highly dynamic, colocalization of myosin-Vb and transferrin (arrows, Fig. ##FIG##0##1D,E,F##; Additional file ##SUPPL##0##1##).</p>", "<p>Figure ##FIG##1##2## and Additional files ##SUPPL##1##2##, ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5##, ##SUPPL##5##6##, ##SUPPL##6##7##, ##SUPPL##7##8## show transferrin accumulation in peripheral compartments as a function of the overexpression level of eGFP-myosin-Vb, which the dynamic tethering hypothesis predicts will cause the coalescence and caging of peripheral endosomes by actin (Fig. ##FIG##1##2A##). A coalescence of actin around the enlarged peripheral endosomes is shown by the colocalization of myosin-Vb and actin (Fig. ##FIG##1##2B,C##).</p>", "<p>HeLa cells that endocytosed fluorescent transferrin <bold>before and during </bold>overexpression of eGFP-myosin-Vb sequestered transferrin in large peripheral compartments decorated with myosin-Vb (Fig. ##FIG##1##2D,E,F##; Additional file ##SUPPL##1##2##), suggesting that fission of the compartments in which myosin-Vb and transferrin normally transiently colocalize (arrow, Fig. ##FIG##0##1D,E,F##; Additional file ##SUPPL##0##1##) was inhibited. By contrast, when transferrin was introduced <bold>after </bold>overexpression of myosin-Vb, transferrin was not colocalized with myosin-Vb in the enlarged peripheral compartments (arrows, Fig. ##FIG##1##2F–K##; Additional files ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5##). In addition, transferrin failed to accumulate in perinuclear compartments. As a negative control, we expressed a truncated myosin-Vb consisting of the head domain and first IQ domain, which had no effect on transferrin localization (data not shown). These data suggest that that overexpression of myosin-Vb prevents transferrin from both entering into and exiting from a normally dynamic, short-lived endocytic compartment.</p>", "<p>In isolation, the static images shown in Figure ##FIG##1##2## can be fit to the anterograde transport model if overexpression caused rapid transport of transferrin from perinuclear compartments while delaying its passage through cortical actin. However, Additional files ##SUPPL##2##3##, ##SUPPL##3##4##, ##SUPPL##4##5## show that transferrin is not reaching perinuclear compartments.</p>", "<p>As these data suggest that fission of vesicles from peripheral endocytic compartments and/or their transport to perinuclear compartments had been prevented by increased tethering to cortical actin, we examined the distribution of the endocytic markers Rab11a, Rab4, and Rab5. Cotransfections with eGFP-myosin-Vb and the recycling endosome marker mRFP-Rab11a showed virtually complete colocalization at high levels of myosin-Vb expression (Additional file ##SUPPL##5##6##). By contrast, little colocalization was observed in cells cotransfected with eGFP-myosin-Vb and the early endosome markers mRFP-Rab4 (Additional file ##SUPPL##6##7##) and mRFP-Rab5 (Additional file ##SUPPL##7##8##), suggesting that trafficking through early endosomes was not prevented. The videos also show that the enlarged endosomes are relatively static, consistent with increased tethering forces and caging by actin.</p>", "<p>In a previous study, we used a chemical-genetic approach to show that induction of tight binding of sensitized myosin-Vb to actin, <bold>before </bold>addition of transferrin, prevented transferrin from accumulating in perinuclear compartments [##REF##14766983##20##]. Our hypothesis is diagrammed in Fig. ##FIG##2##3A##, and the effect of inhibition before transferrin uptake, demonstrated previously, is shown in Fig. ##FIG##2##3B##. If myosin-Vb is required for transport from perinuclear compartments to the plasma membrane, then inducing tight binding of myosin-Vb to actin <bold>after </bold>transferrin loading should increase transferrin accumulation in perinuclear compartments, just as myosin-Vb tail overexpression does. We therefore transfected HeLa cells with Y119G sensitized mutant (Fig. ##FIG##2##3##) and wild-type control (not shown) myosin-Vb, loaded them with fluorescent transferrin, and microinjected the specific inhibitor of Y119G myosin-Vb, <bold><italic>N</italic></bold>⁶-(2-phenylethyl)-ADP (PE-ADP) [##REF##14766983##20##]. Only cells with a punctate eGFP localization, representing lower expression levels, were chosen for microinjection. When PE-ADP was injected 10 min (data not shown) and 30 min (Fig. ##FIG##2##3D,E,F##) following the addition of transferrin, we still observed a decrease in fluorescence intensity in the perinuclear region of the transfected and injected cells (Fig. ##FIG##2##3D,E,F##) as well as rapid movement of transferrin when it did not colocalize with myosin-Vb (Additional file ##SUPPL##8##9##). These data, as well as the limited colocalization between transferrin and myosin-Vb, indicate that myosin-Vb activity is not required to transport transferrin from perinuclear compartments to the plasma membrane. These data are much more consistent with the peripheral tethering hypothesis, because the peripheral site of myosin-Vb function has been bypassed by loading with transferrin before induction of tight binding of myosin-Vb to actin.</p>", "<p>While the inhibition of the Y119G sensitized mutant myosin-Vb in preloaded cells did not cause transferrin accumulation in perinuclear compartments, the data were not as simple as they were predicted to be by the dynamic tethering hypothesis, as myosin-Vb inhibition retarded the depletion of transferrin from perinuclear compartments relative to control cells (Fig. ##FIG##2##3G,H##). Upon closer examination, our induction of binding of myosin-Vb to actin had the general effect of halting nearly all motion of myosin-Vb-decorated structures within the cell (Fig. ##FIG##3##4A##). The motility of eGFP-myosin-Vb before and after microinjection was analyzed using kymographs (Fig. ##FIG##3##4B,C## for the cells shown in Fig. ##FIG##3##4A##, Fig. ##FIG##3##4D,E## for additional negative control cells; also see Additional files ##SUPPL##9##10##, ##SUPPL##10##11##, ##SUPPL##11##12##). Binned measurements of instantaneous particle speeds in the presence and absence of PE-ADP (Fig. ##FIG##3##4F##, Additional files ##SUPPL##9##10## and ##SUPPL##10##11##) show that not only was slower actin-based motility (0.15 – 0.3 μm/s) inhibited, but higher-speed movements of myosin-Vb-decorated particles caused by microtubule-based motors (&gt; 0.7 μm/s) were halted as well. No such inhibition was observed under control conditions, which included cells expressing Y119G myosin-Vb after injection of vehicle plus fluorescent Dextran without PE-ADP (data not shown), as well as cells expressing wild-type myosin-Vb after PE-ADP injection (Fig. ##FIG##3##4G##, Additional file ##SUPPL##11##12##).</p>", "<p>The arrest of microtubule-based motility of myosin-Vb-decorated particles was unexpected, and we initially suspected that it might have been an artifact of high effective ADP concentration in the form of the microinjected PE-ADP analog. To test the hypothesis that myosin-Vb interacts transiently with actin filaments during microtubule-based transport under normal conditions, we measured the speeds of particles decorated with wild-type eGFP-tagged myosin-Vb before and after the addition of latrunculin A. If myosin-Vb (or other myosins) normally interacts with actin filaments, latrunculin A treatment should increase both mean speed and the proportion of vesicles moving at 0.7–1.0 μm/sec. This prediction was confirmed, as latrunculin treatment nearly doubled the proportion of particles exhibiting rapid movement (Figure ##FIG##3##4H##), in contrast with results from melanosome transport in fish melanophores [##REF##14588239##34##]. The modification of the dynamic tethering hypothesis to account for these data is diagrammed in Fig. ##FIG##3##4I## and ##FIG##3##4J##.</p>", "<p>The dynamic tethering hypothesis further predicts that some markers found in peripheral endocytic compartments are likely to be shifted to a more perinuclear distribution by myosin-Vb tail overexpression (Fig. ##FIG##4##5A##). We tested this prediction for early endosomal antigen-1 (EEA1), which had a dispersed pattern in control cells (Fig. ##FIG##4##5B,C,D##, arrowhead), while in cells expressing the eGFP/myosin-Vb tail chimera [##REF##11408590##16##], EEA1 was much more concentrated, in an asymmetric pattern primarily on one side of the nucleus (Fig. ##FIG##4##5B,C,D##, arrows).</p>", "<p>Based on the change in distribution of EEA1 coupled with its failure to colocalize with the myosin-Vb tail, we hypothesize that in the presence of the tail, endosomes still are transported to more perinuclear regions of the cytoplasm, but the fission between their domains that normally occurs in peripheral regions occurs in a more perinuclear location. We then confirmed the effect of the myosin-Vb tail on Rab11a redistribution. As observed by Lapierre et al., the dispersed pattern observed in untransfected control cells (Fig. ##FIG##4##5E,F,G##, arrowheads) was changed to a more perinuclear pattern by overexpression of the eGFP/myosin-Vb tail (arrows).</p>", "<p>We next examined Rab8a, which has been shown to interact <italic>in vitro </italic>with myosin-Vb [##REF##17507647##19##]. We observed a nearly normal distribution of Rab8a despite the overexpression of the myosin-Vb tail (Fig. ##FIG##4##5H,I,J##). These results are consistent with the differences between Rab11a and Rab8a compartments and pathways observed by Roland et al., and indicate that the affinity of the myosin-Vb tail domain for Rab8a is much lower than its affinity for Rab11a. This result also is consistent with their inability to observe interaction between myosin-Vb and Rab8a in a cellular context.</p>", "<p>Since mosaic endosomes have been observed with every possible combination of Rab4, Rab5, and Rab11a [##REF##10811830##35##], we examined Rab4 and Rab5 distribution. Overexpression of the myosin-Vb tail produced a slight alteration in the distribution of Rab4 (Fig. ##FIG##5##6A,B,C,D##), but no significant effect on Rab5 distribution (Fig. ##FIG##5##6F,G,H##), which is puzzling given the association between EEA1 and Rab5 [##REF##7768953##36##].</p>", "<p>To summarize our model, myosin-Vb is associated with multiple compartments, of which only some are involved in transferrin trafficking. Myosin-Vb primarily tethers a subset of peripheral, Rab11a-positive endocytic compartments to cortical actin, opposing forces from dynein or minus-end-directed kinesins and retaining the compartment in the actin-rich periphery. This is analogous to the mechanism of Velcro™, except that instead of hooks bending, the myosin-Vb heads are going through the ATPase cycle and periodically releasing from actin. In this analogy, overexpression of full-length, wild-type myosin-Vb (Fig. ##FIG##1##2##) causes greater retention of normally endocytic compartments in the periphery, leading to their coalescence, because the increase in number of myosins outweighs their individual cycling off and back onto actin. These data strongly suggest that while this compartment is normally rare and transient (Fig. ##FIG##0##1##), all transferrin still must pass through it to reach perinuclear compartments. Both our overexpression of myosin-Vb and overexpression of the myosin-Vb tail create artifacts. In the former case (Fig. ##FIG##1##2##), caging by actin causes coalescence and blockage of both entry and exit; while in the latter case [##REF##11408590##16##], release from actin causes what we believe to be virtually the same compartment to collapse to a perinuclear location. Chemical-genetic inhibition is analogous to preventing individual Velcro™ hooks from bending, but does not prevent entry and exit into this compartment via the peripheral pathway [##REF##14766983##20##].</p>", "<p>Myosin-Va, the founding member of this myosin family, appears to have a similar function, albeit involving different compartments. In melanocytes, we first suggested a peripheral tethering function for myosin-Va based on the mutant phenotype, a perinuclear accumulation of melanosomes [##REF##8962090##37##]. The best-characterized system for melanosome transport has been Xenopus melanophores [##REF##11864991##4##,##REF##17369356##5##,##REF##9443916##38##,##REF##10541038##39##], with similar, but less dynamic, results from murine melanocytes [##REF##9864363##40##]. In both cases, myosin-Va function was hypothesized to provide not only peripheral capture, but transport within the periphery as well. While pauses in microtubule-based movement attributed to myosin-Va have been observed [##REF##10477758##41##,##REF##11553713##42##], these studies represent the first such observation for myosin-Vb. In general, myosin-Vb appears to perform the same function in the endocytic pathway as myosin-Va performs in exocytic pathways, and our future experiments will test the validity of our generalization. In a technical context, our results suggest that membrane compartments cannot necessarily be reliably identified by their locations within the cytoplasm in cells in which trafficking has been grossly perturbed by manipulation, particularly overexpression, of any relevant component.</p>" ]

[]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Myosin-Vb has been shown to be involved in the recycling of diverse proteins in multiple cell types. Studies on transferrin trafficking in HeLa cells using a dominant-negative myosin-Vb tail fragment suggested that myosin-Vb was required for recycling from perinuclear compartments to the plasma membrane. However, chemical-genetic, dominant-negative experiments, in which myosin-Vb was specifically induced to bind to actin, suggested that the initial hypothesis was incorrect both in its site and mode of myosin-Vb action. Instead, the chemical-genetic data suggested that myosin-Vb functions in the actin-rich periphery as a dynamic tether on peripheral endosomes, retarding transferrin transport to perinuclear compartments.</p>", "<title>Results</title>", "<p>In this study, we employed both approaches, with the addition of overexpression of full-length wild-type myosin-Vb and switching the order of myosin-Vb inhibition and transferrin loading, to distinguish between these hypotheses. Overexpression of full-length myosin-Vb produced large peripheral endosomes. Chemical-genetic inhibition of myosin-Vb after loading with transferrin did not prevent movement of transferrin from perinuclear compartments; however, virtually all myosin-Vb-decorated particles, including those moving on microtubules, were halted by the inhibition. Overexpression of the myosin-Vb tail caused a less-peripheral distribution of early endosome antigen-1 (EEA1).</p>", "<title>Conclusion</title>", "<p>All results favored the peripheral dynamic tethering hypothesis.</p>" ]

[ "<title>Additional files</title>", "<p>All videos are of HeLa cells.</p>", "<title>Abbreviations List</title>", "<p>EEA1: early endosomal antigen-1; and PE-ADP: <bold><italic>N</italic></bold>⁶-(2-phenylethyl)-ADP.</p>", "<title>Authors' contributions</title>", "<p>DWP performed most of the experiments, performed most of the data analysis, and designed the project. EJA, PRW, and DZC analyzed particle speeds and assisted in experiments as summer research interns. CMS assisted in performing experiments. JAM designed the project with DWP, performed data analysis, and wrote the manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>This work was funded by NIH R01 GM066901 (JAM). Core facility support was provided by P20 RR15583. Stipend support was provided by the American Cancer Society (DZC), and donations from James Wylder, W. Peter Horst, and Howard Bethel (PRW and EJA). We thank Deb Cabin, George Carlson, John Bermingham, Richard Bennett, and Mike Ehlers for critical reviews of the manuscript.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Model and normal distributions of myosin-Vb and transferrin</bold>. <bold>(A) </bold>Peripheral endosomes are retained in the periphery by multiple myosin-Vb motors whose heads periodically detach from actin as they go through the ATPase cycle, but usually reattaching. <bold>(B) </bold>Dynein (or a minus-end-directed kinesin) attaches to a microtubule and exerts retrograde force. Occasionally, adjacent myosin-Vb detaches from actin (dotted circle), allowing dynein to pull it away from the actin filament. <bold>(C) </bold>Following fission, the daughter vesicle moves retrogradely, carrying myosin-Vb as a passenger. <bold>(D, E, F) </bold>In HeLa cells expressing low levels of eGFP-myosin-Vb, colocalization between myosin-Vb (green) and transferrin (red) is rare (arrow) and transient (also see Additional file ##SUPPL##0##1##).</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Overexpression of full-length, wild-type eGFP-myosin-Vb causes coalescence of peripheral endocytic compartments and inhibits perinuclear accumulation of transferrin</bold>. HeLa cells were transiently transfected with full-length, wild-type myosin-Vb tagged with eGFP and imaged 24 h after transfection. <bold>(A) </bold>Diagram depicting predicted results. <bold>(B, C) </bold>Colocalization of actin on enlarged compartments (arrows) with eGFP-myosin-Vb. <bold>(D, E, F) </bold>In cells expressing high levels of eGFP-myosin-Vb coincident with exposure to transferrin (arrows), large, peripheral organelles decorated with myosin-Vb also contain transferrin. <bold>(G, H, I, J, K, L) </bold>In cells exposed to a 1-min pulse of transferrin 24 h after transfection and 10 min before imaging, transfected cells (arrows) contain large, peripheral organelles decorated with myosin-Vb that lack transferrin. Cells expressing lower levels of myosin-Vb (arrowheads, panel K; too low to be seen in panel J) accumulate less transferrin than the surrounding untransfected cells (arrowheads). Bar, 15 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Inhibition of myosin-Vb after loading with transferrin does not prevent transit from perinuclear recycling endosomes</bold>. HeLa cells transiently expressing sensitized myosin-Vb were loaded with Alexa 546-transferrin, washed, incubated in growth medium for 30 min, and imaged for myosin-Vb and transferrin. <bold>(A) </bold>Diagram depicting predicted results; the sensitized mutant myosin-Vb is shown in red and PE-ADP is shown as a green circle. <bold>(B) </bold>Inhibition of accumulation of transferrin (red) added after myosin-Vb inhibition by microinjection of PE-ADP². Injected cells have blue nuclei. <bold>(C, D, E, F, G, H) </bold>The cell expressing sensitized myosin-Vb (center, panel C) was immediately injected with PE-ADP and the same field was imaged 30 min later (F, G, H). Panels C and D are overlaid in panel E, and panels F and G are overlaid in panel H. Bar, 15 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Chemical-genetic inhibition of myosin-Vb halts myosin-Vb-decorated particles, including those being transported via microtubules</bold>. <bold>(A) </bold>Representative image of two HeLa cells expressing sensitized Y119G mutant eGFP-myosin-Vb before injection of the upper cell with PE-ADP. Bar, 15 μm. <bold>(B and C) </bold>Kymographs from the cells shown in panel A (y axes represent lines wx and yz from panel A). <bold>(D and E) </bold>Kymographs from additional negative control cells expressing wild-type myosin-Vb injected with PE-ADP and wild-type myosin-Vb injected with dextran respectively. <bold>(F and G) </bold>Histograms of instantaneous speeds of myosin-Vb-labeled vesicles before (black bars) and after (white bars) PE-ADP injection in cells expressing wild-type and Y119G mutant eGFP-myosin-Vb respectively; Speeds were measured for 1178 (before injection) and 621 particles (after) for panel F, and 717 and 551 respectively for panel G. <bold>(H) </bold>Instantaneous speeds of wild-type eGFP-myosin-Vb-labeled vesicles before (black bars) and after (white bars) depolymerization of actin by latrunculin A; the Y119G mutant gave indistinguishable results (data not shown). Speeds were measured for 707 (before) and 206 (after) particles. <bold>(I and J) </bold>Diagrams depicting additions to the dynamic tethering hypothesis to accommodate these data. Kinesin is represented with the letter \"k\" for the head domain.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>eGFP-myosin-Vb tail overexpression displaces EEA1 and Rab11a to more perinuclear positions</bold>. HeLa cells were transfected with the eGFP-myosin-Vb tail construct and allowed to express overnight. <bold>(A) </bold>Diagram depicting displacement of peripheral endosomes. <bold>(B) </bold>Immunofluorescent detection of EEA1. (<bold>E, F, G) </bold>Cotransfection with the mRFP-Rab11a construct. <bold>(H, I, J) </bold>Cells cotransfected with the mRFP-Rab8a construct. <bold>(C, F, I) </bold>eGFP-myosin-Vb tail. <bold>(D, G, J) </bold>overlays of B+C, E+F, and H+I respectively; arrows, cells expressing the myosin-Vb tail fragment; arrowheads, control cells not expressing the tail. Bar, 15 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>(A-H) Overexpression of eGFP-myosin-Vb tail causes a slight shift in Rab4 distribution, but has little effect on Rab5 distribution</bold>. HeLa cells were transiently transfected with eGFP-myosin-Vb tail fragment <bold>(B,C,D,F,G,H) </bold>and mRFP-Rab4 <bold>(A,B,C,D) </bold>or mRFP-Rab5 <bold>(E,F,G,H) </bold>and imaged after overnight incubation. Bar, 15 μm.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Low-level expression of full-length eGFP-myosin-Vb (green) shows rare, dynamic colocalization (circles) of myosin-Vb and transferrin (red); same cell as shown in Figure ##FIG##0##1D–F##. Frame acquisition rate, 0.5/sec; elapsed seconds are displayed at lower right.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Overexpression of full-length eGFP-myosin-Vb (green) in the presence of transferrin (red; added at the time of transfection) produces enlarged, less-motile peripheral endosomes decorated with myosin-Vb and containing transferrin at 24 h post transfection; same cells as shown in Figure ##FIG##1##2D–F##. Frame acquisition rate, 0.5/sec; elapsed seconds are displayed at lower right.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Overexpression of full-length eGFP-myosin-Vb produces enlarged, less-motile peripheral endosomes decorated with myosin-Vb; same field as shown in Figure ##FIG##1##2J–L##. Frame acquisition rate, 0.5/sec; frame display rate, 3/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>Overexpression of full-length eGFP-myosin-Vb (not shown) prevents entry of Alexa 546-labeled transferrin (shown) into perinuclear compartments; same field as Additional file ##SUPPL##2##3##. Frame acquisition rate, 0.5/sec; frame display rate, 3/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>Overlay of Additional file ##SUPPL##2##3## (myosin-Vb, green) and Additional file ##SUPPL##3##4## (transferrin, red).</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p>Rab11a (red) colocalizes with eGFP-myosin-Vb (green) at high myosin-Vb expression levels. Frame acquisition rate, 0.5/sec; frame display rate, 6/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S7\"><caption><title>Additional file 7</title><p>Rab4 (red) does not colocalize with eGFP-myosin-Vb (green) at high myosin-Vb expression levels. Frame acquisition rate, 0.5/sec; frame display rate, 6/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S8\"><caption><title>Additional file 8</title><p>Rab5 (red) does not colocalize with eGFP-myosin-Vb (green) at high myosin-Vb expression levels. Frame acquisition rate, 0.5/sec; frame display rate, 6/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S9\"><caption><title>Additional file 9</title><p>Chemical-genetic inhibition of sensitized mutant (Y119G) eGFP-myosin-Vb by PE-ADP microinjection does not prevent movement of transferrin-positive particles. Cells were loaded with fluorescent transferrin (red) 30 min before myosin-Vb was inhibited in the center cell by PE-ADP. Frame acquisition rate, 1/sec; frame display rate, 3/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S10\"><caption><title>Additional file 10</title><p>Chemical-genetic inhibition of sensitized mutant (Y119G) eGFP-myosin-Vb by PE-ADP microinjection (cell on left) halts movement of all myosin-Vb-decorated particles, including those being transported via microtubules; same field as Figure ##FIG##2##3A##. Uninjected control cell is on the right. Frame acquisition rate, 1/sec; frame display rate, 10/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S11\"><caption><title>Additional file 11</title><p>Same conditions as Additional file ##SUPPL##9##10## without a control uninjected cell. Frame acquisition rate, 1/sec; frame display rate, 10/sec.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S12\"><caption><title>Additional file 12</title><p>Negative control cell expressing wild-type eGFP-myosin-Vb; PE-ADP injection (immediately before imaging) does not halt movement of myosin-Vb-decorated particles. Frame acquisition rate, 1/sec; frame display rate, 10/sec.</p></caption></supplementary-material>" ]

[]

[ "<graphic xlink:href=\"1471-2121-9-44-1\"/>", "<graphic xlink:href=\"1471-2121-9-44-2\"/>", "<graphic xlink:href=\"1471-2121-9-44-3\"/>", "<graphic xlink:href=\"1471-2121-9-44-4\"/>", "<graphic xlink:href=\"1471-2121-9-44-5\"/>", "<graphic xlink:href=\"1471-2121-9-44-6\"/>" ]

[ "<media xlink:href=\"1471-2121-9-44-S1.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S2.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S3.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S4.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S5.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S6.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S7.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S8.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S9.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S10.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S11.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2121-9-44-S12.mov\" mimetype=\"video\" mime-subtype=\"quicktime\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>1. INTRODUCTION</title>", "<p>It is a remarkable\nepidemiological observation that whilst ulcerative colitis (UC) is related to\nnonsmoking [##UREF##0##1##–##REF##2598752##4##], the opposite\napplies to Crohn's disease (CD).<italic/>\nPatients with CD are more often smokers compared with the general\npopulation [##REF##6435736##5##], and smoking has an adverse effect on the course of their\ndisease [##REF##2323505##6##]. Several mechanisms for this could be relevant; components of\ntobacco smoke, such as oxidizing chemicals, which, unlike nicotine, have\nprothrombotic effects, could exacerbate microvasculature abnormalities and\nischaemia of the bowel wall [##UREF##1##7##]. It has also been suggested that CD could be\ncaused by an impaired host response to luminal bacteria; this, in turn, could\nbe exacerbated by the immunosuppressive effects of smoking on macrophages [##REF##11385576##8##, ##UREF##2##9##].\nIt is likely that different mechanisms are responsible for the “opposite effects” of smoking in CD and\nUC, which are in many other respects similar diseases. The effects of <italic>smoking</italic> should not be considered synonymous with <italic>nicotine</italic>. Nicotine, as opposed to smoking, may have a beneficial effect in patients\nwith Crohn's colitis, given that there is a considerable overlap in the\ntreatments for the two conditions and nicotine has been shown to be of benefit\nin UC. Although the specific mechanisms\nunderlying this effect remain unclear, nicotine has a number of actions that\ncould be potentially beneficial, including effects on the immune system [##UREF##3##10##]\nand gut motility [##REF##10563544##11##].</p>", "<p>A recent Cochrane\nReview [##UREF##4##12##] has confirmed benefit from transdermal nicotine in active UC: a\nmeta-analysis of two eligible randomized placebo-controlled trials [##REF##8114833##13##, ##REF##9054280##14##] so\nfar performed showed that after 4 to 6 weeks treatment, 19 of 71 patients\ntreated with transdermal nicotine were in remission compared to 9 of 70 given\nplacebo (odds ratio 2.56, 95% confidence interval 1.02–6.45). A nicotine enema has also been developed and\nfound to be of benefit when given as additional therapy in two uncontrolled\npilot studies in active distal UC [##REF##9354193##15##, ##REF##9305473##16##], but not in a recent randomised\ncontrolled trial [##REF##16271342##17##]. A phase I-II\ntrial of delayed release oral nicotine has shown promise [##REF##16306772##18##] but a controlled\ntrial is awaited.</p>", "<p>The aim of this open pilot study was to examine the efficacy and safety of nicotine enemas in active distal Crohn's colitis.</p>" ]

[ "<title>2. MATERIALS AND METHODS</title>", "<title>2.1. Patients</title>", "<p>Patients with CD, based on the clinical, endoscopic, and histological features of Lennard-Jones' criteria [##UREF##5##19##], were recruited from the gastroenterology outpatient department\nof a single centre; the key selection criteria were clinical and sigmoidoscopic evidence of active disease in the rectosigmoid region. Although the presence of CD in other regions\nof the gastrointestinal tract was permitted, the patient's principal clinical problem had to relate to active distal colitis.<italic/>\nPatients were not enrolled if they were current smokers, had other\nunstable medical problems, were pregnant or lactating, had used enemas in the previous week, had changed their CD therapy with mesalazine, steroids, or antibiotics within the last 2 weeks, or had changed immunosuppressive therapy with azathioprine in the previous 3 months.<italic/>\nThe dosage of all concomitant medications was kept unchanged during the study period.</p>", "<title>2.2. Study design</title>", "<p>This was an open pilot study of 4 weeks' duration in which nicotine enemas were given as additional therapy—subjects\ncontinued their conventional treatment without change during the study\nperiod. Each 100 mL liquid enema\ncontained 6 mg of nicotine complexed with 400 mg of the high molecular weight polyacrylic acid carbomer, Carbopol 974P (Goodrich, UK), as already described [##REF##9759592##20##]. At the time of enrolment, a record was made\nof the patient's symptoms of colitis including stool frequency, abdominal pain,\ngeneral well being, any complications of CD and urgency of defaecation; the\nlatter was graded as none, mild, moderate, or severe enough to cause\nincontinence. Although Crohn's colitis\nmay be patchy, sigmoidoscopy with a biopsy of the most inflamed area was also performed by the same investigator in each case.<italic/>Patients were also asked to complete an inflammatory bowel disease quality of life questionnaire (SIBDQ) [##REF##8759664##21##] and blood\ntests were taken for a full blood count, liver and renal function, and\ninflammatory markers.</p>", "<p>During the study, patients kept a diary of their bowel symptoms and any adverse events (AEs). The\npatients were assessed at the end of the 4-week trial period, or at premature withdrawal, or at any other time at the patient's request. The initial assessments were repeated by the\nsame physician. Sigmoidoscopy with a\nbiopsy, again from the most inflamed area, was repeated.</p>", "<title>2.3. Outcome measures</title>", "<p>The main outcome measures used were clinical improvement as measured by Crohn's disease activity index (CDAI) [##REF##1248701##22##], and changes in bowel frequency and urgency of defaecation. Urgency was included because it is a useful\nguide to the severity of inflammation in distal colitis. At sigmoidoscopy, the severity of\ninflammation of the worst affected area was graded visually according to the system described by Dick et al.\n[##REF##14218553##23##]. The biopsy specimens were stained\nwith haematoxylin and eosin and graded by one histopathologist (GTW) according\nto the Truelove and Richards system [##REF##13316140##24##] adapted for Crohn's colitis; see ##TAB##0##Table 1##.</p>", "<title>2.4. Ethical considerations</title>", "<p>This study was\napproved by the Bro Taf Local Research Ethics Committee.</p>" ]

[ "<title>3. RESULTS</title>", "<p>Of the 13 patients recruited, 3 were excluded because they were also given antibiotics for a chest\ninfection, a middle ear infection, and recurrence of a finger infection during the study period. Demographic details of\nthe remaining 10 patients are in ##TAB##1##Table 2##; 7 were male and the mean age was 52\nyears. Seven patients were exsmokers whilst the remainder had never smoked.<italic/>The mean duration of disease relapse was 45 weeks and in 4 patients was greater than 99 weeks. Half of the\npatients were on concomitant oral 5-ASAs, 2 were on prednisolone (10 mg) and 2 were on azathioprine; several patients had been intolerant of thiopurines. Only one patient had recently taken enemas,\nasacol foam. The mean baseline CDAI\nscore was 202 (SD 80, range 73 to 348).<italic/>\nIn addition to their colonic involvement, one patient also had small\nbowel CD. Three patients had disease\nlimited to the left side of the colon.</p>", "<title>3.1. Efficacy</title>", "<p>Patient 10 withdrew from the study after only 2 weeks due to failure to respond to treatment, but was kept in the intention-to-treat analysis; she had the highest CDAI score (348) at baseline; all other patients completed 4 weeks' treatment. Changes in the main outcome\nmeasures for each patient are in ##FIG##0##Figure 1##.<italic/>\nThe mean CDAI score decreased from 202 to 153—the score was\nreduced in 6 patients, unchanged in 3, and increased in one patient. The frequency of bowel movements each day was\nreduced in 8 patients and unchanged in 2, and the urgency to defaecate was reduced in 7 patients, in one case from severe to nil, and was unchanged in the other 3. The sigmoidoscopy score improved in 7 patients and was unchanged in 3, but changes in histology showed no clear trend with a wide variation in the baseline scores.<italic/>One of the two patients taking oral steroids improved sufficiently to consider a gradual reduction of the dose\nafter the study.</p>", "<p>The mean SIBDQ score increased from 39 to 47.<italic/>Mean\nlevels of the inflammatory markers C-reactive protein (CRP), erythrocyte sedimentation\nrate (ESR), and fibrinogen all fell from 22.0 mg/L, 19.1 mm/h, and 4.4 g/L,\nrespectively, to 12.3 mg/L, 12.5 mm/h, and 4.0 g/L, respectively, whilst the mean white cell count was unchanged at 8.4 × 10⁹/L and the mean\nplatelet count increased slightly from 310 to 320 × 10⁹/L.<italic/> Renal function and liver function tests were unaffected.</p>", "<p>The effect of disease location on outcome was briefly considered. The only patient with ileal disease improved\nduring the study, with a CDAI reduction from 150 to 74. Of the 3 patients with disease restricted to the left colon, one improved, one remained the same, and the other deteriorated;\nthe respective changes in CDAI score were from 144 to 67, from 348 to 345, and from 156 to 189. <italic/>In terms of the\nduration of disease relapse, of the 4 patients who had been in relapse for more than 99 weeks, 3 improved, with CDAI changes from 272 to 169, from 200 to 64, and from 150 to 74, whilst one remained the same, with a CDAI change from 73 to 71.</p>", "<title>3.2. Safety</title>", "<p>Eight of the 10 patients experienced an adverse event but none were classified as serious.<italic/>In total, 12 AEs were reported (##FIG##1##Figure 2##) and 11 of these were thought to be related to nicotine, the other being a localised\nskin rash that resolved spontaneously.<italic/>Two-thirds of the AEs occurred on commencement of treatment and were\ntemporary, lasting 2 days or less.<italic/>The\nmost common AE was difficulty sleeping, which included vivid dreams, reported by 4 patients. The other AEs were lightheadedness, nausea, and headache.</p>" ]

[ "<title>4. DISCUSSION</title>", "<p>These are the first observations of topical nicotine in patients with active Crohn's colitis. In the 10 patients, there was a\nCDAI reduction in 6 and an increase in one; the mean score decreased from 202 to 153. Frequency of bowel movements was\nreduced in 8 patients, urgency to defaecate was reduced in 7, and the\nsigmoidoscopy score improved in 7; the mean SIBDQ score increased from 39 to 47. Clinical improvement was noted in\npatients who also had disease in locations other than the rectosigmoid,\nincluding the one patient with small bowel disease.<italic/>Three of the 4 patients with chronically active disease for more than 99 weeks improved. There were no serious AEs and no premature withdrawals due to\nintolerance.</p>", "<p>A relatively small open pilot study of this nature can only provide preliminary data on efficacy and safety. Hence, although our\nobservations suggested improvement in most of the patients, and certainly no overall deterioration, the findings will need to be corroborated by larger randomised controlled studies. Formal\ntests of significance were not performed because, in this relatively small study, they may have been misleading.<italic/>\nInitially, it was planned to recruit 20 patients to the study, but\nrecruitment was slow for two main reasons; 10 patients with active Crohn's colitis, who were identified as suitable for entry to the study, were current smokers and therefore excluded. In\naddition, because the study preparation was an enema, those patients whose principal symptoms were related to left-sided active colitis were\ntargeted. However, identifying such a\nhomogenous group proved hard, as a number of patients screened had to be\nexcluded because they had symptoms that related primarily to other sites of disease involvement. This may have\nreduced potential sources of error from our study, but it will probably make it difficult to recruit sufficient numbers to achieve a larger study of homogeneous patients, as defined by the Vienna\nclassification [##REF##10701144##25##]. For this small\npilot study, full Vienna classification of patients was not performed and subgroup analyses were avoided.</p>", "<p>It is noteworthy that methods used to assess the response of Crohn's colitis to treatment have some limitations. The patchy nature of\nCrohn's colitis means sigmoidoscopy and histology findings should be\ninterpreted with caution. The separate\nrecording and analysis of stool frequency and urgency of defaecation was an attempt to assess some of the more troublesome symptoms of distal colitis, although a contribution from more proximal disease cannot be excluded. This was used in addition to the global\nassessment provided by the CDAI, the more conventional composite scoring system of disease activity that contains systemic features less relevant to this study. Two of the 10 patients had a CDAI\nscore less than 150 at study entry, which might imply disease remission;\nhowever, all patients had rectosigmoid inflammation on sigmoidoscopy and had\nsymptoms of active distal disease.</p>", "<p>The negative\nassociation between smoking and CD raises questions about whether topical\nnicotine is an appropriate treatment for patients with Crohn's colitis. However, this was justified on the basis that\nthe treatments for UC and CD are very similar, and transdermal nicotine has\nbeen found to provide benefit in UC. It\nis possible that the detrimental effect of smoking on CD is mediated through\nmechanisms independent of nicotine; these could, for example, include\nexacerbation of underlying ischaemia of the bowel wall at the microvascular\nlevel [##UREF##1##7##] due to prothrombotic oxidizing chemicals present in tobacco\nsmoke. It has also been suggested that\nCD could be caused by an impaired host response to luminal bacteria; this, in\nturn, could be exacerbated by the immunosuppressive effects of smoking on macrophages [##REF##11385576##8##, ##UREF##2##9##]. These effects could\nmask any benefit from nicotine in Crohn's colitis. It is also possible that the response to\nnicotine differs between ileal and colonic diseases. Rectal enema treatment of the transmural\ninflammation of Crohn's colitis is not well described in the literature,\nhowever it is used in clinical practice.</p>", "<p>Possible\nmechanisms for a therapeutic effect of topical nicotine in distal colitis\ninclude alterations in colonic motility.<italic/>\nNicotine has been shown to reduce tone and muscular activity in the\nsigmoid colon [##REF##10563544##11##], an effect mediated primarily through nitric oxide that is\nreleased by nicotine [##REF##11069313##26##]. Another\npotential mechanism is via a reduction in mucosal tumour necrosis factor\n(TNF<italic>α</italic>), a key cytokine in the generation of inflammation in CD [##REF##2117510##27##]. Nicotine has been found to reduce the secretion of TNF<italic>α</italic> from macrophages, by activation of <italic>α</italic>7 nicotinic acetylcholine receptors [##REF##12508119##28##].</p>", "<p>Our pilot study has shown that, in the 10 patients with active Crohn's colitis, 6 mg nicotine\nenemas were associated with clinical improvement in the majority of patients,\nthey were safe and well tolerated, and did not appear to worsen the\ncondition. Larger randomised controlled\ntrials are needed to confirm these observations and longer-term outcome data\nwould also be of interest.</p>" ]

[]

[ "<p>Recommended by Julian Walters</p>", "<p>\n<italic>Background</italic>. Smoking has a detrimental effect in Crohn's disease (CD), but this may be due to factors in smoking other than nicotine. Given that transdermal nicotine benefits ulcerative colitis (UC), and there is a considerable overlap in the treatment of UC and CD, the possible beneficial effect of nicotine has been examined in patients with Crohn's colitis. <italic>Aims</italic>. To assess the efficacy and safety of nicotine enemas in active Crohn's colitis. <italic>Patients</italic>. Thirteen patients with active rectosigmoid CD; 3 patients were excluded because they received antibiotics.\n<italic>Methods</italic>. Subjects were given 6 mg nicotine enemas, each day for 4 weeks, in an open pilot study. At the beginning and end of the trial, a Crohn's disease activity index (CDAI) score was calculated, sigmoidoscopy was performed, and haematological inflammatory markers measured. \n<italic>Results</italic>. Mean CDAI decreased from 202 to 153—the score was reduced in 6 patients, unchanged in 3, and increased in one. Frequency of bowel movements decreased in 8 patients and the sigmoidoscopy grade was reduced in 7. Mean C-reactive protein decreased from 22.0 to 12.3 mg/L. There were no withdrawals due to adverse events. \n<italic>Conclusions</italic>. In this relatively small study of patients with active Crohn's colitis, 6 mg nicotine enemas appeared to be of clinical benefit in most patients. They were well tolerated and safe.</p>" ]

[]

[ "<title>ACKNOWLEDGMENTS</title>", "<p>J. R. Ingram was supported by the Gastrointestinal Foundation Trust. SLA Pharma gave financial support to the project. The authors are indebted to Dr. J. T. Green (of Cardiff and Vale Hospitals Trust) who referred patients, and to Professor G. T. Williams (GTW) who performed all histological assessments.</p>" ]

[ "<fig id=\"fig1\" position=\"float\"><label>Figure 1</label><caption><p>\n<italic>Outcome measures.</italic> Response of 10 patients\nwith active Crohn's colitis given 6 mg nicotine enemas daily for 4 weeks. Where 2 or 3 patients had the same baseline\nand end values, this is indicated above the connecting line, which is drawn more boldly. CDAI is Crohn's disease\nactivity index. Frequency is the number\nof stools/24 hours. Urgency of\ndefaecation is graded: 0 = none, 1 = mild, 2 = moderate, and 3 = severe enough to cause incontinence. Sigmoidoscopic\nscore is graded 0, normal to 4, fulminant disease. Histological scores are based on acute\ninflammatory activity: grade 0, no polymorphs to grade 4, florid acute\ninflammation with polymorphs and ulceration.<italic/>\nHistology data is given for only 8 patients because the end-of-study\nbiopsies of 2, both with baseline scores of 2, were insufficient for\nanalysis.<italic/>QOL is a score of quality of\nlife as measured by the short inflammatory bowel disease questionnaire [##REF##8759664##21##].<italic/>Paired data were available for CRP in 7 patients and for ESR in 8 patients.</p></caption></fig>", "<fig id=\"fig2\" position=\"float\"><label>Figure 2</label><caption><p>\n<italic>\nAdverse events during study.</italic> Adverse events \nexperienced during nicotine enema treatment with the number of patients\naffected in each case.<italic/>“Sleep prob” refers to disturbed sleep or vivid dreams.<italic/>The “rash” was a 2 cm diameter erythematous maculopapular lesion on the forearm of a patient which resolved spontaneously.</p></caption></fig>" ]

[ "<table-wrap id=\"tab1\" position=\"float\"><label>Table 1</label><caption><p>\n<italic>Histological grade of inflammation.</italic> The histological grade of inflammation present in biopsies taken\nfrom the most inflamed area of the rectosigmoid region at sigmoidoscopy,\nadapted by GTW for Crohn's\ncolitis from the system described by Truelove and Richards [##REF##13316140##24##] for ulcerative\ncolitis.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">Grade of inflammation</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Description</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">No polymorphs</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Small number of\npolymorphs in the lamina propria with minimal cryptitis</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Focal cryptitis\nwith crypt rupture or affecting groups of two or more adjacent crypts</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Florid diffuse\npolymorph infiltrate with crypt abscesses</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Florid acute\ninflammation with ulceration</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"tab2\" position=\"float\"><label>Table 2</label><caption><p>\n<italic>Baseline characteristics of 10 patients with Crohn's colitis.</italic> Extent of disease: 1 = proctitis, 2 = sigmoid colon, 3 = descending\ncolon, 4 = transverse colon, 5 = ascending colon, 6 = pancolitis, 7 = ileal, 8\n= perianal. “Recent enemas” refers to\nany steroid or 5 aminosalicylate (5-ASA) enemas taken from 1 to 3 weeks before\nentry into the study. All concomitant\nmedication doses given are the daily amounts, the only oral steroid taken was\nprednisolone, aza = azathioprine. CDAI =\nCrohn's disease activity index.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\"> No.</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Age (years)</th><th align=\"center\" rowspan=\"1\" colspan=\"1\"> Sex</th><th align=\"center\" rowspan=\"1\" colspan=\"1\"> Exsmoker</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Disease extent</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Duration relapse (weeks)</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Recent enemas</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> 5-ASA (g)</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Oral steroids (mg)</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Aza (mg)</th><th align=\"left\" rowspan=\"1\" colspan=\"1\"> Baseline CDAI score</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">41</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1,2,3,4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">156</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">F</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6,7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">150</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2,5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">150</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">246</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">73</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">200</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">38</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6,8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">167</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">59</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">F</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2,3,4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">&gt;99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">272</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">79</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3,4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">30</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">259</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">144</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">62</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">F</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">+</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2,3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">foam</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">348</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"GRP2008-237185.001\"/>", "<graphic xlink:href=\"GRP2008-237185.002\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[]

[]

[]

[]

[ "<p>Recommended by John Plevris</p>", "<p>There is an obvious, significant, and diachronic reduction of <italic>the\nprevalence of HBV infection</italic> in Greece, concerning the general population as\nwell as some traditionally high-risk groups, mainly as a result of constant\ninforming and the widespread initiation of preventive and prophylactic\nmeasures, as well as the improvement of health care services. Nevertheless,\nthere are special groups and populations (economical refugees, religious\nminorities, HIV-positive patients, abroad pregnant women, prostitutes, etc.) who\nrepresent sacs of high HBV endemicity and need epidemiological supervision and intervention, in order to limit the spread of the infection and to further\nimprove the existing epidemiological data.</p>" ]

[ "<p>Hepatitis B virus (HBV) infection is a major public\nhealth problem worldwide, as more than 2 billion people have been infected,\nwhereas more than 350 million present chronic HBV infection. It is estimated\nthat a significant proportion (15–40%) of chronic HBV infected patients develop\nliver cirrhosis, liver failure, and primary hepatocellular carcinoma (HCC),\nmaking chronic hepatitis B one of the 10 major causes of death worldwide [##REF##12037146##1##].</p>", "<p>The prevalence of the infection varies\namong different areas of the world and among special populations within the\nsame area. About 45% of the world population lives in countries in which HBV\ninfection is hyperendemic (South-Eastern Asia and sub-Saharan Africa),\nwhere the percentage of hepatitis B surface antigen (HBsAg) seropositivity <italic>outranges</italic> 8% of the total\npopulation and the percentage of viral exposure <italic>varies</italic> between 70% and 90%. In these countries, HBV infection\nis vertically transmitted usually during the perinatal period and horizontally\nduring the infancy and early childhood age, leading to extremely high rates of\nchronic HBV infection and preserving the reservoir of chronic hepatitis B\npatients worldwide [##REF##8786047##2##, ##REF##10921373##3##]. Southern countries of\nCentral and Eastern Europe <italic>as well as those of the Mediterranean basin, the Amazon’s sink, Middle East, and Northern\nAfrica</italic> are regions of medium HBV infection\nseroprevalence (HBsAg seropositivity between 2–7%), whereas\ncountries of North-Western Europe and North America are considered to be countries\nwith low HBV endemicity (HBsAg seropositivity &lt;2%). In\nthese countries, the infection is basically transmitted horizontally during the\nadolescent and early adult period, mainly by high-risk sexual activity [##UREF##0##4##].</p>", "<p>Moreover, the annual incidence of HCC is extremely\nhigh in hyperendemic regions of HBV infection (10–150 cases/100.000 people per year) <italic>compared</italic> to regions of lower\nprevalence (1–3 cases of HCC/100.000 people per year), a finding that\nsupports the causative relationship of HBV and HCC. The primary HCC is one of\nthe most common tumours (5th in frequency\nworldwide) and is <italic>considered</italic> responsible for 300 000–500 000\ndeaths annually, representing the 3rd most common cause of death in the\nhyperendemic countries of HBV infection [##REF##14996343##5##].</p>", "<p>Patients with chronic hepatitis B have a threefold\nprobability to die within a decade compared to general population, mainly by\ncauses directly related to chronic liver disease (HCC, hepatocellular failure,\nvariceal bleeding, etc.) [##REF##11772975##6##]. Regarding\nthe cost of patients’ hospitalization, it seems that patients with chronic HBV\ninfection spend more time in the hospital and need more specialized and\nexpensive in-hospital treatment compared to the general population. An\nepidemiological and economotechnical study from a set area of Scotland showed a\nsignificant difference in the duration of hospitalization and the mean cost of\ntreatment, as well as in the number of admissions and readmissions of patients\nwith chronic HBV infection, compared to the control group [##REF##11772975##6##]. The annual cost of\ntreating patients with chronic HBV infection has been retrospectively estimated\nand seems to significantly differentiate between patients in procirrhotic or\ncompensated cirrhotic stages of the disease under treatment and those who\nexhibit decompensated cirrhosis, especially when they undergo liver\ntransplantation procedure. Even the palliative treatment of end-stage HCC costs\nhigher than long-term treatment of early stages of the disease [##REF##15602169##7##].</p>", "<p>A significant decline of the incidence of acute hepatitis\nB cases (67%) has been observed in the USA\nafter 1990, especially among\nhigh-risk groups (such as intravenous drug users, homosexual men, and health\ncare professionals), according to Center of Diseases Control (CDC). Widespread\nvaccination programs, predelivery evaluation of pregnant women and\npassive-active immunoprophylaxis of infants born from chronic HBV infected\nmothers, blood donors control, and immunization of the majority of health care\nprofessionals, children and teenagers have resulted in that decline.\nConsidering the lack of those preventive and precaution measures in many\nhyperendemic countries of the world and the massive immigration observed in the\nlast fifteen years, mainly from countries of median or high prevalence of the\ninfection to countries of low HBV prevalence, the epidemiological data of HBV\ninfection <italic>seem</italic> to be\nsignificantly modified nowadays.</p>", "<p>In Greece,\nthe existing published epidemiological data are difficult to be representative\nto the general population data, mainly because they are referred to specific\npopulations (blood donors, religious-ethnic minorities, economic immigrants,\nsoldiers, children, pregnant women) or high-risk groups (prisoners, drug users,\nhaemodialysis patients, HIV, prostitutes, etc.) over- or underestimating the\nproblem. The National Institute of Employment and the National Statistical\nService reported that the number of recorded foreign immigrants in Greece at the inventory of 2001 was\napproximately 800 000\n(7.2% of recorded Greek population) and the majority of them (65%) <italic>came</italic> from Albania, a country of high\nendemicity of HBV infection.</p>", "<p>In general, the comparison of studies from the early\n70s with others from the late 80s shows a significant decline of HBV prevalence\nin Greece\nof about 50–80%. Studies on military recruits exhibit a significant decline of\nHBsAg prevalence, from 4% in 1973 to 0.95% in 1999, mainly due to the\nmodification of socioeconomical and medical practice parameters and to the\nsignificant increase of successfully vaccinated people [##REF##9915034##8##, ##REF##10442470##9##]. General population published data\nare limited in Greece\nwhereas the best-studied group is that of blood donors. In the larger cohort of\nblood donors studied for 6 consecutive years in Athens, the mean prevalence of HBsAg was\n0.84% [##REF##10972911##10##]. A study\nof a large population of blood donors in Crete island for 5 consecutive years revealed that the mean prevalence of HBsAg\n(0.4%) was significantly lower than <italic>the\none</italic> reported from other compartments of our country [##REF##10607237##11##]. Equally, low\npercentages of HBsAg prevalence were observed in children of school age and\nteenagers of a rural population of Crete (0.33%) and in high-risk hospitalized\npatients (2.66%), reflecting partially the epidemiological data of the general\npopulation of the island [##REF##9258547##12##, ##REF##11208260##13##]. A significant decline of HBsAg prevalence by 2.15% and of the\npercentage of HBV exposure by 22.6% are reported in the first published study\nconcerning the general population, in the region of South-Western Greece,\nwhereas in the region of Epirus in a 3-year prospective study of blood donors,\nthe HBsAg seropositivity <italic>was</italic> of 0.85%, relatively higher than <italic>the\none</italic> reported from other compartments of Greece [##REF##12908721##14##, ##REF##11346702##15##].</p>", "<p>The immigration of populations from countries of high\nendemicity of the infection seems to contribute significantly to the rapid\nmodification of epidemiological data, especially in areas bearing the high\nburden of immigrants. In a serological control of 1020 refugees from South Albania who came and work in Ioannina region, the percentages of HBsAg\nseropositivity and HBV exposure were 22.2% and 70.6%, respectively. Moreover, a\nsignificant proportion of chronic HBV infected Albanian patients were also hepatitis\nB e antigen-positive [HBeAg(+)] (21.1%) and 12.7% of them were chronic hepatitis\nD virus (HDV) infected, representing a<italic/>\npopulation of high infectivity regarding viral hepatitis [##REF##7552639##16##]. Data regarding\nimmigrants living in Athens\nshowed that the prevalence of HBsAg was <italic>significantly</italic> high (15.4%) especially among Albanian and Asian\nrefugees [##REF##12717844##17##].\nLikewise, significant differences of the prevalence of HBV infection are\nreported in the religious minority of Thrace moslems comparing to Greeks from formal Soviet Union who live in the same area\nand the native habitants of Thrace\n(9.3% versus 4.3% versus 3.4%, respectively), revealing a population of high\nendemicity of HBV infection within our country [##REF##11446899##18##].</p>", "<p>Perinatal (vertical) transmission is one of the most\ncommon ways of HBV infection dispersion, mainly in hyperendemic areas of the\nworld and seropositive pregnant women and their neonates represent the basic\ntarget groups for the elimination of vertical transmission, which preserves the\nmain reservoir of chronic HBV infected patients. In the larger group of women\nat reproductive age studied in Greece, the mean prevalence of HBsAg was 1.15%,\nbut was significantly higher among women of Albanian (5.1%) and Asian origin\n(4.2%) compared to Greek women (0.29%). The vast majority (71.34%) of\nHBsAg-positive women were of Albanian origin and about a third of them\nexhibited significant viral replication at perinatal period [##REF##15653423##19##].</p>", "<p>Intravenous drug users and prisoners are also\nhigh-risk groups for viral hepatitis who <italic>were studied</italic> epidemiologically in our country. In a study of\n544 prisoners who were intravenous drug users concomitantly, 6.5% of them\nexhibited HBsAg-positivity whereas among prisoners for sexual\noffences the percentage of HBsAg-positivity <italic>was</italic> higher enough (13%) [##REF##9624725##20##, ##REF##12825735##21##]. The widespread of HBV infection in the\nGreek drug-users community observed in the past decade, according to published\nstudies [##REF##3475213##22##] seems\nto be changed nowadays. In an our recently published study, we investigated the\npresence of serological markers of HBV infection in intravenous drug users\n(IVDU) with chronic hepatitis C virus (HCV) infection and the results were\ncorrelated to the time of drug usage initiation. We found that drug use\ninitiation before 1992 was significantly related to HBV exposure while the vast\nmajority of relatively newer drug users (drug initiation after 1992) were HBV\nseronegatives [##REF##16275544##23##].</p>", "<p>In Greek oncologic patients with solid tumors, the\npercentages of HBsAg-seropositivity were 5.3% and those of HBV\nexposure 44%, while a proportion of them (14%) had clinical and/or biochemical\nexacerbation of liver disease during the chemotherapy schedule; this percentage\nis expected to be much higher in patients with haematological malignancies,\nwith or without steroid administration according to the international\nliterature [##REF##10487614##24##].\nFurthermore, significantly higher prevalence of HBV infection is observed in\nchronic alcoholic patients—with or without\nestablished liver disease—compared to\nhealthy blood donors or nonalcoholic hospitalized patients, which is ascribed\nto their specific and some times unexpected behavior [##REF##8817173##25##].</p>", "<p>Chronic liver disease due to coexisting chronic viral\nhepatitis B and/or C as well as a consequence of hepatotoxicity of the\nantiretroviral therapy is one of the most important factors of morbidity and\nmortality of human immunodeficiency virus- (HIV-) infected patients, since the\nclassic opportunistic infections and the complications of severe\nimmunodeficiency have been significantly diminished. In HIV-seropositive\npatients the probability of chronic HBV infection and chronic liver disease\nafter exposure to HBV is extremely high and is characterized by very high\nlevels of viraemia (serum HBV-DNA) and extremely low percentages of spontaneous\nloss and/or seroconversion of HBeAg [##REF##14738553##26##]. About 13% of a group of HIV-positive patients, mainly\nhomosexual men (68.5%), were HBsAg-positive and the percentage of their\nexposure to HBV infection was 67.4%, representing a high-risk group for viral\nhepatitis [##REF##10841086##27##]. In\na cohort study in Greece, regarding 737 HIV-positive patients, the percentage\nof HBsAg-seropositivity was 12.1% while the majority of\nHIV/HBV coinfected patients (60.9%) were also HBeAg-positive and they exhibited\nextremely high levels of HBV viral load, suggesting the direct uptake of\npreventive measures for this high-risk group, in order to protect its health\nand the public health in general [##REF##15135750##28##].</p>", "<p>An obvious trend of reduction of the HBV prevalence is\nobserved in other traditionally high-risk groups, such as prostitutes, since\nthe percentage of HBsAg-seropositivity (11%) at the early 80s has been\nreduced to 3.3% in the late 90s; these data need to be reevaluated because of\nthe high percentage of people trafficking for sexual reasons, mainly from\ncountries of median-high HBV prevalence to our country, who are not reported or\nsanitary controlled and are thought to represent the most significant cause of\nHBV transmission<italic/> in our days [##REF##7358965##29##, ##UREF##1##30##]. Data from a\nstudy of the Department of Public Order were presented in daily press and\naccording to conservative calculations there are more than 14 000\npeople who are illegally sexually prostituted in our country.</p>", "<p>Finally, the professional exposure in the health care\nworker field has been studied since the 70s, where the percentages of HBsAg\nseroprevalence were 2.4% for medical students and 4.6% for nursing staff. In a\nrecent study from Hippokration Hospital of Athens including 400 nursing staff,\nthe percentage of HBsAg-seropositivity was 1.25% and the HBV exposure\nrate was 16%, but only 61% of that high-risk group were efficiently vaccinated,\nso there is a significant percent of population unprotected for various but \nnonaccepted reasons [##UREF##2##31##].</p>", "<p>In conclusion, although there is an obvious,\nsignificant, and diachronic reduction <italic>of the prevalence of HBV infection</italic> in Greece, concerning the\ngeneral population as well as some traditionally high-risk groups, mainly as a\nresult of constant informing and the widespread initiation of preventive and\nprophylactic measures as well as the improvement of health care services, there\nare special groups and populations (economical refugees, religious minorities,\nHIV-positive patients, abroad pregnant women, prostitutes, etc.) who represent\nsacs of high-HBV endemicity and need epidemiological supervision and\nintervention, in order to limit the spread of the infection and to further\nimprove the existing epidemiological data.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

[]

{ "acronym": [], "definition": [] }

[]

[]

[]

[]

[]

[]

[ "<p>Gastrointestinal disorders (especially diarrhea) are observed in a proportion of patients treated with the\ncurrently approved combination treatment for chronic hepatitis C (CHC), pegylated-interferon alpha (PEG-IFNa) plus ribavirin (RIB) [##REF##12324553##1##]. Several reports\nsuggest that the presence of inflammatory bowel disease (IBD) is not a\ncontraindication for interferon-alpha- (IFNa-) based treatments [##REF##7795286##2##, ##REF##16091058##3##].\nFurthermore, a randomised placebo-controlled trial of PEG-IFNa in patients with active ulcerative colitis\nconcluded that PEG-IFNa is safe but not effective treatment for these patients\n[##REF##14633951##4##]. On the contrary, several reports \n[##REF##7474487##5##, ##REF##11451187##6##, ##REF##16215439##7##, ##UREF##0##8##] revealed that\ntreatment of chronic viral hepatitis with IFNa or PEG-IFNa with or without RIB\nwas related with the onset of clinically and histologically confirmed acute\ncolitis of the IBD type. To our\nknowledge the effect of chronic hepatitis C virus (HCV) infection or PEG-IFNa\nplus RIB combination treatment on large intestine histopathology has not been\ninvestigated, within a clinical trial. The principal aim of our study was to investigate\nthe effect of PEG-IFNa plus RIB treatment on the large intestine histology of\ntreated CHC patients.</p>", "<p>Twenty-four treatment-naïve CHC patients with\nserologically (antiHCV-positive, Abbott Laboratories, Abbott Park, Ill, USA), virologically (serum HCV-RNA detection, Cobas Amplicor HCV test, version 2, Roche Diagnostics, Branchburg, NJ,\nUSA), and histologically (liver biopsy-Ishak scoring system) confirmed CHC and no contraindication of receiving\ncombination treatment with PEG-IFNα2b and RIB were enrolled in this pilot study. All patients were treated with weight-based dosing of pegylated\ninterferon-a2b (Peg-Intron, 1.5<italic>μ</italic>g/kg/week) and genotype-related ribavirin dose\n(Rebetol, 800 mg/day for genotype 2/3 and 1000–1200 mg/day for genotype\n1/4-infected patients, depending on baseline body weight &lt; or ≥ 85 kg,\nresp.) for 24 weeks. Patients were evaluated for the presence of gastrointestinal symptoms,\nby receiving a detailed history, before the beginning of treatment, during the\ntreatment period and at week 24 of treatment. The study population underwent\nrecto-sigmoidoscopic examination prior to the beginning of the treatment\nschedule. Three to five biopsy specimens were taken from the rectosigmoid area.</p>", "<p>Histological findings characteristic of inflammation as well as the presence of architectural disorders and the quantity of\nmucus production, the presence of ulcerations and Paneth cells as well as the\nnumbers of lymphoid follicles in every biopsy specimen were evaluated. Fifteen\npatients underwent the same procedure after the completion of 24-week treatment\ncourse and three of them were also evaluated during treatment because of\ndiarrhea. Ten age-, sex-, and BMI-matched healthy subjects (control group)\nunderwent recto-sigmoidoscopic examination and biopsy. All controls had no\nhistory of inflammatory bowel disease or other gastrointestinal diseases, did\nnot receive any medication and did not report symptoms from the\ngastrointestinal tract. Written informed consent was obtained from each\nparticipant for his or her participation in the study. The study conformed to\nthe ethical guidelines of the 1975 Declaration of Helsinki.</p>", "<p>No pathological macroscopic (endoscopic)\nfindings were identified at baseline as well as in endoscopic re-evaluation in\neither patients or controls. CHC patients had no statistically significant\ndifference in the presence of bowel inflammatory infiltration compared to\ncontrols as shown in ##TAB##0##Table 1##. It is important to note that \na <italic>respectable proportion</italic> of CHC patients\nexhibited architectural disorder and <italic>decreased</italic> mucus production (25%) as well as presence\nof Paneth cells (16.7%), compared to controls, but this does not reach\nstatistical significance possibly due to the small sample size of the study\npopulation. This finding needs further investigation because of the documental\nlymphotropism of HCV and the well-known HCV-related autoimmune manifestations.</p>", "<p>No patient reported diarrhea before the initiation of treatment whereas 3 patients\nreported diarrhea during the treatment course. In particular, the first patient\nreported diarrhea at week 6 of treatment, the second one at week 12, and the\nthird one at week 14. Baseline histology was normal in all three patients.\nHistopathological evaluation of the large intestine at the onset of symptoms\nrevealed mild chronic nonspecific colitis in the first patient (##FIG##0##Figure 1##) and\nnormal large intestine histology in the other two patients, respectively. The\nsame findings were repeated in these patients in the histological re-evaluation\nat week 24 of treatment. Diarrhea spontaneously resolved in all of them within\n5–7 days and none of them followed treatment discontinuation.</p>", "<p>There was no statistically\nsignificant difference between the percentage of patients with large intestine\ninflammation before the initiation and at week 24 of treatment (66.7% versus\n53.3% resp., <italic>P</italic> = .71). Particularly, 6/15 patients exhibited mild\ninflammatory infiltration before the initiation as well as at week 24 and 3/15\nexhibited absence of inflammation both before and at week 24 of treatment.\nMoreover, 4/15 positive patients for the presence of inflammation before\ntreatment had normal large intestine histology at week 24 and finally, 2/15\npatients had no findings of inflammation before treatment but exhibited mild\nnonspecific inflammatory lesions at week 24. No statistically significant\ndifferences were observed before the beginning and at week 24 of combination\ntreatment regarding architectural disorder and decrease of mucus production (<italic>P</italic> = .70),\npresence of Paneth cells (<italic>P</italic> = .10), and the number of lymphoid follicles\nin every biopsy specimen (<italic>P</italic> = .97) as shown in ##TAB##1##Table 2##. Interestingly none\nof 4 patients with detectable Paneth cell at baseline evaluation exhibits\npresence of them at week 24. This finding needs further investigation in\nlarge-scale studies because of the proposed importance of these multifaceted\ncells in the pathophysiology of IBD [##REF##11846026##9##].</p>", "<p>In conclusion, according to the preliminary results of our\npilot study, it seems that the immunomodulatory-antiviral treatment of CHC with\nPEG-IFNa2b plus ribavirin for 24 weeks possibly does not significantly affect\nthe large intestine histology of treated patients, despite the appearance of\nsymptoms from the gastrointestinal tract in a subgroup of them. The effect of\nchronic HCV infection in the intestine histopathology needs further\ninvestigation.</p>" ]

[]

[ "<fig id=\"fig1\" position=\"float\"><label>Figure 1</label><caption><p>Histopathological evaluation of the large\nintestine at baseline (a) and at the onset of symptoms (b) revealed normal\nlarge intestine histology and mild chronic nonspecific colitis in the first\npatient with diarrhea, respectively.</p></caption></fig>" ]

[ "<table-wrap id=\"tab1\" position=\"float\"><label>Table 1</label><caption><p>Comparison of epidemiological and large intestine histopathology data between untreated CHC\npatients and controls.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"1\" colspan=\"1\"/><th align=\"center\" rowspan=\"1\" colspan=\"1\">CHC patients <italic>n</italic> = 24</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Controls <italic>n</italic> = 10</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">\n<italic>P</italic> value</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">Gender (male/female)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">14/10</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6/4</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Age (years)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">37.04 ± 14.02</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">46.00 ± 13.38</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.098</td></tr><tr><td rowspan=\"1\" colspan=\"1\">BMI (kg/m²)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">23.09 ± 3.31</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">23.26 ± 3.78</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.903</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Inflammation (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">14/24 (58.3%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6/10 (60%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Architectural disorder and\ndecrease\nof mucus production (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6/24 (25%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">0/10 (0%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.148</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Paneth cells (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4/24 (16.7%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">0/10 (0%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.296</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Lymphoid follicles</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.33 ± 1.50</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.60 ± 1.43</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.440</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"tab2\" position=\"float\"><label>Table 2</label><caption><p>Comparison of large intestine histopathology and diarrhea data of CHC patients before and \nafter 24 <italic>weeks</italic> of treatment.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"1\" colspan=\"1\"/><th align=\"center\" rowspan=\"1\" colspan=\"1\">CHC patients before treatment <italic>n</italic> = 15</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">CHC patients after 24 weeks of treatment <italic>n</italic> = 15</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">\n<italic>P</italic> value</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">Inflammation (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">10/15 (66.7%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">8/15 (53.3%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.71</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Architectural disorder and decrease of mucus production (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">6/15 (40%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4/15 (26.7%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.70</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Paneth cells</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">4/15 (26.7%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">0/15</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.10</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Lymphoid\nfollicles</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.33 ± 1.54</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">1.73 ± 1.62</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.97</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Diarrhea (%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">0/15</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">3/15 (20%)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">.22</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"GRP2008-637517.001\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>1. INTRODUCTION</title>", "<p>Gastrointestinal manifestations have only very rarely been\ndescribed in patients with chronic lymphocytic leukaemia (CLL). The lymphocytic\ninfiltration seems to depend on the tumour burden and proliferation activity\n[##REF##9178840##1##]. Conventional staging according to Rai or Binet may not accurately reflect\nthe whole extent of the disease. It is not known if CLL patients should\npossibly be candidates for an endoscopic investigation and whether proof of\ngastrointestinal involvement would influence the treatment decisions.</p>", "<p>We present a CLL patient who underwent gastrointestinal\nendoscopies because of anaemia and who was found to have colonic histological\nCLL manifestations in spite of normal macroscopic appearance of the mucosa.</p>" ]

[]

[]

[ "<title>4. DISCUSSION</title>", "<p>Gastrointestinal (GI) CLL involvement is uncommon, and the rare GI\ncomplications generally occur only after transformation of CLL to diffuse large\nB-cell lymphoma (Richter syndrome). Our patient case shows that intestinal\nmanifestations can appear even without any symptoms and without macroscopic\nsigns of CLL in the GI tract. Endoscopies including biopsies are necessary in\nexcluding possible gastrointestinal CLL manifestations. They should be\nperformed especially for patients having GI symptoms or anaemia.</p>", "<p>Recent\nfindings suggest that mantle cell lymphoma has a much higher incidence of\ncolonic presentation than previously reported [##REF##15687889##2##]. It seems to appear mostly in\nasymptomatic patients and is detected microscopically in 50% of patients in a\nbiopsy of a visually benign mucosa. Also, patients with marginal zone B-cell\nlymphomas have a higher incidence of colonic involvement than previously\ndescribed. Both of these lymphomas express the mucosal homing receptor <italic>α</italic>4<italic>β</italic>7\nespecially when situated in the intestine [##REF##15687889##2##–##REF##10706853##5##]. Also, primary\nfollicular lymphoma of intestine is positive for <italic>α</italic>4<italic>β</italic>7 in contrast to nodal\nfollicular lymphoma [##REF##12507894##6##]. Much less is known about the incidence of colonic\nmanifestations of CLL/small lymphocytic lymphoma.</p>", "<p>CLL may cause upper GI haemorrhage by directly infiltrating the gastroesophageal junction or through bleeding from oesophageal varices caused by CLL-associated splenomegaly and portal hypertension [##REF##7717324##7##, ##REF##14989055##8##]. According to one case report, protein-losing enteropathy may be found in CLL patients [##REF##3204683##9##]. Reports also mention gastrointestinal CLL manifestations such as infiltration of the intestinal mucosa in the small bowel as well as CLL presenting as colitis [##REF##920701##10##–##REF##3943435##12##]. CLL, especially after Richter transformation, can cause signs and symptoms suggestive of chronic inflammatory bowel disease [##REF##3943435##12##].</p>", "<p>It has been reported that CLL sometimes occurs concomitantly with other malignant neoplasms including melanoma, basal cell carcinoma, laryngeal carcinoma, and colon carcinoma [##REF##47401##13##–##REF##15175948##15##]. Both cellular and humoral immune responses are often impaired in CLL patients, and the defective immunity in these patients may have had an etiological role in the reported development and rapid progression of their cancers. In the follow-up of CLL patients, we must, therefore, be aware of the possible existence of a second malignant disease [##REF##15175948##15##, ##REF##7414709##16##].</p>", "<p>Gastrointestinal CLL manifestations can also form a route for infectious complications. Sadullah et al. have reported a case, where life-threatening gram-negative sepsis developed in a patient with CLL in association with postchemotherapy neutropenia [##REF##8939393##17##]. In colonoscopy, they found a bacterial typhilitis or neutropenic enterocolitis, which is a well described entity of bowel necrosis seen in immunosuppressed or neutropenic patients. It has also been suggested that the small intestinal bacterial overgrowth can possibly contribute to the lymphoid infiltration of the gastrointestinal mucosa in CLL patients [##REF##2312752##18##]. Other rare described CLL manifestations include intussusception and even perforation of the colon [##REF##9865461##19##, ##REF##15718331##20##].</p>", "<p>The histopathologic differential diagnosis of common benign lymphatic hyperplasias and various malignant lymphoid disorders of intestine may be challenging, and biopsy specimens should be subjected to rigorous analysis including immunophenotypic and possibly genotypic studies. Abundant biopsy specimens are required to avoid sampling error and to provide for adequate diagnostic tissue material, which should be sent fresh without fixative to haematopathology laboratory. Fresh biopsy specimens can usually be successfully subjected to flowcytometric analysis of immunophenotype and specifically immunoglobulin light chain restriction. Additionally, B-cell and T-cell receptor gene rearrangement studies may be helpful in detecting clonal lymphocyte populations. Immunohistochemical staining of tissue sections enable correlation of the immunophenotype to morphologic features. The diagnostic range for CLL should include CD20+/CD5+ coexpression with CD23+ phenotype, and negative staining pattern for Cyclin D1 to exclude mantle cell lymphoma (lymphomatous polyposis). Differential diagnosis of indolent CD5 negative B-cell lymphomas include follicular lymphoma, which usually has CD10+ phenotype, whereas mucosa-associated marginal zone-lymphoma (MALT-lymphoma) lacks specific phenotypic markers and its immunophenotypic diagnosis is mainly based on exclusion. Lymphoepithelial lesions and plasmacytic differentiation are suggestive of MALT-lymphoma.</p>", "<p>In conclusion, also gastrointestinal evaluation should perhaps be part of a complete assessment of the treatment response and remission status in CLL patients in whom the colon was originally involved. If a CLL patient has any symptoms suggesting a possible GI manifestation of the haematologic disease or anaemia not explained by bone marrow infiltration, or hemolysis, the diagnostic evaluation should include endoscopies with adequate biopsies.</p>" ]

[]

[ "<p>Recommended by Paolo Gionchetti</p>", "<p>Various gastrointestinal infiltrations have been described in patients with chronic lymphocytic leukaemia (CLL). Here, we report a 69-year-old man with CLL and anaemia in whom the macroscopic finding of colonoscopy was normal, but the histological specimens revealed lymphocytic leukemia in ileum and in colon. If a CLL patient has any symptoms suggesting a possible GI manifestation of the haematologic disease or anaemia not explained by bone marrow infiltration or hemolysis, the diagnostic evaluation should include endoscopies with adequate biopsies.</p>" ]

[ "<title>2. CASE REPORT</title>", "<p>The patient is a 69-year-old-man, an exsmoker with chronic atrial\nfibrillation and chronic otitis and warfarin and digitalis as his only\nmedications. His past medical history was unremarkable until the end of 2001, when he started to have productive\ncough and was found to have mild leukocytosis. In 2002, the plain chest x-ray\nwas first considered to be suggestive of sarcoidosis. The CT scan showed\nlymphadenopathy (max. 2 cm) in both pulmonary hilar areas, in the axillae, and\nalso below the diaphragm, the ultrasound examination also in the jugular and\nsupraclavicular areas. The pathological\nexamination of mediastinoscopic paratracheal and subcarinal lymph node biopsies\nshowed effacement of the normal lymph node architecture by infiltration of\nsmall, CD5+, CD20+, and CD23+ lymphatic cells with vague pseudofollicular\norganization consistent with the diagnosis of small B-cell lymphocytic\nlymphoma/CLL. Neither CD38 nor overexpression of p53 was observed by\nimmunohistochemistry, but the lymphoma cells expressed ZAP-70 as an adverse\nprognostic factor.</p>", "<p>In 2002, the haemoglobin level was\n133–139 g/L, the\nwhite cell count 11.0–12.9 × 10E9/L\nwith 59% lymphocytes, the platelet count 191–289 × 10E9/L, and\nthe Coombs test negative. Elevated levels of the plasma lactate dehydrogenase\nactivity, 967 U/l (normal below 450 U/l), and the serum thymidine kinase\nactivity, 34 U/l (normal below 8 U/l), were found. The bone marrow aspirate\nshowed a decreased proportion of erythropoiesis as well as granulopoiesis and\nan increased proportion of small mature lymphocytes, up to 80–90% of the\ncellularity.</p>", "<p>The bone marrow biopsy showed 60% overall cellularity. 60% of\ncells were interstitially and diffusely between trabeculae, infiltrating small\nlymphocytes admixed with scarce prolymphocytes and paraimmunoblasts. The\nimmunophenotype was identical to the lymph node infiltrate.</p>", "<p>No treatment was considered necessary, and the patient'S clinical\ncondition remained stable during 2002-2003. In the\nfollow up CT'S the size of lymph nodules\nremained similar. The cough had disappeared, and the patient did not have any\ngeneral symptoms such as fever, abnormal sweating, or weight loss. A small\ntwo-component IgG kappa serum paraprotein (2.6 g/L + 1.0 g/L) was\ndetected. In 2004, after a left-sided\npneumonia, slight progression of the lymphadenopathy in the left pulmonary\nhilus, para-aortal, and mesenterial regions was found without splenomegaly. In\nspite of that, as well as the appearance of mild night sweats, treatment was\nnot considered necessary, as the leukocyte count was only 22.7 × 10E9/L, and no\nanaemia or thrombocytopenia was found. In the bone marrow, a 65–70% lymphatic\ninfiltrate with slight enhancement in the proportion of prominent,\nparaimmunoblast-type cells was seen, the overall cellularity being 45%. The\nperipheral blood cytogenetic analysis revealed 12-trisomy and translocation\nt(4;12), whereas no signs of p53 deletion in chromosome 17, the ATM gene\ndeletion in 11q, or deletion 13q were\nfound by FISH-analysis.</p>", "<p>In 2004, the\nhaemoglobin gradually decreased from a level of above 130 g/L to 110 g/L\nwithout increase in lymphocytosis or signs of hemolysis but with mild\nthrombocytosis. The serum iron content and the transferrin saturation were low\n(6.5 umol/L and 9%, resp.), and when checked in August, one out of three fecal\ntests positive for occult blood. Folic acid (214 nmol/L) and B12-vitamin (380 pmol/l) were within normal range. Serum albumin (40.0 g/L) and ionized calcium\n(1.18 mmol/L/pH7.4) did not suggest that the patient would have had malabsorption.\nSome fluctuation in INR value was found in 2004, but the value was most of the\ntime within the therapeutic range. The transaminases and plasma creatinine were normal. Because the\nhaemoglobin remained abnormal (114–117 g/L) and also\nmicrocytosis developed, endoscopies were arranged to assess the possibility of\ngastrointestinal bleeding. No symptoms suggesting a gastrointestinal cause for\nthe anaemia existed.</p>", "<p>In the gastroscopy, a sliding hernia but no signs of any sources\nfor upper gastrointestinal bleeding were found. The gastroscopy biopsies showed\nchronic gastritis in the antrum and in the corpus. No active gastritis,\natrophic gastritis, <italic>H. pylori, or\nduodenal villous atrofy</italic> were found. Also, ileocolonoscopy was performed\nwith colonic diverticulosis as the diagnosis. Otherwise, the macroscopic view\nappeared normal both in the colon and in the ileum.</p>", "<p>Microscopically dense mucosal and submucosal lymphocytic\ninfiltrates were detected in ileum as well as 4/7 biopsies of colon \n(Figures ##FIG##0##1(a)##,\n##FIG##0##1(b)##, and ##FIG##0##1(c)##), with predominance of small CD20 positive lymphocytes. No\nlymphoepithelial lesions were observed. The cells stained positively also for\nCLL-associated antigens CD5 (low intensity), CD23, and CD43, but were negative\nfor mantle cell-associated antigen cyclin D1. Consecutively, ZAP-70 was\npositive, and no immunohistochemical staining for CD38 or p53 was detected.</p>", "<title>3. PATIENT'S OUTCOME, CURRENT TREATMENT</title>", "<p>After the endoscopies, the patient was put on peroral iron\nsubstitution. After four months, the haemoglobin level had increased to 137 g/L,\nand the patient experienced an improvement in his general condition. Haemoglobin\nhas thereafter remained within normal range until summer 2006. The most likely\nreason for the anaemia in 2004 was the blood loss from the GI track and the\nhistologically confirmed CLL GI-manifestation was the underlying reason. Patient has\nhad no GI symptoms like melena, bloody stools, or stomach pain and because the anaemia\ndisappeared with the iron substitution, no other endoscopic procedures like capsule\nendoscopy or radiological imaging of the small bowel have been assessed. During last two years, haemoglobin has slowly decreased \n(144–127) and leukocyte\nlevel has increased due to the advance of CLL. Despite adverse trisomy 12\nkaryotypic and ZAP-70+ immunophenotypic findings, the clinical condition and\nthe blood lymphocytosis have continuously remained quite stable, and no active\ntreatment for CLL has been initiated.</p>" ]

[]

[ "<fig id=\"fig1\" position=\"float\"><label>Figure 1</label><caption><p>Biopsy specimens revealed multiple diffuse CD20 positive (a) B-cell infiltrates\ninvolving mucosa and submucosa of colon without formation lymphoepithelial\nlesions. B-lymphocytes expressed also CD5 with low intensity (b) and CD23 (c),\ncharacteristic of small lymphocytic lymphoma (CLL).</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"GRP2008-742146.001\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Human cytomegalovirus (HCMV) is a classic example of a group of herpes viruses, which is found universally throughout all geographic locations and socioeconomic groups, and infects 50% of adults in developed countries ##REF##15567122##[1]##. Although HCMV does not cause clinical disease in immunocompetent individuals except as a mononucleosis-like illness which is observed in a small number of infected individuals, HCMV infection is important to the following three high-risk groups: 1) unborn babies with an immature immune system, 2) people who work with children, and 3) immunocompromised people such as organ transplant patients and HIV-infected individuals) ##REF##15567122##[1]##. Epidemiological studies have shown that 15%–30% of unborn babies who acquire congenital HCMV infection display a variable pattern of pathological sequelae within the first few years of life that may include hearing loss, vision impairment and mental retardation ##REF##11961482##[2]##. It has been estimated that in the US alone, each year 8000 newborns have health problems as a results of congenital HCMV infection, with each child costing the US health care system more than $300,000 ##REF##15307033##[3]##. Based on the cost and human suffering that would be relieved by reducing the disease burden associated with HCMV infection, the development of a vaccine to prevent HCMV infection or disease was assigned the highest priority, together with vaccines for HIV, TB and Malaria, by the Institute of Medicine (USA) in 1999 ##UREF##0##[4]##.</p>", "<p>It is now well documented that both humoral and cellular (including CD4⁺ T cells and CD8⁺ T cells) immune responses play an important role in the control of HCMV infection and disease ##REF##15567122##[1]##, ##REF##12415307##[5]##. Therefore a formulation based on viral antigens that activate both humoral and cellular immunity is crucial for a successful HCMV vaccine ##REF##10223683##[6]##, ##UREF##1##[7]##. During the last 30 years, various strategies, including whole virus, subunit vaccines based on recombinant gB protein, vector vaccines expressing immunodominant antigens (gB protein, pp65 and/or IE-1 protein), DNA vaccine and dense bodies have been developed, and some of these formulations have shown encouraging results in preclinical studies and can even induce HCMV-specific immune responses in some clinical studies ##REF##10539854##[8]##, ##REF##16393522##[9]##, ##REF##18035130##[10]##, ##REF##16337831##[11]##. However, none of these vaccines have shown convincing clinical efficacy in the control of HCMV infection or disease, and a clinically licensed HCMV vaccine is still not available.</p>", "<p>In recent years, increasing evidence has shown that HCMV-specific immune responses are not restricted to gB, pp65 and IE-1 antigens as previously understood, but are directed towards more than 70% of the HCMV reading frames ##REF##15368271##[12]##, ##REF##12692225##[13]##, ##REF##16147978##[14]##, ##REF##15039282##[15]##. Therefore, a vaccine which can induce a broad repertoire of HCMV-specific immune responses in different ethnic populations is likely to provide more effective protection against virus-associated pathogenesis. To achieve this goal, we have designed a novel chimeric vaccine based on a replication deficient adenovirus which encodes 46 HCMV T cell epitopes from 8 different HCMV antigens, restricted through multiple HLA class I and Class II alleles, as a polyepitope ##REF##15726667##[16]##. This polyepitope was covalently linked to a truncated form of HCMV-encoded gB antigen which allowed the expression of the HCMV polyepitope and gB proteins as a single fusion protein. Pre-clinical evaluation of this recombinant polyepitope vaccine in HLA A2 transgenic mice (referred to as HHD-2) and humans showed that this formulation is capable of inducing pluripotent cellular and humoral immunity <italic>in vivo</italic> and also readily recalls and expands HCMV-specific CD8⁺ and CD4⁺ T cells.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Construction of recombinant adenovirus encoding HCMV polyepitope, gB and gB-HCMV polyepitope fusion protein</title>", "<p>The amino acid sequence of the 46 contiguous HLA class I and class II-restricted T cell epitopes (##TAB##0##Table 1##) were translated to the nucleotide sequence using human universal codon usage. Oligonucleotides (102–107mer long) overlapping by 20 base pairs and representing the polyepitope DNA sequence, were annealed together by using Splicing by Overlap Extension and stepwise asymmetric PCR ##REF##15726667##[16]##. The final PCR product was cloned into pBluescript II KS⁺ phagemid (Agilent Technologies, Melbourne, Australia) encoded a Kozak sequence, Start methionine followed by 46 contiguous HLA class I and class II-restricted epitopes. The HCMV sequence encoding glycoprotein B (gB) was amplified from the AD169 virus stock by PCR using gene specific primers. This PCR product was designed to encode gB sequence from the alanine residue at position 31 to valine at position 700 with the deletion of the signal sequence. Following amplification the DNA was cloned into pBluescript II KS⁺ phagemid and confirmed by DNA sequence analysis. For the expression of the gB-HCMV polyepitope fusion protein the recombinant HCMV polyepitope insert was excised from the pBluescript II KS⁺ phagemid and cloned into the gB pBluescript construct.</p>", "<p>The assembly and production of the recombinant Ad5F35-based adenoviruses was completed in three stages using a highly efficient, ligation-based protocol of the Adeno-X System (CLONTECH, Palo Alto, CA) (See ##FIG##0##Figure 1##). Firstly, inserts were excised from each of the constructs in pBluescript II KS⁺ phagemid using Xba I/Kpn I restriction enzymes and cloned into the pShuttle expression vector. Following amplification in E.coli, the expression cassette from pShuttle was excised using I-Ceu I/PI-Sec I homing enzymes and cloned into an Ad5F35 expression vector. The recombinant Ad5F35 vector was transfected into human embryonic kidney (HEK) 293 cells, and the recombinant adenoviruses (referred to as Ad-CMVpoly, Ad-gB and Ad-gBCMVpoly) were harvested from the transfected cells by successive freeze-thawing cycles.</p>", "<title>Synthesis of Peptides</title>", "<p>Peptides, synthesized by the Merrifield solid phase method, were purchased from Chiron Mimotopes (Melbourne, Australia), dissolved in dimethyl sulphoxide, and diluted in serum-free RPMI 1640 medium for use in standard T cell assays. Purity of these peptides were tested by mass spectrometery and showed &gt;90% purity</p>", "<title>Animals and immunisation</title>", "<p>HLA A2 transgenic mice (referred to as HHD-2) ##REF##9182675##[52]##, were maintained under conventional conditions the animal facility at the Queensland Institute of Medical Research. These mice are knocked out for β2 microglobulin and H-2D^b and transgenic for a chimeric HLA-A2.1 with the α3 domain derived from H-2D^b to allow interaction with murine CD8 and a covalently attached human β2 microglobulin. These mice were immunised with varying doses of plaque forming units (PFU) of recombinant viruses (Ad-CMVpoly, Ad-CMVgB and Ad-gBCMVpoly) and HCMV-specific humoral and cellular immune responses were evaluated at various time points. Protocols were approved by QIMR animal ethics committee.</p>", "<title>ELISpot assay</title>", "<p>The ELISPOT assay was used to detect HLA A2-restricted HCMV epitope-specific T cells following stimulation with synthetic peptide(s) as described previously ##REF##12692225##[13]##. Briefly, 2×10⁵ responding cells were incubated in triplicate with each peptide epitope (1 µg/ml) for 18 to 20 hrs in 96- well Multiscreen HA filtration plates (MAHA S4150, Millipore, Bedford, MA) coated with anti-IFN-γ monoclonal antibody (Mabtech AB, Nacka, Sweden). After incubation, the plates were extensively washed with Phosphate buffered saline with 0.5% Tween 20 and incubated with a second biotinylated anti-IFN-γ mAb followed by the addition of streptavidin conjugated alkaline phosphatase. Cytokine producing cells were detected as purple spots after a 30-min reaction with 5-bromo-4-chloro-3-indolyl phosphate and nitro blue tetrazolium. Spots were counted automatically using image analysis software. T cell precursor frequencies for each peptide epitope were based on the total number of cells and the number of spot forming cells (SFC) per well (average of 3 wells). Epitope-specific spots were calculated after subtraction of the number of spots in control wells consisting of cells without added peptide (average of six wells).</p>", "<title>Intracellular Cytokine Staining</title>", "<p>Splenocytes from immunised mice or T cells from human donors were incubated for overnight at 37°C with HCMV peptide epitopes (1 µg/ml), or stimulator cells either pre-coated with HCMV peptide epitopes (1 µg/ml) or infected with recombinant vaccinia virus encoding HCMV antigens, in growth medium. Brefeldin A (BD Pharmingen, San Diego, CA) was added during the last 5 hour-incubation. For CD107a staining, anti-CD107a antibody was added one hour before the adding of Brefeldin A. These cells were then washed and incubated with PerCP-conjugated anti-CD8, FITC conjugated anti-CD4 and Allophycocyanin-conjugated anti-CD3 at 4°C for 30 mins. Cells were washed, then fixed and permeabilised with cytofix/cytoperm (BD Pharmingen) at 4°C for 20 minutes. Cells were then washed in perm/wash (BD Pharmingen), incubated with anti-IFN-γ and anti-TNF-α mAbs (BD Pharmingen) at 4°C for 30 mins, washed again with perm/wash, resuspended in PBS and analysed on a FACS Canto.</p>", "<title>Expansion of HCMV specific T-cells from healthy donors using Ad-gBCMVpoly</title>", "<p>A panel of 17 human volunteers were recruited for this study. Each volunteer was asked to sign the consent form as outlined in the institutional ethics guidelines. For the expansion of specific T-cells, peripheral blood mononuclear cells (PBMC) were co-cultured in multi-well tissue culture plates in growth medium with either PBMC (2,000 rad) infected with Ad-gBCMVpoly (MOI of 10∶1) at a responder to stimulator ratio of 2∶1. On day 3, and every 3–4 days thereafter, the cultures were supplemented with growth medium containing recombinant IL-2 (kindly donated by NIH AIDS Research &amp; Reference Reagent Program). These T-cell cultures were assessed for HCMV epitope-specific reactivity on days 10–17.</p>", "<title>ELISA assay for anti-gB and anti-adenovirus antibody</title>", "<p>Serum anti-gB or anti-adenovirus antibody titres were evaluated by ELISA as previously described ##REF##15049001##[53]##. Briefly, PVL microplate 96-well plates (MP Biomedicals, Sydney, Australia) pre-coated with recombinant HCMV gB protein or adenovirus were incubated with serially diluted serum samples for 2 hours at room temperature. After washing with PBS-Tween-20 (PBST), plates were incubated with HRP-conjugated sheep anti-mouse Ig antibody (murine samples) or HRP-conjugated sheep anti-human Ig antibody (human samples) for 1 hour. These plates were washed and incubated with 3.3′, 5.5′-tetramethylbenzidine substrate solution (PanBio, Brisbane, Australia) and the OD at 450 nm was analysed using an ELISA reader. The isotypes of anti-gB antibodies in serum samples were determined by ELISA as described above using the mouse monoclonal antibody isotyping reagent kit (Sigma, IS02-1 kit, Sydney, Australia) according to the manufacturer's protocol.</p>", "<p>Antibody avidity was evaluated as previously described ##REF##14733736##[54]##. Briefly after incubation of plates with serum samples as described above, 5 M Urea (in PBST) was then added to half of the wells for dissociation and the other half received PBST without urea. After incubation for 30 min, plates were washed with PBST and incubated with HRP-conjugated sheep anti-mouse Ig antibody (murine samples) or HRP-conjugated sheep anti-human Ig antibody (human samples) for 1 hour and completed using the standard ELISA. The avidity indices were calculated as the ratio of the OD values with urea divided by the OD values without urea and expressed as a percentage.</p>", "<title>CMV microneutralization assay</title>", "<p>The neutralizing activity of the anti-gB antibody response in vaccinated animals was assessed as described previously ##REF##15047812##[23]##. Briefly serum samples were initially incubated at 56°C for 30 minutes to inactivate complement, followed by serial dilution (25 µl/well) with DMEM medium in 96-well “U” bottom plates. In each well an equal volume of HCMV Ad169 was added and incubated at 37°C for 2 h. This virus was then transferred to infect monolayer of human fibroblast MRC-5 cell culture in 96 well flat bottom plates with 80–90% confluence. After 2 h, plates were washed with DMEM and 200 µl DMEM with 10% FCS were added to each well and then incubated at 37°C for 16–18 h. After incubation, cells were fixed in 100% methanol, incubated with peroxidase blocking reagent (Chemicon, S2001) and then reacted with mouse anti-CMV IE-1/IE-2 monoclonal antibody (Clone MAB810, Chemicon) followed by HRP-conjugated sheep anti-mouse Ig (Chemicon, AP326P). Finally cells were stained with DAB+ substrate (Chemicon, K3467) according to manufacturer's protocol. The numbers of nuclei with brown colour staining were counted using inverted microscope. The neutralizing titre was calculated as the reciprocal of sera dilution that gave 50% inhibition of IE-1/IE-2-expressing nuclei.</p>", "<title>Vaccinia virus recombinant</title>", "<p>Recombinant vaccinia constructs encoding HCMV antigens IE-1 (Vacc.IE-1), gB (Vacc.gB) and a negative control vaccinia virus construct made by insertion of the pSC11 vector alone, which is negative for thymidine kinase (Vacc.TK⁻), have been previously described ##REF##12692225##[13]##.</p>", "<title>Protection assay</title>", "<p>HHD-2 mice were intramuscularly immunised with the indicated vaccine on day 0, followed by intraperitoneal challenge with recombinant vaccinia virus expressing different proteins from HCMV antigens (Vacc.IE1 or Vacc.gB) at a dose of 10⁷ pfu/mouse on day 21. Mice were then sacrificed 4 days later, spleens collected to evaluate epitope-specific T cell response by IFN-γ ICS assay, ovaries collected to determine vaccinia virus load by plaque assay on monkey fibroblast CV-1 cells, and sera collected to evaluate anti-gB Ab titres by ELISA. To determine vaccinia viral titres, monolayers of CV-1 cells in a 6 well flat bottom plates were incubated for 2 h at 37°C with serially diluted ovary lysates. After incubation, 2 ml of RPMI1640 medium supplemented with 2% FCS and 0.75% methylcellulose was added to each well and incubated for further 3 days. After three days, plates were washed with PBS and stained with crystal violet solution (Sigma, HT901) at a working concentration (0.1% crystal violet in 15% ethanol) for 30 min and the number of plaques were counted using standard procedures.</p>" ]

[ "<title>Results</title>", "<title>Immunisation of HHD-2 mice with Ad-CMVpoly and/or Ad-gB vaccine induces multiple antigen-specific cellular and humoral immunity</title>", "<p>Recent studies on the immune regulation of HCMV in healthy virus carriers and transplant patients have clearly indicated that long-term protection from viral pathogenesis is critically dependent on the induction of cellular immunity which is directed towards multiple viral antigens expressed during different stages of HCMV infection ##REF##15368271##[12]##, ##REF##12692225##[13]##, ##REF##16147978##[14]##, ##REF##15039282##[15]##, ##REF##17686874##[17]##. In the first set of experiments we specifically designed our vaccine strategy to induce a cellular immune response against multiple antigens of HCMV using the polyepitope technology ##REF##7541138##[18]##. HLA A2 transgenic mice (referred to as HHD-2) were immunised (intramuscularly) with an adenoviral vector encoding 46 HLA class I and II-restricted T cell epitopes as a polyepitope (referred to as Ad-CMVpoly; 7.5×10⁸ pfu/mouse; ##FIG##0##Figure 1## and ##TAB##0##Table 1##). Ten days after immunisation, <italic>ex vivo</italic> T cell reactivity to the HLA A2-restricted peptide epitopes (pooled; see ##TAB##0##Table 1##) was assessed by ELISPOT technology. It is important to mention here that the virus dosage for vaccination was selected based on our preliminary studies where a range of varying doses were investigated (data not shown). Splenocytes were used as responder cells for the detection of epitope-specific T cells. Data presented in ##FIG##1##Figure 2A## shows that we consistently observed a strong HCMV epitope-specific T cell response following Ad-CMVpoly vaccination. Analysis of T cell responses to the individual epitopes within the polyepitope sequence indicated that during primary immunisation the dominant T cell response was directed towards the VLE epitope derived from IE-1 antigen, although subdominant responses towards other HLA A2-restricted epitopes NLV (pp65), RIF (pp65), VLA (IE-1), IIY (IE-2) AVG (gB) was also detected (##FIG##1##Figure 2B##).</p>", "<p>Recent studies have raised some concerns on the use of adenoviral vectors in humans as the pre-existing immunity to adenovirus may compromise the efficacy of these vaccine formulations ##REF##15905562##[19]##, ##REF##15297053##[20]##, ##REF##15128818##[21]##. To explore this issue, Ad-CMVpoly immunized HHD-2 mice were rested for one or three months and then immunized with the Ad-CMVpoly vaccine (7.5×10⁸ pfu/mouse). Although secondary immunization of mice after one month of vaccination showed very minimal increase in the T cell response (data not shown), a 3–5 fold increase in the T cell response was observed in HHD-2 mice vaccinated after three months of their primary vaccination (##FIG##1##Figure 2C##). More importantly, following secondary immunization, a small but significant increase in the subdominant responses was observed in some animals, while the T cell response towards VLE epitope remained the most dominant component of overall response (##FIG##1##Figure 2D##). It was interesting to note that the hierarchy of these T cell responses in HHD-2 mice was very similar to that observed in HLA A2-positive healthy virus carriers ##REF##15368271##[12]##, ##REF##12692225##[13]##, ##REF##16147978##[14]##. This observation was co-incident with the dramatic decline of antibodies against adenovirus vector 2 to 3 months after immunisation with Ad-CMVpoly (##FIG##1##Figure 2E##).</p>", "<title>Combination of Ad-CMVpoly and Ad-gB induces long lasting memory cellular and humoral immune responses</title>", "<p>It is now firmly established that although T cell responses play an important role in controlling persistent HCMV infection, humoral immune responses also contribute significantly in controlling primary HCMV infection and as well reduce viral load by neutralizing the extra-cellular virus ##REF##11922941##[22]##, ##REF##15047812##[23]##. To ensure that our vaccine strategy can induce both cellular and humoral immune responses, we immunised HHD-2 mice with the mixture of Ad-gB (7.5×10⁸ pfu/mouse) and Ad-CMVpoly (7.5×10⁸ pfu/mouse), and anti-HCMV specific cellular and humoral immune responses in immunised animals were evaluated at different time point by ELISPOT and ELISA respectively. Data presented in ##FIG##2##Figure 3A &amp; B## shows that this vaccination strategy induced both CD8⁺ T cells and gB-specific antibody responses. The levels of CD8⁺ T cells induced by this co-immunisation strategy were comparable to those seen with Ad-CMVpoly alone and were detectable at reasonably high levels on day 75 post-immunisation (##FIG##2##Figure 3A##). The levels of gB-specific antibody responses were maintained at high levels by day 75 post-immunisation, although a small reduction was observed when compared to the levels observed on days 10 and 25 respectively. In contrast, the antibody response showed significant increase in the virus neutralization capacity by day 75 post-immunisation (##FIG##2##Figure 3C##) which was co-incident with the antibody avidity maturation (##FIG##2##Figure 3D##). It is important to mention here that this increase in neutralization capacity was not due to antibody isotype switching (##FIG##2##Figure 3E##), which was consist with previous studies ##REF##11016597##[24]##. These observations suggested that co-delivery of HCMV polyepitope and gB vaccine can induce long lasting memory T cells immunity and antibody responses.</p>", "<title>Covalent linking of HCMV polyepitope with extracellular gB induces pluripotent T cell and antibody responses</title>", "<p>Although co-immunisation with Ad-gB and Ad-CMVpoly induced both humoral and cellular immune responses against HCMV, delivery of this formulation in a human setting may face significant regulatory constraints. To overcome this potential limitation, we constructed another recombinant adenovirus expressing the extracellular domain of gB and HCMV polyepitope as a single polypeptide (referred as Ad-gBCMVpoly). HHD-2 mice were immunised with the Ad-gBCMVpoly vaccine (7.5×10⁸ pfu/mouse) and both humoral and cellular immune responses were evaluated at the indicated time points. Data presented in ##FIG##3##Figure 4A## shows that immunisation with Ad-gBCMVpoly vaccine induced a long-tem memory CD8⁺ T cell response towards the HLA A2-restricted epitopes from HCMV. Furthermore these animals also showed strong gB-specific antibody response and similar to the data presented in ##FIG##2##Figure 3B##, the levels of gB-specific antibody dropped by day 75 post immunisation (##FIG##3##Figure 4B##). A significant increase in the neutralizing activity of the antibody response was observed (##FIG##3##Figure 4C##), which was co-incident with avidity maturation (##FIG##3##Figure 4D##). On the other hand, there was no antibody isotype switching at different time point after immunisation (##FIG##3##Figure 4E##). These observations clearly demonstrated that covalent linking of the gB with the polyepitope sequence does not impair the immunogenicity of each of the components of the vaccine.</p>", "<p>To further characterize the T cell responses induced by Ad-gBCMVpoly vaccine, we next assessed whether immunisation with Ad-gBCMVpoly result in the differentiation of antigen-specific T cells into fully functional effectors. A number of recent studies have demonstrated that the production of TNF-α in addition to IFN-γ by T-cells is a characteristic of greater differentiation and can enhance protection against infectious pathogens ##REF##17558415##[25]##, ##REF##11751978##[26]##, and the translocation of CD107a from intracellular lysosomal and endosomal compartments to the surface of CD8⁺ T cells is a positive marker of degranulation, a requisite process of perforin-granzyme mediated killing function of CTLs ##REF##17056567##[27]##, ##REF##15051762##[28]##. We assessed the level of TNF-α and/or CD107a expression by IFN-γ expressing CD8⁺ T-cells using intracellular cytokine assays. Data presented in ##FIG##4##Figure 5A–B## shows that following <italic>ex vivo</italic> stimulation with HCMV epitopes, CD8⁺ T cells from these mice showed strong IFN-γ expression and a large proportion of these T cells also expressed TNF-α and/or CD107a. Furthermore, after <italic>in vitro</italic> stimulation with individual HCMV peptides, these HCMV peptide-specific CD8⁺ T cells could be expanded and expressed both IFN-γ and TNF-α (##FIG##4##Figure 5C–E##).</p>", "<title>Protection against quasi-virus challenge following immunisation with Ad-gBCMVpoly</title>", "<p>Having firmly established the immunogenicity of Ad-gBCMVpoly vaccine, the next set of experiments was designed to determine protective efficacy of this vaccine. Due to the species restriction, we challenge immunised HHD-2 mice with recombinant vaccinia encoding HCMV antigens (gB and IE-1) to evaluate the protective efficiency of the Ad-gBCMVpoly vaccine. Data presented in ##FIG##5##Figure 6A## shows that HLA A2 mice immunised with Ad-gBCMVpoly vaccine showed significant reduction in the virus load following challenge with Vacc.gB and Vacc.IE-1. This reduction in the virus load was highly antigen-specific as the vaccinated or naïve animals challenged with Vacc.TK- or Vacc.gB, Vacc.IE-1 respectively showed minimal reduction in the viral load. Although Ad-gBCMVpoly immunized mice showed better protection against Vacc.gB when compared to Vacc.IE-1 (##FIG##5##Figure 6A##), this better protection was not due to anti-gB antibodies (##FIG##5##Figure 6B##) as Vacc.gB was not neutralized by serum from immunized animals (data not shown), but due to gB-specific CD4⁺ T cell responses (##FIG##5##Figure 6C##). Nevertheless, the anti-gB humoral response should play an important role in human as it induces HCMV neutralizing antibodies. As expected, the reduction in the Vacc.IE-1 virus load in Ad-gBCMVpoly immunised mice was co-incident with the induction of VLE-specific CD8⁺ T cell responses (##FIG##5##Figure 6D##). It is important to note that Ad-gBCMVpoly immunised mice challenged with Vacc.gB or Vacc.IE-1 showed significantly higher humoral and T cell responses respectively when compared to mice challenged with Vacc.TK-. We also assessed the level of TNF-α expression by IFN-γ expressing CD4⁺ and CD8⁺ T-cells using intracellular cytokine assays. Data presented in ##FIG##5##Figure 6E## shows that following stimulation with gB protein or HCMV IE-1 epitope, a large proportion of CD4⁺ and CD8⁺ T cells from these mice showed strong co-expression of IFN-γ and TNF-α.</p>", "<title>Expansion of multiple antigen-specific human CD8⁺ and CD4⁺ T cells following stimulation with Ad-gBCMVpoly</title>", "<p>Another important aspect of the current study was aimed at exploring the potential efficacy of Ad-gBCMVpoly to recall memory T cell responses from healthy seropositive individuals. PBMC from healthy donors were stimulated with irradiated autologous PBMC-infected with Ad-gBCMVpoly. Following stimulation these T cells were assessed for antigen specificity using intracellular cytokine assays. Data for the gB-specific CD4⁺ and CD8⁺ T cell responses are summarised in ##FIG##6##Figure 7##, while the T cell responses towards the epitopes within the polyepitope sequence are presented in ##TAB##1##Tables 2## &amp; ##TAB##2##3##. To identify the gB-specific T cell responses we used an overlapping set of peptides based on the gB sequence from Ad169 strain of HCMV. This analysis showed that following stimulation with Ad-gBCMVpoly, more than 88% of the individuals showed expansion of gB-specific CD4⁺ T cells. These T cell expansions raged from 2–36% of the total CD3⁺ CD4⁺ T cells (##FIG##6##Figure 7##). CD8⁺ T cell responses directed towards gB epitopes were detected in 70.5% donors which ranged from 2–15% of the total CD3⁺ CD8⁺ T cells. T cells from each donor recognized multiple gB epitopes and most of the donors demonstrated a selective expansion of gB-specific CD4⁺ or CD8⁺ T cells.</p>", "<p>Analysis of the T cell responses towards the epitopes within the polyepitope sequence revealed that there was a rapid expansion of CD8⁺ T cells following stimulation with Ad-gBCMVpoly which recognized multiple epitopes restricted through a number of HLA class I alleles (##TAB##1##Table 2##). In most cases, dominant CD8⁺ T cell expansions directed towards 2–3 different epitopes was observed; whilst in other donors (e.g. D9, D10 and D13) strong T cell reactivity towards more than five epitopes was observed. In vitro testing of these T cells also showed that these cells expressed high levels of CD107 and efficiently recognized HLA-matched HCMV-infected target cells (data not shown). These observations were also confirmed by ex vivo stimulating the PBMC from healthy virus carriers with Ad-gBCMVpoly. A representative data presented in ##FIG##7##Figure 8## clearly shows that ex vivo stimulation of PBMC rapidly stimulated HCMV epitope specific T cells and these cells showed strong expression of IFN-γ. Although the polyepitope sequence was predominantly based on CD8⁺ T cell epitopes, two previously mapped CD4⁺ T cell epitopes were also included in this sequence. As expected, a strong expansion of CD4⁺ T cells specific for these epitopes was observed, however unexpectedly, we also detected low to medium levels of expansion of CD4⁺ T cells which showed reactivity against HLA class I-restricted CD8⁺ T cell epitopes (##TAB##2##Table 3##). A careful analysis of these CD8⁺ T cell epitopes revealed that many of these sequences overlapped the CD4 epitopes mapped recently by other investigators ##REF##8642638##[29]##, ##REF##12085315##[30]##, ##UREF##2##[31]##.</p>" ]

[ "<title>Discussion</title>", "<p>The data presented in this study provides a highly efficient strategy for the prevention of HCMV disease in different clinical settings ranging from congenital infection to primary or reactivation of the virus in immunosuppressed adults. The importance of HCMV as the leading infectious cause of mental retardation and other abnormalities such as deafness in children has been emphasized by its categorization by the Institute of Medicine as a Level I vaccine candidate [i.e. most favourable impact–saves both money and quality-adjusted life years] ##UREF##0##[4]##. Immunocompromised individuals such as transplant recipients and HIV-infected individuals with CD4 counts below 50/µl are also impacted by HCMV infection and this virus is regarded as the most important viral pathogen affecting transplantation, including both solid organ transplant and allogeneic hematopoietic stem cell transplant recipients ##REF##15567122##[1]##, ##REF##12393659##[32]##, ##REF##12749798##[33]##. Extensive studies over the last decade on the immunobiology of HCMV infection has provided detailed insight into the immune regulation of persistent HCMV infection in healthy virus carriers and individuals with HCMV-associated diseases ##REF##15567122##[1]##. Based on these observations, a number of attempts have been made to design a prophylactic vaccine for the control of HCMV infection. The first series of attempts focussed on the use of an attenuated form of the virus as a vaccine ##REF##10223683##[6]##, ##REF##10539854##[8]##, ##REF##6099649##[34]##, ##UREF##3##[35]## however, disappointing results coupled with the regulatory problems associated with the live attenuated HCMV vaccine prompted investigators to switch to the recombinant subunit approach ##REF##9292508##[36]##, ##REF##10980387##[37]##, ##REF##11262198##[38]##, ##REF##11972639##[39]##. Although the subunit vaccine delivery systems and modalities based on HCMV encoded antigens such as gB, pp65 and IE-1 have failed to result in a licensed clinical product, interesting pre-clinical (based on animal models) and clinical data continues to accumulate demonstrating that subunit vaccination has a protective effect against congenital transmission ##REF##16393522##[9]##, ##REF##18035130##[10]##, ##REF##7491815##[40]##, ##REF##8884369##[41]##, ##REF##10479120##[42]##.</p>", "<p>It is now firmly established that long-term latent HCMV infection is very efficiently controlled by virus-specific CD4⁺ and CD8⁺ T cells ##REF##15368271##[12]##, ##REF##12692225##[13]##, ##REF##16147978##[14]##, ##REF##15039282##[15]##, ##REF##17547509##[43]##. Perturbation in the regulation of T cell control often triggers reactivation of HCMV and development of HCMV-associated diseases ##REF##17686874##[17]##, ##REF##10868621##[44]##, ##REF##8142663##[45]##. The concept that a vaccine based on T cell-mediated control would be effective in controlling HCMV diseases grew out of the pioneering work conducted by Riddell and colleagues, who showed that adoptive transfer of donor-derived virus-specific T cells alone were sufficient to reduce the incidence of HCMV disease in allogeneic hematopoietic stem cell transplant recipients ##REF##7577343##[46]##, ##REF##7675046##[47]##. Over the last few years there has been a series of attempts to develop a highly tailored vaccine strategy designed to induce T cell immunity against pp65 and/or IE-1 antigens or defined T cell epitopes from these antigens ##REF##11262198##[38]##, ##REF##15596812##[48]##, ##REF##17049414##[49]##.</p>", "<p>While these strategies provided specificity and safety, their application at the population level are rather limited. Thus other approaches which target multiple antigens might be an advantage by providing wider coverage in different ethnic groups. Furthermore, inclusion of a virus neutralization component in the vaccine formulation has been argued by many investigators, especially in the context of congenital HCMV infection. Indeed the chimeric vaccine developed in this study induced high avidity humoral responses and cellular immunity with a single formulation and provided wider coverage through the inclusion of multiple T cell epitopes restricted through a range of HLA class I and II alleles. Our initial studies with a mixture of adenoviral vectors encoding HCMV polyepitope sequence and gB protein showed that it was possible to induce both humoral and cellular immune responses without compromising the immunogenicity of individual components of the vaccine. Taking into consideration these observations, we designed a chimeric vaccine in which the encoding sequence for the extracellular domain of gB was covalently linked with the polyepitope sequence. Extensive studies with this formulation provided further evidence that co-delivery of gB and the polyepitope as a single polypeptide was highly efficient in generating neutralizing antibodies responses and virus-specific CD8⁺ and CD4⁺ T cell responses in a murine model and healthy virus carriers. Subsequently, we employed an experimental animal model system to determine whether immunisation of HLA A2 transgenic mice with Ad-gBCMVpoly is capable of reducing infection with a recombinant vaccinia virus expressing HCMV antigens (i.e. gB and IE-1). These mice not only showed induction of a strong CD4⁺ and CD8⁺ T cell response following immunisation but also acquired strong resistance to virus infection. Interestingly, Ad-gBCMVpoly immunized showed better protection against Vacc. gB when compared to Vacc.IE-1, which suggested that gB-specific CD4⁺ T cell responses could also inhibit Vacc.gB virus.</p>", "<p>Another important outcome of this study was the longevity of the immune responses induced by the chimeric HCMV vaccine which is particularly critical for the vaccine designed to control congenital infection/disease where long-term memory response over multiple years would be essential. Although the studies outlined here does not allow any firm conclusions on the efficacy of the chimeric polyepitope-based vaccine in humans, it does clearly show that a formulation based on gB and HCMV T cell epitopes can be used as immunogens to induce efficient humoral and T cell responses in vivo. It is important to stress here that a polyepitope-based vaccine for HCMV has a number of advantages over the traditionally proposed vaccines, which are based on either full-length HCMV antigens or synthetic peptide epitopes. There is now convincing evidence that polyepitope proteins are extremely unstable and are rapidly degraded by the proteasome dependent pathway as a result of their limited secondary and tertiary structure ##REF##7541138##[18]##. The rapid degradation of these polypeptides dramatically enhances endogenous presentation of peptide epitopes through the class I and II pathway. On the other hand the full-length HCMV protein antigens are unlikely to be degraded rapidly and may also initiate various intracellular signalling events leading to the interference of presentation of epitopes from other antigens ##REF##11166885##[50]##, ##REF##12028562##[51]##. Finally, the polyepitope-based vaccine is likely to overcome any potential problem of reinfection with different strains of HCMV and unique HLA types in different ethnic groups of the world.</p>", "<p>There is an emerging argument that HCMV vaccine efforts should focus on the development of formulation(s) which are designed to limit or prevent HCMV related diseases rather than to prevent infection itself ##REF##16337831##[11]##. This contention is supported by extensive studies in humans which revealed that although the immune responses generated during natural HCMV infection are unable to clear the latent virus, this response is sufficiently competent to keep the virus under control and restrict virus replication ##REF##12692225##[13]##, ##REF##16147978##[14]##, ##REF##15039282##[15]##. Furthermore, in immunocompromised patients such as HIV-infected individuals and transplant recipients, HCMV related pathogenesis is generally due to reactivation rather than primary infection. Considering the limited efficacy of the currently available HCMV vaccine formulations in protecting against infection in preclinical and clinical studies, we propose that a vaccine to limit or prevent HCMV related disease rather than infection itself is more realistic in the near future.</p>" ]

[]

[ "<p>Conceived and designed the experiments: RK. Performed the experiments: JZ MR LC CS. Analyzed the data: JZ MR LC CS RK. Contributed reagents/materials/analysis tools: LC. Wrote the paper: RK.</p>", "<p>Based on the life-time cost to the health care system, the Institute of Medicine has assigned the highest priority for a vaccine to control human cytomegalovirus (HCMV) disease in transplant patients and new born babies. In spite of numerous attempts successful licensure of a HCMV vaccine formulation remains elusive. Here we have developed a novel chimeric vaccine strategy based on a replication-deficient adenovirus which encodes the extracellular domain of gB protein and multiple HLA class I &amp; II-restricted CTL epitopes from HCMV as a contiguous polypeptide. Immunisation with this chimeric vaccine consistently generated strong HCMV-specific CD8⁺ and CD4⁺ T-cells which co-expressed IFN-γ and TNF-α, while the humoral response induced by this vaccine showed strong virus neutralizing capacity. More importantly, immunization with adenoviral chimeric vaccine also afforded protection against challenge with recombinant vaccinia virus encoding HCMV antigens and this protection was associated with the induction of a pluripotent antigen-specific cellular and antibody response. Furthermore, <italic>in vitro</italic> stimulation with this adenoviral chimeric vaccine rapidly expanded multiple antigen-specific human CD8⁺ and CD4⁺ T-cells from healthy virus carriers. These studies demonstrate that the adenovirus chimeric HCMV vaccine provides an excellent platform for reconstituting protective immunity to prevent HCMV diseases in different clinical settings.</p>" ]

[]

[ "<p>The authors wish to thank Dr Judy Tellam for assistance in preparation of the adenovirus constructs.</p>" ]

[ "<fig id=\"pone-0003256-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g001</object-id><label>Figure 1</label><caption><title>Schematic representation of the construction of a recombinant adenovirus that expresses a synthetic DNA encoding for a polyepitope protein which contains 46 HCMV T-cell epitopes (see box and ##TAB##0##Table 1##).</title><p>Each of the alternate epitope sequences are shown in bold letters. The DNA sequence encoding this polyepitope protein was constructed using overlapping epitope sequence specific primers (referred to as CMV1 to CMV20) as described in the “<xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>” section. This synthetic insert was first cloned into a pBluescript II KS⁺ phagemid, prior to cloning into the pShuttle vector. After amplification in <italic>E.coli</italic>, the expression cassette from pShuttle was excised and ligated into the Ad5F35 expression vector. Following linearization of the DNA using Pac I restriction enzyme, the recombinant Ad5F35 vector was packaged into infectious adenovirus by transfecting HEK 293 cells, and recombinant adenovirus (referred to as Ad-CMVpoly) was harvested from transfected cells by repeated freeze-thawing cycles.</p></caption></fig>", "<fig id=\"pone-0003256-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g002</object-id><label>Figure 2</label><caption><title>HCMV epitope-specific T cell response following primary and secondary immunisation with Ad-CMVpoly vaccine.</title><p>Two different groups of HHD-2 mice were immunised intramuscularly with Ad-CMVpoly (7.5×10⁸ PFU/mouse). <italic>A &amp; B</italic>, Following primary immunisation, animals were sacrificed 10 days post immunisation and HCMV epitope-specific reactivity was assessed in the splenocytes by ELISPOT assays as described in the “<xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>” section. The epitopes tested for T cell reactivity were VLE (IE-1), NLV (pp65), RIF (pp65), VLA (IE-1), IIY (IE-2) AVG (gB). <italic>C &amp; D</italic>, For immunological analysis following secondary immunisation, animals were given booster immunisation (7.5×10⁸ PFU/mouse) 100 days after primary immunisation and then sacrificed 10 days post secondary immunisation. HCMV epitope-specific reactivity was assessed as described above. <italic>A &amp; C</italic> shows ELISPOT data based on the pooled HLA A2-restricted HCMV epitopes, while <italic>B &amp; D</italic> shows relative T cell responses to individual epitopes. The results are expressed as Mean±SE of spot forming cells (SFC) per 10⁶ splenocytes from four individually tested mice. <italic>E,</italic> Anti-adenovirus antibody titre induced by immunisation with Ad-CMVpoly. Serum samples were collected at different time points after immunisation and anti-adenovirus titres were evaluated by ELISA as described in the “<xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>” section. All statistical analyses were conducted using GraphPad Prism 4 software.</p></caption></fig>", "<fig id=\"pone-0003256-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g003</object-id><label>Figure 3</label><caption><title>HCMV-specific effector and memory cellular and humoral immune responses following immunisation with a mixture of Ad-CMVpoly and Ad-gB vaccines.</title><p>\n<italic>A,</italic> HCMV-specific CD8+ T cell responses following immunisation with Ad-CMVpoly and Ad-gB. These T cell responses were assessed using ELISPOT assays on day 10, 25 and 75 post immunisation. The results are expressed as Mean±SE of spot forming cells (SFC) per 10⁶ splenocytes. <italic>B,</italic> gB-specific antibody responses in serum samples from immunised mice on days 10, 25 and 75. Serum samples on day 0 were collected before the immunisation. <italic>C,</italic> Virus neutralizing capacity of antibody responses induced in HHD-2 mice immunised with Ad-CMVpoly and Ad-gB. Serum samples from these mice were pre-incubated with HCMV virus Ad169 and then these virus preps were used to infect MRC-5. Following overnight incubation virus infectivity was assessed using IE-1/IE-2 expression as outlined in the “<xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>” section. <italic>D,</italic> Avidity maturation of gB-specific antibody responses in Ad-CMVpoly and Ad-gB immunised mice. <italic>E,</italic> Immunoglobulin subclass analysis of gB-specific antibody responses in HHD-2 vaccinated mice. Serum samples were collected from three different groups of mice on days 10, 25 and 75 post-immunisation. A minimum of five mice from each group were assessed for HCMV epitope-specific T cell reactivity and humoral immune responses. All statistical analyses were conducted using GraphPad Prism 4 software.</p></caption></fig>", "<fig id=\"pone-0003256-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g004</object-id><label>Figure 4</label><caption><title>HCMV-specific effector and memory humoral and cellular immune responses following immunisation with Ad-gBCMVpoly vaccine.</title><p>\n<italic>A,</italic> HCMV-specific CD8+ T cell responses following immunisation with Ad-gBCMVpoly. These T cell responses were assessed using ELISPOT assays on day 10, 25 and 75 post immunisation. The results are expressed as Mean±SE of spot forming cells (SFC) per 10⁶ splenocytes. <italic>B,</italic> gB-specific antibody responses in serum samples from immunised mice on days 10, 25 and 75. Serum samples on day 0 were collected before the immunisation. <italic>C,</italic> Virus neutralizing capacity of antibody responses induced following immunisation with Ad-gBCMVpoly. Serum samples from these mice were pre-incubated with HCMV virus Ad169 and then these virus preps were used to infect MRC-5. Following overnight incubation virus infectivity was assessed using IE-1/IE-2 expression as outlined in the “<xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>” section. <italic>D,</italic> Avidity maturation of gB-specific antibody responses in Ad-gBCMVpoly immunised mice. <italic>E,</italic> Immunoglobulin subclass analysis of gB-specific antibody responses in HHD-2 vaccinated mice. Serum samples were collected from three different groups of mice on days 10, 25 and 75 post-immunisation. A minimum of five mice from each group were assessed for HCMV epitope-specific T cell reactivity and humoral immune responses. All statistical analyses were conducted using GraphPad Prism 4 software.</p></caption></fig>", "<fig id=\"pone-0003256-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g005</object-id><label>Figure 5</label><caption><title>Cytokine expression by HCMV-specific CD8⁺ T cells from Ad-gBCMVpoly immunised HHD-2 mice.</title><p>\n<italic>A &amp; B,</italic> Ex vivo expression of IFN-γ, TNF-α and CD107a by antigen-specific CD8⁺ T-cells from Ad-gBCMVPpoly vaccinated mice 10 days post-vaccination. Splenocytes were prepared from 3 individual HHD-2 mice 10 days post-vaccination and cultured with individual HCMV peptides overnight. Anti-CD107a antibody and Brefeldin A was added during the last 6 and 5 hours incubation respectively, followed by T cell surface marker and intracellular cytokine staining. Data represent the percentage of IFN-γ expressing CD8⁺ T cells (<italic>A</italic>) and percentage of single, double or triple markers expressing cells among IFN-γ expressing CD8⁺ T cells (<italic>B</italic>). <italic>C–E,</italic> Expression of IFN-γ and/or TNF-α by <italic>in vitro</italic> expanded antigen-specific CD8⁺ T-cells from Ad-gBCMVPpoly vaccinated mice 10 days post-vaccination. Splenocytes pooled from three immunised mice were first stimulated with individual HCMV peptide epitope-pulsed splenocytes for 2 weeks in the presence of recombinant mouse IL-2 at the concentration of 10 IU/ml, then cultured with MRC-5 cells pulsed with corresponding HCMV peptide epitope overnight for intracellular cytokine assay. The HCMV peptide epitopes tested here were VLE (IE-1), NLV (pp65), RIF (pp65), VLA (IE-1) at the concentration of 1 µg/ml. Data represent the percentage of IFN-γ (<italic>C</italic>), TNF-α (<italic>D</italic>) and IFN-γ &amp; TNF-α (<italic>E</italic>) expressing CD8⁺ T-cells. ** (p&lt;0.005) and * (p&lt;0.05) show statistically significant difference between indicated CMV peptide epitopes and control epitope (<italic>A</italic>). Data from one out three experiments with similar results was shown in <italic>C–E</italic>. All statistical analyses were conducted using GraphPad Prism 4 software.</p></caption></fig>", "<fig id=\"pone-0003256-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g006</object-id><label>Figure 6</label><caption><title>Ad-gBCMVpoly induced protection against challenge with recombinant vaccinia expressing gB or IE-1 protein.</title><p>HHD-2 mice were immunised with Ad-gbCMVpoly vaccine and 21 days following vaccination these mice were challenged (intraperitoneal) with recombinant vaccinia encoding gB (Vacc.gB), IE1 protein (Vacc.IE-1) or control vaccinia (Vacc.TK⁻) at 10⁷ pfu virus/mouse. Ovaries, splenocytes and peripheral blood samples were collected four days later and used for assessing viral load, antigen-specific T cell response and gB-specific antibody response. <italic>A,</italic> Virus titres in the ovaries of Ad-gBCMVpoly immunised or naïve HHD-2 mice challenged with Vacc.IE-1, Vacc.gB or Vacc.TK⁻. <italic>B,</italic> gB-specific antibody response in Ad-gBCMVpoly immunised or naïve HHD-2 mice challenged with Vacc.gB or Vacc.TK⁻. <italic>C,</italic>\n<italic>Ex vivo</italic> gB-specific CD3⁺CD4⁺ T cell response in Ad-gBCMVpoly immunised or naïve HHD-2 mice challenged with Vacc.gB or Vacc.TK⁻. Splenocytes from these mice were stimulated with recombinant gB protein (40 µg/ml) overnight and then assessed for IFN-γ production using intracellular cytokine assay. <italic>D,</italic>\n<italic>Ex vivo</italic> IE-1-specific CD3⁺CD8⁺ T cell response in Ad-gBCMVpoly immunised or naïve HHD-2 mice challenged with Vacc.IE-1 or Vacc.TK⁻. Splenocytes from these mice were stimulated with the peptide epitope VLEETSVML (1 µg/ml) overnight and then assessed for IFN-γ production using intracellular cytokine assay. <italic>E,</italic>\n<italic>Ex vivo</italic> expression of IFN-γ and/or TNF-α by antigen-specific CD8⁺ and CD4⁺T-cells from Ad-gBCMVPpoly vaccinated mice, challenged with recombinant vaccinia encoding IE-1 or gB. Splenocytes from immunised mice stimulated with either gB protein or IE-1 peptide epitope overnight for intracellular cytokine assay. Data represent the percentage of TNF-α and IFN-γ &amp; TNF-α expressing CD4⁺ or CD8⁺ T-cells. All statistical analyses were conducted using GraphPad Prism 4 software.</p></caption></fig>", "<fig id=\"pone-0003256-g007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g007</object-id><label>Figure 7</label><caption><title>Expansion of gB-specific T cells following in vitro stimulation of human PBMC with Ad-gBCMVpoly.</title><p>PBMC from a panel of healthy virus carriers (referred to as D1–D17) were co-cultured with autologous PBMC infected with Ad-gBCMVpoly (MOI: 5∶1 or 1∶1) at a responder to stimulator ratio of 2∶1. These cultures were supplemented with rIL-2 (10 U/ml) on day 3 and every 3–4 days thereafter. On day 14, these T cell cultures were tested against a panel of pooled overlapping gB peptides (20 aa long, overlapping by 10 aa) using intracellular cytokine assays. The data presented in the figure shows the percentage of gB-specific CD8+ and CD4+ T cell recovered from each donor following stimulation with Ad-gBCMVpoly.</p></caption></fig>", "<fig id=\"pone-0003256-g008\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.g008</object-id><label>Figure 8</label><caption><title>\n<italic>Ex vivo</italic> stimulation of human PBMC with Ad-gBCMVpoly.</title><p>PBMC from healthy virus carriers were co-cultured with autologous PBMC infected with Ad-gBCMVpoly (MOI: 5∶1) at a responder to stimulator ratio of 2∶1 for 6 h. These T cells were then co-stained with anti-CD3, anti-CD8, PE-labelled anti-INF-γ antibody and APC-labelled MHC-peptide multimers. <italic>A–F</italic>, Percentage of CD8+ T cells expressing INF-γ following mock stimulation or Ad-gBCMVpoly stimulation. <italic>G–L</italic>, Percentage of MHC-peptide pentamer-positive cells expressing IFN-γ following mock stimulation or Ad-gBCMVpoly stimulation. Pentamers used for each of the HCMV epitopes are indicated in G–L.</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003256-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.t001</object-id><label>Table 1</label><caption><title>List of HLA-restricted HCMV T cell epitopes included in the Ad-CMVpoly and Ad-gBCMVpoly.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Epitope order number</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Epitope Sequences</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HLA restriction</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HCMV Antigens</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Parent protein (UL)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Amino acid location</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Abbreviated code</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Reference</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VTEHDTLLY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">245–253</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VTE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KPGKISHIMLDVA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B35/DR3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">283–295</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KPG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NTDFRVLEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">657–665</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NTD</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLEETSVML</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">316–324</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NLVPMVATV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">495–503</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NLV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##8892876##[55]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIFAELEGV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">522–530</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IIYTRNHEV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL122</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">244–251</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IIY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15726667##[16]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CVETMCNEY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">279–287</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CVE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLAELVKQI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">81–89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AVGGAVASV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">731–739</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AVG</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TVRSHCVSK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">52–60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TVR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IMREFNSYK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">682–690</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IMR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GPISHGHVLK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16–24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GPI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##11986243##[56]##, ##REF##11220618##[57]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">14</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AYAQKIFKIL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A23/A24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65?</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">248–257</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AYA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QYDPVAALF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">341–349</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QYD</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YVKVYLESF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">223–231</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YVK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DIYRIFAEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">519–527</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DIY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VFETSGGLVV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">420–429</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VFE</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##11986243##[56]##, ##REF##11220618##[57]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARDHLAVL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp150</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">101–109</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARD</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARAKKDEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B7/B8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">192–200</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TRATKMQVI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B57/B58/Cw6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">211–219</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TRA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HELLVLVKKAQL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DR11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gH</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">276–287</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15459005##[58]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DDYSNTHSTRYV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DR7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">216–227</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DDY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15459005##[58]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QIKVRVDMV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">88–96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QIK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RRRHRQDAL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B8/B27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">539–547</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">RRR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ARVYEIKCR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DNAse</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">274–282</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ARV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NVRRSWEEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp150</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">212–220</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NVR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CPSQEPMSIYVY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">103–114</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CPS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15726667##[16]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">29</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QARLTVSGL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B7</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">158–166</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAR</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">30</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELKRKMMYM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B8</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL123</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">199–207</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IPSINVHHY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">123–131</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IPS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##UREF##4##[59]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEQPTETPP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">IE2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL122</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">381–389</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEQ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15726667##[16]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YAYIYTTYL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">gB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">153–161</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YAY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15726667##[16]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEFFWDANDIY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B44/DRw52</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">511–521</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YEQHKITSY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">372–380</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">YEQ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEPMSIYVY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">106–114</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SEHPTFTSQY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">364–373</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SEH</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12692225##[13]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAIRETVEL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B57/B58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">331–339</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##15726667##[16]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CEDVPSGKL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B40/60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">232–240</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CED</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12947002##[60]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KMQVIGDQY</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B40/60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">215–223</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">KMQ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12947002##[60]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ATVQGQNLK</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">501–509</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ATV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12947002##[60]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HERNGFTVL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B40/60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">267–275</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HER</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12947002##[60]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DALPGPCI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">546–552</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DAL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12947002##[60]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">44</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VYALPLKML</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">A24</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">113–121</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VYA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##11792066##[61]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PTFTSQYRIQGKL</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B38/DR11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">367–379</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PTF</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##8892876##[55]##, ##REF##9971792##[62]##\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QMWQARLTV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B52</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">pp65</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">UL83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">155–163</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">QMW</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n##REF##12085315##[30]##\n</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003256-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.t002</object-id><label>Table 2</label><caption><title>CD8⁺ T cell responses in healthy virus carriers following stimulation with Ad-gBCMVpoly<xref ref-type=\"table-fn\" rid=\"nt101\">a</xref>.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HCMV Epitopes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D1 (A1 A29 B8 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D2 (A1 A3 B7 B8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D3 (A1 A24 B8 B14)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D4 (A23 A24 B27 B41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D5 (A11 A24 B35 B60)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D6 (A1 A31 B8 B51)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D7 (A1 A11 B8 B35)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D8 (A24 A26 B15 B62)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D9 (A2 A11 B13 B27)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D10 (A2 B35 B57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D11 (A3 A23 B35 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D12 (A24 A26 B35 B38)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D13 (A1 A2 B7 B57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D14 (A1 A2 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D15 (A31 A33 B35 B58)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D16 (A1 A2 B7 B37 Cw6&amp;7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D17 (A1 A1 B8 B8 Cw7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D18 (A2 A68 B8 B15 Cw4&amp;7)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VTE (HLA A1; pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++<xref ref-type=\"table-fn\" rid=\"nt102\">b</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KPG (HLA B35; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NTD (HLA A1; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLE (HLA A2; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NLV (HLA A2; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIF (HLA A2 pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IIY (HLA A2 IE-2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CVE (HLA A1; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLA (HLA A2; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">AVG (HLA A2; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TVR (HLA A3; pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IMR (HLA A3; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GPI (HLA A11; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">AYA (HLA A23/A24; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QYD (HLA A24; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YVK (HLA A26; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DIY (HLA A26; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VFE (HLA A29; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARD (HLA B7; pp150)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARA (HLA B7/B8; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TRA (HLA B57/B58; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HEL (HLA DR11; gH)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DDY (HLA DR7; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QIK (HLA B8; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RRR (HLA B8/B27; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ARV (HLA B27; pp28)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NVR (HLA B7; pp150)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CPS (HLA B35; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAR (HLA B7; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELR (HLA B8; IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IPS (HLA B35; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEQ (HLA B41; IE-2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YAY (HLA B41; gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEF (HLA B44; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YEQ(HLA B44; pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEP (HLA B44; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">SHE (HLA B44; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAI (HLA B57/B58 pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CED (HLA B40/60; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KMQ (HLA B40/60; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ATV (HLA A11; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HER (HLA B40/60; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DAL(HLA B51; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VYA (HLA A24; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PTF (HLA B38; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QMW (HLA B52; pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003256-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003256.t003</object-id><label>Table 3</label><caption><title>CD4⁺ T cell responses in healthy virus carriers following stimulation with Ad-gBCMVpoly<xref ref-type=\"table-fn\" rid=\"nt103\">a</xref>.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HCMV Epitopes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D1 (A1 A29 B8 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D2 (A1 A3 B7 B8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D3 (A1 A24 B8 B14)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D4 (A23 A24 B27 B41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D5 (A11 A24 B35 B60)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D6 (A1 A31 B8 B51)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D7 (A1 A11 B8 B35)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D8 (A24 A26 B15 B62)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D9 (A2 A11 B13 B27)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D10 (A2 B35 B57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D11 (A3 A23 B35 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D12 (A24 A26 B35 B38)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D13 (A1 A2 B7 B57)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D14 (A1 A2 B44)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D15 (A31 A33 B35 B58)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D16 (A1 A2 B7 B37 Cw6&amp;7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D17 (A1 A1 B8 B8 Cw7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">D18 (A2 A68 B8 B15 Cw4&amp;7)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VTE (pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++<xref ref-type=\"table-fn\" rid=\"nt104\">b</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KPG (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NTD (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLE (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NLV (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RIF (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IIY (IE-2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CVE (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VLA (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">AVG (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TVR (pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IMR (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">GPI (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">AYA (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QYD (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YVK (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DIY (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VFE (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARD (pp150)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KARA (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TRA (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HEL (gH)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DDY (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QIK (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">RRR (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ARV (pp28)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NVR (pp150)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CPS (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAR (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ELR (IE-1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IPS (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">FEQ (IE-2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YAY (gB)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEF (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">YEQ(pp50)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QEP (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">SHE (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">QAI (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">CED (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">KMQ (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">ATV (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">HER (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">DAL(pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VYA (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PTF (pp65)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">+/−</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">++++</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td colspan=\"19\" align=\"left\" rowspan=\"1\">QMW (pp65)</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><label>a</label><p>T cell response was assessed by intracellular cytokine assays for the secretion of IFN-γ.</p></fn><fn id=\"nt102\"><label>b</label><p>Proportion of IFN-γ-secreting CD8⁺ T cells +/−: &lt;1%, ++: 1–4%, +++: 5–10%, ++++: &gt;10%.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><label>a</label><p>T cell response was assessed by intracellular cytokine assays for the secretion of IFN-γ.</p></fn><fn id=\"nt104\"><label>b</label><p>Proportion of IFN-γ-secreting CD4⁺ T cells +/−: &lt;1%, ++: 1–4%, +++: 5–10%, ++++: &gt;10%.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>This work is supported by the National Health and Medical Research Council (Australia). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003256.g001\"/>", "<graphic xlink:href=\"pone.0003256.g002\"/>", "<graphic id=\"pone-0003256-t001-1\" xlink:href=\"pone.0003256.t001\"/>", "<graphic xlink:href=\"pone.0003256.g003\"/>", "<graphic xlink:href=\"pone.0003256.g004\"/>", "<graphic xlink:href=\"pone.0003256.g005\"/>", "<graphic xlink:href=\"pone.0003256.g006\"/>", "<graphic xlink:href=\"pone.0003256.g007\"/>", "<graphic id=\"pone-0003256-t002-2\" xlink:href=\"pone.0003256.t002\"/>", "<graphic id=\"pone-0003256-t003-3\" xlink:href=\"pone.0003256.t003\"/>", "<graphic xlink:href=\"pone.0003256.g008\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>\n<italic>Vibrio cholerae</italic>, the causative agent of cholera, harbors two non-homologous circular chromosomes ##REF##10952301##[1]##. The majority of genes believed to be necessary for the basic life processes of <italic>V. cholerae</italic> are carried on the 2.96 Mbp chromosome I, whereas the 1.07 Mbp chromosome II only harbors a few essential genes ##REF##10952301##[1]##. The preferential transcription of genes from chromosome II during colon colonization ##REF##12552086##[2]## suggests that this genomic organization is important for pathogenicity. Likewise, other bacteria with multiple chromosomes can adopt several different life cycles ##REF##9928484##[3]##, which led to the idea that multipartite genomes offer a selective advantage for the adaptation to very different environmental conditions.</p>", "<p>Nevertheless, most bacteria harbor a single chromosome. In contrast, there is no apparent limit to the size and numbers of chromosomes harbored by eukaryotic cells. An important difference between bacteria and eukaryotes is that specific machineries appear to exist for the coordinated maintenance of each chromosome of a given bacterium, whereas eukaryotic cells possess a single global system for all chromosomes ##REF##17197419##[4]##–##REF##15612922##[12]##. For instance, the two <italic>V. cholerae</italic> chromosomes harbor different partition systems ##REF##17197419##[4]##,##REF##17158745##[7]## and initiation of their replication is governed by different mechanisms ##REF##17557077##[6]##,##REF##12941279##[8]##,##REF##16923911##[9]##. In addition, many features of <italic>V. cholerae</italic> chromosome II, such as its partition system, are plasmid-like, which raised questions concerning its chromosomal nature ##REF##10952301##[1]##,##REF##16452432##[10]##,##REF##11121066##[13]##. Plasmid replication and segregation are generally not coordinated with the bacterial cell cycle ##REF##15882408##[14]##, further raising questions on the mechanisms ensuring the synchronous management of chromosome I and II.</p>", "<p>A second major difference between bacteria and eukaryotes is intrinsic to the structure of chromosomes: in bacteria, chromosomes are generally covalently closed circular DNA molecules while they are linear in eukaryotes. DNA circularity can result in the formation of chromosome dimers by homologous recombination ##REF##16577496##[15]##, which poses a barrier to the segregation of genetic information if they are not resolved before cell division (##FIG##0##Figure 1A##). Indeed, inactivation of chromosome dimer resolution (CDR) in <italic>Escherichia coli</italic> results in ∼15% cell death per generation under laboratory growth conditions ##REF##10760161##[16]##, which corresponds to the estimated rate of chromosome dimers formed at each cell generation ##REF##9829936##[17]##. This prompted us to study how dimer resolution is achieved on each of the two <italic>V. cholerae</italic> chromosomes.</p>", "<p>The mechanism of CDR was originally elucidated in <italic>E. coli</italic>. In this organism, it depends on the addition of a crossover at <italic>dif</italic>, a 28bp site located at the opposite of the origin of replication on the chromosome, by two related tyrosine recombinases, XerC and XerD (##FIG##0##Figure 1A##; see ##UREF##0##[18]## for a review). In addition, CDR depends on two activities of a cell division protein, FtsK. First, FtsK functions as a DNA pump anchored in the septum ##REF##16916635##[19]##,##REF##11832210##[20]##. It loads on DNA trapped within the division septum due to dimer formation (##FIG##0##Figure 1A##). FtsK loading is oriented by specific DNA motifs, the KOPS, which dictates the orientation of translocation (##FIG##0##Figure 1A##; ##REF##17041597##[21]##). KOPS are skewed on the two replichores of the chromosome with <italic>dif</italic> located at the junction of their polarity ##REF##16301526##[22]##,##REF##16211009##[23]##. Thus, <italic>dif</italic> sites carried by a dimer are brought together by FtsK translocation (##FIG##0##Figure 1A##). Second, FtsK serves to activate recombination at <italic>dif</italic> via a direct interaction with XerD ##REF##16553881##[24]##,##REF##12823825##[25]##. <italic>dif</italic> contains two 11bp binding sites for XerC and XerD, separated by a central region at the outer boundary of which recombination occurs. The interaction between XerD and FtsK allows XerD to perform a first pair of strand exchanges ##REF##11832210##[20]##, resulting in the formation of a Holliday junction (HJ). This HJ is converted to a crossover by a second pair of strand exchanges, which is catalyzed by XerC independently of FtsK (##FIG##0##Figure 1B##, chromosomal pathway). Thus, in <italic>E. coli</italic>, the requirement for FtsK to bring <italic>dif</italic> sites together and to activate the catalytic activity of XerD permits coordination of CDR with the last stage of cell division ##UREF##1##[26]##.</p>", "<p>The <italic>E. coli</italic> pathway of CDR is not universal. For instance, <italic>Streptococci</italic> and <italic>Lactococci</italic> possess only a single tyrosine recombinase, XerS, for CDR ##REF##17630835##[27]##. Plasmid and viruses have also adopted different site-specific recombination systems to avoid multimerization of their genome. In <italic>E. coli</italic>, some of them depend on their own recombinases, such as phage P1, which encodes the Cre tyrosine recombinase ##REF##6220808##[28]##, while others use the two Xer recombinases of their host ##REF##8195072##[29]##,##REF##8402918##[30]##. In the later case, XerC-catalysis initiates recombination independently of FtsK (##FIG##0##Figure 1B##, plasmid pathway, ##UREF##0##[18]##). In this case, however, recombination requires ∼200bp of accessory sequences flanking the plasmid sites and which are bound by accessory proteins.</p>", "<p>Orthologues of <italic>E. coli xerC</italic>, <italic>xerD</italic> and <italic>ftsK</italic> are readily identified on the larger chromosome of the <italic>V. cholerae</italic> strain N16961 (<italic>xerC</italic>\n^Vc, <italic>xerD</italic>\n^Vc, <italic>ftsK</italic>\n^Vc, ##SUPPL##0##Figure S1##) whereas its second chromosome does not encode any site-specific recombination system that could be implicated in CDR apart from the superintegron integrase (IntIA, ##SUPPL##0##Figure S1##). N16961 chromosome I and II both carry <italic>dif</italic>-like sequences, <italic>dif</italic>1 and <italic>dif</italic>2, which were originally identified as integration sites for the Cholera Toxin phage, CTXφ ##REF##12050668##[31]##. The weak filamentous phenotype of <italic>V. cholerae</italic> cells deleted for <italic>xerC</italic> or <italic>dif</italic>1 fits with a defect in CDR ##REF##12050668##[31]##. However, two features of the <italic>V. cholerae</italic> Xer recombination system, which could be linked to the co-existence of distinct, non-homologous chromosomes inside the same bacterium, were intriguing. First, <italic>dif</italic>2 differs from the <italic>dif</italic> consensus of γ-Proteobacteria by 5 bases, four of which belong to the central region (##FIG##0##Figure 1B##). Such a divergence is only found on plasmid sites, which, coupled with the other plasmid-like features of chromosome II, suggested that chromosome II dimer resolution might follow a plasmid pathway. Second, it was reported that the position of cleavage of XerD^Vc on <italic>dif</italic>1 might differ from the one of its <italic>E. coli</italic> orthologue on <italic>dif</italic>\n##REF##15522078##[32]##, even if <italic>dif</italic>1 differs from the <italic>dif</italic> consensus of γ-Proteobacteria by only 2 bases (##FIG##0##Figure 1B##), further raising questions on the exact mechanisms coordinating CDR of chromosome I and II with the cell cycle.</p>", "<p>Here, we present the first formal study of CDR in <italic>V. cholerae</italic> and measure the rate of chromosome dimer formation on its two chromosomes under laboratory growth conditions. We show that the cell division protein FtsK^Vc is required for recombination by XerC^Vc and XerD^Vc at <italic>dif</italic>1 and <italic>dif</italic>2. In addition, we show that the activity of FtsK^Vc is directed by specific DNA motifs, which display the same skewed distribution on the two chromosomes, <italic>dif</italic>1 and <italic>dif</italic>2 being located at the junction of their polarity. Taken together, these results suggest that the same FtsK-dependent mechanism coordinates dimer resolution on each of the two <italic>V. cholerae</italic> chromosomes with cell division. Chromosome II dimer resolution thus stands as a bona fide chromosomal process.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Strains, Plasmids, and Media</title>", "<p>All growth experiments were done in LB-Lennox. Strains and plasmids are listed in ##SUPPL##4##Text S1##. Briefly, <italic>V. cholerae</italic> strains were derived from N16961 ##REF##10952301##[1]## by allele exchange using pDS132 derivatives ##REF##15109831##[38]## and <italic>E. coli</italic> β2163 as a donor strain ##UREF##2##[39]##. <italic>E. coli</italic> strains used for <italic>in vivo</italic> plasmid resolution assays and for growth competition were engineered as previously described in ##REF##12823825##[25]##,##REF##15522074##[40]##. Mutations were confirmed by PCR and sequencing.</p>", "<title>Growth Competition Assay</title>", "<p>For growth competitions, <italic>E. coli</italic> cells were grown at 37°C with a 1000× dilution in fresh media every 12h ##REF##15522074##[40]##. Because of their higher growth rate, <italic>V. cholerae</italic> cells were grown at 30°C with a 10000× dilution every 12h. The numbers of CFU of mutated and parental cells in the cultures were determined by plating on cognate antibiotic plates every 12 or 24h, depending on the mutant growth defect. These numbers were used to calculate the number of generation of the parent cells between each time points and the CFU ratio of mutated versus parent cells at each time point. This ratio varies exponentially with the number of generations. The proportion of cells that the mutant strain fails to produce at each doubling time of its parent is deduced from the coefficient of this exponential. This ratio is a good estimation of the rate of dimer formation (##SUPPL##4##Text S1##).</p>", "<title>In Vitro Xer Assays</title>", "<p>\n<italic>V. cholerae</italic> MBP-XerD and MBP-XerC recombinases were purified using nickel, amylose and heparin columns. The MBP tag was removed by thrombin digestion. <italic>dif</italic>1 and <italic>dif</italic>2 synthetic suicide substrates (##SUPPL##4##Text S1##) were obtained by annealing synthetic oligonucleotides purified by PAGE. 5′-end labeling of oligonucleotides was performed using T4 DNA polynucleotide kinase and [³²P] γ-ATP and 3′end labeling using terminal transferase and [³²P] α-ddATP. Reactions were performed in 20 mM Tris-HCl (pH 7.5), 50 mM NaCl, 0.1mM EDTA, 1 μg/ml of BSA, 40% glycerol and 0.2 pmol of radiolabeled probe for 2 hours at 37°C. Covalent complexes were analyzed by 12% SDS-PAGE and cleavage sites by 12% urea-PAGE. Radioactivity was detected on a STORM (GE Healthcare).</p>", "<title>In Vivo Plasmid Resolution Assays</title>", "<p>\n<italic>E. coli</italic> cells were transformed with the FtsK expression vector and then with the Xer recombination reporter plasmid, as described in ##REF##12823825##[25]##. 10 transformant colonies were pooled in 1 ml of LB, diluted 100× in LB and grown to 0.6 OD at 37°C. Cells were then grown for an extra 2 hours at 37°C in the presence of 0.5% arabinose to induce FtsK production, unless otherwise indicated. Plasmid DNA was hydrolyzed with <italic>Nde</italic>I (single cutter). Recombination efficiency was computed as the amount of replicative product over the sum of the amount of substrate and of replicative product, which were separated by agarose gel electrophoresis and detected with SybrGreen staining using a LAS-3000 (Fuji Life Science).</p>", "<title>Bioinformatics Analysis of Motifs Distribution</title>", "<p>Leading strands were defined as the DNA strand reported in Genbank files downstream of the replication origin up to the terminus and the reverse complement strand from the terminus to the origin. The terminus position was chosen as the first nucleotide of the CDR site. Skew statistical significance was assessed by calculating the probability that the observed skew occurred by chance taking into account the fact that G-rich motifs are likely to be more frequent on the leading strand because of GC skew, as previously described ##REF##17941709##[41]##. Analysis on chromosome II was performed on a chimeric chromosome where the superintegron has been removed because this element carries more than 100 repetitions of the <italic>att</italic>C integration site, which hides the signal provided by octamer motifs.</p>" ]

[ "<title>Results</title>", "<title>Chromosome Dimer Formation in <italic>V. cholerae</italic>\n</title>", "<p>The growth of <italic>V. cholerae</italic> strains deficient in CDR was directly compared to the growth of their parental strain in competition experiments in rich media (##FIG##1##Figure 2##). These experiments revealed a defect of 5.8% and 3% per cell per generation for Δ<italic>dif</italic>1 and Δ<italic>dif</italic>2 cells, respectively, compared to their wild type counterparts. Since these growth defects were entirely suppressed in a <italic>rec</italic>A background (##FIG##1##Figure 2##), they directly reflect the rates of dimer formation on chromosome I and II, f_dimer\n^Chr1 and f_dimer\n^Chr2 (See <xref ref-type=\"sec\" rid=\"s4\">Material and Methods</xref>). The 8.6% growth defect of <italic>xer</italic>C^Vc cells, which was also suppressed in a <italic>rec</italic>A background, reflects the total rate of chromosome dimer formation in <italic>V. cholerae</italic>, f_dimer\n^Chr1+2 (##FIG##1##Figure 2##). Interestingly, f_dimer\n^Chr1+2 equals 1−(1−f_dimer\n^Chr1)(1−f_dimer\n^Chr2), indicating that dimer formation on the two <italic>V. cholerae</italic> chromosomes is independent.</p>", "<title>In Vitro Cleavage by the <italic>V. cholerae</italic> recombinases on <italic>dif</italic>1 and <italic>dif</italic>2</title>", "<p>Recombinase-mediated strand cleavage can be assayed <italic>in vitro</italic> using suicide substrates that contain a nick opposite of the position of cleavage (##FIG##2##Figure 3A##). Cleavage of the continuous strand of a suicide substrate generates a double strand break that prevents re-ligation (##FIG##2##Figure 3B##). This leads to (i) the accumulation of covalent protein/DNA complexes between the attacking recombinase and the 5′-end fragment of the continuous strand and (ii) the accumulation of free 3′-end fragments of the continuous strand (##FIG##2##Figure 3B##). XerC^Ec and XerD^Ec each cleave a specific strand on <italic>dif</italic>\n^Ec. The strand cleaved by XerC^Ec is termed Top strand. The strand cleaved by XerD^Ec is termed Bottom strand. Following this convention, suicide substrates in which the continuous strand is expected to be cleaved by XerC^Vc are called Top strand suicide substrates and suicide substrates in which the continuous strand is expected to be cleaved by XerD^Vc are called Bottom strand suicide substrates (##FIG##2##Figure 3A##).</p>", "<p>Labeling the 5′-end of the continuous strand of suicide substrates allows the detection of covalent recombinase/DNA complexes (##FIG##2##Figure 3C##). The molecular weight of XerC^Vc and XerD^Vc being very similar, we used a maltose binding protein fusion of XerC^Vc (MBPXerC^Vc) in conjunction with XerD^Vc to avoid any confusion between the two possible covalent complexes. For both <italic>dif</italic>1 and <italic>dif</italic>2, MBPXerC^Vc-DNA covalent complexes accumulated when Top strand suicide substrates were used (##FIG##2##Figure 3C##, T1 and T2, respectively), indicating that XerC^Vc cleaves the Top strands of <italic>dif</italic>1 and <italic>dif</italic>2. Furthermore, XerD^Vc-DNA covalent complexes accumulated when Bottom strand suicide substrates were used (##FIG##2##Figure 3C##, B1 and B2), indicating that XerD cleaves the bottom strands of <italic>dif</italic>1 and <italic>dif</italic>2.</p>", "<p>The position of cleavage of XerC^Vc and XerD^Vc were then determined by comparing of the length of the free DNA fragments liberated by recombinase cleavage to a ladder obtained by chemical cleavage at purine bases of the suicide substrates (##FIG##2##Figure 3D##). To this aim, the continuous strands of the suicide substrates were labeled on their 3′ end. Cleavage by tyrosine recombinases generates a 5′OH DNA extremity whereas chemical cleavage leaves a 5′ phosphate. As a consequence, the free DNA fragments had to be first phosphorylated by kinase treatment (##FIG##2##Figure 3D##, PNK) in order to be compared with the chemical cleavage ladder (##FIG##2##Figure 3D##, G+A). We thus found that XerC^Vc and XerD^Vc cleave DNA at the junction between their respective binding site and the central region of <italic>dif</italic>1 and <italic>dif</italic>2 (##FIG##2##Figure 3D##, black arrows).</p>", "<title>FtsK-Dependent Recombination at <italic>dif</italic>1 and <italic>dif</italic>2</title>", "<p>Analysis of the DNA sequence immediately upstream and downstream of <italic>dif</italic>1 and <italic>dif</italic>2 in different Vibrio species did not reveal any conserved motifs that could serve to bind accessory proteins (data not shown). FtsK^Vc was thus left as the most likely candidate for activation of Xer recombination at both sites. To test this possibility, we reconstituted the <italic>V. cholerae</italic> Xer system in <italic>E. coli</italic> cells deleted for their natural FtsK/XerCD system. We used a <italic>xerC</italic> and <italic>xerD E. coli</italic> strain, which was also <italic>fts</italic>K_C\n⁻. This strain produces only the N-terminal domain of FtsK^Ec, essential for viability ##REF##9721304##[33]##, but lacks production of the C-terminal domain of FtsK^Ec, which is necessary for recombination at <italic>dif</italic>\n^Ec\n##REF##11114887##[34]##. XerC^Vc was expressed in conjunction with XerD^Vc from the chromosomal <italic>E. coli xerC</italic> promoter. The production of FtsK^Vc was controlled by placing the full length <italic>fts</italic>K^Vc ORF under an arabinose-inducible promoter on a high-copy number plasmid. A low-copy plasmid carrying two recombination sites in direct repeats was used as a reporter. Recombination between the two repeated sites results in the excision of the intervening DNA, which can be monitored by agarose gel electrophoresis. For both <italic>dif</italic>1 and <italic>dif</italic>2, the amount of recombination correlated with the amount of arabinose used for induction, indicating that Xer recombination at <italic>dif</italic>1 and <italic>dif</italic>2 depends on FtsK^Vc (##FIG##3##Figure 4A##).</p>", "<p>To determine the order of the strand exchanges in the recombination reactions, we monitored plasmid recombination in a set of four strains encoding either wild-type XerC^Vc and XerD^Vc or the XerC_YF\n^Vc and XerD_YF\n^Vc mutants, in which the catalytic tyrosine is replaced by a phenylalanine (##FIG##3##Figure 4B##). For both <italic>dif</italic>1 and <italic>dif</italic>2, no resolution product or HJ intermediate were detected in XerD_YF\n^Vc cells (##FIG##3##Figure 4B##, lane 2, 4, 6 and 8). In contrast, we could detect the accumulation of a HJ intermediate in XerC_YF\n^Vc XerD^Vc cells (##FIG##3##Figure 4B##, lane 3 and 7), indicating that XerD^Vc mediates the first pair of strand exchanges during both <italic>dif</italic>1 and <italic>dif</italic>2-recombination. Recombination products were likely still observed in XerC_YF\n^Vc XerD^Vc cells since other cellular processes than Xer recombination are capable of resolving HJs ##UREF##0##[18]##. However, the amount of product was considerably decreased, indicating that intermediate HJs are preferentially resolved to crossovers by the action of XerC^Vc.</p>", "<p>All together, these results indicate that FtsK^Vc activates recombination at <italic>dif</italic>1 and <italic>dif</italic>2 by promoting the exchange of a first pair of strands by XerD^Vc.</p>", "<title>Species-Specificity in Xer Recombination Activation</title>", "<p>Several residues implicated in the interaction between <italic>E. coli</italic> XerD and FtsK have been mapped ##REF##16553881##[24]##,##REF##12823825##[25]##. These residues are not entirely conserved between the <italic>V. cholerae</italic> and <italic>E. coli</italic> proteins (##FIG##4##Figure 5A##), suggesting that the interactions between the translocase and the recombinases might be specific in these two species. Nevertheless, both FtsK^Ec and FtsK^Vc could activate recombination by XerCD^Ec and XerCD^Vc at <italic>dif</italic>\n^Ec, <italic>dif</italic>1 and <italic>dif</italic>2 (##FIG##4##Figure 5B##). However, the efficiency of recombination varied for each site and for each pairing of translocase/recombinases. XerCD^Ec-recombination at <italic>dif</italic>\n^Ec and <italic>dif</italic>1 reached 80% of efficiency whether FtsK^Ec or FtsK^Vc were produced (##FIG##4##Figure 5B##, XerCD^Ec, <italic>dif</italic>1 and <italic>dif</italic>\n^Ec). In contrast, XerCD^Ec-recombination at <italic>dif</italic>2 was more efficient when activated by FtsK^Ec than FtsK^Vc (##FIG##4##Figure 5B##, XerCD^Ec, <italic>dif</italic>2). In addition, it did not reach 80% efficiency, even in the presence of the cognate partner translocase, FtsK^Ec. XerCD^Vc-recombination at <italic>dif</italic>\n^Ec, <italic>dif</italic>1 and <italic>dif</italic>2 reached 80% of efficiency (##FIG##4##Figure 5B##, XerCD^Vc). However, this required the presence of FtsK^Vc. XerCD^Vc-recombination at <italic>dif</italic>2 even fell below 20% when activated by FtsK^Ec. Thus, the effect of species-specificity is more pronounced on <italic>dif</italic>2 than on <italic>dif</italic>1.</p>", "<title>Importance of the Sequence of the Resolution Sites for the Stringent Control of Xer Recombination</title>", "<p>We noticed that the <italic>V. cholerae</italic> recombinases could promote recombination between <italic>dif</italic>1 sites in the absence of FtsK production, albeit to a very low level (##FIG##4##Figure 5B##, XerCD^Vc, <italic>dif</italic>1, No FtsK). This was further exemplified on <italic>dif</italic>\n^Ec substrates, in which 53% of recombination was observed without FtsK expression (##FIG##4##Figure 5B##, XerCD^Vc, <italic>dif</italic>\n^Ec, No FtsK). Resolution products were detected in the absence of XerC catalysis (##FIG##4##Figure 5C##, XerC_YF\n^Vc strains) but not in the absence of XerD catalysis (##FIG##4##Figure 5C##, XerD_YF\n^Vc strains), signifying that XerD^Vc catalysis initiated recombination. <italic>dif</italic>1 differs from the γ-Proteobacteria consensus by only 2 bp, the substitution of A¹⁷ by G and the substitution of A¹⁰ by T (##FIG##4##Figure 5D##). We therefore analyzed FtsK-independent XerCD^Vc recombination at hybrid sites between <italic>dif</italic>, <italic>dif</italic>1 and <italic>dif</italic>2 to identify residues important for the above observation (##FIG##4##Figure 5D##). A site carrying the single [G-A]¹⁷ substitution promoted a much higher level of FtsK-independent recombination (<italic>dif</italic>12), while recombination at sites carrying the [T-A]¹⁰ and [G-A]¹ substitutions was not altered (<italic>dif</italic>13 and <italic>dif</italic>14). However, the cumulative substitutions of [G-A]¹⁷ and [T-A]¹⁰ increased FtsK-independent recombination to a level equivalent to <italic>dif</italic>\n^Ec-recombination (<italic>dif</italic>15). In addition, when T¹⁰ was altered to A in <italic>dif</italic>2, we observed a faint recombination product (<italic>dif</italic>23), which was significant since FtsK-independent recombination was never observed at <italic>dif</italic>2. Thus, G¹⁷ in the central region of <italic>dif</italic>1 and T¹⁰ in the XerC-binding site of <italic>dif</italic>1 and <italic>dif</italic>2 appear to have an important role in maintaining Xer recombination under the tight control of FtsK in <italic>V. cholerae</italic>.</p>", "<title>\n<italic>V. cholerae</italic> FtsK Orienting Polar Sequences</title>", "<p>We next investigated if FtsK^Vc could serve to bring together the CDR sites carried by dimers of chromosome I or by dimers of chromosome II. Several key residues implicated in KOPS recognition have been identified in the γ domain of FtsK^Ec (##FIG##4##Figure 5A##; N1296; R1300; E1303; ##REF##17057717##[35]##). The conservation of these residues in FtsK^Vc suggested that it could recognize the same motifs (##FIG##4##Figure 5A##; N926; R930; E933). If this was indeed the case, replacing the C-terminal domain of FtsK^Ec with the one of FtsK^Vc should completely rescue CDR in <italic>E. coli</italic> cells since FtsK^Vc fully activates recombination by XerCD^Ec at <italic>dif</italic>\n^Ec (##FIG##4##Figure 5B##, XerCD^Ec, <italic>dif</italic>\n^Ec, FtsK^Vc). Indeed, the fitness of such cells equaled the fitness of wild-type <italic>E. coli</italic> cells in growth competition experiments (##FIG##5##Figure 6A##, NLC^Vc and NLC^Ec), in contrast to cells only expressing the N-terminal domain of FtsK^Ec or a fusion with the C-terminal domain of <italic>H. influenzae</italic> FtsK (##FIG##5##Figure 6A##, N and NLC^Hi).</p>", "<p>To test for the ability of FtsK^Vc to specifically recognize one of the <italic>E. coli</italic> KOPS motifs, we compared the efficiency with which it activates <italic>E. coli</italic> Xer recombination between plasmid-borne <italic>dif^Ec</italic> sites flanked or not by the <named-content content-type=\"gene\">5′-GGGCAGGG-3′</named-content> motif in an orientation that should prevent it from translocating towards <italic>dif^Ec</italic> (##FIG##5##Figure 6B##, KOPS-2 and KOPS-0, respectively). Here we observed that the efficiency of recombination dropped significantly on KOPS-2 when FtsK^Ec or FtsK^Vc were used as activators (##FIG##5##Figure 6B##, FtsK^Ec and FtsK^Vc). We then engineered an allele of <italic>ftsK^Vc</italic> carrying identical mutations to the one shown to abrogate KOPS recognition in FtsK^Ec\n##REF##17057717##[35]##. No difference in recombination efficiency was noticeable between KOPS-0 and KOPS-2 when using this allele or its <italic>E. coli</italic> homologue (##FIG##5##Figure 6B##; FtsK_50C\n^Ec[N1296A; R1300A; E1303A] and FtsK^Vc[N926A; R930A; E933A]). We conclude that FtsK^Vc directly recognizes the <named-content content-type=\"gene\">GGGCAGGG</named-content> motif and that recognition engages amino acids N926, R930 and E933.</p>", "<p>We decided therefore to analyze the skew and frequency of the <named-content content-type=\"gene\">GGGCAGGG</named-content> motif on chromosome I and II. <named-content content-type=\"gene\">GGGCAGGG</named-content> is highly polarized on both chromosomes with statistically significant skews (##FIG##5##Figure 6C##). On chromosome I, the skew switches precisely at <italic>dif</italic>1 whereas on chromosome II one motif is present on the reverse orientation a few kb before <italic>dif</italic>2 (##FIG##5##Figure 6C##). However, it has been shown in <italic>E. coli</italic> that a single non-permissive KOPS motif in the vicinity of <italic>dif</italic> is not sufficient to impair recombination ##REF##16211009##[23]##. The frequency of <named-content content-type=\"gene\">GGGCAGGG</named-content> is low on both <italic>V. cholerae</italic> chromosomes (##FIG##5##Figure 6C##), suggesting that this motif is not sufficient by itself to provide polar orientation of FtsK^Vc. We therefore analyzed the distribution of all octamers motif families with one degenerated position on both chromosomes. We ranked potential candidates according to their skew significance keeping only families that had a skew of at least 80% and a frequency of at least once every 30 kb. Only one family (<named-content content-type=\"gene\">GGGNAGGG</named-content>) was among the 10 best candidates of both chromosomes. This family is highly skewed, frequent (##FIG##5##Figure 6C##) and contains the experimentally active <named-content content-type=\"gene\">GGGCAGGG</named-content> motif. Taken together, these results suggest that the <named-content content-type=\"gene\">GGGNAGGG</named-content> motifs might function as KOPS in <italic>V. cholerae</italic>.</p>" ]

[ "<title>Discussion</title>", "<title>A Common Cell Division-Coordination Mechanism for Dimer Resolution of the Two <italic>V. cholerae</italic> Chromosomes</title>", "<p>The strand exchanges catalyzed by XerC^Vc and XerD^Vc occur at the junction between their respective binding site and the central region of <italic>dif</italic>1 and <italic>dif</italic>2, as previously reported for the <italic>E. coli</italic> recombinases on <italic>dif</italic> (##FIG##2##Figure 3##). FtsK^Vc promotes recombination at both sites by activating a first pair of strand exchanges mediated by XerD^Vc (##FIG##3##Figure 4##), thanks to a species-specific interaction with the recombinases (##FIG##4##Figure 5##). In addition, <named-content content-type=\"gene\">GGGNAGGG</named-content> motifs seem to function as FtsK^Vc-Orienting Polar Sequences, their frequency and distribution on the two <italic>V. cholerae</italic> chromosomes suggesting that the FtsK^Vc-translocase activity helps bring CDR sites together when dimers are formed on chromosome I or on chromosome II (##FIG##5##Figure 6##). We conclude that the same FtsK-dependent mechanism controls dimer resolution on each of the two <italic>V. cholerae</italic> chromosomes. We have previously shown in <italic>E. coli</italic> that the requirement for FtsK to activate Xer recombination delays CDR to the time of septum closure ##UREF##1##[26]##, which is likely to also hold true in <italic>V. cholerae</italic>. Thus, the study of CDR provides the first example of a cell cycle coordination mechanism shared by the two <italic>V. cholerae</italic> chromosomes, which is similar to the way chromosomal maintenance processes are coordinated within the cell cycle of eukaryotes.</p>", "<title>Dimer Formation Is Linked to Replicon Size</title>", "<p>Many bacteria harbor multiple chromosomes, which seems an important determinant of their individual life styles. A few bacterial species harbor linear replicons in addition to circular, such as <italic>Agrobacterium tumefaciens</italic> and the <italic>Borrelia</italic> species ##REF##9928484##[3]##. In the vast majority of cases, however, the multiple chromosomes harbored within a bacterium are circular. Maintenance of circular replicons requires the resolution of dimers created by homologous recombination events. In <italic>V. cholerae</italic>, 5.8% of dimers per cell per generation are formed on the 2.96 Mbp chromosome I and 3% of dimers are created on the 1.07 Mbp chromosome II (##FIG##1##Figure 2##). Under similar growth conditions, 15.6% of dimers are generated on the 4.6Mbp <italic>E. coli</italic> chromosome (##FIG##5##Figure 6##). These results suggest that dimer formation increases with replicon size, possibly reaching a theoretical upper limit of 50% for very large replicons. In addition, the rate of dimer formation seems to vary exponentially with replicon size for small replicons. Based on this hypothesis, the frequency of chromosome dimer formation in <italic>V. cholerae</italic> would be 11% per cell generation if it carried a single circular chromosome of 4.03Mbp. Instead, we measured a total rate of 8.6% for the two chromosomes (##FIG##1##Figure 2##). Thus, the particular genomic organization of the Vibrios seems to minimize chances for chromosome dimer formation, which is theoretically beneficial.</p>", "<title>Generalization to Other Bacteria with Multiple Chromosomes</title>", "<p>Putative <italic>dif</italic> sites were readily identified on each of the two chromosomes harbored by 7 additional γ-Proteobacteria (##FIG##6##Figure 7## and ##SUPPL##1##Figure S2##). To determine <italic>dif</italic> sites in β- and α-Proteobacteria, we generated a profile Hidden Markov Model (HMM) based on the alignment of the putative CDR sites found in the larger chromosome of 27 γ-Proteobacteria using the program HHMER. We then compared each sequence by hand to ensure the proper 6 bp spacing between the putative XerC and XerD binding sites. Putative <italic>dif</italic> sites were thus identified on each of the multiple chromosomes harbored by 10 β-Proteobacteria species and 5 α-Proteobacteria species (##FIG##6##Figure 7## and ##SUPPL##2##Figure S3## and ##SUPPL##3##S4##). A single pair of recombinases orthologous to XerC and XerD was found in each of the 22 additional γ-, β- and α-Proteobacteria harboring multiple chromosomes, suggesting that a single pair of recombinases ensures dimer resolution of each of their non-homologous chromosomes. FtsK orthologues were also found. In addition, putative <italic>dif</italic> sites fell within 10 kb of the GC-skew inflection point (data not shown), suggesting that dimer resolution is under the control of an FtsK-like homologue in all these species. Thus, the adoption of an FtsK-dependent dimer resolution system could be a key evolutionary step in the maintenance of large circular replicons.</p>", "<title>Tuning of <italic>V. cholerae</italic> CDR to Achieve Efficient Recombination on Divergent <italic>dif</italic> Sites</title>", "<p>The sequence of Xer target sites, and especially of their central region, is a crucial determinant in the outcome of recombination ##REF##10523315##[36]##,##REF##12034757##[37]##. Indeed, the central region of <italic>dif</italic> sites found in Proteobacteria with a single chromosome showed a high degree of conservation, most β- and γ-Proteobacteria harboring a ‘canonical’ 5′-TGTATA-3′ motif (##FIG##6##Figure 7## and ##SUPPL##1##Figure S2## and ##SUPPL##2##S3##), suggesting that there is a selective pressure on the sequence of the <italic>dif</italic> central region. This is further illustrated by the lower recombination efficiency of the <italic>E. coli</italic> system on <italic>dif</italic>2 compared to <italic>dif</italic>1 (##FIG##4##Figure 5##). In this regard, the <italic>V. cholerae</italic> Xer recombination system is remarkable since identical recombination efficiencies were obtained with the same pair of recombinases on <italic>dif</italic>1 and <italic>dif</italic>2 (##FIG##3##Figure 4## and ##FIG##4##5##). However, XerCD^Vc-mediated recombination at <italic>dif</italic>2 required a tighter interaction between the recombinases and their partner translocase than at <italic>dif</italic>1, since FtsK^Ec promoted 50% of recombination at <italic>dif</italic>1 but less than 20% at <italic>dif</italic>2 (##FIG##4##Figure 5B##, XerCD^Vc, FtsK^Ec). In addition, a few alterations in the sequence of <italic>dif</italic>1 and <italic>dif</italic>2 decreased the stringency of the control exerted by FtsK^Vc (##FIG##4##Figure 5D##), highlighting the extremely fine tuning of the different components of the <italic>V. cholerae</italic> CDR system.</p>", "<title>Non-Homologous Chromosomes Carry d<italic>if</italic> Sites with Divergent Central Regions</title>", "<p>We observed that in Proteobacteria with multiple chromosomes, the central regions of <italic>dif</italic> sites from non-homologous chromosomes are divergent, as in <italic>V. cholerae</italic> (##FIG##6##Figure 7## and ##SUPPL##1##Figure S2##, ##SUPPL##2##S3##, ##SUPPL##3##S4##). A single exception was found in <italic>Burkholderia xenovarans</italic>, in which two of the three chromosomes of the bacterium harbor a resolution site with an identical central region. We reasoned therefore that some selective pressure imposes the divergence of the central regions of CDR sites carried by the different, non-homologous chromosomes of bacteria with multipartite genomes, which competes with the selective pressure for <italic>dif</italic> central regions to adopt the preferential 5′-TGTATA-3′ motif. Indeed, the presence of <italic>dif</italic> sites with identical central regions on two non-homologous chromosomes could lead to the formation of chromosome fusions by Xer recombination, which would disrupt the selective advantage brought by the multipartite genomic organization. In support of this hypothesis, preliminary experiments indicate that harmonization of the two <italic>V. cholerae dif</italic> sites leads to chromosomal fusions (Val and Barre, unpublished observations). We are currently investigating how these fusions are formed and the consequences of harboring identical <italic>dif</italic> sites on separate chromosomes.</p>" ]

[]

[ "<p>Conceived and designed the experiments: FXB. Performed the experiments: MEV SPK MEK LB FC. Analyzed the data: MEV SPK MEK FXB. Wrote the paper: FXB.</p>", "<p>Unlike most bacteria, <italic>Vibrio cholerae</italic> harbors two distinct, nonhomologous circular chromosomes (chromosome I and II). Many features of chromosome II are plasmid-like, which raised questions concerning its chromosomal nature. Plasmid replication and segregation are generally not coordinated with the bacterial cell cycle, further calling into question the mechanisms ensuring the synchronous management of chromosome I and II. Maintenance of circular replicons requires the resolution of dimers created by homologous recombination events. In <italic>Escherichia coli</italic>, chromosome dimers are resolved by the addition of a crossover at a specific site, <italic>dif</italic>, by two tyrosine recombinases, XerC and XerD. The process is coordinated with cell division through the activity of a DNA translocase, FtsK. Many <italic>E. coli</italic> plasmids also use XerCD for dimer resolution. However, the process is FtsK-independent. The two chromosomes of the <italic>V. cholerae</italic> N16961 strain carry divergent dimer resolution sites, <italic>dif</italic>1 and <italic>dif</italic>2. Here, we show that <italic>V. cholerae</italic> FtsK controls the addition of a crossover at <italic>dif</italic>1 and <italic>dif</italic>2 by a common pair of Xer recombinases. In addition, we show that specific DNA motifs dictate its orientation of translocation, the distribution of these motifs on chromosome I and chromosome II supporting the idea that FtsK translocation serves to bring together the resolution sites carried by a dimer at the time of cell division. Taken together, these results suggest that the same FtsK-dependent mechanism coordinates dimer resolution with cell division for each of the two <italic>V. cholerae</italic> chromosomes. Chromosome II dimer resolution thus stands as a bona fide chromosomal process.</p>", "<title>Author Summary</title>", "<p>During proliferation, DNA synthesis, chromosome segregation, and cell division must be coordinated to ensure the stable inheritance of the genetic material. In eukaryotes, this is achieved by checkpoint mechanisms that delay certain steps until others are completed. No such temporal separation exists in bacteria, which can undergo overlapping replication cycles. The eukaryotic cell cycle is particularly well suited to the management of multiple chromosomes, with the same replication initiation and segregation machineries operating on all the chromosomes, while the bacterial cell cycle is linked to genomes of less complexity, most bacteria harboring a single chromosome. The discovery of bacteria harboring multiple circular chromosomes, such as <italic>V. cholerae</italic>, raised therefore a considerable interest for the mechanisms ensuring the synchronous management of different replicons. Here, we took advantage of our knowledge of chromosome dimer resolution, the only bacterial segregation process for which coordination with cell division is well understood, to investigate one of the mechanisms ensuring the synchronous management of the smaller, plasmid-like, and larger, chromosome-like, replicons of <italic>V. cholerae</italic>.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank D. Chattoraj, D. Mazel, V. Sivanathan and D. Sherratt for the kind gift of plasmids and strains, G. Balavoine, N. Dubarry, B. Michel and C. Possoz for helpful comments. We are grateful to the MIGALE bioinformatics platform (INRA) for providing technical support and computational resources.</p>" ]

[ "<fig id=\"pgen-1000201-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g001</object-id><label>Figure 1</label><caption><title>FtsK-dependent and FtsK-independent Xer recombination.</title><p>A. Chromosome dimer formation and resolution in <italic>E. coli</italic>. The two homologous chromosomes are depicted by thick and thin lines, to allow for the visualization of crossovers. B. Link between the central region of XerCD-target sites (right) and the recombination pathway adopted at these sites (left). The XerCD-<italic>dif</italic> recombination complex is viewed from the C-terminal side of the recombinases, to show the C-terminal interactions of XerC and XerD. Strands cleaved by XerC and XerD in <italic>E. coli</italic> are shown with thick and thin lines, respectively. Positions of strand cleavages by <italic>E. coli</italic> XerC and XerD are indicated by white and black triangles, respectively. The WebLogo was generated using the alignment of putative <italic>dif</italic> sites from the larger chromosome of 27 γ-Proteobacteria (##SUPPL##4##Text S1##). The XerC-binding site, XerD-binding site and central region of <italic>dif</italic>\n^Ec are indicated below the alignment.</p></caption></fig>", "<fig id=\"pgen-1000201-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g002</object-id><label>Figure 2</label><caption><title>Growth competition of <italic>V. cholerae</italic> deficient in CDR strains against their parent.</title><p>f: frequency of cells that the mutant strains fail to produce at each generation compared to their parent.</p></caption></fig>", "<fig id=\"pgen-1000201-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g003</object-id><label>Figure 3</label><caption><title> In vitro cleavage of <italic>dif</italic>1 and <italic>dif</italic>2 by the <italic>V. cholerae</italic> recombinases.</title><p>A. Putative XerC^Vc and XerD^Vc cleavage sites on <italic>dif</italic>1 and <italic>dif</italic>2 and scheme of the suicide substrates used in this study. The top and bottom strands of <italic>dif</italic>1 and <italic>dif</italic>2 are depicted as black and grey strands. Their equivalents in <italic>dif</italic>\n^Ec are cleaved by XerC^Ec and XerD^Ec, respectively. Grey triangles further indicate the positions equivalent to these where XerC^Ec and XerD^Ec cleave <italic>dif</italic>\n^Ec. A white triangle indicates the XerD^Vc-cleavage position reported for <italic>dif</italic>1 ##REF##15522078##[32]##. Top and bottom strand suicide substrates contain a nick opposite the position expected to be cleaved by XerC^Vc and XerDVc if the <italic>E. coli</italic> paradigm is followed, respectively. T1, B1, T2, B2: suicide substrates on <italic>dif</italic>1 and <italic>dif</italic>2, respectively. B. Scheme of a XerC-suicide cleavage reaction. C. Covalent complex formation by MBPXerC^Vc and XerD^Vc on suicide substrates. Schemes of substrates and products are shown on the top and on the right of the gel, respectively. Suicide substrates were labeled on the 5′ side of the continuous strand, as indicated (5′*). D. Cleavage sites of XerC^Vc and XerD^Vc on <italic>dif</italic>1 and <italic>dif</italic>2. Schemes of substrates are shown on the top of the gels. Suicide substrates were labeled on the 3′ side of the continuous strand, as indicated (3′*). PNK: phosphorylation with T4 polynucleotide kinase; G+A: chemical cleavage ladder. Sequences resulting from the chemical cleavage are indicated beside the gels. Bases of the central region and of the XerCD-binding sites are indicated in black and grey, respectively. The deduced cleavage points are indicated by black triangles.</p></caption></fig>", "<fig id=\"pgen-1000201-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g004</object-id><label>Figure 4</label><caption><title>FtsK^Vc-dependent recombination at <italic>dif</italic>1 and <italic>dif</italic>2.</title><p>A. Reconstitution of <italic>V. cholerae</italic> Xer recombination at plasmid-borne <italic>dif</italic>1 and <italic>dif</italic>2 sites in <italic>E. coli</italic> cells. Top panel: gel showing a typical result. A scheme of the substrate and product bands is shown beside the gel. <italic>dif</italic> sites are represented by triangles. Bottom panel: quantification plot displaying the mean and standard deviations of at least three independent experiments. B. Recombination by wild-type (+) and catalytically inactive (YF) recombinases. HJ: HJ intermediate.</p></caption></fig>", "<fig id=\"pgen-1000201-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g005</object-id><label>Figure 5</label><caption><title>Species specificity in Xer recombination.</title><p>A. Amino acid residue conservation in the γ-domain of FtsK and in the C-terminal tail of XerD. Numbers indicate the position of the first and of the last residues of the alignments in the amino acid sequence of the <italic>V. cholerae</italic> proteins. Positions of full conservation and of strong or weaker groups of conservation are indicated by stars, semi-colons or dots, respectively, following the Clustal 1.83 scheme. Black bars and vertical arrows indicate residues implicated in FtsK-XerD interaction and in KOPS recognition in <italic>E. coli</italic>, respectively. B. Species-specificity in Xer recombination on plasmid-borne <italic>dif</italic>1, <italic>dif</italic>2 and <italic>dif</italic>\n^Ec sites. The mean and standard deviation of at least three independent experiments are plotted. ND: not determined. C. FtsK-independent recombination at <italic>dif</italic>\n^Ec by wild-type (+) and catalytically inactive (YF) <italic>V. cholerae</italic> recombinases. D. FtsK-independent recombination by the <italic>V. cholerae</italic> recombinases on hybrid <italic>dif</italic> sites.</p></caption></fig>", "<fig id=\"pgen-1000201-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g006</object-id><label>Figure 6</label><caption><title>\n<italic> V. cholerae</italic> FtsK Orienting Polar Sequences.</title><p>A. Growth competition of <italic>E. coli</italic> cells encoding FtsK hybrids. N: cells carrying a complete deletion of the C-terminal domain and linker region of FtsK^Ec; NLC^Ec: cells carrying full length FtsK^Ec; NLC^Vc and NLC^Hi: cells in which the C-terminal domain FtsK^Ec was replaced by the one of FtsK^Vc and FtsK^Hi, respectively. f: frequency of cells that the parental N strain fails to produce at each generation compared to the FtsK hybrids. B. <named-content content-type=\"gene\">5′-GGGCAGGG-3′</named-content> inhibits recombination activation by FtsK^Vc. Plasmid recombination at <italic>E. coli dif</italic> by XerCD^Ec was induced with 0.5% arabinose. Ec[NRE]: FtsK_50C\n^Ec[NRE]; Vc[NRE]: FtsK^Vc[NRE]. KOPS-0: substrate without <named-content content-type=\"gene\">GGGCAGGG</named-content> sequences; KOPS-2: substrate with triple overlapping <named-content content-type=\"gene\">GGGCAGGG</named-content> sequences in the non-permissive orientation on both sides of the two <italic>dif</italic> sites. C. Scheme of the two <italic>V. cholerae</italic> chromosomes showing the distributions of the <named-content content-type=\"gene\">GGGCAGGG</named-content> and <named-content content-type=\"gene\">GGGNAGGG</named-content> motifs. Upper bars: motifs found in the leading strand; Lower bars: motifs found in the lagging strand. Number, frequency, skew and skew significance (<italic>p</italic>-skew) are indicated for each motif. Recently acquired genomic regions are indicated (superintegron, CTX and TLC prophages and the Vibrio Pathogenicity Island VPI).</p></caption></fig>", "<fig id=\"pgen-1000201-g007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pgen.1000201.g007</object-id><label>Figure 7</label><caption><title>The non-homologous chromosomes of Proteobacteria with multipartite genomes carry divergent <italic>dif</italic> sites.</title><p>Alignment of the chromosome dimer resolution sites of a few Proteobacteria harboring a single or multiple chromosomes. Bases identical to the γ-Proteobacteria <italic>dif</italic> consensus are shaded in black. Species abbreviations follow the KEGG convention.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pgen.1000201.s001\"><label>Figure S1</label><caption><p>XerCD and FtsK tree.</p><p>(2.80 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000201.s002\"><label>Figure S2</label><caption><p>dif sites in gamma-Proteobacteria.</p><p>(6.03 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000201.s003\"><label>Figure S3</label><caption><p>dif sites in beta-Proteobacteria.</p><p>(5.50 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000201.s004\"><label>Figure S4</label><caption><p>dif sites in alpha-Proteobacteria.</p><p>(3.18 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pgen.1000201.s005\"><label>Text S1</label><caption><p>Supplementary methods.</p><p>(0.12 MB DOC)</p></caption></supplementary-material>" ]

[ "<fn-group><fn fn-type=\"COI-statement\"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p>Work in the Barre lab is supported by the 2007 FRM laboratory program, the 2006 EMBO YI program, the CNRS ATIP+ program and the 2005 ANR BLANC program. Work in the El Karoui lab is supported by ACI IMPBio and ANR BLANC programs. M-EV and LB were the recipients of FRM and Région Ile de France fellowships, respectively.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pgen.1000201.g001\"/>", "<graphic xlink:href=\"pgen.1000201.g002\"/>", "<graphic xlink:href=\"pgen.1000201.g003\"/>", "<graphic xlink:href=\"pgen.1000201.g004\"/>", "<graphic xlink:href=\"pgen.1000201.g005\"/>", "<graphic xlink:href=\"pgen.1000201.g006\"/>", "<graphic xlink:href=\"pgen.1000201.g007\"/>" ]

[ "<media xlink:href=\"pgen.1000201.s001.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000201.s002.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000201.s003.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000201.s004.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pgen.1000201.s005.doc\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>MicroRNAs (miRs) are a growing class of non-coding RNAs that is now recognized as a major tier of gene control, predicted to target more than 30% of all human protein-coding genes ##REF##16446010##[1]##,##REF##15652477##[2]##. miRs suppress gene expression via binding to regulatory sites usually embedded in the 3′-UTRs of their target mRNAs, leading to the repression of translation occasionally associated with mRNA degradation. Target recognition involves complementary base pairing of the target site with the miR's seed region (positions 2–8 at the miR's 5′ end), although the exact extent of seed complementarity is not precisely determined, and can be modified by 3′ pairing ##REF##15652477##[2]##–##REF##16736023##[4]##. Despite intensive efforts in recent years, biological functions carried out by miRs have been characterized for only a minority of these genes, and therefore, elucidating regulatory roles played by miRs in various biological networks constitutes one of the major challenges facing biology today. Bioinformatics analyses can significantly contribute to elucidation of miR functions; in particular, the integrated analysis of gene expression data and 3′-UTR sequences that holds promise for systematic dissection of regulatory networks controlled by miRs and of cis-regulatory elements embedded in 3′-UTRs.</p>", "<p>Similar bioinformatics approaches that integrates gene expression data and promoter sequences proved highly effective in delineating transcriptional regulatory networks in a multitude of organisms ranging from yeast to human ##REF##12727897##[5]##–##REF##12855470##[7]##. Microarray measurements reflect the total effect of all regulatory mechanisms that control gene expression, including both transcriptional and post-transcriptional mechanisms; thus, genome-wide expression profiles should yield ample information not only on transcriptional networks, but also on regulatory networks regulated by miRs and RNA binding proteins (RBPs) that modulate mRNA stability, and that usually act via regulatory elements in 3′-UTR of their target genes ##REF##16394137##[8]##. Although mRNA degradation seems to be a secondary mode of miRs' action (with inhibition of translation being the primary one), since each miR is predicted to directly affect the expression level of dozens of target genes, such an orchestrated effect should be discernable by statistical analysis of wide-scale mRNA expression data, even if the effect on each target is only a subtle one. This orchestrated effect could serve as a molecular fingerprint for miRs activity under given biological conditions. Indeed, several pioneering studies provided strong evidence of the ability to computationally decipher miR-mediated regulatory networks from mRNA expression data alone or in correlation with miR expression profiles ##REF##16308420##[9]##–##REF##16477010##[14]##.</p>", "<p>In this study, we applied an integrated analysis of gene expression data and 3′-UTR sequences aimed at identifying miRs that are active in a given biological process. Applying such analysis we discovered in numerous microarray datasets a major bias that resulted in a striking relationship between 3′-UTR AU content and gene response. We show that this surprising link between gene's response and 3′-UTR base composition is secondary to a more basic relationship between gene's response and base composition of its probes on the chip. We demonstrate that this bias causes many false positive calls in computational searches for active miRs from mRNA expression data. Therefore, removal of this bias, which is in order in any analysis of microarray datasets, is of crucial importance when integrating expression data and 3′-UTR sequences to identify regulatory elements embedded in this region. Our results substantiate that computational analysis of mRNA expression data, after appropriate removal of AU biases, can accurately detect active miRs that control various biological processes under physiological conditions.</p>" ]

[ "<title>Methods</title>", "<p>All statistical analyses were performed and plots were generated using the R package (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.r-project.org/\">http://www.r-project.org/</ext-link>).</p>", "<title>Data Analysis of Gene Expression Datasets</title>", "<p>In this study, we analyzed four microarray datasets which used 3′-UTR Affymetrix oligonucleotide chips (that is, chips in which probes are selected from targets' 3-UTRs), and one dataset that used the new generation Affymetrix Human Gene 1.0 ST Array, in which probes are located throughout the target transcripts. Raw data files (CEL files) were downloaded from GEO (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/geo/\">http://www.ncbi.nlm.nih.gov/geo/</ext-link>) or ArrayExpress (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ebi.ac.uk/microarray-as/aer/#ae-main0\">http://www.ebi.ac.uk/microarray-as/aer/#ae-main0</ext-link>) DBs, or obtained directly from the authors of the data.</p>", "<title>Analysis of datasets that used 3′-UTR Affymetrix chips</title>", "<p>The dataset that profiled HPC multi-lineage differentiation ##REF##14701746##[19]## used Affymetrix MGU74Av2 mouse chips. Expression levels were recorded in triplicates at 0, 4, 8, 16, 24, 48, 72, and 168 hrs of differentiation into four lineages: megakaryocytes, neutrophils, erythrocytes and macrophages. The dataset that profiled Stratagene's universal human reference RNA pool in two independent chips (##REF##15955238##[20]##, GSE1158) used Affymetrix HGU133A human chips. The dataset that profiled expression levels in miR155-deficient and control T cells (##REF##17463290##[23]##, E-TABM-232), used Affymetrix MG-430.2 mouse chips. Expression levels were measured in 5 replicates in miR155-deficient and wild-type Th1 and Th2 cells stimulated for 24 hrs with LPS and IL4. The results reported in our study were derived from the Th2 dataset. The dataset that profiled expression level during T cell maturation (##REF##15210650##[24]##, GSE1460), used Affymetrix HGU133A-B human chips. Expression levels were recorded in triplicates in 5 phases during differentiation (intrathymic T progenitor (ITTP) cells, double positive (DP) thymocytes, CD4 single positive (SP4), naïve CD4 T cells from cord blood (CB4), and naïve CD4 T cells from adult blood (AB4).</p>", "<p>All these four datasets were processed by a similar scheme: First, probeset expression levels were calculated using the rma, gcrma, and mas5 methods implemented in the affy ##REF##12582260##[27]## and gcrma packages of the BioConductor project ##REF##16939789##[28]##. Unless otherwise stated, results reported in this paper are the ones obtained using the rma method. Similar results were obtained for data processed by the mas5 and gcrma methods. Second, probeset presence flags were calculated using the mas5calls function implemented in the affy package, and probesets that got more ‘Absent’ calls than a certain threshold were removed from subsequent analysis. (Thresholds for the number of ‘Absent’ calls were: 18 (out of 30 chips) in the HPC differentiation into megakaryocytes dataset; one (out of 2 chips) in the universal RNA pool dataset; 3 (out of 10 chips) in the miR-155 dataset; and 10 (out of 18 chips) in the T cell maturation dataset.) Next, probesets were mapped to their corresponding genes using annotation files provided by Affymetrix, and in cases where a gene was represented by several probesets, we used the measurements of the probeset with the highest median intensity level. Intensity levels over replicate chips were averaged.</p>", "<title>Analysis of the dataset that used the Affymetrix Human Gene 1.0 ST Array</title>", "<p>CEL files of this dataset (##REF##18476829##[22]##, GSE9819) were downloaded from GEO, and probe-set expression values were calculated using rma. In this dataset, we detected significant 3′-UTR bias in a comparison between two chips hybridized with a common Ambion Human Brain Reference RNA pool (sample ids GSM247680 and GSM247680). Probe-level intensities were extracted using the pm function implemented by the affy package. Probes' sequences and genome coordinates were obtained from chip annotation files provided by Affymetrix. Genome coordination of 5′-UTR, CDS and 3′-UTR regions of all annotated human transcripts were extracted from Ensembl using BioMart utilities ##REF##18000006##[29]##. Mapping of probes to 5′-UTR, CDS, and 3′-UTR regions was done by a Perl script written for this purpose. Before generating the probe-level M-AU plot, we performed the following preprocessing steps: a floor cut-off signal, which was set to the first quartile signal, was applied to each chip; probe expression levels were quantile- normalized; and probes whose signal was above median level were flagged as ‘Present’. Log2 of fold-change and AU content were calculated for each probe. To reduce noise, M-AU plot included only probes that were ‘Present’ in at least one of the chips hybridized with the brain reference sample.</p>", "<title>3′-UTR Sequences and miR Target Prediction</title>", "<p>3′-UTR sequences and miR target prediction for human and mouse were downloaded from TargetScanS (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.targetscan.org/\">http://www.targetscan.org/</ext-link>; version 4.0; July 2007). TargetScanS predicts gene targets of miRNAs by searching 3′-UTRs for the presence of conserved 8-mer and 7-mer sites that match the seed region of each miRNA family ##REF##15652477##[2]##. In case a gene has several annotated 3′-UTRs, the longest one is considered.</p>", "<title>Target prediction for randomly permuted miR seeds</title>", "<p>For each conserved miR family, as defined by TargetscanS, we generated 20 randomly permuted seeds derived from the original seed. Targets of these random seeds were predicted by the same program used by TargetScanS for prediction of targets of the original miRs (the program is available at TargetScanS website).</p>", "<title>AU normalization</title>", "<p>Adopting the concepts of MA-plots and intensity-dependent normalization that were introduced by Yang et al. ##REF##11842121##[21]## in order to remove intensity biases from microarray data, we used the robust scatter plot smoother ‘lowess’, implemented in R (with default parameters), to remove the AU bias:where <italic>I₁</italic> and <italic>I₂</italic> are the intensity signals measured for a gene in chip1 and chip2, and <italic>c</italic>(<italic>AU</italic>) is the lowess fit to the M-AU plot (in which the X-axis represents either transcript 3′-UTR, probe-set, or probe's AU content). Applying 3′-UTR-based or probe-set-based AU normalization to the 3′-UTR Affymetrix datasets yielded similar results, as expected, because of the coupling between transcript 3′-UTR and probe-set sequences in these chips.</p>", "<title>Statistical search for candidate active miRs in mRNA expression dataset</title>", "<p>Searching for miRs that are active in a microarray dataset, we utilized miR target prediction produced by TargetScanS, and applied the following statistical test: for each miR family and for each condition in a dataset, we tested whether the set of predicted miR target genes is significantly more induced/repressed than the background set consisting of all the non-target genes (for which 3′-UTR sequence and expression data are available). Target and background sets were compared using the non-parametric Wilcoxon test, and a miR family was putatively considered ‘active’ in a certain condition if the <italic>p</italic>-value obtained for its target set was below 0.05 after applying Bonferroni correction for multiple testing (∼150 miR families were tested).</p>" ]

[ "<title>Results</title>", "<p>We set out to demonstrate that integrated computational analysis of mRNA expression data and 3′-UTR sequences can accurately uncover miRs that participate in the regulation of a given biological process. As the role of miRs in different branches of hematopoiesis is well characterized ##REF##14657504##[15]##–##REF##16325577##[18]##, we first analyzed a dataset that recorded global gene expression profiles for multi-potent hematopoietic progenitor cells (HPCs) undergoing multi-lineage differentiation ##REF##14701746##[19]##. Since miRs often induce degradation of their target mRNAs, we expected the 3′-UTR of genes whose expression is induced during differentiation to be enriched for seed signatures of miRs that become inactive in this process, and vice versa—that the 3′-UTR of genes whose expression is repressed would be enriched for seed signatures of miRs that become active during the process.</p>", "<p>Before employing statistical tests to identify over-represented seed sequences among up- or down-regulated genes, we examined whether a more global trend in base composition could be detected in the 3′-UTR sequences of the responding genes. For example, if the 3′-UTRs of the up-regulated genes are generally more AU-rich compared to the 3′-UTRs of the non-responding genes, then any statistical search for over-represented seed signatures among the up-regulated genes is expected to yield false positive calls for miRs whose seed signature is AU-rich. One effective means for detecting such false positive calls is to repeat the over-representation tests with randomly permuted miR seeds (which preserve the seed's base composition). If an enrichment of a certain miR seed is accounted for merely by base composition, then it is expected to be non-specific and detected also for randomly permuted seeds derived from the original one.</p>", "<p>Therefore, as a first step in the analysis of the HPC dataset, we checked whether a global 3′-UTR base composition trend is associated with the multi-lineage differentiation. We detected a very strong correlation between 3′-UTR base composition and gene response at several time points in this dataset. For example, there was an exceptionally strong relationship between AU content and gene response at the 16 hr time point after induction of HPC differentiation into megakaryocytes: 3′-UTRs of down-regulated genes were significantly more AU-rich than those of up-regulated ones (##FIG##0##Figure 1##). (The mean 3′-UTR AU content of the 5% most down-regulated and most up-regulated genes were 60.6% and 52.7%, respectively, <italic>p</italic>&lt;10⁻⁹⁹, Wilcoxon test.) The other three lineages in this dataset displayed similarly strong trends (##SUPPL##0##Figure S1##).</p>", "<p>The strength of the relationship between 3′-UTR AU content and gene response in the HPC dataset prompted us to search for such trends in other datasets. Surprisingly, we found such relationships, with similarly high statistical significance, in numerous microarray datasets (data not shown). Still more suspicious, we observed the relationship even when we compared different control samples within a dataset. This led us to question whether the relationship observed between 3′-UTR AU content and gene response reflects any true biological regulatory mechanism, or is rather a result of some technical artifact in microarray measurements. We found a definitive answer to this question by analyzing a technical dataset published by van Ruissen et al. ##REF##15955238##[20]##. This dataset profiled a universal reference RNA pool in two independent oligonucleotide chips (Affymetrix HGU133A). Comparing the data from these two arrays, which measure identical and artificial RNA pools, we again found a striking relationship between 3′-UTR AU content and difference in gene expression level (##FIG##1##Figure 2##), pointing to a major AU bias in microarray measurements. This AU response bias is not specific to a particular data preprocessing method, as it existed in data under different preprocessing and normalization schemes; namely, rma, gcrma, and mas5 (##SUPPL##1##Figure S2##). In this technical dataset, we detected no preference for A or U in the bias, and no major 3′-UTR length bias (##SUPPL##2##Figure S3##).</p>", "<p>Next, we sought to elucidate the sources of the AU response bias. A well-documented bias in microarray measurements is the one between probe intensity and response ##REF##11842121##[21]##, which is routinely visualized using M-A plots. We first suspected that the observed association between 3′-UTR AU content and gene response is a mere reflection of the intensity-response bias. However, there was no intensity-bias in the above technical dataset, which points that the 3′-UTR AU response bias is distinct from the intensity-response bias (see ##FIG##2##Figure 3A and 3B##; in the latter, adopting the concept of M-A plots, we introduced the M-AU plot to visualize the AU response bias). The AU response bias exists over a large range of intensities (##SUPPL##3##Figure S4##), and, furthermore, the gcrma method which takes into account the correlation between probe's AU content and intensity did not cancel it.</p>", "<p>In the vast majority of present chips, probes are selected from the 3′-end of target transcripts. This is also the case for the technical dataset that we have analyzed, which used the Affymetrix HGU133A chip. Therefore, as expected, we observed in this dataset also a strong relationship between probeset AU content and response (similar to the one observed between gene's 3′-UTR AU content and response) (##SUPPL##4##Figure S5##). To test whether the AU artifact origins either from base-composition properties of 3′-UTR of target transcripts or of that of the chip probes, the sequence of probes and target 3′-UTRs need to be uncoupled. The new generation Affymetrix chips break this coupling as their probes are selected from all regions of target transcripts. We therefore analyzed a second technical dataset, recently published by Pradervand et al. ##REF##18476829##[22]## which used the new Affymetrix Human Gene 1.0 ST Array. In this dataset too, we detected a strong AU response bias. That is, we observed a significant relationship between probeset AU content and response in a comparison between duplicate control chips. Importantly, carrying out a probe-level analysis, we found that probes located at 5′-UTR and CDS regions show a similar AU bias as probes located at 3′-UTRs (##FIG##3##Figure 4##). This finding indicates that the link between gene's response and 3′-UTR base composition is secondary to a more basic bias in microarray measurements which links gene response with base composition of its probes.</p>", "<p>We next evaluated the effect of the AU bias on computational identification of active miRs from microarray data. Searching for miRs that are active in biological conditions examined in a dataset, we utilized miR target prediction generated by TargetScanS ##REF##15652477##[2]##, and applied the following statistical test: for each miR family and for each condition in a dataset, we tested whether the set of predicted miR target genes is significantly induced or repressed compared to a background set consisting of all the non-target genes (see <xref ref-type=\"sec\" rid=\"s4\">Methods</xref>). The technical dataset which profiled the universal reference RNA pool served us as a negative test case in which no real biological signal exists. Applying the statistical tests to this dataset, we identified nine miR families whose target sets showed statistically significant response (##TAB##0##Table 1##). Of course, in this negative test case, all calls are false positive ones; and, as expected, all the falsely identified miR families had an AU-rich seed (the seed of eight out of the nine calls contained at least 5 A or U bases, while the prevalence of miRs with such seed among all the miRs tested was less than 25%; ##TAB##0##Table 1##). Next, for each miR family identified as significant, we repeated the statistical tests, but this time with randomly permuted miR seeds. In all cases, permuted seeds showed similar statistical significance to the original seeds (##TAB##0##Table 1##), demonstrating the utility of such permutation tests in detecting non-specific results caused by correlation between base composition of miR-seeds and 3′-UTRs of the responding genes.</p>", "<p>As shown, the AU response bias causes many false positive calls in computational search for active miRs from expression data, and therefore its removal is crucial when carrying out integrated bioinformatics analysis of mRNA expression data and 3′-UTR sequences. To remove this bias, we adopted the <italic>lowess</italic> normalization method which is routinely used to remove intensity biases from microarray data ##REF##11842121##[21]##, and adjusted it to cancel AU biases (##FIG##4##Figure 5##) (see <xref ref-type=\"sec\" rid=\"s4\">Methods</xref>). Applying AU normalization did not distort the normalization at the M-A plane (##SUPPL##5##Figure S6##). Importantly, after applying AU normalization to the negative control dataset, no miR family passed the statistical significance threshold (0.0003, which corresponds to 0.05 after Bonferroni correction for multiple testing) (##TAB##0##Table 1##).</p>", "<p>We next searched for an expression dataset that would serve as a positive test case; that is, a dataset that contains known miR signals. We preferred physiologically relevant datasets over ones that over-expressed miRs, which often give expression levels that are far above physiological ones. (Statistical searches for active miRs applied to several datasets that profiled cells over-expressing specific miRs readily detected the correct signals both without and after AU normalization (data not shown).) A recent study that compared expression profiles between stimulated T-cells derived from miR-155 deficient and control mice met this requirement ##REF##17463290##[23]##. As in many other datasets, we observed a strong AU bias in this dataset too, and removed it using the AU normalization (##FIG##5##Figure 6##). Without AU normalization, the statistical tests identified eleven significant miR families; the true hit (miR-155) was the third most significant one (##TAB##1##Table 2##). (Note that five out of the six most significant miRs falsely identified on the negative dataset were detected also in this positive dataset (compare ##TAB##0##Tables 1## and ##TAB##1##2##)). Here too, permutation tests found, in most cases, random seeds whose significance scores were similar to the ones obtained by the original seeds (##TAB##1##Table 2##). In sharp contrast, after AU normalization, only the true miR (miR-155) was detected and its statistical significance was substantially improved (##TAB##1##Table 2##). Importantly, none of the permuted seeds derived from the seed of miR-155 obtained a statistically significant score.</p>", "<p>For a more challenging test case we used a dataset that monitored gene expression profiles in five distinct human T cells sub-populations representing five phases of T cell differentiation ##REF##15210650##[24]##: intrathymic T progenitor (ITTP) cells, double positive (DP) thymocytes, CD4 single positive (SP4), naïve CD4 T cells from cord blood (CB4), and naïve CD4 T cells from adult blood (AB4). To obtain fold-change measures, we divided the expression level at each development phase by the one measured in the mature AB4 T cells. Without AU normalization, the statistical tests identified six significant miR families: the target sets of three were down-regulated in ITTP cells, and the target sets of the other three were up-regulated in the SP4 cells (##TAB##2##Table 3##). After applying the AU normalization to the data, only the three miR-families whose target sets were repressed in ITTP (miR-17.5p, miR-19 and miR-181 families) remained significant (##TAB##2##Table 3##), suggesting that members of these three miR families are active in early phases of T cell development and become inactive as T cells mature. There is evidence that all three miR families detected by the statistical analysis play a role in thymocyte maturation and therefore are true hits. Li et al. recently ##REF##17382377##[25]## showed that miR-181a is highly expressed in immature T cells and that its expression level goes down as T cells proceed through differentiation. That study further showed that miR-181a plays a critical role in augmenting T cell sensitivity, a propensity that is vital to the elimination of self-reacting T cells early during maturation. Regarding miR-17.5p and miR-19 families, Landais et al. recently reported that the miR-106-363 cluster is over-expressed in 46% of human T-cell leukemias tested ##REF##17575136##[26]##. The miR-106-363 cluster is homolog to the miR-17-92 cluster, and miR-19 is contained in both clusters but carries a seed which is different from the one of the other miRs in these two clusters. It is possible that up-regulation of members of the miR-106-363 and miR-17-92 clusters in T-cell leukemia endows these cells with propensities normal to immature T-cells, most probably enhanced proliferation capacity. The identification of true hits on this dataset further demonstrates that computational analysis can accurately dissect active miRs from gene expression data probing cells under physiological conditions. Our statistical analysis utilizes target prediction based on miR seed signatures and therefore cannot distinguish between miRs sharing seed sequences. Empirical biological testing is required to pinpoint which members of the miR-17-92 and miR-106-363 clusters that carry a common seed sequence are actually active during T cell maturation.</p>" ]

[ "<title>Discussion</title>", "<p>In the course of this study we observed in many gene expression datasets a striking association between gene response and 3′-UTR base composition. The high prevalence of such a relationship in microarray datasets, its exceptional statistical strength, and its detection in technical comparisons between replicate arrays, point unequivocally to a major bias in microarray measurements that was heretofore missed. Such a major AU bias in microarray measurements might have gone undetected because gene expression data are commonly analyzed in association with promoter, rather than 3′-UTR sequences, in attempts to unravel cis-regulatory promoter elements that control gene transcription. Only recently, with the emergence of miRs and RNA-binding proteins as key post-transcriptional regulators of gene expression, has gene expression analysis been coupled with analysis of 3′-UTR sequences. Indeed, it was the search for active miRs that motivated us to integrate gene expression and 3′-UTR sequence data, and led us to the detection of the AU response bias in microarray data.</p>", "<p>We demonstrated that this bias is distinct from the well-documented intensity-response and AU intensity biases, and that it originates from a systematic association between probe base composition and response. Using the new generation Affymetrix chips that contain probes selected throughout the transcripts, we uncoupled the sequences of probes and target 3-UTRs. We show that probes exhibit similar AU response bias irrespective of their location in the target transcripts. Therefore, the major link between gene response and 3′-UTR base composition that we observed in vast microarray datasets, is secondary to the general probe AU response bias, and simply reflects the fact that chip probes were selected from 3′-UTRs. A reasonable explanation to the AU response bias is that there are subtle differences in hybridization conditions for different arrays in a dataset, and that the effect of such differences is dependent on probe base composition. Further technical examinations are required to test this point.</p>", "<p>Bioinformatics analysis that integrates gene expression data and 3′-UTR sequences holds promise for systematic dissection of regulatory networks controlled by miRs. However, we demonstrated that the AU response bias causes many false positive calls in such analysis. Permutation tests were highly effective in revealing such false positive hits. Removal of this bias is of crucial importance when aiming to uncover miR-signatures as well as other cis-regulatory elements embedded in 3′-UTRs from mRNA expression profiles. We therefore developed visualization and normalization schemes for the detection and removal of AU biases, and demonstrated that their application to microarray data significantly enhances the computational identification of active miRs. In the case of Affymetrix chips, the normalization scheme that we implemented works at the probe-set or transcript level, and corrects the AU bias in a post-processing step (i.e., ran after probe intensity levels were calculated). A normalization scheme that takes into account the AU response bias at the phase of probe intensity calculation (similar to gcrma, which cancels AU intensity biases) is still required.</p>", "<p>Our results further substantiate that mRNA expression data contain ample information that allows, after proper removal of AU biases, in silico detection of active miRs. Importantly, this is also true when mRNA profiles were measured under physiological conditions. In view of the importance of elucidating regulatory roles played by miRs in various biological networks, we anticipate that the methods introduced in this study for detection, visualization and removal of the AU response bias from microarray data will be in wide use by the research community.</p>" ]

[]

[ "<p>Conceived and designed the experiments: RE RA. Performed the experiments: RE. Analyzed the data: RE. Wrote the paper: RE RA.</p>", "<p>Elucidation of regulatory roles played by microRNAs (miRs) in various biological networks is one of the greatest challenges of present molecular and computational biology. The integrated analysis of gene expression data and 3′-UTR sequences holds great promise for being an effective means to systematically delineate active miRs in different biological processes. Applying such an integrated analysis, we uncovered a striking relationship between 3′-UTR AU content and gene response in numerous microarray datasets. We show that this relationship is secondary to a general bias that links gene response and probe AU content and reflects the fact that in the majority of current arrays probes are selected from target transcript 3′-UTRs. Therefore, removal of this bias, which is in order in any analysis of microarray datasets, is of crucial importance when integrating expression data and 3′-UTR sequences to identify regulatory elements embedded in this region. We developed visualization and normalization schemes for the detection and removal of such AU biases and demonstrate that their application to microarray data significantly enhances the computational identification of active miRs. Our results substantiate that, after removal of AU biases, mRNA expression profiles contain ample information which allows in silico detection of miRs that are active in physiological conditions.</p>", "<title>Author Summary</title>", "<p>MicroRNAs are a novel class of genes that encodes for short RNA molecules recognized to play key roles in the regulation of many biological networks. MicroRNAs, predicted to collectively target more than 30% of all human protein-coding genes, suppress gene expression by binding to regulatory elements usually embedded in the 3′-UTRs of their target mRNAs. Despite intensive efforts in recent years, biological functions carried out by microRNAs have been characterized for only a small number of these genes, making elucidation of their roles one of the greatest challenges of biology today. Bioinformatics analyses can significantly help meet this challenge. In particular, the integrated analysis of microarray mRNA expression data and 3′-UTR sequences holds great promise for systematic dissection of regulatory networks controlled by microRNAs. Applying such integrated analysis to numerous microarray datasets, we disclosed a major technical bias that hampers the identification of active microRNAs from mRNA expression profiles. We developed visualization and normalization schemes for detection and removal of the bias and demonstrate that their application to microarray data significantly enhances the identification of active microRNAs. Given the broad use of microarrays and the ever-growing interest in microRNAs, we anticipate that the methods we introduced will be widely adopted.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank the authors of the microarray datasets analyzed in this paper for making their data publicly available.</p>" ]

[ "<fig id=\"pcbi-1000189-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g001</object-id><label>Figure 1</label><caption><title>Relationship between 3′-UTR AU content and gene response during HPC differentiation.</title><p>Expression profiles were measured at several time points after stimulation of HPC differentiation into megakaryocytes. To visualize the relationships between 3′-UTR AU content and gene response, the genes were sorted for each time point according to their fold of repression/induction relative to the expression level at t0, and the mean 3′-UTR AU content was calculated in a sliding window that encompassed in each step 5% of the genes included in the analysis. (At each step the sliding window was moved to the right by 5% of its size.) Each plot corresponds to the time point indicated above it. Genes are sorted on the X-axis according to their response, from the most repressed genes at the left to the most induced genes at the right. The Y-axis represents the mean 3′-UTR AU content calculated on each sliding window. The <italic>p</italic> value above each plot is for the comparison (Wilcoxon test) between the 3′-UTR AU content of the top 5% (most strongly up-regulated) and bottom 5% (most strongly down-regulated) genes at the corresponding time point. Note the striking relationship between 3′-UTR AU content and gene response at the 16 hr time point.</p></caption></fig>", "<fig id=\"pcbi-1000189-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g002</object-id><label>Figure 2</label><caption><title>Strong relationship between 3′-UTR AU content and gene response detected in a comparison between technical replicates.</title><p>The figure shows the relationship between 3′-UTR AU content and gene fold-change in a comparison between two chips hybridized with identical universal reference RNA pools. The plot was generated as described in the legend to ##FIG##0##Figure 1##. A highly significant relationship between 3′-UTR AU content and gene response was detected in this technical comparison (<italic>p</italic> value = 8.1*10⁻⁸⁴ for the comparison between the bottom and top 5% ‘responding’ genes), pointing to a major AU bias in microarray measurements.</p></caption></fig>", "<fig id=\"pcbi-1000189-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g003</object-id><label>Figure 3</label><caption><title>M-A and M-AU plots.</title><p>(A). M-A plot shows that there is no intensity-response bias in the comparison between the two chips hybridized with identical universal reference RNA pools. The Y axis (denoted as M) represents the log2 fold-change and the X-axis (denoted as A) represents the average log2 intensity. Each dot in the plot corresponds to a gene in the dataset. (B). Adopting the M-A plot concept, we introduced the M-AU plot, in which the Y axis represents the log2 fold-change (as in the M-A plots), and the X axis represents the 3′-UTR AU content of a gene. The M-AU plot shows a major AU bias in this technical dataset. The red line is the lowess smoothing line calculated for the scatter plot.</p></caption></fig>", "<fig id=\"pcbi-1000189-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g004</object-id><label>Figure 4</label><caption><title>The AU response bias is related to probe base composition regardless probe location along the target transcript.</title><p>Probe-level M-AU plot for the comparison between two chips hybridized with a common human brain reference sample. This dataset used the new generation Affymetrix Human Gene 1.0 ST Array, in which probes are located throughout the target transcripts. We generated plots which either included all probes, or included separately only those mapped to the 5′-UTR, CDS, or 3′-UTR of the targets. (As the length of each probe is 25 bases, probe's AU content (X axis) gets only discrete values in the 0–100% range with jumps of 4%). Probes mapped to the different transcript regions exhibited similar level of AU response bias.</p></caption></fig>", "<fig id=\"pcbi-1000189-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g005</object-id><label>Figure 5</label><caption><title>AU normalization.</title><p>M-AU plots without (A) and after (B) applying an AU normalization scheme to the technical dataset which profiled the universal reference RNA pool.</p></caption></fig>", "<fig id=\"pcbi-1000189-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.g006</object-id><label>Figure 6</label><caption><title>AU bias in the miR-155 dataset.</title><p>Relationship between 3′-UTR AU content and gene response in the dataset that compared gene expression profiles between miR-155-deficient and control Th2 cells. (A) Without AU normalization. (B) After applying AU normalization to the dataset. Plots were generated as described in the legend to ##FIG##0##Figure 1##.</p></caption></fig>" ]

[ "<table-wrap id=\"pcbi-1000189-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.t001</object-id><label>Table 1</label><caption><title>Active miRs falsely identified in the negative test case.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"4\" align=\"left\" rowspan=\"1\">Without AU Normalization</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic> Value</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR Seed</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Best Permuted <italic>p</italic> Value<xref ref-type=\"table-fn\" rid=\"nt101\">a</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.186</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.41*10⁻⁹\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">AAAGAAU</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.60*10⁻¹¹\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.543</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.72*10⁻⁷\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">AACAUUC</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.01*10⁻⁷\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.496</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.24*10⁻⁷\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">UUACAUG</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.14*10⁻⁷\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.200b.429</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.07*10⁻⁷\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">AAUACUG</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.84*10⁻¹⁰\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.381</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.41*10⁻⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">AUACAAG</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.48*10⁻¹⁰\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.62*10⁻⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">UCAAGUA</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.07*10⁻⁵\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.203.1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.79*10⁻⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">GAAAUGU</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.34*10⁻⁶\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.132.212</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00017</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">AACAGUC</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0019</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.181</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00029</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<named-content content-type=\"gene\">ACAUUCA</named-content>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.45*10⁻¹⁰\n</td></tr></tbody></table><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"4\" align=\"left\" rowspan=\"1\">After AU Normalization<xref ref-type=\"table-fn\" rid=\"nt102\">b</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic> Value</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Best Permuted <italic>p</italic> Value<xref ref-type=\"table-fn\" rid=\"nt101\">a</xref>\n</td><td align=\"center\" rowspan=\"1\" colspan=\"1\"/></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.186</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0061</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0060</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.500</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0073</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0025</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pcbi-1000189-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.t002</object-id><label>Table 2</label><caption><title>Active miRs identified in the miR-155 dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"3\" align=\"left\" rowspan=\"1\">Without AU Normalization</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic> Value<xref ref-type=\"table-fn\" rid=\"nt103\">a</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Best Permuted <italic>p</italic> Value<xref ref-type=\"table-fn\" rid=\"nt104\">b</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.496</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.56*10⁻¹⁰\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.13*10⁻⁷\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.186</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.43*10⁻⁰⁸\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−2.29*10⁻⁹\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>miR.155</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>7.07*10⁻⁰⁸</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−3.98*10⁻⁶\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.26</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−2.15*10⁻⁰⁶\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.41*10⁻⁷\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.543</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−2.33*10⁻⁰⁶\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−6.04*10⁻⁶\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.25.32.92.363.367</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−6.54*10⁻⁰⁶\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−3.71*10⁻⁷\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.381</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.09*10⁻⁰⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−9.99*10⁻⁸\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.329</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.98*10⁻⁰⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.31*10⁻³\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.331</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.48*10⁻⁰⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.19*10⁻¹\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.493.5p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−3.98*10⁻⁰⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.46*10⁻¹⁰\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.495</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−7.41*10⁻⁰⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−9.60*10⁻⁸\n</td></tr></tbody></table><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"3\" align=\"left\" rowspan=\"1\">After AU Normalization<xref ref-type=\"table-fn\" rid=\"nt103\">a</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic> Value</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Best Permuted <italic>p</italic> Value<xref ref-type=\"table-fn\" rid=\"nt104\">b</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>miR.155</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>1.20*10⁻¹²</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.023</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.142.5p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00083</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.024</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pcbi-1000189-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pcbi.1000189.t003</object-id><label>Table 3</label><caption><title>Active miRs identified in the thymocyte maturation dataset.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"5\" align=\"left\" rowspan=\"1\">Original Dataset</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITTP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DP4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SP4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CB4</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.17.5p.20.93.mr.106.519.d</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.45*10⁻⁹\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0055</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.75</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−7.04*10⁻⁸\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0085</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.52</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.040</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.101</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.76</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0059</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.27*10⁻⁶\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.97</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.144</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0048</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.48*10⁻⁶\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.381</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0064</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.81*10⁻⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.77</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.181</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−5.30*10⁻⁵\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.649</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.35</td></tr></tbody></table><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"5\" align=\"left\" rowspan=\"1\">After Applying AU Normalization</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR ID</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">ITTP<xref ref-type=\"table-fn\" rid=\"nt105\">a</xref>\n^#\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">DP4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">SP4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CB4</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.17.5p.20.93.mr.106.519.d</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.04*10⁻⁹ (−4.27*10⁻³)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0016</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.053</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−2.72*10⁻⁸ (−1.24*10⁻²)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0010</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.08</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">miR.181</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−3.19*10⁻⁵ (−7.07*10⁻⁴)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.67</td></tr></tbody></table></alternatives></table-wrap>" ]

[ "<disp-formula></disp-formula>" ]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s001\"><label>Figure S1</label><caption><p>Relationship between 3′-UTR AU content and gene response during HPC differentiation. The plot was generated as described in the legend to ##FIG##0##Figure 1## and shows the relationship between 3′-UTR AU content and gene response at three time points (4, 8, and 16 h) during HPC differentiation into three lineages (erythrocytes (E), monocytes (M), and neutrophils (N)).</p><p>(0.13 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s002\"><label>Figure S2</label><caption><p>AU bias in microarray data is not specific to a particular preprocessing method. The major AU bias in the dataset that profiled the universal reference RNA pool is not specific to a particular preprocessing method as it existed in data derived using different preprocessing and normalization schemes: rma, gcrma, and mas5.</p><p>(0.12 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s003\"><label>Figure S3</label><caption><p>No preference for A or U in the AU bias. The figure shows the relationship between gene fold-change in the technical dataset and: 3′-UTR AU content, 3′-UTR length, and 3′-UTR single base contents. The figure was generated as described in the legend to ##FIG##0##Figure 1## (<italic>p</italic> values indicated above each plot are for the comparison between the top 5% and bottom 5% genes). In this dataset, there is no preference for A or U in the relationship between 3′-UTR AU content and gene response. No major relationship between 3′-UTR length and gene response was observed here.</p><p>(0.13 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s004\"><label>Figure S4</label><caption><p>The AU response bias exists over large range of intensities. To test whether the AU-response bias is confined to probes with low intensities (which are inherently noisier), we redrew the M-A plot in ##FIG##2##Figure 3A##, and colored each point according to the AU content of the corresponding probe (probes were divided into three groups: High, Medium and Low AU content probes; each group contained one third of the probes included in the analysis). The AU response bias is not associated with low intensity but exists over a large range of intensities.</p><p>(0.33 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s005\"><label>Figure S5</label><caption><p>AU bias using probe-set AU content. M-AU plot in which the X-axis represents probe-set AU content (in contrast to transcript 3′-UTR AU content shown in ##FIG##2##Figure 3B##).</p><p>(0.13 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pcbi.1000189.s006\"><label>Figure S6</label><caption><p>AU normalization does not distort the normalization at the M-A plane. This figure presents the M-A plot after applying AU normalization. While this normalization cancels the major bias detected at the M-AU plane, it has only subtle effect on the M-A plane.</p><p>(0.18 MB TIF)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label>a</label><p>Best <italic>p</italic>-value obtained for 20 randomly permuted seeds derived from the original miR seed.</p></fn><fn id=\"nt102\"><label>b</label><p>After applying AU normalization to the dataset none of the miRs passed the statistical significance threshold (0.0003, which corresponds to 0.05 after Bonferroni correction for multiple testing). In order to compare the results with the original data (without AU normalization), we listed the top two miRs even though they did not pass the threshold.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><label>a</label><p>The sign of the <italic>p</italic>-value marks the direction of the response of the miR target set: positive and negative <italic>p</italic>-values correspond to miRs whose target sets are significantly up- and down-regulated in miR-deficient Th2 cells, respectively, compared to wild type Th2 cells. The results obtained for the true signal in this dataset—miR-155—are emphasized in bold-italic font, and are in the expected direction: that is, the set of miR-155 predicted target genes is up-regulated in miR-155 deficient Th2 cells compared to control Th2 cells.</p></fn><fn id=\"nt104\"><label>b</label><p>Best <italic>p</italic>-value obtained for 20 randomly permuted seeds derived from the original one.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt105\"><label>a</label><p>In parentheses, the best <italic>p</italic>-value in 20 random seed permutations.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p>RE is supported by an EMBO long-term fellowship, and RA by the European Young Investigator Award and Horizon from the Dutch Science Organization (NWO).</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pcbi.1000189.g001\"/>", "<graphic xlink:href=\"pcbi.1000189.g002\"/>", "<graphic xlink:href=\"pcbi.1000189.g003\"/>", "<graphic xlink:href=\"pcbi.1000189.g004\"/>", "<graphic id=\"pcbi-1000189-t001-1\" xlink:href=\"pcbi.1000189.t001\"/>", "<graphic xlink:href=\"pcbi.1000189.g005\"/>", "<graphic xlink:href=\"pcbi.1000189.g006\"/>", "<graphic id=\"pcbi-1000189-t002-2\" xlink:href=\"pcbi.1000189.t002\"/>", "<graphic id=\"pcbi-1000189-t003-3\" xlink:href=\"pcbi.1000189.t003\"/>", "<graphic xlink:href=\"pcbi.1000189.e001.jpg\" mimetype=\"image\" position=\"float\"/>" ]

[ "<media xlink:href=\"pcbi.1000189.s001.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pcbi.1000189.s002.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pcbi.1000189.s003.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pcbi.1000189.s004.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pcbi.1000189.s005.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pcbi.1000189.s006.tif\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Bacterial infections are a major source of morbidity and mortality in HIV- infected children, causing . a wide spectrum of diseases, many of which are included in the WHO and CDC staging systems##REF##3031443##[1]##, ##UREF##0##[2]## In an early USA study predating both trimethoprim-sulfamethoxazole (TMP-SMX) and antiretroviral therapy (ART)##UREF##1##[3]##, there were 160 episodes of minor and 48 serious bacterial infections (SBI) per 100 patient-years in HIV-infected children, demonstrating the extremely high burden of bacterial morbidity. A similar study performed after the introduction of TMP-SMX and zidovudine monotherapy documented a two-year SBI rate of 45% among children receiving TMP-SMX.##REF##7935655##[4]##. In a randomized controlled trial of TMP-SMX prophylaxis for HIV-infected children in Zambia, the SBI admission rate was 19 per 100 child-years in the TMP-SMX group and 29 in the placebo group (P = 0.09), and the cumulative two-year probability of dying in hospital from SBI (predominantly pneumonia) was 7% on TMP-SMX and 12% on placebo (P = 0.08).##REF##17148971##[5]## Thus, data from varied settings documented high rates of SBI in children and a protective effect of TMP-SMX.</p>", "<p>Since the widespread availability of antiretroviral therapy (ART), there has been a marked decrease in the morbidity and mortality of bacterial infections in both resource rich and resource limited settings ##REF##17606567##[6]##, ##REF##18450865##[7]##. In the USA, pneumonia is still the most common bacterial infection in HIV-infected children on ART, however, in comparison with the pr-ART era, the incidence has decreased from 11 to 2 events per 100 person years.##UREF##2##[8]## In a Californian cohort, bacterial infections accounted for 60 hospitalizations for 64 children in 1994, versus only 8 for 101 children in 2001.##REF##15356789##[9]## The hospitalization rate for SBI was only 14.2 per 100 person years for a Thai cohort of children on ART.##REF##17243067##[10]## Nevertheless, bacterial infections remained the most common reason for hospitalization.</p>", "<p>HIV-infected children have a greater risk of bacterial infections than their HIV-negative counterparts##REF##17467514##[11]##, and these infections are more invasive, more likely to disseminate, and have worse outcome in HIV-infected children.##REF##17467514##[11]##–##REF##11236037##[13]## Also, HIV-infected children often have multiple diagnoses and polymicrobial infections.##REF##17467514##[11]##, ##REF##10996984##[12]## All organ systems can be involved by bacterial infections, and concomitant bacteraemia is common. Abscess formation in internal organs and skin can also occur. Otitis media (OM), acute sinusitis and mastoiditis are also common. By far the most frequent cause of bacterial morbidity in all HIV-infected children is pneumonia, both with and without TMP-SMX prophylaxis.##REF##17148971##[5]##\n</p>", "<p>The emergence of antimicrobial resistant organisms is a global problem, not restricted to children with HIV. However, the widespread use of TMP-SMX for prophylaxis may exacerbate antimicrobial resistance. In a South African study, only four of 26 <italic>S. pneumoniae</italic> from HIV-infected children with community acquired pneumonia were sensitive to TMP-SMX.##REF##17467514##[11]## Resistance was unaffected by TMP-SMX prophylaxis, arguing that resistance may be firmly established in the community. The antimicrobial resistance patterns from blood cultures from HIV infected and uninfected children have been compared in only a few settings. The resistance of <italic>both S. pneumoniae</italic> and <italic>S. aureus</italic> to TMP-SMX was significantly higher in the HIV-infected group's isolates in Soweto ##REF##10913417##[14]##. In three African studies, almost 15% of the isolates from HIV-infected children were multiply resistant <italic>E. coli</italic> or Methicillin resistant <italic>staphylococcus aureus</italic> (MRSA). ##REF##10913417##[14]##–##UREF##4##[16]## However, in the Ugandan children, organisms from HIV-infected children were either more sensitive or had the same profile as uninfected children.##UREF##4##[16]## Therefore it is unclear how widespread antimicrobial resistance is in HIV-infected children.</p>" ]

[ "<title>Methods</title>", "<title>Objectives</title>", "<p>We sought to evaluate the spectrum of bacterial infection, causative organisms, and antibiotic resistance patterns of an inpatient cohort of HIV-infected children.</p>", "<title>Participants</title>", "<p>We conducted a retrospective cohort study of all HIV-positive pediatric admissions to a Pediatric ward in an urban public sector hospital in Cape Town between January 2002 and June 2006. Over 50% of all admissions are HIV-infected. The referral population is a largely black African population living in rapidly growing settlements with residents of predominantly low socioeconomic status. Data were collected from paper charts and computer records. Where more than one hospitalization per patient occurred, only the first was examined.</p>", "<p>Children between one month and nine years of age with laboratory confirmed HIV-infection, SBI and hospitalization for 5 or more days, were eligible for inclusion.</p>", "<title>Description of investigations</title>", "<p>The following were considered SBI: bacterial sepsis, bacterial pneumonia, urinary tract infection, and/or meningitis. For bacterial sepsis, children had organisms identified on blood culture. Diagnosis of bacterial pneumonia was made by clinical findings, laboratory results including high white blood cell count with neutrophil predominance, lobar consolidation on chest radiograph, and blood cultures when available. For meningitis, either an organism was isolated from cerebrospinal fluid or the chemistry and cell counts were suggestive of bacterial infection. Coagulase negative staphylococcus only included as a pathogen if isolated from more than one culture or from a patient with indwelling invasive lines. All <italic>S. aureus</italic> isolates were considered pathogenic, as the patients were ill. An infection was considered community acquired if symptomatic at admission or if cultures taken at or before 48 hours after admission were positive. If positive cultures or new symptoms appeared after 48 hours, the infection was considered nosocomial or hospital acquired ##UREF##5##[17]##.</p>", "<p>Clinical specimens submitted for bacterial culture were inoculated into appropriate media depending on the nature of the specimen. Organisms were identified by standard biochemical and/or serological methods. Antimicrobial susceptibility testing was done by the Kirby-Bauer disc diffusion technique, and MICs (if necessary) were performed using E-tests. Susceptibilities were not available for all specimens from 2002–2003. Therefore, susceptibilities represent more recent specimens.</p>", "<title>Ethics</title>", "<p>Approval for this study was obtained from the University of Cape Town Faculty of Health Sciences Research Ethics Committee. Exemption from informed consent was granted as this was a retrospective study with no identifying data.</p>" ]

[ "<title>Results</title>", "<title>Cohort Demographics</title>", "<p>One hundred and forty-one children met inclusion criteria. The median age was 1.2 years (IQR 0.5–2.3) and 65 (46%) were female (##TAB##0##table 1##). The median weight on admission was 6.7 kg (IQR 4.7–9.6)), 16 (11.4%) with a diagnosis of marasmus and a further 27 (19%) labeled as failure to thrive.</p>", "<p>Approximately one third of children received ART(n = 55). However, the median time on ART was only 6 days (IQR -8–35), and many were started during this hospitalization. There were 40 children on tuberculosis treatment; some children were receiving both ART and TB treatment (n = 16; 11.3%). The median CD4 percentage was 17.2% (IQR 9.7–22.7), with a median absolute CD4 count of 509 cells/mm³ (IQR 244–759). The median hospital length of stay was 13 days (IQR 6–34 days). There were 13 deaths in hospital with the remainder being discharged.</p>", "<title>Spectrum of Disease</title>", "<p>A lower respiratory tract infection was diagnosed in 95 (67%) of the children, while 74 (53%) had bacterial sepsis. The most prevalent bacterial infections in this cohort of hospitalized children were pneumonia and sepsis (##TAB##0##Table 1##). However, most other organ systems were affected, including the central nervous system (meningitis), lung, mastoid, bone and joints. A high proportion of patients with pneumonia, meningitis, and urinary tract infection had concomitant bacteremia. <italic>Mycobacterium tuberculosis</italic> was a frequent concomitant infection. Eight deaths had dual diagnoses of sepsis and pneumonia, and one had both sepsis and a UTI.</p>", "<title>Responsible Organisms</title>", "<p>The relative frequencies of specific bacterial isolates from blood, urine and CSF cultures of HIV-infected children are shown in ##TAB##1##table 2## (excluding mycobacteria). The most common pathogen isolated from blood was <italic>S. pneumoniae</italic> followed by <italic>S aureus</italic>. The most common gram negative organism was <italic>K. pneumoniae</italic>. All <italic>K. pneumoniae</italic> isolates were from blood cultures taken more than two days into the admission, implying a nosocomial origin. In contrast, all but two <italic>S pneumoniae</italic> from blood culture were within two days of admission, therefore probably community acquired. The organisms most frequently present when the outcome was fatal were <italic>S aureus</italic> (n = 3, all MRSA), Coagulase negative staphylococcus (n = 3) and <italic>K pneumoniae</italic> (n = 3). Five of the 13 children who died grew multiple pathogenic organisms in blood or urine.</p>", "<title>Susceptibility Patterns</title>", "<p>The antimicrobial susceptibility patterns of each of the more prevalent organisms are shown in ##TAB##2##table 3##. <italic>S. pneumoniae</italic> and <italic>H. influenza</italic> isolates were generally highly susceptible, whereas the majority of the <italic>K. pneumoniae</italic> isolates, most likely nosocomial, were highly resistant. All <italic>K. pneumoniae</italic> isolates were extended spectrum beta-lactamase producing; the only single antibiotic to which all <italic>K. pneumoniae</italic> isolates were susceptible was Meropenem. <italic>S. aureus</italic> whether community-acquired or nosocomial, was often resistant to TMP-SMX, and clindamycin, both frequently used antibiotics for resistant staphylococci. . Although community-acquired non-typhoid salmonella (NTS) were susceptible to first-line antibiotics such as ampicillin, the more frequently hospital-acquired organisms were more resistant. MRSA was isolated from a third of the blood cultures of children who died, as was <italic>K. pneumoniae</italic>, therefore resistant organisms were possibly responsible for a relatively high proportion of the mortality, and appropriate empiric therapy was not used.</p>" ]

[ "<title>Discussion</title>", "<p>In this cohort of hospitalized HIV-infected children, pneumonia was the most common SBI resulting in hospitalization. There was frequent coincident bacteremia. This is consistent with other HIV-infected pediatric cohorts described from both developing and developed settings##REF##17148971##[5]##, ##UREF##2##[8]##. The relative prevalence of most bacterial pathogens is similar to that of HIV-uninfected children. In a large Kenyan study <italic>S. pneumoniae, H. influenzae</italic>, NTS, and <italic>E. coli</italic> were more common in HIV-infected children ##REF##15635111##[18]##. These organisms were commonly seen in malnourished children in the pre-HIV era. <italic>S. pneumoniae</italic> is the most common organism in other cohorts, with <italic>S. aureus</italic>, <italic>Salmonella</italic> species, and <italic>Enterobacteriaceae</italic> occurring frequently ##REF##7935655##[4]##, ##REF##17467514##[11]##, ##REF##10913417##[14]##, ##UREF##3##[15]##. <italic>P. aeruginosa</italic> is also seen occasionally. The proportion of <italic>H influenzae</italic> is influenced by the introduction of the <italic>H. influenzae</italic> type B (Hib) vaccine, in 1999 in South Africa.</p>", "<p>Bacteria that were assumed to be predominantly community acquired were generally susceptible to first line or narrow spectrum antibiotics (those that target generally only one class of bacteria). This included the <italic>S. pneumoniae</italic> isolates. In other settings, multi-drug resistant <italic>S. pneumoniae</italic> were increasing in frequency before introduction of the pneumococcal conjugate vaccine ##REF##18435393##[19]##, ##UREF##6##[20]##. In children with community acquired pneumonias in Soweto, South Africa, 50% of the <italic>S. pneumoniae</italic> isolates from the HIV-infected children were penicillin resistant versus 23% of the HIV-negative children's isolates.##REF##10913417##[14]## The community-acquired <italic>S. aureus</italic> isolates were, however, all MRSA. The empiric treatment of community acquired bacterial infections in HIV-infected children in resource limited settings should bear in mind the antimicrobial susceptibility patterns of the region. Penicillin and ampicillin are effective against most penicillin-non-susceptible pneumococcal isolates in the case of isolated respiratory tract infections. The clinician must consider viral, fungal, and mycobacterial infections in the differential diagnosis of bacterial infections and treat accordingly.</p>", "<p>The high proportion of <italic>K. pneumoniae</italic> resistant to third generation cephalosporin is highly concerning, particularly since all these infections were acquired after two days in hospital, and therefore probably hospital-acquired. Highly resistant organisms have been described from a similar setting ##UREF##3##[15]##, and is likely due to extended spectrum beta lactamase production. Since not all <italic>K. pneumoniae</italic> isolates were susceptible to piperacillin-tazobactam or amikacin, clinicians should consider empiric carbapenems for suspected hospital-acquired sepsis.</p>", "<p>Nosocomial infections are more common in HIV-infected than in uninfected adults, with the most frequently isolated bacterial pathogens being <italic>S. aureus and P. aeruginosa</italic>, a high proportion of which are methicillin resistant ##REF##16501896##[21]##. Nosocomial infections in HIV-infected adults have a high mortality. There are few data on nosocomial bacterial infections in HIV-infected children. In a cohort of children hospitalized with TB, nosocomial infections were more common in HIV-infected patients, and more frequently fatal ##UREF##7##[22]##. Although our data do not reflect the overall prevalence of nosocomial infections in hospitalized HIV-infected children due to our study design, the data may represent common resistance patterns of these organisms.</p>", "<p>The most effective public health approach to improving infectious disease burden is vaccination. Effective vaccines are licensed for Hib and <italic>S. pneumoniae</italic>. Both are polysaccharide protein conjugate vaccines. The Hib vaccine is now widely available including in developing countries. Although the estimated efficacy of the Hib vaccine is decreased and the risk for vaccine failure increased in HIV-infected children,##REF##16107294##[23]##, ##REF##12075763##[24]## the introduction of Hib vaccine into countries with high HIV prevalence has greatly decreased Hib disease burden.##REF##17128361##[25]## In 2000, a pneumococcal conjugate vaccine (PCV) was licensed in the USA. Although PCV is less immunogenic in HIV-infected children than non-infected children,##UREF##8##[26]## this also seems to improve in children receiving ART.##REF##17006288##[27]## A similar 9-valent PCV has been extensively studied in South Africa, and similar efficacy is seen in these HIV-infected infants.##REF##17023095##[28]## Unfortunately, PCV is not widely accessible to children in less resourced countries, and its access should become a global priority.</p>", "<p>These data confirm that pneumonia is the most common SBI in HIV-infected children, but with a wide spectrum of presentation. The predominance of MRSA is alarming. The high proportion of nosocomially acquired highly resistant <italic>K. pneumoniae,</italic> suggest that infection control practices should be implemented to avoid the spread of antibiotic resistance. While overuse of broad-spectrum antibiotics should be avoided, judicious limited use is indicated for suspected nosocomial sepsis.</p>", "<title>Limitations</title>", "<p>The limitations of these data are that they are retrospective and therefore incomplete. In addition, the isolation of organisms is dependant on adequate blood volumes and rapid transport to the microbiology laboratory, both of which may have been limited in the setting of sick, malnourished children in a resource-limited hospital. Our findings may not be generalizable to other better resourced settings such as those with more nursing staff, and less ward crowding, or where all HIV-infected children are on ART.</p>" ]

[]

[ "<p>Conceived and designed the experiments: HBJ. Performed the experiments: LCH. Analyzed the data: HBJ AW LM. Wrote the paper: HBJ MC. Provided clinical expertise: HBJ. Performed the data collection, and some statistical analysis: LCH. Performed literature review: MFC. Contributed to the laboratory methods and interpretation: AW. Revised the manuscript: MFC LM. Supervised study design and statistical analysis: LM.</p>", "<p>Current address: Department of Pediatrics, University of Washington, Children's Hospital and Regional Medical Center, Seattle, Washington, United States of America</p>", "<title>Background</title>", "<p>Serious bacterial infections are a major source of morbidity and mortality in HIV-infected children. The spectrum of disease is wide, and responsible organisms vary according to setting. The use of antibiotic prophylaxis and the emergence of multi-drug resistant bacteria necessitate examination of responsible organisms and their antibiotic susceptibility.</p>", "<title>Methodology/Principal Findings</title>", "<p>A retrospective cohort study of all HIV-positive pediatric admissions at an urban public sector hospital in Cape Town between January 2002 and June 2006 was conducted. Children between the ages of one month and nine years with laboratory confirmed HIV status, serious bacterial infection, and a hospital length of stay of 5 days or more, were eligible for inclusion. Organisms isolated from blood, urine, and cerebral spinal fluid cultures and their antimicrobial susceptibility were examined, and compared according to timing of isolation to distinguish nosocomial versus community-acquired. One hundred and forty-one children were identified (median age 1.2 years), 39% of whom were on antiretrovirals started before or during this hospitalization. Bacterial infections involved all organ systems, however pneumonia was most common (67%). <italic>S. pneumoniae</italic> and <italic>S. aureus</italic> were the most common gram positive and <italic>K. pneumoniae</italic> was the most common gram negative organism. <italic>K pneumoniae</italic> isolates were resistant to many first and second line antibiotics, and were all considered nosocomial. All <italic>S. aureus</italic> isolates were methicillin resistant, some of which were community-acquired.</p>", "<title>Conclusions/Significance</title>", "<p>Bacterial infections are an important source of co-morbidity in HIV-infected children in resource-limited settings. Clinicians should have a low threshold to initiate antibiotics in children requiring hospitalization. Broad-spectrum antibiotics should be used judiciously. Clinicians caring for HIV-infected children should be cognizant of the most common organisms affecting such children, and of their local antimicrobial susceptibilities, when treating empirically for serious bacterial infections.</p>" ]

[]

[ "<p>The authors acknowledge the G25 ward staff and medical records at Groote Schuur Hospital.</p>" ]

[]

[ "<table-wrap id=\"pone-0003260-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003260.t001</object-id><label>Table 1</label><caption><title>Demographics and spectrum of serious bacterial disease in hospitalized children with HIV.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Characteristic</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">n (%)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gender</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Males</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">76 (54)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Females</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">65 (46)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">On ART</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">55 (39)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">On TB medication</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">39 (28)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mortality</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13 (9)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Age at admission (yrs)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.2 (0.5–2.34)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Median (IQR)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Weight at admission (kg)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.7 (4.7–9.6)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Median (IQR)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Temp. at admission (°C)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">37.3 (36.5–38.3)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Median (IQR)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Birth weight (kg)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.8 (2.8–3.0)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mean (95% CI)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hemoglobin on admission</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.1 (8.1–10.3)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Median (IQR)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Concomitant Diagnoses</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TB</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40 (28)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TB meningitis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2 (1)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gastroenteritis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">54 (38)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PEM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">16 (11)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Fungal sepsis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 (2.3)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Failure to thrive</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">29 (21)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bacterial Infections</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40 (28)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bacterial sepsis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">74 (52)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Pneumonia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">95 (67)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"> % Bacteremic pneumonia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Bacterial meningitis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 (3)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"> % Bacteremic meningitis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Urinary tract infection</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15 (11)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"> % Bacteremic UTI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">87</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Skin or soft tissue, including abscess</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2 (1.5)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Osteomyelitis or septic arthritis</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (0.7)</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003260-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003260.t002</object-id><label>Table 2</label><caption><title>Bacterial isolates from hospitalized HIV-infected children with serious bacterial infections*</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">Blood n = 128 (%<xref ref-type=\"table-fn\" rid=\"nt102\">1</xref>)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Urine n = 21 (%<xref ref-type=\"table-fn\" rid=\"nt103\">2</xref>)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">CSF n = 36 (%<xref ref-type=\"table-fn\" rid=\"nt103\">2</xref>)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">N (%) assumed nosocomial (&gt;48 hours)<xref ref-type=\"table-fn\" rid=\"nt104\">3</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>S. pneumoniae</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">21 (16)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (2.8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2/22 (9%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>S. aureus</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">14 (11)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">9/14 (64%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Coagulase negative staphylococcus<xref ref-type=\"table-fn\" rid=\"nt105\">4</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">4/4 (100%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>E. coli</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5 (4)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5 (24)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">7/10 (70%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>K. pneumoniae</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">11 (9)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2 (9.5)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">13/13 (100%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hemophilus spps</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8 (7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (2.8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1/9 (11%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>S. typhi</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Non typhoid salmonella</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9 (7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (4.8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">7/10 (70%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>S. milleri</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (100%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Enterococcus faecalis</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2 (9.5)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">5/6 (83%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Enterococcus faecium</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (100%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Enterobacter species</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6 (4)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">4/6 (67%)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>P. aeruginosa</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1 (4.8)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Acinetobacter</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4 (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">3/4 (75%)</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003260-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003260.t003</object-id><label>Table 3</label><caption><title>Antibiotic susceptibilities of the most common organisms isolated from blood cultures of children with serious bacterial infections, according to time of isolation.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td colspan=\"13\" align=\"left\" rowspan=\"1\">% susceptible</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"2\" align=\"left\" rowspan=\"1\">\n<italic>S. pneumoniae</italic>\n</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">\n<italic>S. aureus</italic>\n</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">\n<italic>H. influenzae</italic>\n</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">\n<italic>E. coli</italic>\n</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">Non-typhoid salmonella</td><td colspan=\"2\" align=\"left\" rowspan=\"1\">\n<italic>K. pneumoniae</italic>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Time</italic> ( Total n)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (14)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (9)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (4)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (3)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (6)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>≤48 hrs</italic> (0)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>&gt;48 hrs</italic> (10)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Penicillin/Ampicillin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">79<xref ref-type=\"table-fn\" rid=\"nt106\">a</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50<xref ref-type=\"table-fn\" rid=\"nt106\">a</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Amoxicillin +clavulanate</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20<xref ref-type=\"table-fn\" rid=\"nt107\">b</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">TMP-SMX</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">17</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Cloxacillin/Methicillin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">3^rd generation Cephalosporin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">93<xref ref-type=\"table-fn\" rid=\"nt108\">c</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Erythromycin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">86</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gentamicin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clindamycin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Ofloxacin/Ciprofloxacin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">67</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">40</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Amikacin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">78</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">90<xref ref-type=\"table-fn\" rid=\"nt106\">a</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Pipericillin/Tazobactam</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">75<xref ref-type=\"table-fn\" rid=\"nt106\">a</xref>,<xref ref-type=\"table-fn\" rid=\"nt108\">c</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">50<xref ref-type=\"table-fn\" rid=\"nt106\">a</xref>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Meropenem</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Vancomycin</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">100</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">NT</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><fn id=\"nt101\"><label/><p>ART–antiretroviral therapy, TB–Tuberculosis, PEM-Protein energy malnutrition, IQR–Interquartile range.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt102\"><label>1</label><p>Percent of positive cultures, including fungal and mixed or skin flora</p></fn><fn id=\"nt103\"><label>2</label><p>Percent of all cultures sent. Urine cultures were not done if urine dipstick was normal unless suspicion was high.</p></fn><fn id=\"nt104\"><label>3</label><p>The proportion of nosocomial infections presented here reflects that from children hospitalized for five days or longer, and not necessarily the proportion of nosocomial infections from hospitalizations of all HIV-infected children.</p></fn><fn id=\"nt105\"><label>4</label><p>Coagulase negative staphylococcus only included as a pathogen if isolated from more than one culture or with indwelling invasive lines.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt106\"><label>a</label><p>The remainder were intermediate sensitivity</p></fn><fn id=\"nt107\"><label>b</label><p>Five isolates intermediate susceptibility</p></fn><fn id=\"nt108\"><label>c</label><p>One unknown</p></fn><fn id=\"nt109\"><label/><p>NT–not tested</p></fn><fn id=\"nt110\"><label/><p>NA–not applicable</p></fn><fn id=\"nt111\"><label/><p>TMP-SMX–Trimethoprim sulfamethoxazole</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>LCH was supported in part by the Palo Alto/University Rotary Club, the Waterfront Rotary Club of Cape Town, and the Rotary Foundation, through the Ambassadorial Scholar program, none of whom had any role in the design, conduct, analysis, interpretation and preparation of the research or manuscript.</p></fn></fn-group>" ]

[ "<graphic id=\"pone-0003260-t001-1\" xlink:href=\"pone.0003260.t001\"/>", "<graphic id=\"pone-0003260-t002-2\" xlink:href=\"pone.0003260.t002\"/>", "<graphic id=\"pone-0003260-t003-3\" xlink:href=\"pone.0003260.t003\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Understanding the ways in which organisms allocate energy is fundamental for linking behavioral and life-history traits to evolutionary fitness, and for identifying drivers of physiological adaptation. Basal metabolic rate (BMR) characterizes the maintenance energy requirements of individuals and as such is a core descriptor of a species' energy turn-over rate and, ultimately, its energetic niche in the environment ##UREF##0##[1]##–##UREF##2##[3]##. BMR is the lower limit of the metabolic scope of a normothermic endotherm and represents maintenance energy demands in the absence of thermoregulatory, digestive or activity-related increases in metabolism ##UREF##0##[1]##–##UREF##2##[3]##. Both the processes underlying the body mass-dependence of BMR ##UREF##3##[4]##–##REF##12000958##[6]## and the determinants of body mass-independent variation in BMR have proved to be of enduring interest to ecological and evolutionary physiologists ##UREF##4##[e.g. 7]##, ##UREF##5##[8]##–##REF##17517640##[12]##.</p>", "<p>Significant geographic variation in maintenance energy requirements in mammals and birds has been noted. In small mammals (&lt;1 kg), BMR varies along a continuum from high BMR in species inhabiting highly seasonal, colder environments with more predictable rainfall at high latitudes to low BMR in warmer, less predictable habitats in the semi-tropics ##UREF##5##[8]##, ##UREF##7##[10]##, ##REF##15674767##[13]##. These correlations between BMR and physical environments in small mammals have been interpreted in a supply-demand adaptive framework, with low BMR in mammals from warm, arid environments viewed as an adaptive trait that minimizes energy requirements during unpredictable bottlenecks in food supply ##UREF##5##[8]##, ##UREF##7##[10]##. Higher BMR in species inhabiting colder, more mesic habitats is thought to facilitate high rates of thermoregulatory heat production during rapid heat loss at low environmental temperatures ##UREF##5##[8]##, ##UREF##7##[10]##. For birds, Weathers ##REF##28309699##[14]## found that BMR generally increases with latitude toward the poles, and recent studies have shown similar intraspecific patterns ##REF##17517640##[12]##, ##REF##28307657##[15]##, ##UREF##9##[16]##. Several recent comparative studies of avian BMR have produced evidence that birds inhabiting desert habitats have evolved lower BMR than their mesic counterparts ##REF##11009400##[17]##, ##UREF##10##[18]##. A recent study comparing multiple environmental predictors found strong evidence for a negative effect of average annual temperature of capture locations on avian BMR, but none for habitat net primary productivity ##REF##17148258##[19]##. This is consistent with similar results for avian field metabolic rates rates ##UREF##11##[20]## and suggests that the major environmental correlate of avian BMR is ambient temperature, with elevated BMR associated with cold environments and vice versa. Such temperature-associated variation in BMR could reflect phenotypic plasticity or genotypic adaption ##UREF##12##[21]##–##REF##17170153##[25]##.</p>", "<p>In mammals, relative mobility has been identified as a major determinant of selection acting on maintenance energy demands (Lovegrove, 2000). Whereas the BMR of small mammals is correlated with temperature and habitat aridity, the absence of similar correlations in large mammals is attributed primarily to the capacity of larger species to avoid localized energetic shortfalls by migrating ##UREF##5##[8]##. Interspecific variation in relative mobility is even more pronounced in birds, since even small species undertake seasonal long-distance movements, escaping adverse local conditions for parts of the year. Mobility or migratory tendency may affect avian BMR in at least three possible ways: i) long-distance movements may pose specific demands on the energetics of migrating species, e.g. in terms of high rates of energy acquisition in preparation for migration ##REF##11331517##[26]##–##REF##28565716##[29]##, leading to higher BMR compared to non-migrants; ii) only seasonal presence in the breeding region may remove some of the selection pressures on BMR (e.g. survival of cold winters) that affect non-migrants; iii) given environmental effects on BMR, occupation of different environments alone may cause non-migrant – migrant differences in BMR (migrants tend to breed at higher latitudes with colder temperatures). Several authors have noted that long-distance migrant shorebirds have higher BMR than expected on the basis of body mass alone ##UREF##16##[30]##–##UREF##18##[32]##, but a general test of the effect of migratory tendency on avian BMR and the relative role of environmental effects has been lacking.</p>", "<p>Recent work has seen an increased appreciation for intraspecific variation in BMR, specifically individual variation due to phenotypic plasticity ##UREF##19##[33]##–##UREF##21##[35]##. In addition to short-term thermal acclimations, individual birds may adjust BMR as a component of seasonal acclimatization (e.g. to cold winter temperatures) or as part of their migratory cycle ##UREF##20##[34]##. For select migrant species the individual BMR has been shown to vary strongly just before and after the breeding season with significant changes during migration ##UREF##15##[27]##, ##UREF##22##[36]##. The variation in BMR found across species thus reflects a number of sources of phenotypic variation, including body mass, genotypic adaptation, phenotypic plasticity – and their interactions with climatic conditions - and phylogenetic inertia. To date a common phylogenetic structure has been assumed for the BMR of both migrant and non-migrants, but migratory tendency may cause different relative strengths of a phylogenetic signal due to different degrees of within-individual variation. In non-migrants little seasonal variation in BMR is expected before winter ##UREF##20##[34]##, but in migrants BMR on breeding grounds may vary strongly within and between individuals in the context of their migration. We hypothesize that this variation may affect the strength of the correlates of interspecific BMR variation and potentially lead to a weaker phylogenetic signal in migrants compared to non-migrants.</p>", "<p>In this study, we use an extensive global dataset to analyze the influence of migratory tendency on the magnitude and environmental correlates of avian BMR. Specifically, we ask the following questions: i) Across a broad set of species, do migrants generally have higher BMR than non-migrants? ii) What are the strongest environmental predictors of BMR? iii) Can a potential effect of migratory tendency on BMR alternatively be explained by their occupation of different environments? iv) Do migrants and non-migrants show intrinsic differences in their BMR-environment relationships? Finally - and over-arching all of these issues - v) what is the role of phylogeny in shaping these relationships and is it stronger in non-migrants than migrants?</p>" ]

[ "<title>Materials and Methods</title>", "<title>BMR and body mass data</title>", "<p>We obtained BMR (Watts) and body mass (<italic>M</italic>, g) data for wild-caught populations of 135 species from McKechnie et al. ##UREF##21##[35]##. We included estimates of BMR irrespective of the sample size from which they were generated, but tested for bias resulting from this approach (see below). For each datum, we consulted the original source for the location at which the experimental individuals were captured (online supporting material for McKechnie et al. 2006 at <ext-link ext-link-type=\"uri\" xlink:href=\"http://dx.doi.org/10.1098/rspb.2005.3415\">http://dx.doi.org/10.1098/rspb.2005.3415</ext-link>). In cases where the co-ordinates of the capture site were not reported, we obtained these from the Alexandria Library Digital Gazetteer (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.alexandria.ucsb.edu/gazetteer/\">http://www.alexandria.ucsb.edu/gazetteer/</ext-link>). We classified each species as non-migrant (71 species) or migrant (64 species) using secondary literature and further separated migrants into those performing long-distance (inter-continental, 29 species) or short distance (intra-continental, 35 species) seasonal movements. Data included only birds captured on their breeding grounds (i.e., data from winter quarters are excluded). For the environmental analyses, we excluded 38 species from the dataset of McKechnie et al. ##UREF##21##[35]## for which not all the environmental variables (see below) were available. This yielded a final data set of 97 species.</p>", "<title>Environmental predictor variables</title>", "<p>For each BMR datum, we extracted the following environmental variables from the CRU CL2.0 data-set in 10-minute (0.167°) resolution and over the period 1961–1990 ##UREF##23##[37]##: mean monthly temperature (<italic>Temp avg</italic>, °C), mean monthly temperature of hottest three months (<italic>Temp max</italic>, °C), mean monthly precipitation (<italic>Prec avg</italic>; mm/month), absolute difference between average January and July temperature (<italic>Temp range</italic>, °C), log₁₀-transformed difference between average maximum and minimum monthly precipitation (<italic>Prec range</italic>, mm), and mean coefficient of variation of the monthly precipitation estimates across all 30 years (<italic>Prec CoV</italic>). We obtained estimates of net primary productivity (<italic>NPP</italic>, t Carbon ha⁻¹ y⁻¹) estimates for the period 1960–90 from the DOLY model in 0.5° resolution ##UREF##24##[38]## and evaluate effects of average annual NPP (<italic>NPP avg</italic>, t Carbon ha⁻¹ y⁻¹) and average NPP of the most productive three months (<italic>NPP max</italic>, t Carbon ha⁻¹ 3months⁻¹). We also obtained average potential evapotranspiration (<italic>PET avg</italic>, mm) data from a 0.5° gridded global dataset ##UREF##25##[39]##. PET is the amount of moisture which, if available, would be removed from a given land area by soil evaporation and plant transpiration. We used these data to calculate an aridity index (<italic>Aridity Index</italic>) as average monthly precipitation/average monthly PET, where moist areas have high aridity index and arid areas a low index. Several other variables measuring environmental conditions or their seasonality were evaluated, but excluded from the final analysis for their poor predictive ability or co-linearity with already included predictors.</p>", "<title>Model fitting and analysis – environmental effects on BMR</title>", "<p>We initially analyzed the BMR data following McKechnie et al. ##UREF##21##[35]##, using a generalized least squares approach whereby covariance among species is accounted for using a phylogeny ##UREF##26##[40]##–##REF##10553904##[42]##. The strength of the phylogenetic signal in each model was assessed using the parameter λ which measures and controls for the degree of phylogenetic dependence in the model residuals ##REF##10553904##[42]##, ##UREF##28##[43]##, estimated using a maximum-likelihood approach.</p>", "<p>Our first set of analyses addresses the effects of single environmental predictors on avian BMR without distinguishing between migratory strategies. We fit general linear models (GLM) to the overall data set, using log₁₀-transformed BMR as a continuous dependent variable, and successively add log₁₀-transformed <italic>M</italic> (continuous) and passerine/non-passerine membership (<italic>Pass/non-p.</italic>, categorical). The passerine/non-passerine variable was added since there are significant differences in <italic>M</italic> between passerines and non-passerines, and omitting this variable leads to an under-estimation of the scaling exponents relating BMR to <italic>M</italic>\n##UREF##21##[35]##, ##UREF##29##[44]##.</p>", "<p>Environmental correlates on avian BMR may arise via the different geographic distributions and environmental associations of migratory vs. non-migratory species with different BMR. In the next set of analyses we therefore sought to examine how in this dataset environmental variables and thus environmental niches of birds and their migratory strategy interact with each other, and how this is affected by phylogeny. To do this we fitted linear models in which the environmental variables were individually treated as response variables, and migratory strategy used as a predictor. These analyses therefore test whether there are significant differences between migrants and non-migrants in terms of the broad-scale environments they occupy. We controlled for phylogeny in fitting these models and estimated the <italic>λ</italic> statistic, as described above, to determine whether there was phylogenetic signal in the patterns of environment occupancy.</p>", "<title>Model fitting and analysis – contrasting migrants and non-migrants</title>", "<p>Next we repeated the previous analysis of single environmental correlates of BMR separately for migrants and non-migrants, with <italic>M</italic> and <italic>Pass/non-p</italic> as covariates and evaluated model fits using the Akaike Information Criterion ##UREF##30##[45]##. Using the approach of analyzing single environmental predictors it was not clear whether the predictors that explain BMR variation are the same for migrants and non-migrants. This is because first, a large number of potential combinations of predictors exist many of which possess similar degrees of explanatory power; and second, the predictors are correlated with each other. Further complicating this analysis was the problem that the degree of phylogenetic dependence differs between the migrants and non-migrants. This makes it difficult to deal with both groups of species together in a single analysis. In the next stage of the analysis we therefore (i) reduced the set of predictors down to a core set of environmental variables measuring key aspects of the environment. Specifically we looked at the effects of average NPP, average temperature and average precipitation. (ii) We analyzed migrants and non-migrants separately to see whether the overall responses appeared different. (iii) We combined all variables into a single multiple regression analysis in order to examine the effects of all of these simultaneously and analyzed the effects using a sequential decomposition of variance. We introduced <italic>M</italic> and <italic>Pass/non-p</italic> as initial predictors. We then added <italic>Temp_avg</italic> as this was, according to the initial analysis, clearly the strongest environmental correlate of BMR. The other predictors were then added after this (note that the order in which these variables were added did not affect the results). We note that any broad-scale analysis of this sort is complicated by the overlap in information (collinearity) between alternative predictors such different environmental variables or environmental and behavioral-ecological determinants, and the cause - effect assumptions inherent in statistical modeling approaches.</p>", "<title>Model fitting and analysis – effects of BMR sample size</title>", "<p>In the above analyses, we included BMR data irrespective of the number of individuals per population sampled. To verify that the inclusion of data measured in only one or two individuals did not bias the results, we repeated the environmental variable analyses described above after weighting the BMR and <italic>M</italic> data for each species by the number of individuals used. In no instance did the significance, direction or strength of an effect change. At most, partial coefficient values altered slightly after data were weighted.</p>" ]

[ "<title>Results</title>", "<p>We first use the full dataset (N = 135) without phylogenetic control to illustrate core correlates of avian basal metabolic rate (BMR) and to demonstrate the significance of migratory tendency. Confirming previous studies we find that in a two-predictor model BMR increases consistently and strongly with body mass (<italic>M</italic>: b = 0.744, t = 30.89, p&lt;0.001) and is additionally significantly higher in Passerines than Non-Passerines (<italic>Pass/non-p</italic>.: b = 0.082, t = 5.595, p&lt;0.001). We first test for a potential effect of migratory tendency on BMR only controlling for body mass (##FIG##0##Fig. 1##). We find that in migrants BMR is much higher than in non-migrant birds (Migratory: b = 0.044, t = 3.93, p&lt;0.001). The effect of migratory tendency is confirmed in the three-predictor model controlling for <italic>Pass/non-p.</italic> membership which yields the best overall fit (Migratory: b = 0.032, <italic>t</italic> = 3.05, p&lt;0.01, full model adjusted r² = 0.912). Refinement of the binary migratory tendency variable to a three-level distinction of non-migrant, short and long-distance migrants did not significantly improve the model fit suggesting that BMR did not differ between those two broad categories of migration distance.</p>", "<p>These effects retain their strength when the dataset is restricted to those populations for which available environmental data allows further analysis (N = 97): not accounting for phylogeny, but controlling for <italic>M</italic> and <italic>Pass/non-p.</italic> migrants have higher BMR than non-migrants (<italic>b</italic> = 0.061, <italic>t</italic> = 2.55, <italic>p</italic> = 0.012). For this dataset we examine the additional effect of phylogeny. We find that when phylogeny is controlled for the migrant/non-migrant difference appears no longer to be significant (<italic>b</italic> = 0.036, <italic>p</italic> = 0.174), with the maximum likelihood value of <italic>λ</italic> being significantly different from zero (<italic>λ</italic> = 0.82; test versus <italic>λ</italic> = 0: <italic>P</italic>&lt;0.001).</p>", "<p>We then evaluated whether environment can explain variation in BMR above and beyond these three predictors, specifically within migrants and non-migrants. All of the ten putative environmental correlates we tested are highly correlated with latitude and many also with each other (##TAB##0##Table 1##). Variables with strongest co-linearity include average annual temperature (<italic>Temp avg</italic>, r≥0.5 for 8 out of 9 relationships) and average net primary productivity (<italic>NPP avg</italic>, r≥0.5 for 5 out of 9 relationships). We identified six which had strong associations with BMR: <italic>NPP avg</italic>, <italic>NPP max</italic>, <italic>Prec avg</italic>, <italic>Temp avg</italic>, <italic>Temp max</italic>, <italic>PET</italic>, and <italic>Temp range</italic> (##TAB##1##Table 2##). None of these associations became non-significant when phylogeny was controlled for and, indeed, the estimated effects of several were even stronger when phylogeny was controlled for (including, <italic>Temp avg</italic>, <italic>Temp max, PET and Temp range</italic>; ##TAB##1##Table 2##), revealing the complexity of the influence of phylogeny on BMR in this dataset.</p>", "<p>The observed environmental correlates may at least partially arise from the different environmental niches occupied by birds with different migratory strategies and associated differences in BMR. In our data, the mean absolute latitude occupied by migrants was 38.2°, whereas the corresponding values for non-migrants is 24.0°, and significantly lower. Similarly, the mean <italic>Temp avg</italic> for migrants is 15.21°C, and 19.14°C for non-migrants. Although the two groups do not differ in terms of <italic>NPP</italic>, <italic>NPP max</italic>, <italic>Prec range</italic> or <italic>Prec CoV</italic> they do in terms of the other environmental variables (##TAB##2##Table 3##): Temperature (maximum, average and range), <italic>PET</italic>, and <italic>Aridity index</italic> are all significantly associated with migratory tendency - this suggests that the negative effect temperature and associated variables have on avian BMR may at least partially be the result of the colder, more seasonal environments occupied by migrants with potentially higher BMR.</p>", "<p>To investigate the generality of putative environmental correlates and their interactive effect with phylogeny we therefore repeated the single-predictor environment analyses separately for migrants and non-migrants. In migrants we found strong evidence for an influence of environmental variables, especially <italic>Temp avg and PET</italic>, <italic>Aridity</italic>, <italic>Temp range</italic> and <italic>Prec range</italic> (see ##TAB##3##Table 4##). In all cases, accounting for phylogeny increased the estimated effect. However, the estimated values of <italic>λ</italic> were low (range 0 to 0.74) and in all cases were not significantly different from zero, indicating a low degree of phylogenetic dependence. In non-migrants the situation with respect to phylogeny is quite different: maximum likelihood values of <italic>λ</italic> are high and not significantly different from one (range 0.92 to 1; ##TAB##3##Table 4##). There were somewhat fewer significant environmental correlates of BMR compared to migrants, with only <italic>NPP max</italic>, <italic>Temp avg</italic>, <italic>Temp max</italic>, and <italic>Temp range</italic> being significant in the models for non-migrants. In both groups heat related variables, specifically <italic>Temp avg</italic>, were the strongest predictors. While the statistical strength of <italic>Temp avg</italic> is much weaker than that of <italic>M</italic>, the variation of BMR along a temperature gradient is nevertheless considerable: a non-migrant bird at a location with on average 8°C annual temperature has basal energy fluxes that are 48% higher than a bird of the same size at a 28°C location (e.g. for a 10g passerine bird (95 c.i.): BMR (8°C) = 0.154 (±0.087) <italic>W</italic>, BMR (28°C) = 0.081 (±0.051) <italic>W</italic>, for <italic>λ</italic> = 0). We note that the models in ##TAB##3##Tables 4a and 4b\n## include passerine/non-passerine differences, which are phylogenetic effects, and that the strength of this effect differs between migrants and non-migrants. However, the results we report are essentially the same when the analysis is repeated without this variable included (##SUPPL##0##Table S1##).</p>", "<p>We develop a final multi-predictor model of migrant and non-migrant BMR which confirms the importance of temperature: when fitted as a combined model the major environmental correlate of BMR is <italic>Temp avg</italic>, irrespective of migratory status (##TAB##4##Table 5##). The degree of phylogenetic dependence also varies between migrants and non-migrants. In the case of the former, the maximum likelihood value of <italic>λ</italic> is not different from zero, whereas in the latter case it is not significantly different from 1 (##TAB##4##Table 5##).</p>" ]

[ "<title>Discussion</title>", "<title>Migrants vs non-migrants</title>", "<p>A considerable component of body mass-independent variation in avian BMR can statistically be explained by migratory tendency: the minimum normothermic maintenance energy requirements of migrants are significantly higher than those of non-migrants, at least when phylogeny is not accounted for. This has implications for comparative studies, since comparisons of the energetic traits of non-migrants with those of migrants may lead to misleading conclusions regarding physiological adaptation. The physiological divergence we have identified between migrant and non-migrant birds is consistent with observations that several species of migrant shorebirds have higher BMR than expected on the basis of body mass ##UREF##16##[30]##–##UREF##18##[32]##.</p>", "<p>Why should BMR be higher in migrants than in non-migrant species? One possibility is that compared to species with more sedentary life histories the metabolic machinery for long-distance migration involves elevated maintenance costs. Avian energy intake rates as well as maximum thermogenic metabolic rates are positively correlated with BMR ##UREF##31##[46]##, ##REF##11818416##[47]##. A mechanistic link between elevated BMR and the capacity for sustained activity is supported by the observation that in Rock Doves (<italic>Columba livia</italic>), the metabolic intensity (cytochrome <italic>c</italic> oxidase activities) of pectoral muscles is higher in active birds than in sedentary individuals. The elevated BMR of migrant species may also in part reflect the timing of metabolic measurements and the influence of flight muscle hypertrophy preceding long-distance migratory flights in species such as Red Knots <italic>Calidris canutus</italic>\n##REF##10504319##[48]##.</p>", "<p>A second set of possible explanations for the higher BMR of migrants compared to non-migrants concerns their uneven latitudinal distribution. During the breeding season migrants generally occur in environments that are colder (##FIG##1##Figure 2##) and where the short time window available for breeding may impose particularly high energy demands. According to the former view, the elevated BMR of migrants may simply reflect the correlation between BMR and <italic>Temp avg</italic>. This idea is not new; Kvist and Lindström ##UREF##32##[49]## showed that the BMR of migrant shorebirds is highest on the Arctic breeding grounds before migration, and lowest while on tropical wintering grounds. Lindström and Klaassen ##UREF##18##[32]## confirmed the generality of elevated BMR in shorebirds while in the Arctic, and hypothesized that the reduction of BMR exhibited by migrants as they move from high to tropical latitudes reflects changing requirements for thermoregulatory heat production. Many non-migrant species rapidly up- or down-regulate BMR in response to thermal acclimation ##REF##11003826##[22]##, ##UREF##13##[23]##, ##UREF##33##[50]##, with BMR up-regulation associated with cold air temperatures and <italic>vice versa</italic>. Intra-individual variation in BMR often reflect changes in organ size ##REF##2386245##[51]##, ##REF##10441080##[52]##, but may also reflect changes in the metabolic intensity of specific tissues ##UREF##34##[53]##.</p>", "<p>In our analysis, migrant data came from much higher latitudes and colder regions than data for non-migrants. In the combined non-migrant/migrant dataset several environmental variables exceed migratory tendency as predictor (##TAB##1##Table 2##): after accounting for either <italic>Temp avg</italic>, <italic>PET</italic> or <italic>Temp range</italic> there is no significant difference in BMR between migrants and non-migrants. In view of the considerable phenotypic flexibility in BMR exhibited by long-distance migrants ##REF##17170153##[25]##, ##UREF##18##[32]##, ##UREF##35##[54]##, ##UREF##36##[55]##, and the consistent negative relationship between BMR and air temperature in laboratory acclimation studies ##REF##11003826##[22]##, ##UREF##13##[23]##, ##REF##17170153##[25]##, ##UREF##33##[50]##, it seems likely that the higher BMR of migrants we report here is determined in part by temperature effects. However, the BMR data currently available for long-distance migrants on their tropical wintering grounds are too few to rigorously test this hypothesis.</p>", "<title>Environmental correlates of avian BMR</title>", "<p>Our analyses confirm the previously observed considerable body mass-independent variation in avian BMR that can be attributed to several environmental variables. For interpretation of specific environmental effects we focus on single-predictor environmental relationships as high collinearity of environmental variables (##TAB##0##Table 1##) hampers the interpretation of multi-predictor models. Average temperature (<italic>Temp avg</italic>) emerges as the most significant single environmental predictor of BMR, confirming the findings of White et al. (2007). BMR is significantly lower in warmer environments among all species included in our analysis, as well as within non-migrant and migrant subsets. These observations are consistent with Weathers' ##REF##28309699##[14]##'s finding that avian BMR increases with increasing latitude, Wiersma et al.'s ##REF##17517640##[12]## observation that tropical birds have lower BMRs than their temperate counterparts, as well as with the negative correlation between temperature and BMR in mammals ##UREF##7##[10]##. A negative effect of <italic>Temp avg</italic> on avian BMR has also been demonstrated to explain intraspecific variation ##UREF##9##[16]##, ##REF##16153046##[56]##. Moreover, numerous studies of thermal acclimation or acclimatization have found that birds adjust BMR in response to changing thermoregulatory demands ##UREF##12##[21]##–##UREF##13##[23]##, ##REF##17170153##[25]##, ##UREF##33##[50]##, ##UREF##37##[57]##, ##UREF##38##[58]##. In studies involving thermal acclimation under laboratory conditions, BMR can be adjusted by more than 20% over time scales of several weeks ##REF##11003826##[22]##, ##REF##17170153##[25]##, ##UREF##33##[50]##.</p>", "<p>Within and among migrants and non-migrants, BMR exhibited no correlation or a negative relationship with net primary productivity (which correlates positively with average temperature), a similar observation to that of White et al. (2007). This conflicts with the pattern among five species of <italic>Peromyscus</italic> mice under common-garden conditions ##UREF##39##[59]##. Furthermore, the lack of a positive effect of habitat energy availability on avian BMR indicates that the apparent independence of individual energy demand and supply at broad scales found for field metabolic rate ##UREF##11##[20]## is manifested at the level of BMR. An increase in maintenance metabolism with decreasing NPP could also potentially reflect greater mobility among desert species that have to cover larger areas to acquire sufficient resources to breed. Unpredictable fluctuations in food availability, driven by erratic rainfall, have traditionally been viewed as one of the major factors driving the evolution of low BMR in desert endotherms ##UREF##40##[60]##, and more recently have been invoked as a major determinant of zoogeographical patterns of mammalian BMR ##UREF##5##[8]##, ##UREF##7##[10]## Whereas precipitation variability has been found to be strongly negatively associated with the BMR of small mammals ##UREF##7##[10]##, a recent study found the opposite for birds (White et al. 2007). Here we were not able to confirm any significant effect of precipitation variability on BMR. We interpret our results as evidence that the low BMR of desert bird species is determined primarily by temperature effects, rather than magnitude and variability in energy availability.</p>", "<p>We emphasize, however, that our findings are correlational. BMR has long been viewed as a fixed, taxon-specific parameter, with adaptation inferred from interspecific variation remaining after scaling and/or phylogenetic patterns of descent have been accounted for. However, there is increasing evidence for considerable phenotypic flexibility in BMR, with substantial within-individual adjustments occurring over short time scales ##UREF##41##[61]##. Thus, interspecific variation in BMR reflects in part the conditions to which birds are acclimatized or acclimated at the time of metabolic measurements, and not necessarily genotypic divergence.</p>", "<title>Disparate phylogenetic structure</title>", "<p>Our results indicate a hitherto unappreciated complexity in the phylogenetic structure of the examined associations. Previous analyses of these types of data ##UREF##26##[40]## and of BMR in birds in particular ##REF##15674767##[13]##, ##UREF##19##[33]## have assumed a common phylogenetic dependence across the whole data set analyzed. In this dataset migrants appear to have a much lower degree of phylogenetic dependence than non-migrants. This is consistent with the idea that in migrants post- and pre-migration changes in BMR within individuals cause intraspecific variation which then leads to BMR to appear phylogenetically more labile than in non-migrants (at least when measured in summer). Alternatively, it may also reflect a closer adaptation to more constant environmental conditions in migrants, but as we do not find much stronger environmental associations for them we believe this to be unlikely. These results suggest that future analyses may benefit from exploring more complex mosaic models of evolution and, ideally, datasets that include intraspecific genetic information.</p>", "<title>Conclusions</title>", "<p>By analyzing BMR of migrants and non-migrants separately for a large number of species we have shed further light on an apparent pattern of physiological divergence among birds. The higher summer BMR of many migrant populations confirms that the observations of several authors working on migrant shorebirds ##UREF##16##[30]##–##UREF##18##[32]## represent a general pattern. We find that the higher BMR of migrants may at least partly be due to the latitudinal distribution of their breeding grounds at higher latitudes and thus colder climates. While ambient temperature exerts a strongly negative effect on both migrant and non-migrant BMR, our analysis reveals that overall different environmental variables are correlated with the variation of BMR in these two groups. Our results confirm the need to consider and, ideally, to quantify environmental effects when addressing topics such as the body size dependence of metabolic rate or when developing models of population energy fluxes.</p>", "<p>In conclusion it appears that broad-scale climatic gradients constraints, specifically those related to temperature, present a stronger constraint on avian BMR than migratory tendency. But different climatic associations and a much weaker phylogenetic signal point to different control of BMR in migrants that appears to be characterized by strong phenotypic flexibility. Further empirical work on winter vs. summer BMR in both migrants and non-migrants across environments will help to establish the full extent of phenotypic flexibility in each group and provide a fuller picture of its environmental determinants. Ultimately, such work may be extended to help understand the shapes and phylogenetic inertia of reaction norms across different migratory and other behavioral strategies. In our study we were able to only indirectly draw inference about the exact pathway that causes the statistically strong association between climate and phenotypic variation. But especially for migratory tendency the phylogenetically labile environmental control of BMR emphasizes the significance of phenotypic plasticity. Promising additional insights are likely to be gained from any study that was able to explicitly and simultaneously address environment - BMR association within individuals, within (and ideally across) populations and across species. Such studies, logistically challenging they may be, may be able to reconcile broad-scale comparative/eco-geographic perspectives that are concerned with the broad interspecific patterns with ecophysiological viewpoints that have helped appreciate the importance of small scale and intraspecific variation arising from phenotypic flexibility.</p>" ]

[ "<title>Conclusions</title>", "<p>By analyzing BMR of migrants and non-migrants separately for a large number of species we have shed further light on an apparent pattern of physiological divergence among birds. The higher summer BMR of many migrant populations confirms that the observations of several authors working on migrant shorebirds ##UREF##16##[30]##–##UREF##18##[32]## represent a general pattern. We find that the higher BMR of migrants may at least partly be due to the latitudinal distribution of their breeding grounds at higher latitudes and thus colder climates. While ambient temperature exerts a strongly negative effect on both migrant and non-migrant BMR, our analysis reveals that overall different environmental variables are correlated with the variation of BMR in these two groups. Our results confirm the need to consider and, ideally, to quantify environmental effects when addressing topics such as the body size dependence of metabolic rate or when developing models of population energy fluxes.</p>", "<p>In conclusion it appears that broad-scale climatic gradients constraints, specifically those related to temperature, present a stronger constraint on avian BMR than migratory tendency. But different climatic associations and a much weaker phylogenetic signal point to different control of BMR in migrants that appears to be characterized by strong phenotypic flexibility. Further empirical work on winter vs. summer BMR in both migrants and non-migrants across environments will help to establish the full extent of phenotypic flexibility in each group and provide a fuller picture of its environmental determinants. Ultimately, such work may be extended to help understand the shapes and phylogenetic inertia of reaction norms across different migratory and other behavioral strategies. In our study we were able to only indirectly draw inference about the exact pathway that causes the statistically strong association between climate and phenotypic variation. But especially for migratory tendency the phylogenetically labile environmental control of BMR emphasizes the significance of phenotypic plasticity. Promising additional insights are likely to be gained from any study that was able to explicitly and simultaneously address environment - BMR association within individuals, within (and ideally across) populations and across species. Such studies, logistically challenging they may be, may be able to reconcile broad-scale comparative/eco-geographic perspectives that are concerned with the broad interspecific patterns with ecophysiological viewpoints that have helped appreciate the importance of small scale and intraspecific variation arising from phenotypic flexibility.</p>" ]

[ "<p>Conceived and designed the experiments: WJ RPF AEM. Performed the experiments: WJ RPF AEM. Analyzed the data: WJ RPF AEM. Contributed reagents/materials/analysis tools: WJ RPF AEM. Wrote the paper: WJ RPF AEM.</p>", "<p>Basal metabolic rate (BMR) represents the minimum maintenance energy requirement of an endotherm and has far-reaching consequences for interactions between animals and their environments. Avian BMR exhibits considerable variation that is independent of body mass. Some long-distance migrants have been found to exhibit particularly high BMR, traditionally interpreted as being related to the energetic demands of long-distance migration. Here we use a global dataset to evaluate differences in BMR between migrants and non-migrants, and to examine the effects of environmental variables. The BMR of migrant species is significantly higher than that of non-migrants. Intriguingly, while the elevated BMR of migrants on their breeding grounds may reflect the metabolic machinery required for long-distance movements, an alternative (and statistically stronger) explanation is their occupation of predominantly cold high-latitude breeding areas. Among several environmental predictors, average annual temperature has the strongest effect on BMR, with a 50% reduction associated with a 20°C gradient. The negative effects of temperature variables on BMR hold separately for migrants and non-migrants and are not due their different climatic associations. BMR in migrants shows a much lower degree of phylogenetic inertia. Our findings indicate that migratory tendency need not necessarily be invoked to explain the higher BMR of migrants. A weaker phylogenetic signal observed in migrants supports the notion of strong phenotypic flexibility in this group which facilitates migration-related BMR adjustments that occur above and beyond environmental conditions. In contrast to the findings of previous analyses of mammalian BMR, primary productivity, aridity or precipitation variability do not appear to be important environmental correlates of avian BMR. The strong effects of temperature-related variables and varying phylogenetic effects reiterate the importance of addressing both broad-scale and individual-scale variation for understanding the determinants of BMR.</p>" ]

[ "<title>Supporting Information</title>" ]

[]

[ "<fig id=\"pone-0003261-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.g001</object-id><label>Figure 1</label><caption><title>Avian BMR increases with body mass, and is higher in migrants than non-migrants.</title><p>A Individual data points and partial regression fits for non-migrants (black, solid line) and migrants (open, dotted line). B average residuals (±s.e.) from the overall regression of log BMR on log body mass for non-migrants and migrants. Full dataset (N = 135).</p></caption></fig>", "<fig id=\"pone-0003261-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.g002</object-id><label>Figure 2</label><caption><title>Partial residual plots of core environmental correlates of BMR for the combined dataset of both migrant (black circles) and non-migrant birds (open circles).</title><p>Each panel shows the effect of a single predictor on BMR controlled for body size and Pass/non-p membership. Regression lines are those significant for combined non-migrant – migrant data (##TAB##1##Table 2##). Negative residual outlier (&lt;−0.4 partial residual value) is the group-living Green Woodhoopoe (<italic>Phoeniculus purpureus</italic>).</p></caption></fig>" ]

[ "<table-wrap id=\"pone-0003261-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.t001</object-id><label>Table 1</label><caption><title>Correlation matrix of environmental variables and species traits in the analysis.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>BMR</italic>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Abs. latitude</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>0.41</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.50</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.50</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.61</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.87</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.65</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.90</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>0.22</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>0.71</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>−0.61</italic></bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>−0.09</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold><italic>0.51</italic></bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.43</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.42</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.09</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.12</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.05</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.95</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.99</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.85</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.64</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.63</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.44</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.85</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.50</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.64</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.63</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.45</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.52</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.55</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.55</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.55</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.69</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.57</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.39</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.82</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.83</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.22</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.63</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.55</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.51</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.70</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.37</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.45</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.44</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.54</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.51</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>−0.73</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.14</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.24</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.30</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.35</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.02</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003261-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.t002</object-id><label>Table 2</label><caption><title>Environment has strong effects on avian BMR, above and beyond migratory tendency.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">λ = 0</td><td colspan=\"5\" align=\"left\" rowspan=\"1\">ML λ</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">λ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">P (λ = 0)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−137.27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7288</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-9</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−151.18</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7153</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-9</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.82</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.92E-4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pass/non-P</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1233</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>5.92E-4</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1437</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0935</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Migratory</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0611</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0124</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0355</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1741</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−143.78</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0081</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0024</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−155.46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0072</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0075</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.31E-4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−144.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0331</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0017</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−155.61</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0290</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0067</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.80</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">8.52E-4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−141.51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0018</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0078</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−154.92</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0017</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0099</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.50E-4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−168.15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0125</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.38E-8</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−193.93</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0133</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-9</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.93</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.83E-7</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−149.63</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0106</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0001</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−165.87</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0118</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>3.40E-5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.56E-5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−148.34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0016</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0002</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−165.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0017</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>3.91E-5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.87</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.29E-5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−134.13</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0242</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7216</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−148.82</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0605</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3508</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.83</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.27E-4</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−147.68</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0039</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0003</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−171.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0052</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.28E-6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.91</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.38E-6</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−135.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0321</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3223</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−151.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0567</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0782</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">6.06E-5</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−134.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0001</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.9856</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−149.28</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0003</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3951</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.29E-4</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003261-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.t003</object-id><label>Table 3</label><caption><title>Differences in environmental associations of migrants and non-migrants.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Variable</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">F_1,95\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">λ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">λ = 0, λ = 1</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.03</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.86</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.91</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** .***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.08</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.78</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.94</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** .***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{***. ***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">19.46</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.73E-5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.76</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{***. ***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">9.93</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.20E-3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.96</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{***. ***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">27.39</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.01E-6</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** . ***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity Index</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">13.69</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.60E-4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** .***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">10.51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.65E-3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** .***}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.40E-1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{*** .**}\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CoV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.15</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.46E-1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n^{***. ns}\n</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003261-t004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.t004</object-id><label>Table 4</label><caption><title>Environmental correlates of BMR across migrants (a) and non-migrants (b) accounting for <italic>M</italic> and <italic>Pass/non-P.</italic>\n</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"8\" align=\"left\" rowspan=\"1\">Migrants</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">λ = 0</td><td colspan=\"5\" align=\"left\" rowspan=\"1\">ML λ</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">λ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">P(λ = 0)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−109.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.737</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-8</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−109.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.737</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-8</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pass/non-P</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.111</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0058</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.111</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0058</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0051</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0895</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0051</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0895</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−109.38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0187</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1308</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−109.38</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0187</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1308</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0023</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0582</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0023</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0582</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−125.70</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0104</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>3.38E-5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−126.33</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0125</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.40E-6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.74</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.42</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−116.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0883</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0026</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−116.81</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0883</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0026</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−123.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0019</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>8.11E-5</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−125.32</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0026</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>5.49E-6</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.63</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.23</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−112.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1616</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0255</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−112.35</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1616</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0255</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0025</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0819</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−110.20</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0025</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0819</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−112.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.1388</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0183</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−112.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.1388</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0183</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−107.50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0021</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.452</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−107.50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0021</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.452</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td></tr></tbody></table><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"8\" align=\"left\" rowspan=\"1\">Non-migrants</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">λ = 0</td><td colspan=\"5\" align=\"left\" rowspan=\"1\">ML λ</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">AIC</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">b</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">p</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">λ</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">P (λ = 0)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−40.31</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.707</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1E-16</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−49.76</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.680</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1E-16</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0021</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pass/non-P</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.127</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.032</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.138</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.278</td><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−43.58</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0107</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0168</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−52.27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0089</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0219</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0032</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−44.63</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0441</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0098</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−53.21</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0370</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0137</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0034</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−42.01</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0020</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0380</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−50.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0016</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0559</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.92</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0041</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−53.90</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0140</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0001</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−62.11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0120</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0002</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.93</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0042</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp max</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−43.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.1245</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0143</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−54.36</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.1220</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0084</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0012</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>PET</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−41.25</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0013</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0568</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−50.62</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0011</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0519</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0022</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Aridity</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−38.79</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.1562</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.2352</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−47.16</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0853</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.4849</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.98</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0038</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−45.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0044</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0061</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−54.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0041</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0090</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.95</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0036</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec range</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−37.47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0218</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6366</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−49.11</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0634</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1389</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.00</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0006</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec CV</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−37.50</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0002</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6146</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−46.88</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0002</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6640</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.99</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0022</bold>\n</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"pone-0003261-t005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003261.t005</object-id><label>Table 5</label><caption><title>Combined effects of select environmental variables on BMR in migrants and non-migrants.</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Term</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Non-Migrants</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">Migrants</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>b</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>t</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>b</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>t</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>p</italic>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>M</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.6743</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">15.40</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.64E-14</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.7078</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">22.89</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.00E-9</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Pass/non-p.</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.2149</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.10</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0419</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.1602</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.55</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0142</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Temp avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0108</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−3.34</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>0.0019</bold>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0129</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−5.48</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<bold>1.73E-6</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>Prec avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0009</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.60</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.5514</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0061</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.70</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0949</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">\n<italic>NPP avg</italic>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−0.0073</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">−1.04</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.3041</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0171</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">0.0720</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">λ = 0.93 (λ = 0: p = 0.004, λ = 1: p = 0.52)</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">λ = 0.81 (λ = 0: p = 0.11, λ = 1: p = 2E-6)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td colspan=\"3\" align=\"left\" rowspan=\"1\">\n<italic>AIC = −57.40; N</italic> = 45, <italic>R</italic>\n² = 0.88</td><td colspan=\"3\" align=\"left\" rowspan=\"1\">\n<italic>AIC = −123.67; N</italic> = 52, <italic>R</italic>\n² = 0.93</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003261.s001\"><label>Table S1</label><caption><p>Environmental correlates of BMR across migrants and non-migrants, accounting only for body mass.</p><p>(0.07 MB DOC)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label/><p>Abbreviations: BMR – log₁₀ basal metabolic rate; <italic>M</italic> - log₁₀ body mass; Abs. latitude (not analyzed further) – absolute latitude; <italic>NPP avg</italic> – average annual net primary productivity (t Carbon ha⁻¹ y⁻¹); <italic>NPP max</italic> – total NPP of most productive three months; <italic>Prec avg</italic> – avg monthly precipitation (mm); <italic>Temp avg</italic> – average annual temperature (°C); <italic>Temp max</italic> – average temperature of the warmest three months (°C); <italic>PET avg</italic> – average potential evapotranspiration (mm); <italic>Aridity</italic> – <italic>Prec avg</italic>/<italic>PET avg</italic>; <italic>Temp range</italic> – absolute difference between average January and July temperature (°C); <italic>Prec range</italic> – difference between average maximum and minimum monthly precipitation (mm); <italic>Prec CV</italic> – coefficient of variation of monthly precipitation across 30 years (%). All absolute values of r &gt;0.38 are significant at p&lt;0.001. Values≥0.5 are highlighted in bold (N = 97).</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt102\"><label/><p>BMR was first modeled as a function of body mass (<italic>M</italic>), passerine/non-passerine differences (<italic>Pass/non-P</italic>) and migratory tendency (<italic>Migratory</italic>). Controlling for these three variables, subsequently single environmental predictors were tested for their effect on BMR. The table shows the fitted parameter (<italic>b</italic>), the estimate of the AIC and the <italic>P</italic>-value testing whether the parameter is significantly different from zero. Parameters were estimated singly, and we conducted two analyses for each parameter: first one in which phylogeny was ignored (λ = 0), and then one in which we estimate Pagel's <italic>λ</italic>, and set it equal to its maximum likelihood value (ML λ). We tested whether the maximum likelihood estimate of <italic>λ</italic> was different from zero, i.e. whether the data show significant phylogenetic signal.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><label/><p>We tested whether the average values of the environmental variables differed between migrant and non-migrant populations in the dataset, by fitting a linear model for each variable separately in which it was treated as the dependent variable and migratory tendency as a predictor. Shown is the F-ratio for the model, together with the P-value. For each model we estimated Pagel's <italic>λ</italic>, and set this equal to its maximum likelihood value. We tested whether this was different from zero and one (respectively as indicated by the superscripts) in order to determine whether significant phylogenetic signal existed (ns = not significant; ^* = p&lt;0.05; ^** = p&lt;0.01; ^*** = p&lt;0.0001). For other details see ##TAB##1##Table 2##.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt104\"><label/><p>For other details see ##TAB##1##Table 2##. For results.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt105\"><label/><p>Models were fitted including all predictors simultaneously. Shown are the parameter estimates (<italic>b</italic>), and <italic>t</italic> and <italic>p</italic> values testing for difference of b from zero. For each model we accounted for phylogeny by including Pagel's <italic>λ</italic>, and setting this equal to its maximum likelihood value. We tested whether <italic>λ</italic> was different from zero and one in order to determine whether significant phylogenetic signal existed. For other details see ##TAB##1##Table 2##.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>W.J. was funded by the Emmy Noether Program of the Deutsche Forschungsgesellschaft (DFG) and the National Science Foundation (grant BCS-0648733). A.E.M. received funding from the National Research Foundation and the DST/NRF Centre of Excellence at the Percy FitzPatrick Institute. RPF is a Royal Society University Research Fellow. The study was facilitated by an Astor Travel Grant from the University of Oxford to R.P.F. and W.J.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003261.g001\"/>", "<graphic id=\"pone-0003261-t001-1\" xlink:href=\"pone.0003261.t001\"/>", "<graphic id=\"pone-0003261-t002-2\" xlink:href=\"pone.0003261.t002\"/>", "<graphic id=\"pone-0003261-t003-3\" xlink:href=\"pone.0003261.t003\"/>", "<graphic id=\"pone-0003261-t004-4\" xlink:href=\"pone.0003261.t004\"/>", "<graphic id=\"pone-0003261-t005-5\" xlink:href=\"pone.0003261.t005\"/>", "<graphic xlink:href=\"pone.0003261.g002\"/>" ]

[ "<media xlink:href=\"pone.0003261.s001.doc\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Outbreaks of highly pathogenic avian influenza (HPAI) H5N1 virus were first recorded in Guangdong, China in 1996 ##REF##10484749##[1]##. Since its emergence, the A/goose/Guangdong/1/96 (Gs/GD) virus lineage has become the longest recorded HPAI virus to remain endemic in poultry ##REF##17075062##[2]##. The ecological success of this virus in diverse avian and mammalian species ##REF##17250978##[3]## with frequent introduction to humans suggests this virus is the most likely candidate of the next human pandemic ##UREF##0##[4]##. Therefore, the evolutionary and ecological characteristics of its emergence from wild birds into poultry are of considerable interest.</p>", "<p>The virus gradually became endemic in poultry in different regions of China, developing into genetically and antigenically distinct sublineages ##REF##15241415##[5]##,##REF##16473931##[6]##. The geographic spread of these sublineages outside China is also unprecedented, with two sublineages spreading to Southeast Asia in late 2003, and another westwards to Central Asia, Europe, Africa, the Middle East and the Indian subcontinent in mid-2005 ##REF##10484749##[1]##, ##REF##15241415##[5]##–##REF##16823443##[9]##. During mid-2005, one sublineage (Fujian-like or clade 2.3.4) became dominant in China and subsequently spread to Laos, Thailand and Vietnam ##REF##17075062##[2]##,##REF##18394281##[10]##.</p>", "<p>Influenza surveillance in southern China has revealed that the Gs/GD virus lineage underwent extensive genetic reassortment to generate many different reassortant viruses (or genotypes) between 1997 and 2006 ##REF##15241415##[5]##,##REF##16473931##[6]##. The non-reassortant Gs/GD-like viruses were prevalent only from 1996 to 2000 ##REF##11878904##[11]##. Afterwards, all H5N1 viruses detected were reassortant genotypes. Amongst all recognized reassortants, only genotypes B, X0, W, Z, G and V, were persistent for more than two years or predominant at different time points, while many genotypes were only detected occasionally ##REF##15241415##[5]##,##REF##16473931##[6]##.</p>", "<p>While the genetic and antigenic evolution and geographic spread of the HPAI H5N1 panzootic viruses are well documented after the initiation of systematic surveillance in 2000 ##REF##15241415##[5]##, little is known about the source and early evolutionary dynamics of H5N1 virus. In particular, it is still unknown whether the Gs/GD virus itself was a reassortant virus or introduced wholly from migratory waterfowl. Even though the internal gene sources for most genotypes have been identified from aquatic birds ##REF##17507485##[12]##, the order of emergence and reassortment events that generated these genotypes remains to be answered.</p>", "<p>Recently, Dugan et al. ##REF##18516303##[13]## described an evolutionary dynamics of avian influenza virus (AIV) in wild bird populations. They found that the viruses exist as a large pool of functionally equivalent genes, under strong purifying selection, and reassort without overall loss of virus fitness resulting in many transient genotypes. Other studies have shown that all eight gene segments of the HPAI H5N1 viruses exhibit rapid nucleotide and amino acid substitution rates in comparison to other subtypes and that reassortment with the wild bird AIV gene pool has increased H5N1 genotype diversity, producing both persistent and transient genotypes ##REF##15241415##[5]##,##REF##17507485##[12]##,##REF##16945980##[14]##. However, the mechanism behind the population behavior of H5N1 viruses has still not been investigated. Here we aim to address these gaps in our knowledge of the evolutionary dynamics of HPAI H5N1 viruses through the estimation of divergence times of gene segments of major reassortants and population dynamics analyses of H5N1 viruses in poultry.</p>" ]

[ "<title>Methods</title>", "<title>Virus and viral sequence data</title>", "<p>We sequenced the full genome of 31 low pathogenic avian influenza H5 viruses plus 135 HPAI H5N1 viruses isolated from our surveillance program in southern China or otherwise available in our repository (GenBank accession numbers CY028924–CY029507, CY030878–CY031006, EF597247–EF597498). A further 114 partial gene sequences from 29 H5N1 and other subtype viruses isolated from 2000–2005 were also resequenced to provide full-length genomes. These sequences were analyzed together with all publicly available sequence data, including genes from 93 H6 and 279 H9 viruses that were also recently sequenced in our laboratories. Viral genome sequencing was conducted as previously described ##REF##17075062##[2]##,##REF##12077307##[24]##.</p>", "<title>Phylogenetic reconstruction and Bayesian skyline plots</title>", "<p>To estimate the times of divergence, a total of nine full-length datasets were analyzed: two Eurasian datasets for the H5-HA and N1-NA, and seven Asian datasets for each of the influenza gene segments, except the NA gene. To examine changes in genetic diversity during the evolution of the Gs/GD lineage, we constructed Bayesian skyline plots using a modified Asian HA dataset. This modified dataset consisted of only HA genes of viruses isolated from chicken (n = 54), duck (n = 52), goose (n = 15), pheasant (1) and Guinea fowl (1) in China.</p>", "<p>To estimate the rates of nucleotide substitution and TMRCAs, we used a Bayesian Markov chain Monte Carlo (MCMC) method as implemented in the program BEAST v1.4.7 ##REF##17996036##[17]##,##REF##12136032##[26]##. Each gene was analyzed with the codon based SRD06 nucleotide substitution model ##REF##16177232##[27]##. For each analysis the Bayesian skyline coalescent model was used ##REF##15703244##[16]##. Three clock models were compared statistically for each dataset using a Bayes factor test in Tracer v1.4 ##REF##11371589##[28]##,##UREF##2##[29]##: the strict clock that assumes a single evolutionary rate along all branches, and the uncorrelated lognormal relaxed (UCLD) clock and uncorrelated exponential relaxed (UCED) clock that allow evolutionary rates to vary along branches within lognormal and exponential distributions, respectively ##REF##16683862##[15]##. A Bayes factor test of clock models showed that the UCED clock was most appropriate for datasets other than PB2 and PB1, for which the UCLD clock most appropriately described the data. For each dataset, three to five independent Bayesian MCMC runs were conducted for 10–20 million generations sampled to produce 10,000 trees. Convergence of the runs was confirmed using Tracer v1.4 ##UREF##2##[29]## and effective sample size values of &gt;500 indicated a sufficient level of sampling. The results of the multiple runs were then combined using LogCombiner v1.4.7 ##REF##17996036##[17]##. Mean evolutionary rates and divergence times were calculated using TreeAnnotator v1.4.7 and TreeStat v1.1 after the removal of an appropriate burnin, 10–20% in most cases, and phylogenetic trees were visualized with FigTree v1.1.2 ##REF##17996036##[17]##,##UREF##3##[30]##,##UREF##4##[31]##.</p>", "<p>Finally, to evaluate if the TMRCAs of each of the gene segments of a given genotype were significantly different or not, the TMRCA of each gene segment was compared to the remaining genes of the genotype using a Bayes factor test ##REF##11371589##[28]##. This test was calculated in as follows; given a genotype, the probability of any gene (e.g. PB2) being older than any other segment (e.g. PB1) divided by the probability of PB1 being older than PB2 given the data (tree estimates of TMRCA) multiplied by the inverse estimation for the priors (PB1 being older than PB2 divided by PB2 being older that PB1 of the priors) was calculated for each Bayesian MCMC run ##REF##18418375##[19]##.</p>", "<title>Detection of selection pressure</title>", "<p>To determine selection pressures on the HA of Gs/GD-like H5N1 viruses in poultry the modified Asian H5-HA dataset was analyzed using the single-likelihood ancestor counting (SLAC) ##REF##15703242##[32]## and genetic algorithm (GA) methods ##REF##15509724##[33]## available in DataMonkey ##REF##15713735##[34]## and HYPHY ##REF##15509596##[35]##. The SLAC method calculates global and site-specific nonsynonymous (<italic>d</italic>\n_N) and synonymous (<italic>d</italic>\n_S) nucleotide substitution rate ratios (ω = <italic>d</italic>\n_N\n<italic>/d</italic>\n_S) based on the BEAST generated phylogenetic tree and the best-fit nucleotide substitution model. The GA method assigns four ω classes to each lineage in search of the model of lineage-specific evolution that best fits the data ##REF##15509724##[33]##. The probability (≥95%) of ω being &gt;1 along a specific lineage was calculated from the averaged model probability of all models rather than by inference from the single best-fitting model ##REF##15509724##[33]##. This approach does not require any <italic>a priori</italic> hypothesis of lineage-specific evolution.</p>" ]

[ "<title>Results</title>", "<title>Study design</title>", "<p>In the present study, all H5N1 influenza viruses with a hemagglutinin gene derived from A/goose/Guangdong/1/96 were designated as belonging to the “Gs/GD lineage”. The H5N1 reassortants from the Gs/GD lineage were referred to by their genotype designation, such as B, X0, Z, V, W and G, as described previously ##REF##15241415##[5]##,##REF##16473931##[6]##. Non-reassortant viruses with all eight gene segments closely related to A/goose/Guangdong/1/96 were referred to as “Gs/GD-like”.</p>", "<p>Our results are presented in four parts: 1) estimation of the time of emergence of the Gs/GD-like virus; 2) estimation of the dates of emergence of genotypes; 3) estimation of the dates of emergence of H5N1 clades; and 4) description of the evolutionary dynamics of HPAI H5N1 viruses in poultry in China. Phylogenetic analysis was conducted using relaxed clock and Bayesian skyline coalescent models ##REF##16683862##[15]##,##REF##15703244##[16]## as implemented in the BEAST software package version 1.4.7 ##REF##17996036##[17]##.</p>", "<p>First, dates of divergence of the H5-hemagglutinin (HA) and N1-neuraminidase (NA) genes of representative Eurasian viruses were estimated. Due to the large number of Gs/GD-like H5N1 virus sequences available, a representative subset of H5N1 sequences were aligned with all publicly available avian H5-HA and N1-NA sequences. The final datasets consisted of 116 H5-HA and 89 N1-NA genes of 1,014 and 1,356 nucleotides in length, respectively, and are referred to as “Eurasian” datasets. Because the exact isolation dates of many viruses were not available, the mid-years of virus isolation were used as calibration points.</p>", "<p>For dating the emergence of the internal genes of the GsGD-like virus and of the H5N1 genotypes, we used internal gene datasets (referred to as “Asian” datasets) that included representative viruses of all identified H5N1 genotypes, plus viruses of other subtypes from poultry and wild aquatic birds. The mid-years of virus isolation were used as calibration points to estimate the time of incorporation of novel gene segments into Gs/GD-like genotypes. Because the non-structural (NS) genes of Gs/GD-like viruses (allele A) and most of its reassortants (allele B) are highly divergent ##REF##10484749##[1]##, the time of most recent common ancestor (TMRCA) for each allele were calculated separately.</p>", "<p>To estimate the dates of emergence of different Gs/GD-like H5N1 clades, H5-HA datasets were recruited that contained representative viruses of known H5N1 variants. The final dataset consisted of the complete HA gene (1,733 nucleotides in length) of 192 viruses, and is also referred to as the “Asian” H5-HA dataset. The exact dates of sampling were known for most of these samples and were used as calibration time points. For those sequences for which exact virus isolation dates were not available, the mid-month date (either the 14th or 15th) was used as the calibration point. However, in some instances, only the date of initial detection of an H5N1 outbreak was available and this was used for calibration ##UREF##1##[18]##.</p>", "<p>Finally, to examine changes in genetic diversity during the evolution of the Gs/GD lineage in China, we constructed Bayesian skyline plots of the virus population described by a modified Asian H5-HA dataset ##REF##18418375##[19]##. This dataset consisted of HA genes of viruses isolated from chicken (n = 54), duck (n = 52), goose (n = 15), pheasant (1) and Guinea fowl (1) in China.</p>", "<title>Rates of nucleotide substitution</title>", "<p>Our analyses showed that the mean substitution rates for the H5 and N1 datasets were 4.77×10⁻³ and 5.19×10⁻³ substitutions per site, per year (subst/site/year), respectively, which were significantly higher than the rates of the internal gene segments (1.84–2.62×10⁻³ subst/site/year) (##TAB##0##Table 1##). These rates are similar to those previously described for avian, human, equine and swine influenza viruses ##REF##16945980##[14]##,##REF##9223253##[20]##,##REF##9739336##[21]##.</p>", "<title>Emergence of the Gs/GD virus</title>", "<p>Analysis of the Eurasian H5-HA dataset revealed four distinct H5 lineages currently circulating in Eurasia: the Gs/GD lineage plus two lineages exclusively of European virus isolates (groups A and B) and one containing isolates from throughout Eurasia (group C) (##FIG##0##Figure 1A##, ##SUPPL##0##S1A##). The time of divergence of these four lineages (node I) was Jul 1989 (95% highest posterior density Jul 1986–Jun 1992) (##FIG##0##Figure 1A##; ##TAB##1##Table 2##). The TMRCA for the Gs/GD lineage (node IV) was estimated to be Jan 1994 (95% highest posterior density (HPD) Apr 1992–Nov 1995) (##FIG##0##Figure 1A##; ##TAB##1##Table 2##). The TMRCAs of the remaining groups are presented in ##TAB##1##Table 2##.</p>", "<p>Similarly, multiple N1-NA lineages were also recognized in Eurasia (##FIG##0##Figure 1B##, ##SUPPL##0##S1B##). The TMRCA for the Gs/GD lineage NA (node V) was estimated to be Oct 1994 (HPD Mar 1993–Jan 1996) (##FIG##0##Figure 1B##; ##TAB##1##Table 2##). It was noted that the N1 gene of the HK/97-like H5N1 virus clustered along with the NA genes of H6N1 viruses from poultry (node VII), with an estimated TMRCA of Jan 1994 (HPD Aug 1990–Oct 1996) (##FIG##0##Figure 1B##; ##TAB##1##Table 2##). The TMRCA for each of the internal gene segments of the Gs/GD-like viruses were estimated using the Asian datasets and ranged from Jul 1993 for the polymerase acidic (PA) gene to May 1995 for the NS gene (##FIG##1##Figure 2## and ##TAB##2##Table 3##).</p>", "<p>Bayes factor (BF) tests showed no significant difference between TMRCAs of all eight gene segments of the Gs/GD viruses (##SUPPL##3##Table S1##). These results indicate that the common ancestor of the Gs/GD-like virus was generated, probably in wild waterfowl, approximately 2 years before it was first detected in poultry in 1996.</p>", "<title>Generation of H5N1 reassortant viruses</title>", "<p>The TMRCAs of the internal gene segments for each major H5N1 genotype (B, X0, W, Z, G and V) were estimated using the Asian datasets from which we inferred the dates of emergence of these genotypes (##FIG##1##Figures 2## and ##FIG##2##3##; ##TAB##2##Table 3##). The mean TMRCAs for the internal genes of genotype B virus ranged from Apr 1995 to Nov 1997 (##TAB##2##Table 3##). Bayes factor tests showed that the internal genes of genotype B were incorporated from three different sources (##SUPPL##3##Table S1##). This suggests that the three internal gene segments of genotype B virus (polymerase basic 2 (PB2), polymerase basic 1 (PB1), polymerase acidic (PA)) were derived from the same virus (mean TMRCA range Nov 1995–Jul 1997), while the NP and NS genes (mean TMRCA range Apr 1995–Nov 1996) was from a different source (##TAB##2##Table 3##), while the M gene (mean TMRCA Nov 1997) was from an independent sources. Therefore, genotype B virus was generated from viruses of four independent sources, i.e. it contains surface genes from Gs/GD and internal genes from three other sources. The mean TMRCA of the last incorporated sources (M gene) was Nov 1997. This date represents the earliest possible time when all genotype B internal gene segments co-circulated in the poultry gene pool in China. Therefore, genotype B virus was generated after mid-1997 (##FIG##2##Figure 3##).</p>", "<p>Both genotypes B and W appear to have emerged during the same period, i.e. after mid-1997 (##FIG##2##Figure 3##). Genotype W shares four internal gene segments (PB1, PA, M and NS) with genotype B, while its PB2 and NP segments are from two different aquatic sources (##FIG##1##Figures 2## and ##SUPPL##1##S2##). The TMRCAs for the PB2 and NP genes were estimated at Dec 1996 (HPD Feb 1993–Mar 2000) and Jan 1995 (HPD Mar 1992–Jan 1997), respectively, and these dates were significantly different (##TAB##2##Tables 3## and ##SUPPL##3##S1##). These results suggest that genotype W has been generated through a reassortment of viruses from six different sources.</p>", "<p>However, the estimated number of gene sources for genotypes B and W should be treated with caution. As the mid-year of isolation (e.g. 2000.5) was used to calibrate the internal gene datasets, the extension of confidence intervals to account for this error indicates that the three internal gene sources for genotype B may not be significantly different. The availability of the date of isolation for viruses would be needed to estimate the age of gene sources for genotypes B and W with greater confidence.</p>", "<p>Genotype X0 does not share any internal genes with genotypes B and W, and has incorporated internal genes from two different sources, i.e. the PB1, PA, M and NS genes were from one source, and while PB2 and NP genes are from another (##FIG##1##Figures 2## and ##SUPPL##1##S2##). For genotype X0 virus, the mean TMRCA range of the internal genes was Apr 1992 to May 2000 (##TAB##2##Table 3##). The TMRCAs of the PB1, PA, M and NS genes were not significantly different (##SUPPL##3##Table S1##). However, the TMRCAs of the NP and PB2 genes were significantly earlier than the other genes, but without significant difference between them, suggesting a common source. The averaged TMRCA means of the five most recent internal genes (Jul 1999) indicates that genotype X0 was generated after mid 1999 (##TAB##2##Table 3## and ##FIG##2##Figure 3##).</p>", "<p>The predominant genotype Z virus was derived from genotype B, with which it shares five internal genes (PB2, PB1, PA, M and NS). The NP gene has a common source with genotype X0 viruses. The TMRCA of the NP gene (##FIG##1##Figure 2A##) was estimated at Dec 1999 (HPD Sep 1998–Jan 2001), indicating that genotype Z emerged late 1999/early 2000 (##FIG##2##Figure 3## and ##TAB##2##Table 3##). Genotype V virus shares all internal genes with genotype Z except for the PA gene. The PA gene of genotype V viruses are most closely related to viruses isolated from the aquatic gene pool and therefore is most likely derived from an aquatic source (##FIG##1##Figure 2B##). The TMRCA for the PA gene was estimated as Mar 2002 (HPD Jan 2001–Jan 2003), suggesting genotype V was generated after early-2002 (##TAB##2##Table 3##). Genotype G viruses have five internal genes (PB2, PB1, PA, M and NS) in common with genotype W, while the NP gene groups with those from genotype Z and V viruses (##FIG##1##Figures 2## and ##FIG##2##3##). Therefore, it was not possible to estimate the date of emergence of genotype G virus.</p>", "<title>Geographical expansion of H5N1</title>", "<p>The introduction to Indonesia occurred approximately 3–4 months before the introduction to Vietnam and Thailand (##FIG##3##Figure 4## and ##TAB##3##Table 4##). The TMRCA for viruses isolated from Vietnam, Thailand and Malaysia (clade 1, node VI) was estimated at Mar 2003 (HPD Oct 2002–Aug 2003), while the TMRCA for the Indonesia viruses (clade 2.1, node VIII) was estimated at Nov 2002 (HPD Jul 2002–Feb 2003) (##FIG##3##Figure 4##). A BF test indicated these dates were significantly different. Both of these TMRCAs are approximately 3–6 months before the first observed H5N1 outbreaks in the field in these countries.</p>", "<p>The TMRCA of the Qinghai-like HA variant (clade 2.2, node IX) was estimated as Dec 2004 (HPD Aug 2004–Feb 2005), while the Fujian-like HA TMRCA (clade 2.3.4, node XIII) was estimated as Sep 2004 (Mar 2004–Feb 2005) (##FIG##3##Figure 4##). These TMRCAs were not significantly different (##SUPPL##3##Table S1##), indicating that these two variants arose during the same period.</p>", "<title>Estimation of genetic diversity and selection pressure</title>", "<p>Coalescent reconstruction using a HA-H5 dataset of poultry isolated in China revealed a rapid increase in the relative genetic diversity of Gs/GD lineage viruses from mid-1999 to 2000 (##FIG##4##Figure 5A##). It was during this period, preceding the current epizootic, that each of the major HA lineages were generated and subsequently became widespread in poultry throughout China (##FIG##4##Figure 5B##).</p>", "<p>Analysis of selection pressures show that the HA of all the major H5N1 sublineages (or clades) were subject to strong purifying selection (mean ratio of rates of nonsynonymous to synonymous substitutions per site, <italic>d</italic>\n_N/<italic>d</italic>\n_S = 0.272). However, four amino acid sites (positions 138, 140, 141 and 156) were under positive selection (<italic>P</italic>&lt;0.05), consistent with previous results for AIV ##REF##16945980##[14]##,##REF##16713612##[22]##,##REF##16439620##[23]##.</p>" ]

[ "<title>Discussion</title>", "<p>We used extensive sequence data and relaxed clock models to date each of the eight gene segments of the Gs/GD-like H5N1 virus. Previously, phylogenetic analyses have shown that the gene segments of Gs/GD-like viruses were most closely related to those viruses from migratory birds ##REF##17507485##[12]##. However, the time of introduction into poultry was not established. We have shown that the prototype virus was likely introduced into poultry as a non-reassortant low pathogenic avian influenza H5N1 virus, rather than being generated by reassortment within poultry. We have also shown that the reassortment events that generated these H5N1 genotypes occurred locally in domestic duck after the Gs/GD-like virus introduction (##FIG##2##Figure 3##).</p>", "<p>Our data help provide insights into the sequence of events that led to each of the three H5N1 transmission waves. Previously, the earliest records of H5N1 wave 1 outbreaks in Vietnam and Indonesia were August and October 2003, respectively ##REF##16713612##[22]##. However, estimation of the TMRCAs of these two lineages indicates that H5N1 virus introduction to Indonesia occurred approximately 3–4 months before the introduction to Vietnam. Furthermore, both of these estimated dates of introduction are approximately 3–6 months before the first observed H5N1 outbreaks in these countries. This may represent the time for disease development and under reporting once outbreaks occurred. In contrast, the TMRCAs of the wave 2 and 3 H5N1 viruses indicated that these HA variants arose during the same period in late 2004.</p>", "<p>Analysis of virus population dynamics revealed a rapid increase in the genetic diversity of Gs/GD lineage in poultry in China from mid-1999 to early 2000. This corresponds with the period when each of the major Gs/GD-like H5N1 variants or sublineages diverged and subsequently became widespread in poultry throughout China ##REF##16473931##[6]##. It is likely that combined strong ecological and evolutionary factors led to this rapid increase in diversity, namely, the spread of the virus through large, immunologically naive poultry populations consisting of diverse species coupled with relatively high rates of nucleotide substitution and selection pressure in the HA. Interestingly, the first detection of current H5N1 reassortants occurred in early 2000, some time after the 1997 Hong Kong ‘Bird Flu’ outbreak in poultry occurred ##REF##11878904##[11]##. This leads us to hypothesize that these reassortant viruses, particularly genotypes B, X0, W and Z, were also generated during this period. This hypothesis is supported by our field data in which different H5N1 genotype viruses have been isolated from the same market on the same sampling occasion ##REF##12077307##[24]##,##REF##15148370##[25]##.</p>", "<p>We also explored a possible mechanism to explain the population behavior of this virus, particularly the generation and maintenance of multiple H5N1 reassortants. The frequent reassortment of the polymerase complex (PB2, PB1, PA and NP) and matrix genes observed in H5N1 viruses indicates that the fitness landscape is similar to that observed for AIV in their natural gene pools, wherein little or no change in fitness is associated with frequent reassortment of functionally equivalent gene segments ##REF##15241415##[5]##,##REF##16473931##[6]##,##REF##18516303##[13]##. The presence of most of these internal genes in domestic duck before their detection in H5N1 genotypes suggests that reassortment occurred in these hosts ##REF##11878904##[11]##.</p>", "<p>We propose a specific mechanism to explain observed patterns of genetic drift and reassortment in H5N1. First, AIV (of different subtypes) from the natural gene pool in wild birds are introduced into domestic duck. In domestic duck, these viruses undergo regular reassortment with endemic H5N1 viruses. Subsequently, transmission of these reassortant viruses within large highly connected populations of duck and other poultry species results in frequent interspecies transmission and genetic drift. Therefore, it is likely that this process selects for relatively fit viruses with a broad host range which are subsequently exported to other geographical regions. It is interesting to note that further reassortment has not been observed once those H5N1 viruses were transmitted out of China. We suggest that host population structures elsewhere may not result in the same intense multi-species transmission we observe in southern China.</p>" ]

[]

[ "<p>Conceived and designed the experiments: DV GJS YG. Performed the experiments: DV JB LD JXZ. Analyzed the data: DV JB LD YG. Wrote the paper: DV JB SR HC JSMP GJS YG.</p>", "<p>The highly pathogenic avian influenza (HPAI) H5N1 virus lineage has undergone extensive genetic reassortment with viruses from different sources to produce numerous H5N1 genotypes, and also developed into multiple genetically distinct sublineages in China. From there, the virus has spread to over 60 countries. The ecological success of this virus in diverse species of both poultry and wild birds with frequent introduction to humans suggests that it is a likely source of the next human pandemic. Therefore, the evolutionary and ecological characteristics of its emergence from wild birds into poultry are of considerable interest. Here, we apply the latest analytical techniques to infer the early evolutionary dynamics of H5N1 virus in the population from which it emerged (wild birds and domestic poultry). By estimating the time of most recent common ancestors of each gene segment, we show that the H5N1 prototype virus was likely introduced from wild birds into poultry as a non-reassortant low pathogenic avian influenza H5N1 virus and was not generated by reassortment in poultry. In contrast, more recent H5N1 genotypes were generated locally in aquatic poultry after the prototype virus (A/goose/Guangdong/1/96) introduction occurred, i.e., they were not a result of additional emergence from wild birds. We show that the H5N1 virus was introduced into Indonesia and Vietnam 3–6 months prior to detection of the first outbreaks in those countries. Population dynamics analyses revealed a rapid increase in the genetic diversity of A/goose/Guangdong/1/96 lineage viruses from mid-1999 to early 2000. Our results suggest that the transmission of reassortant viruses through the mixed poultry population in farms and markets in China has selected HPAI H5N1 viruses that are well adapted to multiple hosts and reduced the interspecies transmission barrier of those viruses.</p>", "<title>Author Summary</title>", "<p>H5N1 influenza virus has been responsible for poultry outbreaks over the last 12 years—the longest recorded example of highly pathogenic avian influenza (HPAI) circulation in poultry. The ecological success of this virus in diverse species of both poultry and wild birds with sporadic introduction to humans suggests that it is a likely source of the next human pandemic. Genome sequences of H5N1 viruses reveal extensive genetic reassortment (mixing) with other influenza subtypes to produce many H5N1 genotypes that have developed into multiple genetically distinct clades, some of which have spread to affect over 60 countries. Here, we analyze all available sequence data of avian influenza viruses from Eurasia and show that the original HPAI H5N1 virus (referred to as A/goose/Guangdong/1/96) was likely introduced directly into poultry as an intact virus particle from wild aquatic birds. In contrast, H5N1 genotypes were generated in aquatic poultry populations after the introduction of A/goose/Guangdong/1/96 virus. Our results suggest that the transmission of reassortant viruses through the diverse poultry populations in farms and markets in China has selected H5N1 viruses that are well-adapted to multiple hosts and reduced the interspecies transmission barrier of those viruses.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>We thank CL Cheung, Huang Kai and Wang Jia, State Key Laboratory of Emerging Infectious Diseases, for collection and processing of samples.</p>" ]

[ "<fig id=\"ppat-1000161-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.g001</object-id><label>Figure 1</label><caption><title>Dated phylogeny of the surface genes of H5N1 viruses isolated in Eurasia.</title><p>The HA gene (A) and N1 gene (B) trees scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. Red branches indicate Gs/GD lineage H5N1 viruses. Identical phylogenetic trees with virus names are shown in ##SUPPL##0##Figure S1##. TMRCAs and HPDs for each of the nodes marked with Roman numerals are given in ##TAB##1##Table 2##.</p></caption></fig>", "<fig id=\"ppat-1000161-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.g002</object-id><label>Figure 2</label><caption><title>Dated phylogeny of the internal genes of viruses isolated in Asia.</title><p>The NP (A), PA (B) and PB2 (C) gene trees scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. Red branches indicate Gs/GD lineage H5N1 viruses. Identical phylogenetic trees with virus names are shown in ##SUPPL##1##Figure S2##. TMRCAs and HPDs for each of the major H5N1 genotype internal genes are given in ##TAB##2##Table 3##.</p></caption></fig>", "<fig id=\"ppat-1000161-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.g003</object-id><label>Figure 3</label><caption><title>Diagram representing the emergence of major H5N1 reassortant viruses.</title><p>Virus particles outlined in black represent donor viruses (with mean TMRCAs above the particle) and those outlined in red represent characterized H5N1 genotypes placed at the year of first detection. Gene segments are ordered PB2, PB1, PA, HA, NP, NA, M and NS from top to bottom within the virus particle diagram. Arrows represent possible reassortment pathways of genotype development. The start of the black arrows (filled circles) indicate the earliest possible time of corresponding genotype generation. Colored arrows represent reassortment between existing H5N1 genotypes.</p></caption></fig>", "<fig id=\"ppat-1000161-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.g004</object-id><label>Figure 4</label><caption><title>Dated phylogeny of the HA gene of H5N1 viruses isolated in Asia.</title><p>The tree is scaled to time (horizontal axis) and was generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. TMRCAs and HPDs for each of the major H5N1 lineage are given in ##TAB##3##Table 4##.</p></caption></fig>", "<fig id=\"ppat-1000161-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.g005</object-id><label>Figure 5</label><caption><title>Population dynamics of genetic diversity of H5N1 viruses isolated from poultry in China.</title><p>Bayesian skyline plot of the HA gene (A) showing changes in genetic diversity of H5N1 viruses. A measure of genetic diversity is given on the y-axis with the 95% HPD shown in blue. The red dashed line indicates the mean TMRCA of the Gs/GD lineage; the blue dashed line represents the time of the first detected H5N1 outbreak China. HA gene tree (B) scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. Numbers to the right of the HA tree indicate H5N1 clades based on the World Health Organization nomenclature system ##UREF##5##[36]##. An identical phylogenetic tree with virus names is shown in ##SUPPL##2##Figure S3##. The red vertical bar in both panels indicates the period of divergence of major H5N1 lineages in poultry.</p></caption></fig>" ]

[ "<table-wrap id=\"ppat-1000161-t001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.t001</object-id><label>Table 1</label><caption><title>Best-fit relaxed clock model and mean nucleotide substitution rates</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Dataset</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gene</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Uncorrelated relaxed clock model</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mean substitution rate (×10⁻³)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Substitution rate HPD (×10⁻³)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasian</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">H5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.77</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.88–5.74</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">N1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">5.19</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.17–6.17</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Asian</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">PB2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">lognormal</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.41</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.92–2.90</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">PB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">lognormal</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.59</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.13–3.04</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">PA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.62</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.9–3.2</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">NP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.47</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.9–3.03</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.84</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.3–2.30</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">NS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2.51</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1.77–3.44</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">H5</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.23</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.58–4.93</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">N1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">exponential</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">4.27</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">3.27–5.25</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"ppat-1000161-t002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.t002</object-id><label>Table 2</label><caption><title>Estimated TMRCAs for the Eurasian H5-HA and N1-NA datasets</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Dataset</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Node<xref ref-type=\"table-fn\" rid=\"nt101\">1</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Description</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Mean TMRCA (95% HPD)<xref ref-type=\"table-fn\" rid=\"nt102\">2</xref>\n</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">H5 HA dataset</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">I</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Current Eurasia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1989.51 (1986.52–1992.42)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gs/GD+out-group</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1991.69 (1989.06–1993.83)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">III</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Hokkaido/Singapore</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.21 (1992.19–1995.91)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">IV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Gs/GD H5N1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.04 (1992.27–1995.84)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">V</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Europe A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.64 (1993.64–1997.06)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">VI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Europe B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1997.88 (1995.47–1999.39)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">VII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1992.48 (1992.71–1993.49)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">N1 NA dataset</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">I</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Current Eurasia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1985.83 (1980.32–1989.67)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1989.21 (1986.30–1991.01)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">III</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1991.40 (1988.73–1993.94)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">IV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1992.59 (1990.45–1994.71)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">V</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GsGD</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.81 (1993.23–1996.02)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">VI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GsGD with 20 AA deletion</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1999.42 (1997.05–2001.23)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">VII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">HK97</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.08 (1990.61–1996.79)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">VIII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia A</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.33 (1992.10–1998.08)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">IX</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.03 (1992.04–1995.75)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">X</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Eurasia C</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1996.19 (1993.68–1998.49)</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"ppat-1000161-t003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.t003</object-id><label>Table 3</label><caption><title>TMRCAs of internal gene segments of H5N1 viruses</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\"/><td align=\"left\" rowspan=\"1\" colspan=\"1\">GsGD (Gs/GD/1/1996)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">X (Dk/ST/4912/2001)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B (Ck/HK/YU562/01)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">W (Dk/Zhejiang/52/00)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Z (Ck/HK/YU22/02)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">V (B.bird/Hunan/1/04)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">G (Dk/Guangxi/13/04)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PB2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.34 (1992.01–1995.95)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1996.04 (1991.11–1999.75)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1997.58 (1995.63–1999.39)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1996.96 (1993.12–2000.19)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B<xref ref-type=\"table-fn\" rid=\"nt103\">*</xref>\n</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">W</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PB1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.77 (1993.62–1995.71)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2000.41 (1999.37–2001.26)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.84 (1993.1–1998.27)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">PA</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1993.52 (1989.21–1996.05)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1999.16 (1996.56–2000.88)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1997.29 (1994.73–1999.29)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2002.18 (2001.03–2003.06)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NP</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1993.67 (1990.46–1995.94)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1992.29 (1988.19–1996.43)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.32 (1991.69–1998.41)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.08 (1992.21–1997.06)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1999.94 (1998.67–2001.06)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">X0</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">X0</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">M</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1994.23 (1990.7–1996.36)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1999.49 (1997.42–2001.08)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1997.83 (1995.58–1999.7)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">NS</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1995.35 (1992.33–1997.29)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1999.31 (1997.25–2001.14)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1996.88 (1993.7–1999.46)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">B</td></tr></tbody></table></alternatives></table-wrap>", "<table-wrap id=\"ppat-1000161-t004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.ppat.1000161.t004</object-id><label>Table 4</label><caption><title>Estimated TMRCAs for H5N1 HA clades</title></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">Nodes</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Description</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">TMRCA (95% HPD)</td></tr></thead><tbody><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">I</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">GsGD</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">1993.75 (1992.50–1994.96)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">II</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">X-series</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2000.70 (2000.11–2001.18)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">III</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clades 1, 2, 8, 9</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2000.74 (2000.06–2001.36)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IV</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clade 1</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2001.16 (2000.57–2001.66)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">V</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Vietnam, Thailand, Malaysia (VTM)+precursor</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2000.74 (2000.06–2001.36)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">VTM</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2003.22 (2002.80–2003.62)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Indonesia+precursor</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2002.52 (2002.09–2002.84)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">VIII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clade 2.1 (Indonesia)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2002.87 (2002.58–2003.12)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">IX</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clade 2.2 (Qinghai lineage)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2004.93 (2004.59–2005.14)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">X</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clade 2.3</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2002.64 (2002.06–2003.16)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">XI</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clades 2.3.1, 2.3.2</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2002.88 (2002.39–2003.29)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">XII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clades 2.3.3, 2.3.4</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2003.91 (2003.11–2004.70)</td></tr><tr><td align=\"left\" rowspan=\"1\" colspan=\"1\">XIII</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Clade 2.3.4 (Fujian-like)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">2004.68 (2004.17–2005.09)</td></tr></tbody></table></alternatives></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"ppat.1000161.s001\"><label>Figure S1</label><caption><p>The HA gene (A) and N1 gene (B) trees scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. Red branches indicate Gs/GD lineage H5N1 viruses.</p><p>(1.33 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"ppat.1000161.s002\"><label>Figure S2</label><caption><p>The PB2 (A), PB1 (B), PA (C), NP (D), M (E) and NS (F) gene trees scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs. Red branches indicate Gs/GD lineage H5N1 viruses.</p><p>(1.65 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"ppat.1000161.s003\"><label>Figure S3</label><caption><p>HA gene tree of H5N1 viruses isolated from poultry in China, scaled to time (horizontal axis) generated using the SRD06 codon model and uncorrelated relaxed clock model. Nodes correspond to mean TMRCAs and blue horizontal bars at nodes represent the 95% HPDs of TMRCAs.</p><p>(0.43 MB PDF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"ppat.1000161.s004\"><label>Table S1</label><caption><p>(0.07 MB PDF)</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><fn id=\"nt101\"><label>1</label><p>Nodes indicate TMRCAs of major H5 and N1 lineages, as shown in ##FIG##0##Figures 1A, B##.</p></fn><fn id=\"nt102\"><label>2</label><p>The dates are presented as year followed by proportion of days.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"nt103\"><p><bold>*:</bold> Refers to the gene being derived from an earlier H5N1 genotype.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p>This study was supported by the Li Ka Shing Foundation, the National Institutes of Health (NIAID contract HHSN266200700005C), the Area of Excellence Scheme of the University Grants Committee (Grant AoE/M-12/06) and Research Grants Council (HKU 7512/06 M) of the Hong Kong SAR Government. GJDS is supported by a career development award under NIAID contract HHSN266200700005C.</p></fn></fn-group>" ]

[ "<graphic id=\"ppat-1000161-t001-1\" xlink:href=\"ppat.1000161.t001\"/>", "<graphic xlink:href=\"ppat.1000161.g001\"/>", "<graphic id=\"ppat-1000161-t002-2\" xlink:href=\"ppat.1000161.t002\"/>", "<graphic xlink:href=\"ppat.1000161.g002\"/>", "<graphic id=\"ppat-1000161-t003-3\" xlink:href=\"ppat.1000161.t003\"/>", "<graphic xlink:href=\"ppat.1000161.g003\"/>", "<graphic xlink:href=\"ppat.1000161.g004\"/>", "<graphic id=\"ppat-1000161-t004-4\" xlink:href=\"ppat.1000161.t004\"/>", "<graphic xlink:href=\"ppat.1000161.g005\"/>" ]

[ "<media xlink:href=\"ppat.1000161.s001.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"ppat.1000161.s002.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"ppat.1000161.s003.pdf\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"ppat.1000161.s004.pdf\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Conditional gene targeting allows for spatial and temporal control of gene expression both <italic>in vitro</italic> and <italic>in vivo</italic>. Several systems for conditional gene targeting exist, such as Flp/Frt, Cre/Loxp, ΦC31-att, Mx-1/IFN-l·α, and Tet on/off ##REF##14723844##[1]##, ##REF##16254565##[2]##. One of the most popular is the Cre-loxp system: a medline search for “Cre recombinase” yields over 2000 publications, of which about 900 represent transgenic mice ##REF##17579640##[3]##. For this approach, a portion of a gene is flanked by loxp sites, 34 base pair sequences consisting of two 13 base inverted repeats flanking 8 non-palindromic bases. Cre recombinase, nominally specific for these sites ##REF##17284462##[4]##, ##REF##10689186##[5]##, either excises or inverts flanked sequences depending on the relative orientation of the two loxp sites, leading to changes in gene function and/or expression. Historically, the popularity of the Cre/loxp system derives from its apparent high fidelity, absence of canonical recognition sites in the mammalian genome, and its high efficiency of recombination as compared to other strategies ##REF##8698848##[6]##, ##REF##11327805##[7]##.</p>", "<p>Most of the work using the Cre-loxp system has been predicated on the assumption that Cre, without Loxp targets, is largely inactive in vertebrate cells. This assumption may have arisen in part due to the lack of overt pathology in Cre expressing mice ##REF##16326700##[8]##, but given the ability of mammals to tolerate significant somatic cell death this conclusion clearly requires validation. Several studies, highlighted recently in two articles ##REF##17579640##[3]##, ##REF##17898721##[9]## have shown that use of the Cre-loxp system in eukaryotic cells carries with it numerous potential confounders such as variable efficiency of Cre expression and/or recombination, variability in germline recombination, and, contrary to the previously mentioned assumption, Cre mediated toxicity ##REF##11163229##[10]##–##REF##16971543##[14]##.</p>", "<p>In order to gain temporal and spatial control over conditional gene targeting, ligand regulated forms of Cre are often utilized. The tamoxifen-regulated Cre variants Cre-ER^T (Cre fused to a mutated human estrogen receptor that binds tamoxifen or 4-hydroxytamoxifen (OHT) but not endogenous estrogens, ##REF##11481484##[11]##, ##UREF##0##[15]##–##REF##16208373##[18]##), and mer-Cre-mer (mCrem, which fuses Cre to two mutated murine estrogen receptors responsive to tamoxifen/OHT but not endogenous estrogens, much like Cre-ER^T above ##REF##17671434##[19]##, ##REF##8604292##[20]##) are favored ligand-regulated Cres because of their reputation for tight regulation in the absence of their tamoxifen/OHT ligands ##REF##8604292##[20]##–##REF##11440973##[25]##. Tamoxifen/OHT-regulatable Cre fusion proteins demonstrate titratable toxicity, suggesting that Cre mediated toxicity is dose- and exposure time-dependent. Over the course of these titration studies it was observed that even in the absence of the inducing ligand some cytotoxicity and/or gene expression could be seen in several cell systems, including DT40 B lymphocytes ##REF##11481484##[11]##, ##REF##17671434##[19]##, ##UREF##1##[26]##, ##REF##11944939##[27]##. Additionally, it has been suggested that ligand independent effects of inducible Cre may be altered by the expression level of the Cre protein ##UREF##1##[26]##. These results call the efficiency of regulation of these Cre variants into question, and suggest a need for a better understanding of how the parameters of inducible Cre expression, Tamoxifen/OHT dose, and Tamoxifen/OHT time of exposure interact to affect tight regulation of ligand-induced Cre activity.</p>", "<p>Our lab makes extensive use of DT40 B-cells as a model system because they support facile gene targeting and are well validated for studies of lymphocyte signaling and physiology ##REF##1913816##[28]##–##REF##17623898##[34]##. To effect conditional gene targeting in these cells, we have historically used mCrem ##REF##11385574##[35]##. In the process of generating a Cre-mediated reversible switching line with a fluorescent readout of Cre activity (##FIG##0##Fig. 1A##), we observed a high level of ligand-independent mCrem activity. To understand how best to implement mCrem-based conditional gene targeting, we have used this system to explore the parameters governing tamoxifen-induced mCrem activity. The results of our investigation show that the level of mCrem expression correlates with Cre activity independent of OHT treatment: high expression leads to abundant ligand-independent activity, while low mCrem expression essentially abolishes activity. Evaluation of time and dose effects in clones with variable expression of mCrem suggests important limitations on the use of mCrem for applications requiring temporally correlated Cre activity within cell populations.</p>" ]

[ "<title>Materials and Methods</title>", "<title>Cell Culture</title>", "<p>DT-40 B lymphocytes were cultured at 37°C with 5% CO₂ in RPMI 1640 Medium (Mediatech Inc.) supplemented with 10% fetal bovine serum (FBS; Mediatech Inc.), 2% chicken serum (Invitrogen), 10 units/ml penicillin/streptomycin (Mediatech Inc.), 2 mM glutamine (Mediatech Inc.) and beta mercaptoethanol (50 µM; Sigma).</p>", "<title>Molecular Biology</title>", "<p>The “Flip” Construct backbone containing the loxp sites, 2 MCS sites, and the SV40 and BGH poly-A signals was synthesized by DNA 2.0, Inc. Subsequently, the CMV promoter, chicken NUDT9 cDNA, mCherry cDNA, and a B-actin-Neomycin resistance cassette were inserted using various restriction sites. The Left and Right homology arms extended from exon 4 to exons 1 and 7 respectively. Integration of the Flip construct into the NUDT9 locus was verified using the following primers, which span the Neo-Right homology Arm and the Right homology arm-genomic locus junctions in their product: Forward: <named-content content-type=\"gene\">ACATAGCGTTGGCTACCCGTGATA</named-content>, Reverse: <named-content content-type=\"gene\">ACTGCTTTGAAGGCCACACATTCC</named-content>. The product of this PCR was also sequenced following gel- or PCR purification. Following transfection, clones were selected in G418 (2 mg/mL, invitrogen), and selected clones were screened for targeted integration via PCR.</p>", "<p>Mer-Cre-mer, expressed in the pcDNA5T/O vector (invitrogen), was a generous gift from Michael Reth by way of Tomo Kurosaki. Following transfection of mer-Cre-mer, clones were selected in hygromycin (2 mg/mL, Calbiochem), and selected clones were evaluated for mer-Cre-mer expression by western blot. Clones were lysed and 50 µg of protein from each clone were run on an 8% SDS-PAGE gel. Mer-Cre-mer was visualized using polyclonal rabbit anti-Cre antibody (1∶2000, Novagen, Inc.). β-actin controls were stained with a mouse polyclonal anti-β actin antibody (1∶40,000, Sigma). The secondary antibody was peroxidase conjugated donkey anti-rabbit from Amersham Pharmaceuticals.</p>", "<p>Stable tranfection of DT-40 B lymphocytes was carried out using a Bio-Rad Gene-Pulser electroporation apparatus. Cells (1×10⁷/0.5 ml serum-free medium) were pulsed in 0.4-cm cuvettes with 50 µg plasmid DNA at 550 V and 25 µF.</p>", "<title>Flow Cytometry</title>", "<p>FACS analyses were performed on either a BD FACSAria (Becton-Dickenson) or a BD LSRII (Becton-Dickenson), using a green laser (561 nm) to excite the mCherry protein (excitation max: 587 nm, emission max: 610 nm). Cells were resuspended in media as described above, without the color indicator. 10,000 events were collected for each panel. Sorting experiments were carried out on the BD FACSAria.</p>", "<title>Cre induction</title>", "<p>Cells expressing mer-Cre-mer were induced using 1 µM, 100 nM, 10 nM, or 1 nM 4-Hydroxytamoxifen (OHT) for 48, 24, 10, 5, 2, or 1 hour, or left untreated. Following tamoxifen treatment, cells were centrifuged at 500× <italic>g</italic> for 5 minutes to collect the cells, resuspended in 10 mL RPMI, and centrifuged again to wash the cells. The cells were then resuspended in standard medium and grown in culture for 3–50 days.</p>" ]

[ "<title>Results</title>", "<title>DT40 B lymphocytes transfected with a reversible switching construct and expressing mer-Cre-mer show OHT-independent inversion of the floxed cassette</title>", "<p>To better understand the function of the Nudix-type ADPR-hydrolase NUDT9, our lab targeted this gene for deletion in DT40 chicken B cells. Since we were unable to target both alleles with classical knockout constructs, we reasoned that loss of NUDT9 must be lethal in this cell type, and that therefore a conditional knockout strategy would be required. We chose to proceed with a reversible switching construct (##FIG##0##Fig. 1A##), in which a chicken NUDT9 cDNA and an mCherry fluorescence reporter were present in inverted orientation to one another. This organization afforded us a fluorescent readout of Cre activity, with activity in 100% of cells correlating to roughly 50% red fluorescent cells ##REF##15629431##[24]##. Following selection of a clone that had stably integrated the construct (##FIG##0##Fig. 1B##), we transfected this clone, designated 27Flip, with a vector constitutively expressing mCrem under the control of the CMV promoter.</p>", "<p>Following transfection of the 27Flip cells with the mCrem containing vector, stably expressing clones were identified and a highly expressing clone, designated 27Flip/Cre20 was selected on the basis of an mCrem western blot (##FIG##0##Fig. 1C##). Based on previous work ##REF##8604292##[20]##, ##REF##15629431##[24]##, it was anticipated that prior to treatment with OHT, 27Flip/Cre20 cells would show no mCherry fluorescence, similar to the parental 27Flip line. However, the 27Flip/Cre20 clone showed a sub population with robust red fluorescence (##FIG##0##Fig. 1D##) prior to any tamoxifen exposure. Thus, we sought to identify the cause of mCherry expression in these cells.</p>", "<title>Sustained OHT-independent flipping of the floxed cassette in 27Flip/Cre20 cells is a stable, ongoing process</title>", "<p>We initially hypothesized that electroporation or other stressors associated with transduction of DT40 cells with the mCrem containing construct might lead to inefficient exclusion of mCrem from the nucleus and subsequent Cre dependent switching of our construct in affected cells. To test this hypothesis, we sorted mCherry negative (“white”) and mCherry-positive (“red”) cells by flow cytometry, and monitored the fluorescence of the separated populations over time in the absence of OHT (##FIG##1##Fig. 2##). If mCrem activity were a transient event associated with electroporation, these sorted populations would be expected to remain stable over time. However, we observed that white cells showed an outgrowth of red cells and vice versa over a course of 7 weeks in culture. Interestingly, red cells converted to white cells more rapidly, a phenomenon potentially related to idiosyncratic differences in susceptibility of the flip cassette to recombination, or a survival disadvantage associated with loss of NUDT9 expression. These results suggested that in contrast to previous results, mCrem was capable of mediating significant levels of constitutive recombination activity. Because such unlicensed mCrem dependent recombination is a potential confounding factor for the reversible switching approach to conditional gene inactivation, we set out to better characterize this phenomenon.</p>", "<title>Sustained OHT-independent Cre activity in 27Flip/Cre20 cells correlates with mer-Cre-mer expression level</title>", "<p>Several previous observations suggest that control of mCrem recombination is less than perfect ##REF##11481484##[11]##, ##REF##8604292##[20]##, ##UREF##1##[26]##, ##REF##11944939##[27]##. Based on these observations, we were interested in clarifying the role of mCrem expression level in OHT-independent recombination. We hypothesized that low frequency OHT-independent recombination by mCrem is mCrem intrinsic, and thus that OHT-independent Cre activity should be demonstrable in other mCrem expressing clones, and furthermore that as more mCrem would provide more activity, the level of constitutive flipping should correlate with mCrem expression level. To test this hypothesis, we re-transfected 27Flip cells with the mCrem containing vector to generate a panel of 27Flip/Cre clones expressing varying amounts of mCrem by western blot (##FIG##2##Fig. 3A##). These clones were assigned to either “high” (27Flip/Cre15 and -20) or “low” (27Flip/Cre26, -31, and -35) mCrem expressing categories and compared for flipping in the presence and absence of 1 µM OHT (##FIG##2##Fig. 3B##). Consistent with mCrem possessing intrinsic OHT-independent recombination activity, clones with high expression showed OHT-independent Cre activity, while low expressing clones exhibited little to no activity. Although the apparent decrease in flipping for the high expressing clones at high OHT concentrations suggested a potential difference in efficiency of recombination depending on the orientation of the cassette, repeating these experiments revealed variation in the size of the red population ranging from 38–60% that changed from day to day (data not shown), suggesting that background fluctuations in the population occur in the context of constitutive ongoing flipping. Importantly, all clones responded well to OHT treatment based on their establishing a ∼50∶50 ratio of red to white cells over a 48 hour OHT treatment (with a 50/50 ratio indicating flipping in ∼100% of cells). Note that clone 35, which at first glance appeared to have less red cells than other clones, showed poorer separation of red and white populations than other clones, making the percentage of white vs. red cells less precise in this clone than others.</p>", "<title>OHT-dependent mCrem activity saturates by 10 nM OHT</title>", "<p>In a previous study ##REF##15629431##[24]## an OHT concentration of 50 nM was used to induce mCrem mediated recombination, significantly lower than the 1 µM used in the studies above. Thus, we wanted to investigate the interaction between mCrem expression level and OHT dose for induction of mCrem mediated recombination. Thus, we treated both the high and low expressing 27Flip/Cre clones with 100, 10, or 1 nM OHT for 48 hours, and compared the treatment groups for Cre activity at 5 days after the start of OHT treatment (##FIG##3##Fig. 4##). Since during OHT treatment the construct spends equal time in the forward and reverse orientations, all cells express mCherry during this time: as such, we included a “rest” period of 3+ days to allow white cells to lose any residual fluorescence. Clones 15 and 20 with constitutive flipping activity exhibited only minor changes in population distribution after OHT treatment - these minor changes may reflect differing efficiencies of flipping in the forward and reverse directions or differential effects of tamoxifen toxicity on the two populations at the higher doses. Clones with lower mCrem expression all exhibited dose dependent recombination, with the clone with the lowest apparent mCrem expression (based on a qualitative assessment of the western blot in ##FIG##2##Fig. 3A##), 27Flip/Cre31, showing the lowest level of activity at 1 nM Cre. This result suggests that at sufficiently low OHT concentration, mCrem expression level becomes limiting for recombination efficiency. Nevertheless, although mCrem expression in this clone was near the limit of detection in our western blot, we saw flipping in 100% of cells at 10 nM OHT, suggesting that this concentration is sufficient to maximize Cre activity when applied for 48 hours. Consistent with previous work ##REF##11481484##[11]## we observed significant mCrem mediated toxicity at 1 µM and 100 nM OHT, which decreased at 10 nM and was essentially absent at 1 nM. In addition, the frequency of cell death was consistently higher among high mCrem expressors as compared to low expressors at 100 and 10 nm OHT, plateauing at 1 µM and being undetectable at 1 nM for all clones (data not shown).</p>", "<title>Efficiency of OHT-dependent Cre activity correlates with duration of OHT exposure</title>", "<p>We noted that at all concentrations of OHT, the majority of treated cells became positive for red fluorescence within 24 hours (data not shown), suggesting that the majority of cells may already have initiated switching well before the 48 hours of OHT exposure typically employed by our and other labs ##REF##15629431##[24]##. We therefore set out to identify the effect of varying OHT exposure time in clones expressing different amounts of mCrem. We treated the 27Flip/Cre clones with 1 nM OHT for 1, 2, 5, 10, and 24 hours before removing OHT and allowing the cells to grow for five days in culture, at which point we examined the cells for red fluorescence by FACS (##FIG##4##Fig. 5A##). In all clones except the high expressor 27Flip/Cre15, a steady decline in recombination activity was evident as OHT exposure time decreased: for 27Flip/Cre15 flipping was already at ∼100% in the untreated population. Coupled with the dose response of the various clones, these results also provided further support for our conclusion from ##FIG##2##Fig. 3## that recombination efficiency decreases with decreasing mCrem expression. Flipping in 100% of the cells in all clones except 27Flip/Cre15 was not seen at exposure times less than 48 hours.</p>", "<p>Surprisingly, we observed low level induction of Cre activity at even 1 hour of 1 nM OHT exposure, a much shorter time than is typically used for mCrem induction. Consequently we were curious if, by using a high concentration of mCrem we might be able increase the percentage of cells with Cre activity at early time points. Since we showed that 100% of 27Flip/Cre31 cells underwent flipping at 10 nM applied for 48 hours (##FIG##3##Fig. 4##), we reasoned that a ten fold excess of this saturating concentration would be sufficient to induce rapid Cre activity. Thus we applied 100 nM OHT to 27Flip/Cre31 cells for short periods of time, allowed the cells to grow in culture for 5 days, and then analyzed flipping by FACS (##FIG##4##Fig. 5B##). Under these conditions, we detected roughly 50% of cells undergoing flipping after 4 hours of treatment with 100 nM OHT, and that roughly 1% of cells had undergone flipping within just 10 minutes of OHT treatment. These results suggest that although high concentration/short time exposure of OHT can induce detectable recombination, recombination does not occur with any degree of synchronicity in DT40 cells, even within cells of a clonal population.</p>" ]

[ "<title>Discussion</title>", "<p>Although some studies of the mCrem system ##REF##8604292##[20]##, ##REF##15629431##[24]##, ##REF##7784172##[36]## have suggested that mCrem mediated recombination is tightly controlled in the absence of ligand, work from other labs suggested ligand independent mCrem mediated recombination might occur, albeit at low frequency ##REF##11481484##[11]##, ##REF##17671434##[19]##, ##UREF##1##[26]##, ##REF##11944939##[27]##. This discrepancy has not been systematically addressed to date <italic>in vitro</italic> or <italic>in vivo</italic>. This prompted us to use a reversible switching system for analysis of the parameters governing tamoxifen/OHT-regulated mCrem recombination of a genomic target. In this report, we show that robust mCrem expression correlates with a high level of tamoxifen/OHT-independent Cre activity, while clones expressing mCrem at the limit of western blot detection exhibit extremely tight regulation. Additionally, we demonstrate that the Tamoxifen/OHT dose response of clones varies with mCrem expression level.</p>", "<p>In contrast to our results, it has been previously shown that in DT40 cells expressing a reversible switching construct and mCrem, little to no OHT-independent Cre activity occurred ##REF##15629431##[24]##. These differences may be due to epigenetic differences at the respective integration loci ##REF##11306549##[37]## or possibly the serendipitous use of a low mCrem expressing clone (Cre expression levels were not examined in those studies). Although it is difficult to predict or control the former, our results clearly show that limiting mCrem expression may be effective in controlling tamoxifen/OHT-independent mCrem mediated recombination, although at the expense of potentially requiring higher dose or duration of OHT treatment to induce maximal recombination. Thus, future studies using reversible switching should evaluate clones with a range of low but detectable mCrem expression to identify those which minimize unregulated mCrem activity but provide maximal recombination at the desired OHT does and time of exposure. Furthermore, it is important to monitor the stability of both the forward and reverse populations in any reversible switching study (particularly if an antibiotic resistance cassette is integrated in either direction, since this may mask switching out of the given orientation), for evidence of OHT-independent mCrem mediated recombination. If unlicensed Cre activity is an issue, clones that appear mCrem negative by western blot should be screened via FACS with or without OHT treatment, since such clones may express mCrem at levels low enough to be undetectable by western blot but nevertheless be capable, as our results suggest, of mediating mCrem dependent recombination.</p>", "<p>Given that we observed tamoxifen/OHT-independent Cre activity in several high expressing clones, we speculate that this phenomenon is an intrinsic property of mCrem in DT40 cells, possibly because of their small cytoplasmic volume, which may encourage mCrem nuclear translocation as expression increases. It is probably further generalizable that higher expression levels of mCrem in any cell line or <italic>in vivo</italic> model will lead to a greater risk for unlicensed activity: previous findings suggest that tamoxifen/OHT-independent Cre activity also occurs in mice and murine cells cultured <italic>in vitro</italic>\n##UREF##1##[26]##, ##REF##11944939##[27]##. Thus, our results suggest that investigators should limit mCrem expression in any Cre-loxp based model system where tight ligand-dependent regulation of mCrem activity is crucial (our results in ##FIG##2##Figs. 3B##, and ##FIG##3##4## indicate that even minimal expression of mCrem is sufficient for 100% penetrance of Cre activity given an adequate OHT dose and time of exposure).</p>", "<p>Previous studies have examined the effects of tamoxifen/OHT dosage on inducible Cre-mediated recombination, but never in the context of variable Cre expression. Thus, our results provide insight on tamoxifen/OHT dose and/or time of exposure adjustments that must be made at varying Cre expression levels. If low mCrem expressing clones are selected for study, as we recommend above, investigators can expect that a sufficiently high dose of OHT must be applied if 100% penetrance of recombination is desired. Surprisingly, in our system a “sufficiently high dose” titrated to only 10 nM OHT applied for 48 hours for our lowest mCrem expressing clone, a dose 100 fold lower than our standard OHT dose and 5 fold lower than the dose used in a previous study ##REF##15629431##[24]##. Since work from our lab and others suggests that mCrem mediated toxicity correlates with OHT dose, we recommend the use of 10 nM OHT for 48 hours to maximize penetrance while minimizing toxicity. This recommendation is supported by our time course studies, since even in the highly expressing clone 27Flip/Cre20, 1 nM OHT exposure times of 24 hours or less resulted in decreased Cre activity. Nevertheless, exposure time and/or OHT dose can be adjusted considerably depending on mCrem expression and the desired level of penetrance. The finding that Cre activity is evident in some 27Flip/Cre31 cells within 10 minutes of high dose OHT (100 nM) application, but that activity in 100% of cells cannot be achieved within 4 hours was surprising, as it suggests that induction of mCrem activity within even a clonal cell population is highly asynchronous. Whether better synchronicity can be achieved by examining only cells at a similar point in the cell cycle or by applying toxic doses of ligand for short periods of time are interesting areas for future investigation.</p>", "<p>In conclusion, we show for the first time that robust mCrem expression allows Cre activity independent of ligand binding, while low mCrem expressing clones are largely free of this effect, and that tamoxifen/OHT dose response correlates with changing mCrem expression. Time and dose-dependent effects on mCrem activity suggest limitations on the use of conditional targeting approaches for applications which require tight temporal coordination of Cre action within a cell population.</p>" ]

[]

[ "<p>Conceived and designed the experiments: BB AMS. Performed the experiments: BB. Analyzed the data: BB. Contributed reagents/materials/analysis tools: BB AMS. Wrote the paper: BB.</p>", "<p>Conditional gene targeting using the Cre-loxp system is a well established technique in numerous <italic>in vitro</italic> and <italic>in vivo</italic> systems. Ligand regulated forms of Cre have been increasingly used in these applications in order to gain temporal and spatial control over conditional targeting. The tamoxifen-regulated Cre variant mer-Cre-mer (mCrem) is widely utilized because of its reputation for tight regulation in the absence of its tamoxifen ligand. In the DT40 chicken B cell line, we generated an mCrem-based reversible switch for conditional regulation of a transgene, and in contrast with previous work, observed significant constitutive activity of mCrem. This prompted us to use our system for analysis of the parameters governing tamoxifen-regulated mCrem recombination of a genomic target. We find that robust mCrem expression correlates with a high level of tamoxifen-independent Cre activity, while clones expressing mCrem at the limit of western blot detection exhibit extremely tight regulation. We also observe time and dose-dependent effects on mCrem activity which suggest limitations on the use of conditional targeting approaches for applications which require tight temporal coordination of Cre action within a cell population.</p>" ]

[]

[]

[ "<fig id=\"pone-0003264-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003264.g001</object-id><label>Figure 1</label><caption><title>DT40 B lymphocytes transfected with a reversible switching construct and expressing mer-Cre-mer show 4-hydroxytamoxifen independent Cre activity.</title><p>\n<italic>A</italic> Schematic of the “Flip” construct. Exon 4 of NUDT9 was replaced with a CMV promoter, an in-frame region (containing a NUDT9 cDNA and an inverted mCherry cDNA, each followed by a poly-A region) flanked by loxp sites, and a neomycin selection cassette. Treatment of cells stably expressing the construct with 4-hydroxytamoxifen (OHT) should lead to reversible flipping of the floxed region, as shown in the cartoon, and subsequent expression of mCherry red fluorescent protein in ∼50% of the cells. <italic>B</italic> Stable integration of the Flip construct was verified in clone #27 via genomic PCR. The positive control represents a different construct that could be amplified with the same primer set. <italic>C</italic> Following stable transfection of clone #27 with a mer-Cre-mer (mCrem) expressing vector, cells from various clones were lysed and 50 µg of protein from each were run on an 8% SDS-PAGE gel. mCrem was visualized with polyclonal rabbit anti-Cre antibody (1∶2000, Novagen), and a highly expressing clone, 27Flip/Cre20 was selected for further study (red circle). <italic>D</italic> 27Flip and 27Flip/Cre20 cells were analyzed by flow cytometry, as indicated. In contrast to the 27Flip parental line, the mCrem expressing 27Flip/Cre20 cells showed robust red fluorescence in a large subpopulation despite the absence of the mer- ligand OHT.</p></caption></fig>", "<fig id=\"pone-0003264-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003264.g002</object-id><label>Figure 2</label><caption><title>Sustained OHT-independent flipping of the floxed cassette in 27Flip/Cre20 cells is a stable, ongoing process.</title><p>mCherry (+) and mCherry (−) 27Flip/Cre20 cells were separated by FACS and grown in culture for ∼7 weeks. During this time period, a steady decrease in the purity of the sorted populations was observed by flow cytometry. X-axis, mCherry fluorescence, Y-axis, cell number.</p></caption></fig>", "<fig id=\"pone-0003264-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003264.g003</object-id><label>Figure 3</label><caption><title>Sustained OHT-independent flipping of the floxed cassette in 27Flip/Cre20 cells correlates with mer-Cre-mer expression level.</title><p>\n<italic>A</italic> Following stable transfection of 27Flip cells with an mCrem expressing vector, 5 clones expressing various amounts of mCrem were selected. Cells from the clones were lysed and 50 µg of protein of each were run on an 8% SDS-PAGE gel. MCrem was visualized with polyclonal rabbit anti-Cre antibody (1∶2000, Novagen), with β-actin visualized with a polyclonal mouse antibody (1∶40000, Sigma) as a loading control. 27Flip/Cre15 and -20 were designated “high expressors”, and 27Flip/Cre26, -31, and -35 were designated “low expressors”. <italic>B</italic> 27Flip/Cre clones were either left untreated or treated with 1 µM OHT for 48 hours and then allowed to grow in culture for 18 days: all clones were subsequently analyzed by flow cytometry. The 27Flip parental cell line was used as a negative control.</p></caption></fig>", "<fig id=\"pone-0003264-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003264.g004</object-id><label>Figure 4</label><caption><title>OHT-dependent flipping of the floxed cassette saturates by 10 nM OHT.</title><p>27Flip/Cre clones were either left untreated or treated with 1, 10, or 100 nM OHT for 48 hours and then allowed to grow in culture for 5 days from the onset of OHT treatment: subsequently all clones were analyzed by flow cytometry. 27Flip parental cells were used as a negative control. X-axis, mCherry fluorescence, Y-axis, cell number.</p></caption></fig>", "<fig id=\"pone-0003264-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003264.g005</object-id><label>Figure 5</label><caption><title>Efficiency of OHT-dependent flipping of the floxed cassette correlates with duration of OHT exposure in low mCrem expressors.</title><p>\n<italic>A</italic> 27Flip/Cre clones were either left untreated or treated with 1 nM OHT for 24, 10, 5, 2, or 1 hours, and then allowed to grow in culture for 5 days: subsequently all clones were analyzed by flow cytometry. 27Flip parental cells were used as a negative control. <italic>B</italic> 27Flip/Cre31 cells were either left untreated or treated with 100 nM OHT for 1, 2, 5, 10, 30, 60, 120, or 240 minutes and then allowed to grow in culture for 5 days: subsequently all clones were analyzed by flow cytometry. X-axis, mCherry fluorescence, Y-axis, cell number.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>ARCS foundation, NCI training grant, NIH R01 GM64091</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003264.g001\"/>", "<graphic xlink:href=\"pone.0003264.g002\"/>", "<graphic xlink:href=\"pone.0003264.g003\"/>", "<graphic xlink:href=\"pone.0003264.g004\"/>", "<graphic xlink:href=\"pone.0003264.g005\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>In the last 20 years, there has been a dramatic increase in the emergence of antibiotic-resistant bacteria, leading to elevated bacterial pathogenesis at the global level ##REF##17940239##[1]##, ##REF##17940231##[2]##. In particular, the emergence of drug resistant strains of <italic>Mycobacterium tuberculosis</italic> (MDR- and XDR-TB) and the increased occurrence of methicillin-resistant <italic>Staphylococcus aureus</italic> (MRSA) infections, indicate that drug resistance is a major public health problem ##REF##17940239##[1]##, ##REF##17940231##[2]##. Recent reports indicate that in the United States MRSA infections cause more deaths than HIV/AIDS, whereas the development of new antibiotics has significantly slowed down since the early 1990s ##REF##17940239##[1]##, ##REF##17940231##2##, ##REF##18276850##3##. Therefore, developing sensitive and cost-efficient detection systems that can quickly identify if (1) a particular bacterium is resistant to antibiotics, (2) the pharmacological agents which the microorganism is susceptible to and (3) the agents' appropriate effective dosage is vital for successful treatment and prevention of epidemics. Traditionally, the determination of antimicrobial susceptibility to antibiotics is facilitated after isolation of the microorganism and examination of its growth in media containing various antimicrobial agents, in a process that can take up to 48 hours ##UREF##0##[4]##, ##REF##11420333##[5]##. Hence, developing fast and accurate antimicrobial susceptibility assays is important for the clinic and the pharmaceutical industry.</p>", "<p>Nanotechnology offers a unique alternative for the development of detection methods for bacterial targets that require less preparation time and smaller sample volumes, while offering enhanced sensitivity and faster detection kinetics ##REF##16004566##[6]##, ##REF##9748157##[7]##, ##REF##15738981##[8]##, ##REF##15826019##[9]##, ##REF##17298004##[10]##. In particular, nanosensors that not only detect the presence of a particular pathogenic agent directly, but can also make an indirect detection through the assessment of the pathogen's metabolic activity, e.g., via the monitoring of the rate of consumption of nutrients in solution, would be of great utility. The development of such nanosensors will be of significant importance, because they will be able to interrogate whether the pathogen is still metabolically active and reproducing in the presence of a particular antibiotic. Currently, most contemporary nanoparticle-based immunoassays cannot distinguish between metabolically active and dead pathogens ##REF##17298004##[10]##, ##REF##18228547##[11]##. Recently, a novel gold nanoparticle-based method for the assessment of bacterial susceptibility via surface plasmon resonance shifts was reported ##REF##18198893##[12]##. The main drawbacks of this technique are the small, although significant, changes in the surface plasmon band and the assay's inability to work in turbid or opaque media, due to the media's strong scattering and absorbance that mask the nanoparticles' plasmonic band. Hence, as some microorganisms, like <italic>Staphylococcus epidermidis</italic> and <italic>Neisseria</italic> spp. among many others, can be present in the blood of infected patients (septicemia), requiring isolation and growth in blood- containing media, it is vital to have clinical diagnostic assays for the assessment of antimicrobial susceptibility in blood ##REF##17457359##[13]##, ##REF##16032562##[14]##.</p>", "<p>Consequently, we reasoned that a more robust system, which quickly determines bacterial susceptibility independent of the solution's optical properties, could be developed using magnetic nanosensors and detection via water relaxation ##REF##12134166##[15]##. According to the literature, it is widely acknowledged that a major benefit of using magnetic relaxation methods is that molecular detection can be achieved in opaque media, such as cell lysates, tissue extracts and complex biological fluids, notably blood, with high specificity and sensitivity ##REF##17298004##[10]##, ##REF##12134166##[15]##, ##REF##12926940##[16]##. Therefore, we hypothesized that bacterial-susceptibility-monitoring nanosensors could be designed to differentially respond to the presence of various concentrations of nutrients, such as complex carbohydrates (e.g. starch). Although superparamagnetic nanoparticles have been used as magnetic relaxation sensors for the detection of various targets ##REF##17298004##[10]##, ##REF##12134166##[15]##, ##REF##12926940##[16]##, ##REF##17335265##[17]##, ##REF##14744779##[18]##, ##REF##18428168##[19]##, ##REF##11902860##[20]##, ##REF##17193579##[21]##, ##REF##15114571##[22]##, these nanoprobes have not been previously utilized for the detection of metabolic activity, which might lead to the potential development of nanosensors capable of determining antimicrobial susceptibility in complex media. The polysaccharide nanosensors' clustering should result in a significant change in the spin-spin relaxation time (T2) of the solution's water protons, facilitating the reliable identification of effective antimicrobial agents. This can be achieved using dextran-coated iron oxide nanoparticles along with a protein with high affinity to carbohydrates, such as Concanavalin A (ConA) ##REF##15183773##[23]##, ##UREF##1##[24]##, in a competition assay. Specifically, we hypothesized that upon Con A-induced clustering, the dextran-coated iron oxide nanoparticles can differentially respond to the polysaccharide levels associated with bacterial metabolism and growth. Hence, the higher the rate of bacterial metabolic activity, the fewer amount of the available polysaccharides (such as starch) would be, resulting in prominent changes in the sample's ΔΤ2 when compared to those of the sterile medium (##FIG##0##Figure 1##).</p>" ]

[ "<title>Materials and Methods</title>", "<title>Synthesis of iron oxide nanoparticles</title>", "<title>Reagents</title>", "<p>All the reagents used were of AR (Analytical Reagent) grade. Nitrogen-purged double-distilled water was used throughout the reaction. Iron salts, FeCl₂.4H₂O and FeCl₃.6H₂O, were obtained from Fluka. Dextran (MW 10kDa) was received from Amersham. TEOS: tetraethylorthosilicate (Fluka), APTS: 3-(amino-propyl)triethoxysilane (Aldrich) and THPMP: 3-(trihydroxysilyl)propylmethyl-phosphonate (Gelest Inc) were used as received from the suppliers.</p>", "<title>Procedure</title>", "<p>The dextran-coated iron oxide nanoparticles were prepared as previously reported in the literature ##REF##12926940##[16]##. The aminated silica-coated iron oxide nanoparticles were prepared using a previously published protocol ##UREF##2##[31]##, with modifications in order to yield stable nanoparticles via a water-based synthesis. Specifically, iron oxide nanocrystals were formed via the alkaline precipitation method, by mixing a solution of iron salts (0.202 g FeCl₂.4H₂O, 0.488 g FeCl₃.6H₂O, 88.7 µL HCl in 2 mL distilled water) with an ammonium hydroxide solution (830 µl NH₄OH in 15 mL distilled water). Then, 20 seconds after the initiation of the iron oxide nanocrystal formation, a TEOS-THPMP-APTS solution was added (6180 µL THPMP, 2680 µL TEOS, 670 µL APTS) under continuous vortexing. The as-synthesized nanoparticle suspensions were centrifuged to remove large particles. Both the amino-silica- and dextran-coated nanoparticles were washed several times with distilled water and concentrated through an Amicon 8200 cell (Millipore Ultrafiltration membrane YM–30 k). Finally, the nanoparticle suspensions were stored at 4°C until further use.</p>", "<title>Conjugation of Concanavalin A to aminated silica-coated iron oxide nanoparticles</title>", "<p>Two milliliters of aminated silica-coated iron oxide nanoparticles (R2 = 225 mM⁻¹s⁻¹, [Fe] = 0.47 mg/ml) were used for the conjugation of Con A to the nanoparticles' surface. Initially, in 1 mL of cold MES buffer (0.1 M, pH 6.0) 4.8 mg EDC (Pierce) and 3 mg NHS (Pierce) were dissolved. Then, 2 mg of lyophilized Con A (Type V, Sigma) were dissolved in 2 mL cold MES buffer (0.1 M, pH 6.0). Subsequently, the Con A solution was mixed with the EDC/NHS solution, followed by a 3-minute low-speed rotary mixing at room temperature. Finally, the aminated silica-coated iron oxide nanoparticles were added to the Con A (amine-reactive NHS-ester form) solution, followed by periodical rotary mixing at low speed and storage at 4°C. The resulting Con A-conjugated silica-coated iron oxide nanoparticles were purified from any unbound protein via magnetic separation using an MES buffer-equilibrated (0.1 M) LS25 MACS® column (Miltenyi Biotec).</p>", "<title>Characterization</title>", "<p>Dynamic light scattering (DLS) studies were done using a PDDLS CoolBatch 40T instrument using Precision Deconvolve 32 software. Iron concentration was determined spectrophotometrically after acid digestion of the nanoparticles' suspension, whereas R2 relaxivity measurements were obtained using a 0.47T mq20 NMR analyzer (Minispec, Bruker, Germany). Starch sensing with the magnetic nanoparticles was performed using serial dilutions of starch (∼75% amylopectin, ∼25% amylose, S-516, Fisher) in non-starch containing MH broth (DIFCO™, BD). The concentration of Con A conjugated to the silica-coated iron oxide nanoparticles was determined through the BCA assay, in accordance to the manufacturer's protocol (Pierce), after magnetic separation of the nanoparticle suspension using an MES buffer-equilibrated (0.1 M) LS25 MACS® column (Miltenyi Biotec).</p>", "<title>Bacterial cultures</title>", "<p>In order to investigate if the dextran-coated iron oxide nanoparticles can monitor the starch utilization due to bacterial metabolic activity, different populations of <italic>Escherichia coli</italic> (strain 8739 from ATCC) were grown in starch-containing MH broth (DIFCO™, BD) for 2 hours at 37°C. For determination of the minimum inhibitory concentration, <italic>Escherichia coli</italic> (10⁶ CFU), <italic>Serratia marcescens</italic> (ATCC, 10⁶ CFU) and <italic>Shigella sonnie</italic> (strain 9290 from ATCC, 10⁶ CFU) were grown in a starch-containing MH broth (DIFCO™, BD), for 2 hours at 37°C in the presence or absence of ampicillin. For determination of MIC in blood, bacterial stocks (10⁶ CFU) were grown in the presence or absence of ampicillin in a 5%-blood-supplemented starch-containing MH broth, for 2 hours at 37°C. Defibrinated sheep blood was obtained from the Colorado Serum Company, simulating bacterial isolation and growth in typical blood agar plates. For studies requiring heat inactivation, <italic>E. coli</italic> bacteria were autoclaved in the culture tubes for 10 minutes. Upon incubation or inactivation, all bacterial stocks were placed in a Fisher Isotemp freezer (Fisher Scientific, Hampton, NH), until further use.</p>", "<title>Sample preparation for relaxation measurements</title>", "<p>Aliquots of 10 µl (either of the aforementioned bacteria or media) were added into 190 µl nanoparticle working solution (0.02 µg/µL in Ca²⁺/Mg²⁺-free 1× PBS for both the dextran-coated and Con A-conjugated polysaccharide nanosensors). For the dextran-coated polysaccharide nanosensors, 10 µL Con A (Sigma, 1 µg/µl) were added in order to induce nanoparticle clustering.</p>", "<title>Measurement of proton relaxation times</title>", "<p>Spin-spin relaxation times (T2) were measured using a 0.47 T mq20 NMR analyzer (Minispec, Bruker, Germany). T2 values were obtained before and after addition of the aliquot, and through the time course of the study. For the quantification of starch, we prepared serial dilutions of sterile starch-supplemented MH broth (DIFCO™, BD) in sterile non-starch-supplemented MH broth (DIFCO™, BD). Subsequently, the dextran-coated polysaccharide nanosensors' sensitivity and dose response to the analyte (starch) was evaluated, by monitoring the changes in the spin-spin relaxation time. In this case, ΔΤ2 is denoted as the difference between the relaxation time of the solution's initial dispersed state before addition of the MH broth aliquot (T2_in) and the solution's T2 after addition of the MH broth aliquot (T2′). Thus, ΔT2 = |T2′−T2_initial|. For all other measurements, including <italic>E.coli</italic>'s metabolic activity monitoring via carbohydrate quantification and magnetic relaxation-mediated antimicrobial susceptibility assessment, ΔΤ2 is denoted as the difference between the T2 of a sample and the corresponding sterile control sample (ΔΤ2 = |Τ2_sample−T2_control|), where the sterile control was starch-containing MH which is used for the growth of these microorganisms. The sterile control used for the nanoparticle-mediated antimicrobial susceptibility assessment in blood was 5%-blood-supplememted starch-containing MH broth. All experiments and measurements were carried out in triplicate and data were expressed as mean±standard error, unless otherwise denoted. Response curves were obtained by fitting the data on a sigmoidal curve, using Origin 7.5 (OriginLab, Northampton, MA). Statistical analyses were performed on SPSS 11.5 (SPSS Inc., Chicago, IL).</p>", "<title>Broth dilution assay for determination of Minimum Inhibitory Concentration (MIC)</title>", "<p>Broth dilution assay (standard method for measuring MIC) was achieved by inoculating serial dilutions of ampicillin in sterile starch-containing MH broth, with either <italic>E. coli</italic>, <italic>S. marcescens</italic>, or <italic>S. sonnei</italic> (10⁶ CFU), followed by a 24-hour long incubation at 37°C. Bacterial growth was assessed based on the broth's turbidity, where absence of turbidity was an indicator of successful antimicrobial susceptibility. The lowest ampicillin concentration where the MH broth is clear indicates the minimum concentration of ampicillin that can successfully inhibit bacterial growth ##UREF##0##[4]##, ##REF##11420333##[5]##.</p>" ]

[ "<title>Results</title>", "<title>Polysaccharide quantification and bacterial metabolic activity monitoring</title>", "<p>In our first set of experiment, we investigated if our dextran-coated iron oxide nanoparticles (d = ∼150 nm, R2 = 300 mM⁻¹s⁻¹) were responsive to changes in starch concentration upon bacterial growth. Initial studies in phosphate buffered saline showed that the nanosensors quickly clustered after addition of Con A, (##SUPPL##0##Figure S1##) forming stable nanoassemblies that induced prominent changes in the T2 within an hour (##SUPPL##1##Figure S2##). During initial optimization studies, we found that a Con A concentration of 1 µg/µL and a nanoparticle solution with a concentration of 0.02 µg Fe/µL provided optimum results (##SUPPL##2##Figure S3##). Thus, we used this iron concentration in all of our experiments. Lower iron concentrations increased the error in the measurement, whereas higher concentrations sacrificed sensitivity and detection kinetics, requiring higher concentrations of Con A. Next, we assessed the capability of our nanosensors to sense variations in MH broth's starch concentration. In these experiments we added our nanosensors (0.02 µg Fe/µL) to solutions containing increasing amounts of starch in MH broth and Con-A (1 µg/µL). We anticipated that in this competition assay and at low concentrations of starch, the Con A would be able to cluster the dextran-coated magnetic nanosensors resulting in prominent changes in T2. However, as the amount of starch increases, smaller changes in T2 are expected, as Con A would primarily bind to starch. Results showed that after a 30-minute-long incubation at room temperature, a dose-dependent response curve was obtained (<italic>R</italic>\n² = 0.99), demonstrating that the changes in T2 were inversely proportional to the starch concentration, in accordance with our hypothesis (##FIG##1##Figure 2A##). Notably, the dextran-coated polysaccharide nanosensors were able to quantify starch from concentrations of 77.5 ng/µl, which is the initial starch concentration of a typical MH broth, to 1.5 ng/µL.</p>", "<p>We then examined if these polysaccharide nanoprobes can respond to changes in the starch concentration of MH broth (initial starch concentration = 77.5 ng/µl) due to bacterial metabolic activity. In these experiments, magnetic nanoprobe solutions (0.02 µg Fe/µL) containing aliquots of increasing amounts of <italic>E. coli</italic> were incubated with Con A. Results showed that upon addition of Con A, a dose-dependent response was observed (<italic>R</italic>\n² = 0.99), after a 30-minute incubation at room temperature (##FIG##1##Figure 2B##). The higher the bacterial population (expressed in Colony Forming Units, CFU) the larger the changes in T2 (ΔΤ2). This is attributed to the fact that higher bacterial populations utilize more amounts of starch via their metabolic activities, resulting in a concomitant reduction of the media's carbohydrates. As a result, addition of Con A promotes the formation of extensive nanoassemblies, as expected. Notably, even at low bacterial populations (10²–10⁴ CFUs) significant changes in T2 were detected. Hence, this demonstrates the high sensitivity of the nanosensors in detecting bacterial metabolic activity, even in the presence of as few as 10² CFUs. This is of grave importance in order to prevent septicemia, as very few bacteria in circulation may cause systemic infection leading to death. In control experiments we found that in the absence of Con A, the presence of increasing amount of bacteria does not affect the T2 of the nanoparticle solution. Specifically, all samples containing either sterile media or different bacterial loads exhibited similar T2 values, suggesting that the presence of bacteria does not alter the spin-spin relaxation times of the non-assembled state (##SUPPL##3##Figure S4##). To further corroborate our results, we used heat-inactivated bacteria to inhibit their metabolic activity. Consequently, nominal differences were observed between the samples of heat-inactivated bacteria and sterile medium (##SUPPL##4##Figure S5##).</p>", "<title>Antimicrobial susceptibility assessment using dextran-coated magnetic nanosensors</title>", "<p>Based on our dextran-coated magnetic nanosensors' ability to sense carbohydrate utilization due to microbial metabolism, we examined if these nanosensors can be used for the identification of antimicrobial susceptibility and determination of an antibiotic's minimum inhibitory concentration (MIC). As MIC predicts the success of a particular antibiotic and is an important clinical parameter that dictates treatment in order to minimize adverse side effects, such as renal failure, quick determination of MIC is of paramount importance ##REF##11420333##[5]##. Thus, we first examined if the presence of antibiotics in the media might induce non-specific nanoparticle clustering, potentially interfering with the assay's carbohydrate specificity. In these control studies, a bacterial population (10⁶ CFU) which is typically used in MIC experiments was incubated in the presence of different antibiotic concentrations. Results showed that these culture conditions did not affect the spin-spin relaxation times of the nanoparticle solution, indicating absence of non-specific antibiotic-mediated nanoparticle assembly (##SUPPL##5##Figure S6##). Subsequently, we examined if bacterial growth and the corresponding carbohydrate uptake are affected by the presence of a particular antibiotic. After incubating <italic>E. coli</italic> for 2 hours in the presence of ampicillin, we took 10-µL bacterial culture aliquots in order to examine them using the dextran-coated polysaccharide nanosensors. Thirty minutes after addition of Con A distinct changes in the T2 were observed, indicating the presence of two cohorts (##FIG##2##Figure 3A upper panel##). Specifically, the starch utilization and growth of <italic>E. coli</italic> were suppressed at ampicillin concentrations above 8 µg, as demonstrated by the low changes in the ΔΤ2 compared to the sterile medium. Furthermore, the nanoparticle-derived MIC of 8 µg was confirmed through the turbidity method, which is the current gold standard for antimicrobial susceptibility determination (##FIG##2##Figure 3A lower panel##). Although both assays provided identical results, the dextran-coated polysaccharide nanosensor assay yielded faster results with an overall time of 2.5 hours (2 hours for bacterial-antibiotic incubation and 30 minutes for nanoparticle readout), as opposed to 24 hours. In addition, the nanosensor-based assay requires smaller bacterial culture volumes (10 µL) as opposed to the turbidity MIC method (2 mL). The latter is of particular logistics importance during epidemics and drug discovery efforts, as it facilitates the simultaneous and cost-effective screening of multiple samples, eliminating the need of tedious visual examination of numerous cultures.</p>", "<p>Subsequently, we further validated the antimicrobial susceptibility potential of dextran-coated polysaccharide nanosensors using other bacteria. <italic>Shigella sonnie</italic>, a close relative of the highly pathogenic and Shiga-toxin producer <italic>Shigella dysenteriae,</italic> had an ampicillin MIC of 8 µg (##SUPPL##6##Figure S7##). Similar to <italic>E. coli</italic>, these results were also obtained within 2.5 hours. Then, we investigated if our assay can determine bacterial drug resistance via the changes in spin-spin relaxation time. As a model system, we used the hospital-acquired pathogen <italic>Serratia marcescens</italic>\n##REF##16914034##[25]##. This pathogen is resistant to many antibiotics, including ampicillin, due to the presence of resistance plasmids, and is used as a model organism for bacterial drug resistance ##REF##6321357##[26]##, ##REF##7785978##[27]##. Thirty minutes after addition of Con A into the nanoparticle solution, all samples exhibited similar ΔΤ2 values with no statistically significant differences, indicating that this pathogen is not susceptible to ampicillin (##FIG##2##Figure 3B upper panel##). Confirmation of our results was achieved via the turbidity method, where after 24 hours all cultures had a reddish turbid appearance, due to the characteristic production of the pigment prodigiosin by <italic>S. marcescens</italic>\n##REF##12876793##[28]## (##FIG##2##Figure 3B lower panel##).</p>", "<p>Due to the fact that many bacteria can either cause septicemia or require growth in optically turbid media, it is important to assess bacterial susceptibility in these complex matrices. However, most current methods cannot be utilized for the detection of molecular targets and assessment of antimicrobial susceptibility in blood, due to the strong absorbance and scattering from the matrix's constituents, including platelets and red blood cells (##SUPPL##7##Figures S8## and ##SUPPL##8##S9##). Therefore, considering these drawbacks and the facts that bacterial isolation is a major limitation step in diagnosis and that certain pathogenic microorganisms require growth in specialized media, we investigated if the dextran-coated polysaccharide nanosensors can assess antimicrobial susceptibility in blood. Recently, we reported the high-throughput bacterial susceptibility determination, using the surface plasmon band shifts of gold nanoparticles ##REF##18198893##[12]##. However, this method cannot be used in opaque media, such as blood, due to the matrix's intrinsic optical properties, masking the nanoparticles' plasmonic band (##SUPPL##7##Figure S8##). To investigate this, we used <italic>E. coli</italic> and <italic>S. marcescens</italic> cultures in blood-supplemented MH broth, grown in the presence of ampicillin for 2 hours at 37°C. Aliquots of these cultures (10 µL) were obtained and added into the dextran-coated polysaccharide nanosensors working solution, followed by 10-µL Con A treatment (1 µg/µL). After 45 minutes post-Con A addition at room temperature, we determined that <italic>E. coli</italic>'s ampicillin MIC was 8 µg (##FIG##3##Figure 4A##), without observing any nanoparticle precipitation (##SUPPL##9##Figure S10##). Additionally, the <italic>S. marcescens</italic>' drug resistance was identified after an hour-long incubation at 25°C (##FIG##3##Figure 4B##).</p>", "<title>Antimicrobial susceptibility assessment using Concanavalin A-conjugated polysaccharide nanosensors</title>", "<p>Often times a slight modification in the nanosensors' design and/or the protocol followed can result in significant improvements in either the sensitivity or speed of the assay ##REF##17461429##[29]##, ##REF##18205426##[30]##. Therefore, we hypothesized whether conjugating Con A to the surface of the magnetic nanoparticles would allow for faster kinetics and shorter the detection time. For these experiments, we conjugated Con A directly to aminated silica-coated iron oxide nanoparticles. We chose silica-coated instead of dextran-coated iron oxide nanoparticles to avoid possible cross reaction with the dextran on the nanoparticle's surface. In this non-competition assay (##FIG##4##Figure 5##), the Con A-conjugated silica coated nanosensors would facilitate the direct sensing of the levels of carbohydrates in solution, as opposed to the competition assay that requires two reagents; the dextran-coated nanoparticles and the Con A for successful sensing. The aminated silica-coated nanoparticles were synthesized using a modified water-based synthetic protocol ##UREF##2##[31]##. The resulting nanoparticles were monodispersed, having a diameter of 145 nm (##SUPPL##10##Figure S11A##) and an R2 relaxivity of 225 mM⁻¹s⁻¹.</p>", "<p>In our first set of experiments with the aminated silica-coated nanoparticles, we determined whether these nanoparticles clustered non-specifically in the presence of Con A in solution. As expected, we observed that Con A did not induce any changes in the relaxation times of the nanoparticles (##SUPPL##11##Figure S12##). This demonstrates that the silica coating on these nanoparticles lacks any carbohydrate epitopes, rendering them suitable for the non-competition-based sensing of carbohydrates. Therefore, we conjugated Con A to the aminated silica-coated nanoparticles, via carbodiimide chemistry, resulting in Con A-carrying nanoparticles with a hydrodynamic diameter of ∼160 nm (##SUPPL##10##Figure S11B##) (R2 = 225 mM⁻¹s⁻¹, [Con A] = 0.03 µg/µL). First, we compared the kinetic profiles of the dextran-coated nanosensors and Con A-conjugated nanosensors using bacterial <italic>E. coli</italic> blood cultures (10⁶ CFU grown in the presence of 2 µg ampicillin). Interestingly, we found that the non-competition assay with the Con A-conjugated nanosensors (##FIG##5##Figure 6, curve B##) provided faster results than the competition assay that utilizes the dextran-coated nanosensors (##FIG##5##Figure 6, curve A##). Specifically, the competition assay format reached its end-point after a 45-minute incubation, whereas the non-competition assay reaches its end-point within 5 minutes upon addition of the bacterial sample. These findings support our hypothesis of achieving faster kinetics due to the direct conjugation of Con A to the nanoparticles.</p>", "<p>Then, we examined if MIC determination can be achieved using these Con A-conjugated nanosensors, in blood cultures of <italic>E. coli</italic> and <italic>S. marcescens</italic>. Immediately upon addition of the bacterial sample into the nanoparticle solution, distinct changes in the T2 were observed. Specifically, within 5 minutes the Con A-nanosensors were able to determine that <italic>E. coli</italic> had an ampicillin MIC of 8 µg (##FIG##6##Figure 7A##), in line with the data from the dextran-coated nanosensors in the competition assay or the turbidity test. Likewise, within 5 minutes the Con A-conjugated nanosensors assessed that <italic>S. marcescens</italic> was resistant to ampicillin, further corroborating the findings that the non-competition assay format provides faster results than the competition-based assay of the dextran-coated nanosensors (##FIG##6##Figure 7B##).</p>" ]

[ "<title>Discussion</title>", "<p>Concluding, we have shown that superparamagnetic iron oxide nanoparticles, either dextran-coated supplemented with Con A or Con A-conjugated nanosensors, can be used for the quantification of polysaccharides, assessment of metabolic activity and determination of antimicrobial susceptibility in complex matrices, such as blood, through magnetic relaxation. This approach outperforms optical-based assays, which cannot be utilized in opaque media. Additionally, both iron oxide nanoparticle assay formats require very small sample volumes, are equally reliable to gold standard methods, and do not require any sample preparation, in contrast to other techniques ##REF##18181646##[32]##. Notably though, the Con A-conjugated polysaccharide nanosensor assay yields faster results, without compromising sensitivity and reliability, due to faster binding kinetics. Also, as there is no need for the addition of a second reagent (Con A), this format might be particularly useful for point-of-care diagnostics and applications in the field. Furthermore, the iron oxide nanoprobes can be easily adapted for the high-throughput screening of multiple clinical and environmental samples, preventing epidemics and promoting drug discovery. In view of the recent advancements in NMR technology ##REF##17897853##[33]##, ##REF##15817815##[34]##, ##REF##18217773##[35]##, the high-throughput and/or field analysis of multiple samples in complex media should be feasible, even outside of the typical laboratory setting. Overall, we believe that these assays can expedite clinical decision-making and may facilitate the faster discovery of potential antimicrobial agents. Further studies are in progress to determine microbial susceptibility to antifungal and antibacterial agents in clinical samples and other matrices.</p>" ]

[]

[ "<p>Conceived and designed the experiments: JMP. Performed the experiments: CK SN. Analyzed the data: CK SN JMP. Wrote the paper: CK SN JMP.</p>", "<p>Considering the increased incidence of bacterial infections and the emergence of multidrug resistant bacteria at the global level, we designed superparamagnetic iron oxide nanoparticles as nanosensors for the assessment of antimicrobial susceptibility through magnetic relaxation. In this report, we demonstrate that iron oxide nanosensors, either dextran-coated supplemented with Con A or silica-coated conjugated directly to Con A, can be used for the fast (1) quantification of polysaccharides, (2) assessment of metabolic activity and (3) determination of antimicrobial susceptibility in blood. The use of these polysaccharide nanosensors in the determination of antimicrobial susceptibility in the clinic or the field, and the utilization of these nanoprobes in pharmaceutical R&amp;D are anticipated.</p>" ]

[ "<title>Supporting Information</title>" ]

[ "<p>The authors thank Alisa Tinkham and Israth Abdulsamad for culturing the various microorganisms.</p>" ]

[ "<fig id=\"pone-0003253-g001\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g001</object-id><label>Figure 1</label><caption><title>Proposed model for the assessment of antimicrobial susceptibility using dextran-coated polysaccharide nanosensors and Concanavalin A (ConA).</title><p>In this competition assay, the dextran on the surface of the iron oxide nanoparticles and the starch in solution compete for binding to Con A. This results in changes in the degree of Con-A induced magnetic nanoparticle clustering upon bacterial metabolic uptake of starch.</p></caption></fig>", "<fig id=\"pone-0003253-g002\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g002</object-id><label>Figure 2</label><caption><title>Nanoparticle-mediated sensing of polysaccharide levels and monitoring of bacterial metabolic activity.</title><p>(A) Quantification of starch in sterile MH broth, and (B) determination of starch consumption due to bacterial metabolism in MH broth, using the dextran-coated polysaccharide nanosensors.</p></caption></fig>", "<fig id=\"pone-0003253-g003\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g003</object-id><label>Figure 3</label><caption><title>Antimicrobial susceptibility screening in MH broth with dextran-coated polysaccharide nanosensors.</title><p>(A) Determination of <italic>E. coli</italic>'s minimum inhibitory concentration in MH broth, using the changes in spin-spin relaxation times (ΔT2, upper panel) (Means±SE; p&lt;0.05) and the turbidity method (lower panel). (B) Identification of <italic>S. marcescens</italic>' resistance to ampicillin via ΔΤ2 (upper panel, Means±SE) and the turbidity assay (lower panel). The corresponding amount of ampicillin is indicated in the graphs and pictures of the bacterial cultures.</p></caption></fig>", "<fig id=\"pone-0003253-g004\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g004</object-id><label>Figure 4</label><caption><title>Dextran-coated polysaccharide nanosensor-mediated determination antimicrobial susceptibility in blood.</title><p>(A) Assessment of <italic>E. coli</italic>'s ampicillin MIC, and (B) identification of <italic>S. marcescens'</italic> ampicillin resistance in blood (Means±SE; p&lt;0.05).</p></caption></fig>", "<fig id=\"pone-0003253-g005\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g005</object-id><label>Figure 5</label><caption><title>Schematic representation of the assessment of antimicrobial susceptibility using Concanavalin A-conjugated polysaccharide nanosensors.</title><p>The use of silica-coated nanoparticles and the direct conjugation of Con A to the capping matrix result in a non-competition-based assay format, which may potentially provide faster readout times.</p></caption></fig>", "<fig id=\"pone-0003253-g006\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g006</object-id><label>Figure 6</label><caption><title>Kinetic profiles of the competition and non-competition assay formats.</title><p>Point A represents the end-point of the competition assay utilizing the dextran-coated polysaccharide nanosensors, whereas Point B corresponds to the end-point of the non-competition assay based on the Con A-conjugated polysaccharide nanosensors.</p></caption></fig>", "<fig id=\"pone-0003253-g007\" position=\"float\"><object-id pub-id-type=\"doi\">10.1371/journal.pone.0003253.g007</object-id><label>Figure 7</label><caption><title>Antimicrobial susceptibility in blood using Con A-conjugated polysaccharide nanosensors.</title><p>(A) Determination of <italic>E. coli</italic>'s ampicillin MIC in blood, and (B) determination of <italic>Serratia marcescens</italic>' drug resistance in blood with the Con A-conjugated polysaccharide nanosensors, five minutes after addition of the bacterial aliquot into the nanoparticle solution (Means±SE; p&lt;0.05).</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s001\"><label>Figure S1</label><caption><p>Size distribution of dextran-coated polysaccharide nanosensors <bold>(A)</bold> before addition of Con A, and <bold>(B)</bold> one hour after Con A addition (1 µg/µl), indicating the formation of nanoparticle clusters.</p><p>(0.30 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s002\"><label>Figure S2</label><caption><p>Treatment with 10 µl of Con A (1 µg/µl) facilitates the clustering of dextran-coated iron oxide nanoparticles, resulting in prominent changes in the solution's spin-spin relaxation time (T2).</p><p>(0.24 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s003\"><label>Figure S3</label><caption><p>Standard curve for determination of Con A's optimum concentration using a nanoparticle solution with a concentration of 0.02 µg Fe/µl.</p><p>(0.24 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s004\"><label>Figure S4</label><caption><p>In the absence of ConA, the IO NPs were in a non-assembled state, exhibiting the same T2 regardless of the presence of bacteria, after a 30-minute incubation. <bold>1</bold>. Water, <bold>2</bold>. Sterile medium (with starch), <bold>3</bold>. Sterile medium (no starch), <bold>4</bold>. 10² CFU <italic>E. coli</italic>, <bold>5</bold>. 10³ CFU <italic>E. coli</italic>, <bold>6</bold>. 10⁴ CFU <italic>E. coli</italic>, <bold>7</bold>. 10⁵ CFU <italic>E. coli</italic>, <bold>8</bold>. 10⁶ CFU <italic>E. coli</italic>, <bold>9</bold>. 10⁸ CFU <italic>E. coli</italic>, <bold>10</bold>. 10⁹ CFU <italic>E. coli.</italic>\n</p><p>(0.29 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s005\"><label>Figure S5</label><caption><p>The behavior of IO NPs is independent of the heat-inactivated bacterial population, but it is dependent of active bacterial metabolism. The graph depicts data obtained after a 30-minute incubation at room temperature, in the presence of Con A. Linear fit was applied with an R² = 0.14 (OriginPro 7.5). Similar results were obtained after 0-, 90- and 150-minute incubations.</p><p>(0.25 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s006\"><label>Figure S6</label><caption><p>In the absence of ConA, the IO NPs exhibited the same T2, regardless of the presence of bacteria and antibiotic. <bold>1</bold>. Water, <bold>2</bold>. Sterile medium (with starch), <bold>3</bold>. Sterile medium (no starch), <bold>4</bold>. 64 µg ampicillin, <bold>5</bold>. 8 µg ampicillin, <bold>6</bold>. 2 µg ampicillin, <bold>7</bold>. 1 µg ampicillin, <bold>8</bold>. 0 µg ampicillin.</p><p>(0.28 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s007\"><label>Figure S7</label><caption><p>Determination of the minimum inhibitory concentration of <italic>Shigella sonnie</italic> using the changes in spin-spin relaxation times (ΔT2) after a 30-min incubation at 25° (Means ± SE; p &lt;0.05). The dotted line indicates the threshold of the drug's successful inhibition.</p><p>(0.41 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s008\"><label>Figure S8</label><caption><p>UV-vis profile of a bacterial culture growing in 5%-blood-supplemented MH broth. <italic>E. coli</italic> (10⁶ CFU) were incubated for 2 hours at 37° in the presence of 4 µg ampicillin, in 5%-blood-supplemented starch-containing MH broth. Then, a 50-µl bacterial culture aliquot was diluted in 950 µl 1× PBS (Ca²⁺/Mg²⁺-free), resulting in similar to the relaxation setup bacterial aliquot dilution. The strong absorbance of blood in the visible spectrum suggests that optical-based methods spanning from 400 to 800 nm may not be effective for MIC determination in this matrix.</p><p>(0.25 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s009\"><label>Figure S9</label><caption><p>Size distribution of <bold>(A)</bold> dextran-coated gold nanoparticles and <bold>(B)</bold> 5%-blood-supplemented MH broth, indicating that the clustering of dextran-coated gold nanoparticles cannot be used for antimicrobial susceptibility assessment in blood.</p><p>(0.30 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s010\"><label>Figure S10</label><caption><p>Blood cultures in nanoparticle solution demonstrating the absence of nanoparticle precipitation and the optical nature of the solution (numbers indicate the corresponding concentration of ampicillin in µg).</p><p>(0.36 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s011\"><label>Figure S11</label><caption><p>Size distribution of silica-IO nanoparticles <bold>(A)</bold> prior and <bold>(B)</bold> after Con A conjugation.</p><p>(0.29 MB TIF)</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"pone.0003253.s012\"><label>Figure S12</label><caption><p>Absence of Con A-induced clustering in silica-coated IO nanoparticles, indicating the lack of carbohydrate-containing moieties on the nanoparticles' surface.</p><p>(0.29 MB TIF)</p></caption></supplementary-material>" ]

[ "<fn-group><fn fn-type=\"COI-statement\"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding: </bold>The study was partially funded by a UCF NSTC Startup Fund and the NIH CA101781 grant, both awarded to Dr. J. Manuel Perez. Besides funding this work, the sponsors did not have any role in designing or conducting these studies.</p></fn></fn-group>" ]

[ "<graphic xlink:href=\"pone.0003253.g001\"/>", "<graphic xlink:href=\"pone.0003253.g002\"/>", "<graphic xlink:href=\"pone.0003253.g003\"/>", "<graphic xlink:href=\"pone.0003253.g004\"/>", "<graphic xlink:href=\"pone.0003253.g005\"/>", "<graphic xlink:href=\"pone.0003253.g006\"/>", "<graphic xlink:href=\"pone.0003253.g007\"/>" ]

[ "<media xlink:href=\"pone.0003253.s001.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s002.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s003.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s004.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s005.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s006.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s007.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s008.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s009.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s010.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s011.tif\"><caption><p>Click here for additional data file.</p></caption></media>", "<media xlink:href=\"pone.0003253.s012.tif\"><caption><p>Click here for additional data file.</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<title>Importance of interim analyses</title>", "<p>The simplest approach for evaluating results of a clinical trial is to plan just one statistical analysis at the end of the study, using a fixed-sample size design: planning and conduction are easy, and the methods for estimation are well established. This approach, which is convenient and effective when all observations are available in a short period of time, is less appropriate when data become available sequentially. This is the case in studies on chronic diseases, like cancer, in which recruitment may last many years, so that the first outcomes can be observed when the accrual is still ongoing. In such situations there might be ethical, practical and economic reasons for looking at the data before the planned end of the study.</p>", "<p>Data monitoring conducted during a continuing study may focus on performance, data integrity, safety and treatment effect. The assessment of study performance in terms of quality of data, protocol adherence, recruitment rate, is normally performed periodically in an informal way, adopting modalities that can be grouped under the definition of \"internal monitoring\". In contrast, the tasks of \"external monitoring\" are to evaluate data integrity, safety and efficacy of treatments and to provide advice on continuing the study as originally planned, or suggesting changes in its conduct, or even on stopping it. This advice is mainly based on trial results, but should take into account the context of information external to the trial available at the moment of the analysis[##REF##1876782##1##].</p>", "<p>This process of \"interim analysis\" is usually conducted by a data and safety monitoring committee (DSMC), usually composed by an independent group of experts in the involved fields (biostatistician, clinical researcher, epidemiologist, clinician with expertise in the disease under investigation) [##REF##1876782##1##,##UREF##0##2##].</p>", "<p>Formal interim analysis offers several advantages, since this approach makes the process of acquiring and disseminating results more efficient and a beneficial treatment can be made available sooner. Ethical reasons play also a role in the decision to stop a trial, since there is a responsibility to minimize the number of subjects treated with an unsafe, ineffective or clearly inferior treatment. On the other hand, conducting an interim analysis may also have drawbacks, since immature results on small numbers of patients will provide imprecise or even biased point and interval estimates of the treatment effect, increasing the error in inferential process [##REF##3231947##3##]: when a clinical trial is closed because a treatment difference has been detected, the estimate of the magnitude of that difference will overstate the \"true\" value [##UREF##1##4##]. Finally, trials stopped early are likely to be of small size, and as a consequence their results may lack both statistical precision and credibility, since medical community might remain sceptical, even in case of highly significant results. Therefore, while informal reviews are necessary, the process of repeatedly evaluating data must be done with caution, especially early in the course of a trial when the number of both participants and events related to safety and efficacy are relatively small [##REF##14980749##5##]. For these reasons some investigators strongly recommend that the results of such trials should be treated with scepticism [##REF##16264162##6##].</p>", "<p>From the statistical viewpoint, monitoring methods can be classified according to whether the method is frequentist or Bayesian [##REF##7973217##7##] and comprehensive reviews of statistical aspects of monitoring can be found in Whitehead [##UREF##2##8##], Jennison and Turnbull [##UREF##3##9##] and Piantadosi [##UREF##4##10##]. However, regardless of the specific method used, a key issue is that statistical rules are only a part of the question, as they tend to oversimplify the information relevant to the decision that must be taken. The decision to stop a trial before the prespecified final analysis should not be guided only by statistical considerations, but also by practical issues (toxicity, ease of administration, costs, etc.), as well as clinical considerations. For this reason it is preferable to refer to statistical methods as guidelines, rather than rules [##REF##7973210##11##]. Despite these statistical and ethical implications of conducting an interim analysis, information on explicit adoption of planned monitoring is still scarce, basically driven by the published reports of studies, which rarely include details on the strategies for data monitoring and interim analysis. It seemed therefore of interest to investigate the forms of monitoring and interim analysis used in randomised clinical trials in cancer in order to gather information of the quality of research protocols activated in Italy on cancer patients.</p>" ]

[ "<title>Methods</title>", "<p>We assessed protocols available in the OsSC database [##REF##15145650##12##] [see additional file ##SUPPL##0##1##] relative to oncological studies submitted to Italian ECs from January 1st 2000 to May 2005 and evaluated and accepted by the coordinating centre by the end of October, 2005. We restricted the evaluation to protocols of randomised studies with a time to event endpoint, such as overall survival (OS) or progression free survival (PFS). A template data extraction form was developed and tested in a pilot phase. Selection of relevant protocols and data extraction were performed independently by two evaluators, with differences in the data assessment resolved by consensus with a third reviewer, referring back to the original protocol.</p>", "<p>Information was obtained on a) general characteristics of the protocol (identification number, experimental phase, year of EC opinion release, type of sponsor, involved countries, study objective; b) disease localization and patient setting; c) study design (aim of the study, primary endpoint, number of arms, expected number of events to observe and of patients to randomise, planned number of centres involved in the trial, duration of the study, as well as of the accrual and follow-up periods); d) interim analyses, if present (number, type, objective, timing); e) DSMC, if planned (composition and tasks).</p>", "<p>Results were reported using adequate descriptive statistics, such as absolute and relative frequencies for categorical variables and median (interquartile range) for continuous variables, unless otherwise specified.</p>", "<p>The association between the use of interim analyses and/or DSMC and potential determinants, such as type of sponsor, involved countries, year of submission, experimental phase and total duration of the study was estimated by a logistic regression model. Results are reported as odds ratios (ORs) and their 95% confidence intervals (95% CIs).</p>", "<p>Analyses were performed using SAS (Statistical Analysis System, SAS Institute Inc., Cary, NC, US, Version 8.20) software.</p>" ]

[ "<title>Results</title>", "<p>Seven hundreds ninety-six cancer protocols were identified and manually checked in order to locate the eligible trials.</p>", "<p>Figure 1 reports the flow diagram of the selection of relevant protocols [see additional file ##SUPPL##1##2##]. From 796 oncological studies found, only 150 (18.8%) were eligible and evaluable for analysis, while the others were excluded for the reasons described in the diagram.</p>", "<p>Table 1 describes the characteristics of evaluated trials [see additional file ##SUPPL##2##3##].: the majority of the protocols included in this project are international (102, 68.0%), and conducted on solid tumours (129, 86.0%). The more frequently investigated diseases are lung (36, 24.0%) and breast cancers (35, 23.3%). 107 out of 129 (83.0%) of the protocols on solid tumours were conducted in the setting of advanced disease (data not shown). The great majority (138, 92.0%) of the studies were aimed at detecting a difference in efficacy between arms, and the primary endpoint was overall survival in 64 cases (42.7%). The planned median number of patients to randomise and of events to observe was 520 (25°–75° percentiles: 300–820) and 384 (25°–75° percentiles: 218–616), respectively. The expected proportion of events at the end of the study, a good index of patient prognosis, calculated as the ratio of these two latter variables, had a median value of 0.69 (25°–75° percentiles: 0.47–0.78). The median study duration was 42.5 months (25°–75° percentiles: 29–60), given by a median accrual period of 24 months (25°–75° percentiles: 18–36) and a subsequent follow-up of 18 (25°–75° percentiles: 12–30). The median number of experimental centres was 70 (25°–75° percentiles: 35–120), but this information is reported only in 65 protocols.</p>", "<p>Table 2 shows the presence of interim analyses and/or of a DSMC [see additional file ##SUPPL##3##4##]. 106 (70.7%) protocols planned some form of monitoring, for example on safety, protocol compliance or recruitment rate. When focusing on formal efficacy analysis, this number decreases to 86 (66.2%), because in 20 cases the only checks concerned matters such as safety, feasibility and recruitment rate. The establishment of a DSMC was reported in 98 (65.3%) cases: 84 (56.0%) with a planned interim analysis and 14 (14.7%) in which an interim analysis was not planned. Overall neither form of monitoring took place in 30 out of 150 protocols (20.0%). The median number of interim analyses was 2, ranging from 1 to 9. Among the 86 protocols with an efficacy analysis, 34 (39.5%) planned only 1 interim analysis, 32 (37.2%) 2 interim analysis, 10 (11.6%) 3 interim analysis; and 10 (11.6%) more than 3 analyses,</p>", "<p>Table 3 shows the main characteristics of the interim efficacy analyses [see additional file ##SUPPL##4##5##]. Of note, among the 86 protocols with an efficacy analysis, in 2 cases the endpoint was not reported, while in 6 (7.0%) it was related to activity, and therefore different from that of the final analysis.</p>", "<p>The timing of interim analyses for efficacy was planned according to the proportion of observed events (for example for 2 analyses, the first when 33% of the planned total number of events had been observed and the second at 66%) in 54 (62.8%) protocols, according to the proportion of patients (for example again for 2 analyses after the enrolment of 33% and 66% of the planned total number of patients) in 22 (25.6%) protocols and based on calendar time (for example yearly after the first two years of recruitment) in the remaining 10 (11.6%) cases.</p>", "<p>The most frequent type of statistical approach for the analysis was the frequentist method, using the O'Brien and Fleming boundaries: alone in 45 out of 86 (52.3%) studies or together with conditional power in 6 (7.0%). Conditional power alone was used in 6 studies, while a Bayesian approach was used in only one study. In 5 protocols the statistical monitoring method, and therefore the stopping rules, was not specified.</p>", "<p>Criteria for stopping were reported in 77 (89.5%) of the protocols, mostly represented by the achievement of a significant difference between arms (52, 60.5%). It is of note that in 2 studies, no mention was made of either the statistical approach or the stopping rules to be adopted.</p>", "<p>In 24 (24.5%) out of 98 protocols, the only commitment of DSMC was safety. Efficacy was considered in 68 protocols (69.4%). In one study it was the only task of DSMC, while in the remaining 67 the DSMC was in charge of monitoring both safety and efficacy. The composition and frequency of DSMC meetings are reported only in 34 (34.7%) and 40 (40.8%) protocols, respectively. The DSMC was stated to be independent in 80 (81.6%) of the protocols. The committee usually consisted of 3 or 4 members, always including a statistician, In 8 cases sponsor representatives could participate as non voting-member. The frequency of the meetings was generally twice a year.</p>", "<p>Table 4 shows the results of univariate and multivariate logistic models, assessing the association among selected characteristics of the study protocols and the presence of both interim analysis and DSMC [see additional file ##SUPPL##5##6##]. In both models, the only variable associated with the presence of an interim analysis was the international organization of the study, accounting for an odds ratio of 3.72 (95% CI 1.70–8.13) and of 4.75 (95% CI 1.38–16.4), respectively. The most important factors associated with the presence of DSMC are a commercial sponsor (OR 4.37, 95% CI 1.38–13.9) and international collaboration (OR 10.9, 95% CI 3.06–38.6).</p>" ]

[ "<title>Discussion</title>", "<p>This project was aimed at assessing the prevalence of interim analyses and DSMC in randomised clinical trials in cancer, using as source the database including all phase II-III trials submitted to Italian ECs from January 2000 to May 2005. The Italian registry of clinical trials gave an unique opportunity to obtain this information and allowed a critical appraisal of the statistical designs utilized in current cancer clinical trials in Italy.</p>", "<p>The reason for choosing a protocol registry rather than literature data, stems from the observation that in published papers the quality of details relative to the description of statistical methods is often scarce, and it is possible that, despite the accuracy of such a search strategy, the information regarding the approaches adopted for monitoring clinical trials is not completely or accurately captured. Moreover, even when reported, statistical analysis of cancer published trials usually concerns protocols designed years before the study publication and, as a consequence, data derived from even the most recent published literature may not be completely appropriate to represent the currents trend of interim analysis and DSMC use. Finally, since Italian registry includes several international protocols, it may also be considered an important source of information generalizable also to ongoing researches in European countries.</p>", "<p>The most important conclusion arising from this study is that at present around 30% of the protocols do not incorporate any form of interim analysis plan, and only 56% of protocols can be considered adequately planned for monitoring the trial. Although this result suggests an increasing use of monitoring tools with respect to the past, it is still not completely satisfactory. Despite the availability of several statistical methods for interim analysis, the almost uniquely approach is the frequentist method while the Bayesian approach is rarely considered, although in the context of monitoring it would be more useful for its characteristics of flexibility in incorporating external evidence.</p>", "<p>Interim analysis plans are still described very infrequently, even in the more recent protocols, denoting insufficient attention to this issue not only by the researchers, but also by ethical committees who have a responsibility to consider the ethical and scientific aspects of the submitted studies. In this context there is a discrepancy between the perceived importance of data monitoring boards and their presence (65.3% of the protocols) and the lack of information regarding their composition and their role. It is encouraging that the timing of interim analysis was usually related to the number of events and almost half of the trials adopted no more than one planned interim analysis, thus reducing the risk of biased estimation.</p>", "<p>Interim analyses play a fundamental role in the balance between the need of timely information regarding the treatment effect and the control of false positive errors and estimation bias. Moreover, the adoption of a statistical approach for data monitoring, no matter of which type is chosen, effectively protects the study from the risk of incorrect early stopping. If no stopping rule is adopted, the probability of early stopping with a higher estimation is noticeably increased [##REF##14980749##5##,##REF##2605969##13##].</p>", "<p>Stabilization of the estimates happens when a substantial amount of events have occurred. The finding that estimation bias tends to be reduced, as expected, when the observed number of events is closer to the planned size, is particularly important for cancer clinical trials for non-statistical reasons. With time to event endpoints, a potential problem with stopping a trial early is that the early survival experience with short follow-up may not accurately reflect the complete experience with time. A new treatment may be very toxic, leading to a few early deaths, but may also have much better long-term results than the standard treatment. Overall, the new treatment may be viewed as better than the standard, but an early look at the data may suggest stopping for lack of efficacy. The opposite is also possible, since early suggestions of treatment efficacy may decline over time.</p>", "<p>Another factor that should be considered is the scientific and ethical relationship that links the decision of stopping a trial early with its implication for ongoing trials, addressing the same clinical question, or when a confirmatory trial is planned. These issues were well quantified by a systematic review of Montori et al.⁶, analysing 143 randomised clinical trials (RCTs) stopped early for benefit, and generally published in high-impact medical journals and were industry-funded drug trials. The proportion of all RCTs published that were stopped early for benefit increased from 0.5% in 1990–1994 to 1.2% in 2000–2004. On average, RCTs recruited only 63% of the planned sample and stopped after a median of 13 months of follow-up, 1 interim analysis, and when a median of only 66 patients had experienced the end point driving study termination (event). The median risk ratio among truncated RCTs was high: 0.53 (25°–75° percentiles: 0.28–0.66). One hundred thirty-five (94%) of the 143 RCTs did not report at least 1 of the following: the planned sample size the interim analysis after which the trial was stopped, whether a stopping rule informed the decision, or an adjusted analysis accounting for interim monitoring and truncation (n = 129).</p>" ]

[ "<title>Conclusion</title>", "<p>Our results add important information relative to the methodological quality of clinical studies. Research conducted so far took into consideration only published report and achieved qualitatively similar findings. The DAMOCLES working party²addressed several different issues, using different methodological approaches: systematic literature reviews of DSMC, small group processes in decision-making; sample surveys of reports of RCTs, recently completed and still ongoing RCTs and policies of major organisations involved in RCTs; case studies of selected DSMCs; and interviews with experienced DSMC members. The results of these studies indicated that only about a quarter of main RCT reports mention use of a DSMC and wide variation exists in the structure and organisation of DSMCs, with little guidance on how they should operate. Our research suggests that there is an increased proportion of studies reporting use of DSMC, but is qualitatively in agreement with these conclusions. The study clearly indicates that much has still to be done in making trialists aware of the statistical analyses that should be implemented, of the impact of results of interim analyses on the final decision to be taken, and of the role of DSMC. Our findings may be also be of help in the identification of the questions to be addressed by further research for improving organisation and conduction of clinical trials. In this sense, the survey of Italian protocols seems of particular interest. Although we are aware that the results may be valid for the Italian research context and not totally generalisable to other countries, we think that this enquiry represents a good basis for debating the issues on how to improve monitoring of clinical trials. It also emphasises the importance of the adoption of national registries and encourages the replication of this kind of research in other countries were national registries of clinical trials are available.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Although interim analysis approaches in clinical trials are widely known, information on current practice of planned monitoring is still scarce. Reports of studies rarely include details on the strategies for both data monitoring and interim analysis. The aim of this project is to investigate the forms of monitoring used in cancer clinical trials and in particular to gather information on the role of interim analyses in the data monitoring process of a clinical trial. This study focused on the prevalence of different types of interim analyses and data monitoring in cancer clinical trials.</p>", "<title>Methods</title>", "<p>Source of investigation were the protocols of cancer clinical trials included in the Italian registry of clinical trials from 2000 to 2005. Evaluation was restricted to protocols of randomised studies with a time to event endpoint, such as overall survival (OS) or progression free survival (PFS). A template data extraction form was developed and tested in a pilot phase. Selection of relevant protocols and data extraction were performed independently by two evaluators, with differences in the data assessment resolved by consensus with a third reviewer, referring back to the original protocol. Information was obtained on a) general characteristics of the protocol b) disease localization and patient setting; c) study design d) interim analyses; e) DSMC.</p>", "<title>Results</title>", "<p>The analysis of the collected protocols reveals that 70.7% of the protocols incorporate statistical interim analysis plans, but only 56% have also a DSMC and be considered adequately planned. The most concerning cases are related to lack of any form of monitoring (20.0% of the protocols), and the planning of interim analysis, without DSMC (14.7%).</p>", "<title>Conclusion</title>", "<p>The results indicate that there is still insufficient attention paid to the implementation of interim analysis.</p>" ]

[ "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We are very grateful to Professor Robert Souhami for his suggestions that greatly improved the manuscript.</p>" ]

[]

[]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Box: The \"Osservatorio Nazionale sulla Sperimentazione Clinica dei Farmaci\". The Box reports details on Osservatorio</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Figure 1 – Search flow diagram. The figure shows the reasons for protocols selection</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Table 1 – Description of 150 evaluable trials. The table gives information on selected characteristics of evaluable trials</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>Table 2 – Presence of interim analyses and of a DSMC (n = 150). The table provides details on presence of interim analysis and DSMC</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>Table 3 – Characteristics of the interim efficacy analyses (n = 86). The table provides details on characteristics of interim analysis</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p>Table 4 – Relationship among presence of interim analysis/DSMC and selected protocol. characteristics – Odds Ratios (95% Wald Confidence Intervals) at multivariate analysis. The table provides details on logistic analysis for evaluating the association of selected protocol characteristics and presence of interim analysis plan and DSMC.</p></caption></supplementary-material>" ]

[]

[]

[ "<media xlink:href=\"1745-6215-9-46-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1745-6215-9-46-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1745-6215-9-46-S3.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1745-6215-9-46-S4.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1745-6215-9-46-S5.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1745-6215-9-46-S6.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Ultrasound (US) has been used to enhance thrombolytic therapy, for example, in the treatment of stroke. In this setting, US is usually applied over the temporal bone, exposing the obstructed vessel to US concomitantly with treatment with thrombolytic drugs [##REF##15548777##1##, ####REF##12849182##2##, ##REF##12783427##3####12783427##3##]. The enhancement of various thrombolytic drugs has been demonstrated during <italic>in vitro </italic>clot lysis at frequencies, ranging from 20 kHz to 4.5 MHz [##REF##15925878##4##, ####REF##12624644##5##, ##REF##15588966##6##, ##REF##15936499##7####15936499##7##]. Positive effects on clinical outcome have been reported when high frequency US has been used <italic>in vivo </italic>[##REF##15548777##1##,##REF##11823681##8##]. However, in the CLOTBUST trial, the effects were found not to be statistically significant [##REF##15548777##1##]. This is in contrast to the results from <italic>in vitro </italic>studies of US-enhanced thrombolysis, where considerable enhancement effects of the clot lysis have been shown as a result of exposure to US [##REF##15936499##7##,##REF##17854867##9##,##REF##16493016##10##]. This discrepancy might be explained by the attenuation of US intensity passing through the temporal bone structure during high frequency US exposure, although direct comparison between <italic>in vitro </italic>and <italic>in vivo </italic>results should be made carefully one possible explanation for the different levels seen could be attenuation induced by the skull bone. There have been reports of decreases in the output intensity between 86.8% and 99.2% when US is applied over the temporal bone [##REF##15591211##11##,##REF##17894619##12##]. Low frequency US on the other hand, has greater penetration through bone tissue compared to high frequency US, which results in higher US intensities reaching the obstructed vessel [##REF##10320316##13##,##REF##11839413##14##]. However, low frequency US has been shown to induce a higher rate of bleeding complications during US-enhanced thrombolysis <italic>in vivo </italic>[##REF##15947262##15##].</p>", "<p>Other factors of US than intensity and frequency also seem to affect the results during US-enhanced thrombolysis. We have previously only found, during pulsed-wave US SK induced clot lysis, enhanced effects at low intensity (0.5 W/cm²) [##REF##8571471##16##,##REF##15993473##17##]. During pulsed-wave US exposure of r-PA induced clot lysis, enhancement effects occur both at high and low intensities (i.e. ≤ 0.25 W/cm²or &gt; 2.0 W/cm²) [##REF##16479192##18##]. The enhancement effects might thus depend on duty cycle, i.e. the number of pulses sent [##REF##17854867##9##,##REF##7660413##19##,##REF##17337113##20##]. Meunier et al reported increasing effects on tissue type plasminogen activators mediated clot lysis depending on increasing duty cycle [##REF##17337113##20##]. However, Holland et al failed to verify the same duty cycle dependency [##REF##17854867##9##]. Others have shown higher grades of enhancement using CW-US exposure than when pulsed-wave US exposure was used [##REF##12624644##5##,##REF##11978418##21##].</p>", "<p>The aim of this study was to investigate the changes in the effect of clot lysis of r-PA and SK during low-intensity, high-frequency CW-US exposure, intensities within the area following attenuation from the skull bone.</p>" ]

[ "<title>Methods</title>", "<p>The methods employed for clot formation and clot lysis evaluation, and the ultrasonic properties of the model have been described in detail previously [##REF##15993473##17##,##REF##16479192##18##,##UREF##0##22##]. Only a brief description will thus be given below.</p>", "<title>Clot formation</title>", "<p>Blood clots were made using fresh venous blood from seven healthy volunteers (3 men and 4 women, age 47.5 ± 12.5 year (mean ± SD)) not receiving anticoagulation treatment and with no history of coagulation disturbances. After collection the blood was immediately transferred to a Teflon-coated bottle. The collected blood was then anticoagulated using citrate-phosphate-dextrose adenine (CPDA). Each blood clot was made from 1.4 ml CPDA-anticoagulated blood to which 0.025 mmol CaCl₂had been added to induce coagulation. The blood was then left to coagulate around a wool yarn (100 m/54 g, Peer Gynt, Sandnes Uldvarefabrik A/S, 4300 Sandnes, Norway) in a plastic test-tube for one hour [##REF##15993473##17##,##REF##16479192##18##,##UREF##0##22##].</p>", "<title>Determination of clot lysis</title>", "<p>Following one hour of coagulation, the clot was carefully extracted together with the wool yarn and mounted in a plastic frame that was lowered into a clot container with 160 ml of r-PA or SK mixed NaCl solution [##REF##15993473##17##,##REF##16479192##18##,##UREF##0##22##].</p>", "<p>To evaluate clot lysis 1 ml samples of the thrombolytic solution were taken from the clot container every 20 minutes during one hour (20, 40 and 60 min) to estimate the haemoglobin (Hb) leakage from the clot. The sample was added to 4 ml of Drabkins solution and the Hb content (mg) was measured by spectrophotometer at 540 nm, as described elsewhere [##REF##6398614##23##]. To determine clot lysis the loss of Hb (mg) in each individual clot (following 20, 40 and 60 min of exposure) was divided by the Hb content (mg) of a fully lysed clot (from each volunteer), resulting in an estimation of percentage clot lysis (equation 1) [##UREF##0##22##].</p>", "<p></p>", "<title>Thrombolytic drugs</title>", "<p>Two thrombolytic drugs were used in the present study, 0.25 U of r-PA (Rapilysin 10 U^®, Roche Registration Ltd, Hertfordshire, Great Britain) was mixed in 160 ml 0.9% NaCl solution resulting in a concentration of 0.001562 U/ml. The other was SK, (Streptase^®, 1.5 million international units, Hoechst Marion Roussel AB, Stockholm, Sweden), and 3600 IU mixed in 160 ml 0.9% NaCl solution with a resulting concentration of 22.5 IU/ml. These concentrations of the thrombolytic drugs are optimised for use in this <italic>in vitro </italic>method, the optimisation procedure has been described in detail previously [##UREF##0##22##].</p>", "<title>Ultrasound exposure</title>", "<p>Continuous-wave US emitted by an unfocused piezoelectric transducer (CERAM AB, Lund, Sweden) with a resonance frequency of 1 MHz (diameter = 16 mm, area = 2.0 cm²and a near field ending 42 mm from transducer surface) was used in all experiments. The transducer was excited by an electronic system consisting of a function generator (HP 3314A, Hewlett-Packard, Washington, USA) and an RF power amplifier (ENI 240L, ENI, Rochester, New York, USA). Prior to experiments the transducer were calibrated by determining spatial-average temporal-average intensity in W/cm²by measuring the total pressure of US radiation on an electrical balance (Model UPD-DT-1, Ohmic Instrumental co). Needle hydrophone exploration of field distribution for the transducer were performed in degassed water, but exact values of intensity were not measured (Figure ##FIG##0##1##).</p>", "<p>The effect of one hour of 1 MHz CW-US exposure, at intensities 0.0125, 0.025, 0.05, 0.1, 0.15, 0.3, 0.6, 0.9 and 1.2 W/cm²on clot lysis induced by either SK or r-PA was evaluated. For each thrombolytic drug (n = 2, SK and r-PA) and each intensity (n = 9) interventional clots (US-exposed, n = 6) were submerged in thrombolytic solution and exposed to CW-US while control clots (also submerged in thrombolytic solution, n = 6) were left unexposed to US. Thus, the total number of clots used were 216.</p>", "<title>Statistical analysis</title>", "<p>Wilcoxon's signed rank test, was used to assess differences between interventional and control clots at each intensity, following 20, 40 and 60 min of exposure. In all statistical comparisons, P-values below 0.05 were considered significant.</p>", "<title>Ethical considerations</title>", "<p>The experiments described in the present study were conducted with the consent of each participant, and were approved by the Regional Ethical Review Board in Lund (approval: 879/2004).</p>" ]

[ "<title>Results</title>", "<title>Streptokinase treated clots</title>", "<p>Statistically significant decreases in clot lysis were seen at 0.9 W/cm²following 20 min (-2%), 40 min (-2%) and 60 min (-4%) CW-US exposure of SK-treated clots (P &lt; 0.05 in all cases). At an intensity of 1.2 W/cm²the decrease in clot lysis following 20 min of CW-US exposure was 3% and following 40 and 60 min of CW-US exposure 3 and 8%, respectively (P &lt; 0.05 in all cases) (see Table ##TAB##0##1## and Figure ##FIG##1##2##). No increase in clot lysis was seen in clots treated with SK at any time or intensity of CW-US exposure.</p>", "<title>Reteplase treated clots</title>", "<p>In the experiments using r-PA, statistically significant increases in clot lysis were seen following CW-US exposure at intensities of 0.05 W/cm²(3%, P &lt; 0.05), and at 0.3 W/cm²following 40 and 60 min of exposure (1%, P &lt; 0.05 and 8%, P &lt; 0.05) and at 0.6 W/cm²following 40 and 60 min (5%, P = 0.03 and 8%, P &lt; 0.05) of exposure. Increased clot lysis was seen at all times following CW-US exposure at intensities of 0.9 and 1.2 W/cm²(0.9 W/cm²: 20 min: 3%, P &lt; 0.05, 40 min: 4%, P &lt; 0.05, 60 min: 7%, P &lt; 0.05 and at 1.2 W/cm²: 20 min: 8%, P &lt; 0.05, 40 min: 15%, P &lt; 0.05, 60 min: 10%, P &lt; 0.05). No significant decrease in lysis was seen at any time or US intensity in clots treated with r-PA (see Table ##TAB##0##1## and Figure ##FIG##1##2##).</p>" ]

[ "<title>Discussion</title>", "<p>The use of high frequency US to enhance thrombolysis during the treatment of stroke has shown promising results [##REF##15548777##1##,##REF##12783427##3##]. However, clot lysis levels <italic>in vivo </italic>have not been in the same levels as those reported <italic>in vitro </italic>[##REF##15936499##7##,##REF##17854867##9##,##REF##16493016##10##]. This may well be due to the attenuation of intensity as US passes through the temporal bone during high-frequency US exposure [##REF##15591211##11##], although direct comparison between <italic>in vitro </italic>and <italic>in vivo </italic>results should be made carefully. In the CLOTBUST trial, an intensity of 0.75 W/cm²was used [##REF##15548777##1##], which would result in intensities between 0.01 and 0.06 W/cm²(following attenuation) reaching the obstructed vessel and the thrombus. We previously observed no enhanced fibrinolytic effects during pulsed-wave US exposure of r-PA-treated clots in this range of intensities [##REF##16479192##18##], however effects were seen in the small intensity range between 0.125 and 0.25 W/cm². In the present study, using CW-US exposure, a statistically significant increase in lysis of r-PA treated clots was seen at low intensity (0.05 W/cm², 3% increase, P = &lt; 0.05). Thus, applying high-frequency CW-US to r-PA treated stroke patients may improve clinical results. However, different frequencies were used in the present study (1 MHz) and in earlier clinical studies (2 MHz) [##REF##15548777##1##,##REF##12783427##3##], and the results should therefore be compared with care, also direct comparison between in-vitro and in-vivo results should be made with care. Another explanation could be that the number of patients included in the CLOTBUST-trial was to small to achieve statistical significance, this despite efforts to include a sufficient number of patients [##REF##15095554##24##].</p>", "<p>In the present study, increasing enhancement of the clot lysis was seen in the experiments on r-PA treated clots (intensities ≥ 0.3 W/cm²), which are intensities higher than can be expected after passing through the skull bone [##REF##15591211##11##]. In the present experiments on r-PA treated clots, enhancement of lysis was at lower intensities compared to our earlier study using pulsed-wave US exposure [##REF##16479192##18##]. However, it would be difficult reach such levels of intensity both with pulsed and CW-US, due to the high attenuation of the skull bone and considering the limited levels of out put intensity recommended in transcranial Doppler US [##REF##15255769##25##].</p>", "<p>In the present study no enhanced effects of SK were seen at any intensity level used. This is a contradictory result when compared to results from studies with pulsed-wave US exposure [##REF##8571471##16##,##REF##15993473##17##]. Thus, the mechanisms by which US enhance clot lysis might vary between CW-US exposure and pulsed-wave US exposure. This study shows decreased effects of clot lysis at intensities ≥ 0.9 W/cm², a finding that has been seen earlier during pulsed-wave US exposure [##REF##8571471##16##,##REF##15993473##17##], however at higher intensities (≥ 2 W/cm²). This might indicate that also duty cycle is an important factor influencing the results in US-enhanced clot lysis, not only intensity. Streptokinase is still considered by some to be a useful thrombolytic drug in the clinical setting [##REF##14697452##26##,##REF##17111203##27##]. However, it does not appear to be suitable, in the setting of US enhanced thrombolysis, based on the decrease in effects induced by US exposure, according to the results in the present and earlier studies [##REF##8571471##16##,##REF##15993473##17##]. In the earlier studies it was possible to modulate the stereochemistry of SK by exposing it to US of different intensity levels of pulsed US. These effects occurred at US intensities below the prescribed upper limit of exposure of the human body to US energy (Mechanical Index &lt; 1.9) [##REF##15993473##17##]. Therefore, during SK treatment of any thrombotic disorders, possible undesired effects of exposure to US should be considered. And when using US to enhance the effects of SK in clinical situations, we recommend it to be restricted since reliable calculations and measurements of local US intensities in the treatment area is hard to perform. Streptokinase has also been shown to be associated with a higher risk of intracranial bleeding than other thrombolytic drugs, and is therefore not recommended for clinical use in the treatment for stroke [##REF##15383482##28##].</p>", "<p>We have previously demonstrated a direct effect on the thrombolytic substance during exposure with pulsed-wave US exposure, effects associated with both decreased and increased effects on clot lysis [##REF##15993473##17##,##REF##16479192##18##]. This was not examined in the present study, and we therefore do not know whether this effect exist when using CW-US. A recent study failed to reveal any changes in enzymatic activity of both SK and r-PA following US exposure [##REF##16545433##29##]. Direct effects on the molecules of thrombolytic drug following CW-US exposure must therefore be investigated in the future.</p>", "<title>Limitations</title>", "<p>The use of pure 0.9% NaCl solution as medium for experiments of fibrinolysis might not be the optimal solution for exploring when fibrinolytic effects are optimised. Previous studies have explored fibrinolytic effects in pure 0.9% NaCl solution showing them to be stable or partly reduced, but not totally inactivated [##REF##1154313##30##, ####REF##12682204##31##, ##REF##12525593##32####12525593##32##]. Results from earlier studies [##REF##8571471##16##,##REF##12766386##33##] in vitro adding fibrinolytic drugs to pure 0.9% NaCl solution have been reproduced and verified in vivo [##REF##9930279##34##,##REF##10790341##35##] as well as in clinical studies [##REF##12914878##36##]. The use of pure 0.9% NaCl solution without addition of plasminogen might explain the limited levels of clot lysis seen in the present study [##REF##1613318##37##,##REF##7671373##38##]. How this affects the results in the present method has to be studied in the future.</p>" ]

[ "<title>Conclusion</title>", "<p>Increasing intensities of CW-US exposure resulted in increased clot lysis of r-PA-treated blood clots, but decreased clot lysis of SK-treated clots. Continuous-wave US may thus be useful in US-enhanced clot lysis during stroke treatment with r-PA.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Ultrasound (US) has been used to enhance thrombolytic therapy in the treatment of stroke. Considerable attenuation of US intensity is however noted if US is applied over the temporal bone. The aim of this study was therefore to explore possible changes in the effect of thrombolytic drugs during low-intensity, high-frequency continuous-wave ultrasound (CW-US) exposure.</p>", "<title>Methods</title>", "<p>Clots were made from fresh venous blood drawn from healthy volunteers. Each clot was made from 1.4 ml blood and left to coagulate for 1 hour in a plastic test-tube. The thrombolytic drugs used were, 3600 IU streptokinase (SK) or 0.25 U reteplase (r-PA), which were mixed in 160 ml 0.9% NaCl solution. Continuous-wave US exposure was applied at a frequency of 1 MHz and intensities ranging from 0.0125 to 1.2 W/cm². For each thrombolytic drug (n = 2, SK and r-PA) and each intensity (n = 9) interventional clots (US-exposed, n = 6) were submerged in thrombolytic solution and exposed to CW-US while control clots (also submerged in thrombolytic solution, n = 6) were left unexposed to US.</p>", "<p>To evaluate the effect on clot lysis, the haemoglobin (Hb) released from each clot was measured every 20 min for 1 hour (20, 40 and 60 min). The Hb content (mg) released was estimated by spectrophotometry at 540 nm. The difference in effect on clot lysis was expressed as the difference in the amount of Hb released between pairs of US-exposed clots and control clots. Statistical analysis was performed using Wilcoxon's signed rank test.</p>", "<title>Results</title>", "<p>Continuous-wave ultrasound significantly decreased the effects of SK at intensities of 0.9 and 1.2 W/cm²at all times (P &lt; 0.05). Continuous-wave ultrasound significantly increased the effects of r-PA on clot lysis following 20 min exposure at 0.9 W/cm²and at 1.2 W/cm², following 40 min exposure at 0.3, 0.6, 0.9 and at 1.2 W/cm², and following 60 min of exposure at 0.05 0.3, 0.6, 0.9 and at 1.2 W/cm²(all P &lt; 0.05).</p>", "<title>Conclusion</title>", "<p>Increasing intensities of CW-US exposure resulted in increased clot lysis of r-PA-treated blood clots, but decreased clot lysis of SK-treated clots.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>BMH designed the investigation, performed the experiments, the statistical analysis and interpretation of the results, as well as the preparation of the manuscript. JC assisted with the statistical analysis and the preparation of the manuscript. AR supervised and designed the investigation as well as participated in the preparation of the manuscript. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2261/8/19/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>We was able to perform the present study thanks to funding from Torsten Westerströms stiftelse and Universitetssjukhusets i Lund stiftelser och donationer för forskning.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>The field distribution for the transducer used in the present study</bold>. Needle hydrophone exploration of field distribution for the transducer. Scanning was performed over an area of 50 × 30 mm²in the y- and z-direction starting close to the transducer surface. No exact values of intensity were measured. Clots were placed 30 mm from the transducer surface.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>Difference in clot lysis following continuous-wave ultrasound exposure</bold>. Difference in clot lysis following 20, 40 and 60 min of continuous-wave ultrasound exposure at different intensities, presented as the difference between ultrasound-exposed clots and control clots: □ = clots exposed continuous-wave ultrasound and streptokinase (n = 6), ■ = clots exposed to continuous-wave ultrasound and reteplase (n = 6). Wilcoxon's signed rank test was used to assess statistical differences, * = P &lt; 0.05.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Difference in clot lysis following continuous-wave ultrasound exposure.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Intensity (W/cm²)</bold><break/><bold>Time (Min)</bold></td><td align=\"right\"><bold>US+SK (n = 6)</bold></td><td align=\"right\"><bold>Control (n = 6)</bold></td><td align=\"right\"><bold>P-value</bold></td><td align=\"right\"><bold>US+r-PA (n = 6)</bold></td><td align=\"right\"><bold>Control (n = 6)</bold></td><td align=\"right\"><bold>P-value</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>0.0125</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">13 (11–29)</td><td align=\"right\">13 (11–29)</td><td align=\"right\">0.69</td><td align=\"right\">7 (5–11)</td><td align=\"right\">6 (4 – 9)</td><td align=\"right\">0.08</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">27 (19–47)</td><td align=\"right\">23 (21–36)</td><td align=\"right\">0.25</td><td align=\"right\">16 (9–22)</td><td align=\"right\">12 (7–25)</td><td align=\"right\">0.25</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">43 (22–59)</td><td align=\"right\">31 (23–54)</td><td align=\"right\">0.12</td><td align=\"right\">22 (14–42)</td><td align=\"right\">22 (10–43)</td><td align=\"right\">0.46</td></tr><tr><td align=\"left\"><bold>0.025</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">15 (13–26)</td><td align=\"right\">16 (13–31)</td><td align=\"right\">0.34</td><td align=\"right\">9 (5–12)</td><td align=\"right\">7 (3–10)</td><td align=\"right\">0.25</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">25 (18–33)</td><td align=\"right\">22 (19–40)</td><td align=\"right\">0.60</td><td align=\"right\">16 (10–19)</td><td align=\"right\">15 (7–17)</td><td align=\"right\">0.17</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">34 (21–58)</td><td align=\"right\">30 (23–49)</td><td align=\"right\">0.25</td><td align=\"right\">36 (13–37)</td><td align=\"right\">27 (10–37)</td><td align=\"right\">0.12</td></tr><tr><td align=\"left\"><bold>0.05</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">15 (12–27)</td><td align=\"right\">17 (15–21)</td><td align=\"right\">0.69</td><td align=\"right\">8 (4–10)</td><td align=\"right\">7 (5–10)</td><td align=\"right\">0.46</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">21 (18–35)</td><td align=\"right\">25 (21–36)</td><td align=\"right\">0.08</td><td align=\"right\">16 (13–19)</td><td align=\"right\">12 (11–22)</td><td align=\"right\">0.34</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">39 (28–52)</td><td align=\"right\">36 (27–52)</td><td align=\"right\">0.46</td><td align=\"right\">26 (20–30)</td><td align=\"right\">24 (17–28)</td><td align=\"right\">&lt;0.05</td></tr><tr><td align=\"left\"><bold>0.1</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">18 (13–27)</td><td align=\"right\">15 (10–31)</td><td align=\"right\">0.69</td><td align=\"right\">7 (6–10)</td><td align=\"right\">8 (4–9)</td><td align=\"right\">0.50</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">22 (19–37)</td><td align=\"right\">21 (15–42)</td><td align=\"right\">0.35</td><td align=\"right\">15 (10–18)</td><td align=\"right\">17 (3–12)</td><td align=\"right\">0.92</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">32 (25–46)</td><td align=\"right\">29 (20–49)</td><td align=\"right\">0.35</td><td align=\"right\">28 (23–34)</td><td align=\"right\">24 (13–39)</td><td align=\"right\">0.60</td></tr><tr><td align=\"left\"><bold>0.15</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">17 (14–27)</td><td align=\"right\">17 (13–24)</td><td align=\"right\">0.60</td><td align=\"right\">7 (5–11)</td><td align=\"right\">7 (5–8)</td><td align=\"right\">0.25</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">28 (19–38)</td><td align=\"right\">23 (16–34)</td><td align=\"right\">0.17</td><td align=\"right\">15 (14–17)</td><td align=\"right\">15 (11–18)</td><td align=\"right\">0.60</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">35 (21–44)</td><td align=\"right\">39 (23–49)</td><td align=\"right\">0.12</td><td align=\"right\">28 (20–41)</td><td align=\"right\">25 (16–37)</td><td align=\"right\">0.75</td></tr><tr><td align=\"left\"><bold>0.3</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">16 (14–17)</td><td align=\"right\">17 (13–25)</td><td align=\"right\">0.69</td><td align=\"right\">8 (3–12)</td><td align=\"right\">7 (2–11)</td><td align=\"right\">0.12</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">26 (19–48)</td><td align=\"right\">25 (18–35)</td><td align=\"right\">0.25</td><td align=\"right\">14 (12–29)</td><td align=\"right\">13 (8–21)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">38 (37–58)</td><td align=\"right\">35 (22–62)</td><td align=\"right\">0.46</td><td align=\"right\">30 (24–51)</td><td align=\"right\">22 (15–39)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>0.6</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">14 (5–16)</td><td align=\"right\">13 (9–16)</td><td align=\"right\">0.92</td><td align=\"right\">29 (18–35)</td><td align=\"right\">25 (18–31)</td><td align=\"right\">0.08</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">19 (10–23)</td><td align=\"right\">17 (12–21)</td><td align=\"right\">0.60</td><td align=\"right\">31 (19–52)</td><td align=\"right\">27 (16–43)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">23 (14–26)</td><td align=\"right\">21 (16–26)</td><td align=\"right\">0.92</td><td align=\"right\">41 (28–57)</td><td align=\"right\">33 (22–44)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>0.9</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">26 (18–29)</td><td align=\"right\">27 (22–31)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">23 (18–29)</td><td align=\"right\">20 (14–29)</td><td align=\"right\">&lt;0.05</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">34 (30–42)</td><td align=\"right\">36 (27–42)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">44 (31–47)</td><td align=\"right\">39 (25–42)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">38 (30–42)</td><td align=\"right\">42 (33–51)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">50 (43–60)</td><td align=\"right\">43 (39–45)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>1.2</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td align=\"left\"><bold>20</bold></td><td align=\"right\">26 (22–29)</td><td align=\"right\">29 (26–34)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">17 (14–23)</td><td align=\"right\">9 (8–10)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>40</bold></td><td align=\"right\">32 (28–33)</td><td align=\"right\">35 (30–38)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">36 (26–38)</td><td align=\"right\">21 (19–22)</td><td align=\"right\">&lt; 0.05</td></tr><tr><td align=\"left\"><bold>60</bold></td><td align=\"right\">32 (30–37)</td><td align=\"right\">41 (37–44)</td><td align=\"right\">&lt; 0.05</td><td align=\"right\">42 (36–48)</td><td align=\"right\">32 (25–35)</td><td align=\"right\">&lt; 0.05</td></tr></tbody></table></table-wrap>" ]

[ "<disp-formula id=\"bmcM1\"><label>(1)</label><mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\" name=\"1471-2261-8-19-i1\" overflow=\"scroll\"><mml:semantics><mml:mrow><mml:mi>%</mml:mi><mml:mtext> clot lysis</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mtext>experimental clot Hb</mml:mtext></mml:mrow><mml:mrow><mml:mtext>fully lysed clot</mml:mtext></mml:mrow></mml:mfrac><mml:mo stretchy=\"false\">(</mml:mo><mml:mo>×</mml:mo><mml:mn>100</mml:mn><mml:mo stretchy=\"false\">)</mml:mo></mml:mrow></mml:semantics></mml:math></disp-formula>" ]

[]

[]

[]

[]

[]

[ "<table-wrap-foot><p>Clot lysis (%) of clots exposed to streptokinase concomitantly with continuous-wave ultrasound at different intensities (n = 6 for each intensity) for one hour (US+SK) and clots exposed to streptokinase alone (n = 6 for each intensity, (control clots)) and in clots exposed to reteplase concomitantly with continuous-wave ultrasound at different intensities (n = 6 for each intensity) for one hour (US-r-PA) and reteplase alone (n = 6 for each intensity, (control clots)). Results are presented as medians and 5^th– 95^thpercentiles. Wilcoxon's signed rank test was used to assess statistical difference.</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2261-8-19-1\"/>", "<graphic xlink:href=\"1471-2261-8-19-2\"/>" ]

[]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Recently, chronic obstructive pulmonary disease (COPD) has been defined by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) as a disease characterized by progressive, not fully reversible, flow limitation and \"associated with an abnormal inflammatory response of the lungs to noxious particles and gases\" [##UREF##0##1##]. Thus, a central role has been attributed to the chronic inflammatory response that in humans is present throughout the airways and parenchyma and that participates in the progression and exacerbation of this disease [##UREF##1##2##].</p>", "<p>The attempt to reduce, with the use of anti-inflammatory agents, lung inflammatory cell infiltration is most appealing since such an effect would also reduce the lung burden of both proteases and oxidants. In an approach aiming at modulating the chronic inflammatory response, corticosteroids are used. However, these drugs have been found to be largely ineffective in attenuating inflammation in patients with COPD [##REF##10556133##3##]. The resistance to corticosteroids may involve an impaired activity of the enzyme histone deacetylase, related to oxidative stress. In fact, a blunted activity of this enzyme is associated with a reduced response to corticosteroids and an enhanced expression of inflammatory cytokines [##UREF##2##4##].</p>", "<p>Thus, as indicated in the GOLD guidelines, there is a pressing need to develop new agents capable of suppressing the inflammatory response [##UREF##0##1##]. The phosphodiesterases are a large family of intracellular enzymes that degrade cyclic nucleotides. Among these the phosphodiesterase 4 (PDE4) isoenzyme specifically targets 3', 5'-cyclic adenosine monophosphate (cAMP), a second messenger that exerts inhibitory effects on many inflammatory cells. Neutrophils, macrophages and CD8+ T-lymphocytes play a significant role in COPD and these cells have been shown to substantially express PDE4. Thus, substances that prevent the degradation of cAMP by inhibiting the activity of PDE4 will enhance the anti-inflammatory action of this second messenger [##UREF##3##5##].</p>", "<p>In a previous investigation we reported that the specific PDE4 inhibitor roflumilast, given orally either at 1 mg/kg or at 5 mg/kg to mice acutely exposed to cigarette smoke, partially but significantly prevented the smoke-induced lung neutrophilia.</p>", "<p>Additionally, when given orally at the same doses, in a chronic (7 months) model of cigarette smoke exposure, the high (5 mg/kg) but not the low dose of roflumilast completely prevented the smoke-induced development of emphysema and the drop in desmosine lung content. Thus, this study showed for the first time that a phosphodiesterase 4 inhibitor such as roflumilast, could fully prevent parenchymal destruction induced by cigarette smoke [##REF##15961691##6##].</p>", "<p>Recent reports indicate that inflammatory cells both of the innate (macrophages, neutrophils) and adaptive immune system (B lymphocytes, CD4+ T-lymphocytes, CD8+ T-lymphocytes) or cells linking innate and adaptive immunity (dendritic cells) may play an important role in the development of cigarette smoke-induced emphysema [##UREF##4##7##, ####REF##14582923##8##, ##REF##15215480##9####15215480##9##]. It was thus of interest to investigate the effect of roflumilast on the influx into the lung of the inflammatory cells of the innate and adaptive immune system. This was done with immunohistochemical methods coupled with a morphometrical assessment using the paraffin embedded blocks of the previous study.</p>", "<p>This investigation could be of help in clarifying the importance of these cells for the development of cigarette smoke-induced emphysema. In fact, since the low dose of roflumilast did not prevent the development of emphysema while the high dose completely blocked it [##REF##15961691##6##], it would be of interest to analyze the recruitment of inflammatory cells under both these conditions.</p>" ]

[ "<title>Methods</title>", "<p>In the present investigation the paraffin blocks of a previous study were used [##REF##15961691##6##]. Briefly, five groups of 2 months old male mice of the strain C57 Bl/6J were treated as follows: 1) no treatment/air exposed, 2) roflumilast 5 m/kg p.o./air exposed, 3) no treatment/smoke exposed, 4) roflumilast 1 mg/kg p.o./smoke exposed, and 5) roflumilast 5 mg/kg p.o./smoke exposed. All animal experiments were conducted in conformity with the \"Guiding Principles for Research Involving Animals and Human Beings\" and approved by the Local Ethics Committee of the University of Siena.</p>", "<p>After chronic exposure to room air or cigarette smoke for seven months, the animals were sacrificed and the lungs fixed in formalin (5%) at a pressure of 20 cm H₂O. Lung volume was measured by water displacement. All lungs were then dehydrated, cleared in toluene and embedded in paraffin. Tissue sections (7 μm) were pre-treated with 3% hydrogen peroxide to inhibit the activity of the endogenous peroxidases. For antigen retrieval, the sections were heated in a microwave for 20 min in citrate buffer 0.01 M, pH 6.0, and allowed to cool slowly to room temperature. The slides were then incubated with 3% bovine serum albumin for 30 min at room temperature to block non-specific antibody binding, and then exposed to the following primary antibodies: prediluted rabbit polyclonal to myeloperoxidase (undiluted) (Abcam, Cambridge, UK), rat monoclonal anti-mouse MAC-3 (1:20) (BD Pharmingen, Buccinasco, Italy), rat monoclonal anti-mouse CD45/B220 (1:20) (BD Pharmingen, Buccinasco, Italy), rat monoclonal anti-mouse to CD4 (1:1000) (Abcam, Cambridge, UK), overnight at 4°C.</p>", "<p>For myeloperoxidase detection, the tissue sections were rinsed and incubated with sheep anti-rabbit IgG (1:100) (Sigma Immuno Chemicals) for 30 min. at room temperature. The staining was revealed by adding peroxidase-antiperoxidase complex (1:200) (Sigma Immuno Chemicals) prepared from rabbit serum.</p>", "<p>For MAC-3, CD4 and CD45R/B220 detection, the sections were rinsed and incubated with goat polyclonal anti-rat biotinylated IgG (1:100) (Abcam, Cambridge, UK) for 30 min. at room temperature. The staining was revealed by adding Streptavidin-horseradish peroxidase (BD Pharmingen, Buccinasco, Italy).</p>", "<p>Detection was accomplished by incubation in diaminobenzidine (DAB) freshly dissolved in 0.03% H₂O₂in 50 mM Tris/HCl, pH 7.6. As negative controls for the immunostaining, the primary Ab was replaced by nonimmunized rabbit or rat serum.</p>", "<p>The M.O.M. immunodetection kit (Vector Laboratories, Burlinghame, CA) was used for both immunodection of mouse monoclonal to CD8-α (1:100) (Santa Cruz Biotecnology Inc, Europe) and to fascin (1:200) (Abcam, Cambridge, UK), a protein highly restricted to dendritic cells deriving from the different dendritic cell subsets [##REF##8579121##10##]. Fascin is specifically expressed only in mature but not in immature dendritic cells [##REF##11123310##11##] and its expression is a prerequisite for full T-cells activation [##REF##17255360##12##].</p>", "<p>The Vector M.O.M. immunodetection kit is designed specifically to localize mouse primary monoclonal and polyclonal antibodies on mouse tissues by using a novel blocking agent and reducing the undesired background staining. Immunostaining was revealed by using the M.O.M. detection kit with DAB substrate.</p>", "<p>The volume fractions of the immunopositive cells were determined by point counting using a grid with 48 points, a 20× objective and a computer screen for a final magnification of 580×. Twenty fields were examined for each pair of lungs for a total of 960 points. The number of points that fell on stained cells was divided by the total number of points on the lung section. This number was then multiplied by the volume of the lung corrected by the weight of the mouse to give the total volume of the specifically stained cells in the lung [##UREF##5##13##].</p>", "<p>The number of animals (N) was 5 in all groups except in the group \"smoke: macrophages\" where N = 7; \"smoke+R1: macrophages\" where N = 6; and \"smoke+R5: macrophages\" where N = 7.</p>", "<p>The significance of the differences was calculated using one-way analysis of variance (ANOVA). A p-value of &lt; 0.05 was considered significant.</p>" ]

[ "<title>Results</title>", "<p>Following chronic smoke exposure, the inflammatory cells of both the innate immune system and of the adaptive immune system were significantly increased in the lung tissue when compared to air exposure.</p>", "<p>The neutrophils, which could be observed mainly peribronchially but also in the lung parenchyma (Fig. ##FIG##0##1A##), were increased by 97% (p &lt; 0.01, Fig. ##FIG##0##1B##). Roflumilast, at the dose 1 mg/kg, did not significantly affect this increase, while at the dose 5 mg/kg, prevented the increase in neutrophil V_Vby 78% (p &lt; 0.01) (Fig. ##FIG##0##1B##).</p>", "<p>The macrophages, which were observed throughout the lung parenchyma (Fig. ##FIG##1##2A##) were increased by 107% (p &lt; 0.01) in comparison to air exposure (Fig. ##FIG##1##2B##). Roflumilast, at the dose 1 mg/kg, did not significantly affect (by 19%) the cigarette smoke-induced increase in macrophage V_V, but at the dose 5 mg/kg suppressed the increase in macrophage V_Vby 82% (p &lt; 0.01) (Fig. ##FIG##1##2B##). This effect is slightly more potent of what previously reported [##REF##15961691##6##].</p>", "<p>The dendritic cells expressing fascin were increased by 217% (p &lt; 0.01) (Fig. ##FIG##2##3B##). These cells were found perivascularly (Fig. ##FIG##2##3A##) in the airway walls and in the parenchyma, as well as organized in lymphoid follicles. Roflumilast, at the dose 1 mg/kg reduced by 42% (p &lt; 0.05) (Fig. ##FIG##2##3B##) the increase in V_Vof mature dendritic cells with the potential ability to activate T-cell proliferation. A similar effect was obtained with the dose 5 mg/kg (-48%, p &lt; 0.05) (Fig. ##FIG##2##3B##).</p>", "<p>B-lymphocytes, which were exclusively found organized in the lymphoid follicles observed both peribronchially (Fig. ##FIG##3##4A##) and in the parenchyma, were increased by 436% (p &lt; 0.01) (Fig. ##FIG##3##4B##). The low dose of roflumilast potentiated, not significantly, by 26% the increase in B cell V_V. This increase was due to a very high value observed in one lung of this group and this is reflected by the unusually high SEM of this group. Roflumilast, at the dose 5 mg/kg, prevented the increase in B-lymphocyte V_Vby 100% (p &lt; 0.01) (Fig. ##FIG##3##4B##).</p>", "<p>The CD4+ T-lymphocytes, which were found perivascularly (Fig. ##FIG##4##5A##), in the airways and in the lymphoid follicles were increased in the lungs of the mice exposed to cigarette smoke by 524% (p &lt; 0.01) (Fig. ##FIG##4##5B##). The low dose of roflumilast reduced the increase in CD4+ cell V_Vby 55% (p &lt; 0.05) and the high dose by 98% (p &lt; 0.01) (Fig. ##FIG##4##5B##).</p>", "<p>Following chronic exposure to cigarette smoke CD8+ T-lymphocytes were visualized perivascularly, peribronchially, and in lymphoid follicles (Fig. ##FIG##5##6A##) and were increased by 417% (p &lt; 0.01) (Fig. ##FIG##5##6B##). Both doses of roflumilast showed a similar inhibition of the influx of these cells: 91% at 1 mg/kg and 88% at 5 mg/kg, respectively (both p &lt; 0.001) (Fig. ##FIG##5##6B##).</p>" ]

[ "<title>Discussion</title>", "<p>The main points of this study are: (<italic>i</italic>) the effect of chronic smoke exposure on the recruitment of inflammatory cells of both the innate and adaptive immune system and (<italic>ii</italic>) the effect of the two doses of roflumilast on this recruitment.</p>", "<p>With regard to inflammatory cells of the innate immune system, cigarette smoke exposure resulted in an increase of approximately 100% of both neutrophil and macrophage V_V. In particular, neutrophil V_Vwas increased by 97% after 7 months cigarette smoke exposure. This result is consistent with the data of a recent report where neutrophils, also assessed morphometrically, were increased by 155% in the lung of C57 Bl/6J mice exposed for one year to cigarette smoke [##REF##16387805##14##]. A pronounced increase of neutrophils was found in bronchoalveolar lavage fluids (BALFs) of mice with the same background and after exposure to cigarette smoke for 6 months [##REF##16055867##15##,##REF##16540505##16##].</p>", "<p>In COPD in man, an increased number of neutrophils is recovered from sputum and BALFs however, there are relatively small increases of neutrophils in the airways or parenchyma [##REF##7582312##17##]. The lack of a significant increase in neutrophils in the lung parenchyma has been attributed to the rapid transit that these cells make through the airways and the lung parenchyma [##REF##8370343##18##]. In our opinion, the discrepancy between animal and human data may be explained by the different methodology used for performing bronchoalveolar lavage that is known to be representative in humans of a small region of the lung (segmental lavage).</p>", "<p>In the present study, cigarette smoke exposure resulted in an increase in lung macrophage V_Vby 107%. Similarly, in a recent study macrophages were increased by 81% in mice exposed to cigarette smoke for one year as compared to air exposed animals [##UREF##5##13##]. Further, an investigation of the time course of the increase of inflammatory cells following cigarette smoke exposure revealed a progressive biphasic increase in BALF macrophages. There was a slight but significant increase after 7 days, and a marked increase after 6 months. In the lung, the number of macrophages increased significantly after 12 weeks and remained elevated up to 6 months. [##REF##16055867##15##]. Similarly, in patients with COPD, there is a marked increase in the number of macrophages both in BALF and in the lung parenchyma [##UREF##6##19##].</p>", "<p>In the present study activated dendritic cells, B-lymphocytes and CD4+ and CD8+ T-lymphocytes were also markedly increased after cigarette smoke. The results of the dendritic cells are supported by recent data obtained in the mouse showing a strong increase of dendritic cells in the lung in response to cigarette smoke [##REF##16055867##15##,##REF##8532391##20##]. The dendritic cells are antigen presenting cells and the most likely explanation for the increased number of these cells could be their recruitment as a response either to smoke inhalation or to tissue damage. Dendritic cells would then take up, process and present antigenic substances contained either in cigarette smoke or extracellular matrix degradation products to T-cells. Additionally, dendritic cells are not only antigen presenting cells but also following cigarette exposure they produce MMP-12 thus, having the potential for a direct damaging effect [##REF##16192742##21##].</p>", "<p>The present results regarding the T-cells are consistent with the data of a recent work where the total number of T-lymphocytes was assessed in the lung of mice following cigarette smoke exposure. At 6 months, total number of CD4+ T-lymphocytes was increased 2-fold while CD8+ T-lymphocytes increased by 43%. Additionally, the number of activated CD4+ and CD8+ T-cells was also found to be increased [##REF##16055867##15##]. In an attempt to elucidate the role for CD8+ cells in emphysema, CD8+ T cell-deficient (CD8-/-) mice were chronically exposed to cigarette smoke. In contrast to wild-type mice that displayed macrophage, lymphocyte, and neutrophil recruitment followed by emphysema, CD8-/- mice had a blunted inflammatory response and did not develop emphysema. The hypothesis was put forward whereby the CD8+ T-cell product, IFN-gamma-inducible protein-10, would induce production of MMP-12 causing lung destruction and generating chemotactic factors [##REF##17548647##22##].</p>", "<p>In the present study B-lymphocytes, which were found in peribronchial and parenchymal lymphoid follicles, were increased by more than 4-fold. Additionally as mentioned above, mature dendritic cells, CD4+ and CD8+ T-lymphocytes were also seen in the lymphoid follicles. Although CD4 and CD8a are expressed in some monocyte/macrophages or in some KN and dendritic cells, our findings are consistent with recent data reported in the mouse after chronic smoke exposure [##REF##16399994##23##]. The formation of lymphoid follicles defines the appearance of an adaptive immune response [##REF##16921123##24##], and the colocalisation of lymphocytes and mature dendritic cells in one site suggests that these cells are functionally communicating [##REF##14647481##25##].</p>", "<p>The question that arises is what is the potential role of the B-cells in the development of emphysema. At present, is unclear against which antigen this B-cell proliferation may be directed. The hypothesis of an antigen of microbial nature has been put forward in man [##REF##15215480##9##]. Additionally, as mentioned above, there are at least two alternative potential sources that should be considered, cigarette smoke components and degradation products of extracellular matrix [##UREF##4##7##]. Another hypothesis suggests that cigarette smoke, via an oxidative challenge, could modify lung proteins in such a way to make them immunogenic [##REF##14514931##26##].</p>", "<p>In COPD patients all these cells of the adaptive immune system are prominent [##REF##17332482##27##, ####REF##9517597##28##, ##REF##15325838##29####15325838##29##] however, their specific role in the development of the disease is still a matter of discussion. Similarly, the role of the innate immunity in the development of cigarette smoke induced emphysema has not been clarified.</p>", "<p>In the present study roflumilast, at the dose of 5 mg/kg provided a marked and significant protection against the influx into the lungs of the inflammatory cells of both the innate and adaptive immune system and this dose of roflumilast has been previously reported to completely prevent the development of emphysema [##REF##15961691##6##]. Thus, the present results would support a role for all these inflammatory cells in the development of emphysema and suggest that inhibition of their recruitment may prevent the development of the disease.</p>", "<p>However, the low dose of roflumilast had no effect on neutrophil and macrophage V_Vbut prevented the increase of dendritic cells with the potential to activate T-cell proliferation by 42%, that of CD+4 positive cells by 55% and almost completely (91%) blocked that of CD8+ positive cells. This low dose of roflumilast did not have any effect on the development of emphysema [##REF##15961691##6##].</p>", "<p>All these data taken together could be interpreted to signify that the inflammatory cells of the innate immune system are likely to play a major role in the development of emphysema. This, since their influx is associated with the presence of this disease and conversely when their recruitment is prevented there is no emphysema (as it is the case with the dose 5 mg/kg of roflumilast). On the other hand, the inflammatory cells of the adaptive immune system probably do not play a major role since emphysema can fully develop even when the activation of dendritic cells, and the number of CD4+ and CD8+ positive cells is significantly reduced or blocked (as with the dose 1 mg/kg roflumilast).</p>", "<p>This conclusion is consistent with the results of a previous study performed in SCID mice chronically exposed to cigarette smoke. These mice lack functional B- and T-cells and peribronchial lymphoid follicles. In these mice cigarette smoke induced a progressive increase of neutrophils and macrophages in BALF, and induced significant emphysema. [##REF##16359546##30##].</p>", "<p>In a recent work Robbins and co-workers specifically investigated the impact of chronic tobacco smoke exposure on respiratory immune defence mechanisms [##REF##12920055##31##]. C57Bl/6J mice were chronically exposed to cigarette smoke and emphysematous lesions were observed after 6 months and were even more pronounced by 10 months. Cigarette smoke exposure reduced the number and the maturation of dendritic cells in the lung by altering their costimulatory molecule expression profile without affecting the CD4+ and CD8+ T-cell compartments. The differences in dendritic as well as in CD4+ and CD8+ T-cell profiles observed in different studies dealing with smoking mice may be accounted to the different methodological procedures (i.e. manner of smoking, time of exposure, number or type of cigarette) in use in different labs. All these data taken together strongly suggest that the cells of the adaptive immune system do not play a major role in the development of emphysema in smoking mice. However, we cannot exclude at the present time a role for adaptive immune responses in the progression of emphysematous lesions induced by cigarette smoking.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion the results of the present study coupled with the data of the literature indicate: (<italic>i</italic>) chronic exposure to cigarette smoke in mice results in a significant recruitment into the lung of inflammatory cells of both the innate and adaptive immune system, as assessed by morphometry; (<italic>ii</italic>) roflumilast at the higher dose exerts a protective effect against the recruitment of all these cells and at the lower dose against the recruitment of dendritic cells and T-lymphocytes; (<italic>iii</italic>) these findings underline the role of innate immunity in the development of pulmonary emphysema and (<italic>iiii</italic>) support previous results indicating that the inflammatory cells of the adaptive immune system do not play a central role in the development of cigarette smoke induced emphysema in mice.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>We reported that roflumilast, a phosphodiesterase 4 inhibitor, given orally at 5 mg/kg to mice prevented the development of emphysema in a chronic model of cigarette smoke exposure, while at 1 mg/kg was ineffective. Here we investigated the effects of roflumilast on the volume density (V_V) of the inflammatory cells present in the lungs after chronic cigarette smoke exposure.</p>", "<title>Methods</title>", "<p>Slides were obtained from blocks of the previous study and V_Vwas assessed immunohistochemically and by point counting using a grid with 48 points, a 20× objective and a computer screen for a final magnification of 580×. Neutrophils were marked with myeloperoxidase antibody, macrophages with Mac-3, dendritic cells with fascin, B-lymphocytes with B220, CD4+ T-cells with CD4+ antibody, and CD8+T-cells with CD8-α. The significance of the differences was calculated using one-way analysis of variance.</p>", "<title>Results</title>", "<p>Chronic smoke exposure increased neutrophil V_Vby 97%, macrophage by 107%, dendritic cell by 217%, B-lymphocyte by 436%, CD4+ by 524%, and CD8+ by 417%. The higher dose of roflumilast prevented the increase in neutrophil V_Vby 78%, macrophage by 82%, dendritic cell by 48%, B-lymphocyte by 100%, CD4+ by 98% and CD8+ V_Vby 88%. The lower dose of roflumilast did not prevent the increase in neutrophil, macrophage and B-cell V_Vbut prevented dendritic cells by 42%, CD4+ by 55%, and CD8+ by 91%.</p>", "<title>Conclusion</title>", "<p>These results indicate (<italic>i</italic>) chronic exposure to cigarette smoke in mice results in a significant recruitment into the lung of inflammatory cells of both the innate and adaptive immune system; (<italic>ii</italic>) roflumilast at the higher dose exerts a protective effect against the recruitment of all these cells and at the lower dose against the recruitment of dendritic cells and T-lymphocytes; (<italic>iii</italic>) these findings underline the role of innate immunity in the development of pulmonary emphysema and (<italic>iiii</italic>) support previous results indicating that the inflammatory cells of the adaptive immune system do not play a central role in the development of cigarette smoke induced emphysema in mice.</p>" ]

[ "<title>Competing interests</title>", "<p>PAM, GL, BL, ML and GDC, have no financial competing interests associated with this study. RB is employed by Nycomed GmbH.</p>", "<title>Authors' contributions</title>", "<p>PAM contributed to the morphometrical analysis and wrote the draft of the manuscript. PAM, RB and GL participated in the design of the study, analysed the results and contributed to the final version of the manuscript. ML coordinated the animal experimentation. ML, BL, and GDC performed the histochemical reactions and participated to the morphometrical analysis. All authors read and approved the final manuscript.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2466/8/17/prepub\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>This work was supported with funds from the University of Siena, Siena Italy (PAR grants to ML and GL). Nycomed GmbH funded in part some of the expenses incurred in the course of this study and covered the publication expenses.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>A</bold>. Immunohistochemical reaction for neutrophil myeloperoxidase on a lung of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. <bold>B</bold>. Neutrophil volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups; * = p &lt; 0.01 versus air exposed, ++ = &lt; 0.01 versus smoke exposed. Scale Bar = 40 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p><bold>A</bold>. Immunohistochemical reaction for macrophage Mac-3 on lung parenchyma of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. <bold>B</bold>. Macrophage volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups except \"CS -\" where N = 7, \"CS +R1\"where N = 6 and \"CS +R5\" where N = 7; * = p &lt; 0.01 versus air exposed, ++ = &lt; 0.01 versus smoke exposed. Scale Bar = 40 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>A</bold>. Immunohistochemical reaction for dendritic cell fascin observed perivascularly on a lung of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. <bold>B</bold>. Dendritic cell volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups except \"CS +R1\"where due to technical problems N = 3; * = p &lt; 0.01 versus air exposed, + = &lt; 0.05 versus smoke exposed. Scale Bar = 40 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>A</bold>. Immunohistochemical reaction for B-lymphocyte CD45/B220 organized in a lymphoid follicle on a lung of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. <bold>B</bold>. B-cell volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups. * = p &lt; 0.01 versus air exposed, ++ = &lt; 0.01 versus smoke exposed. Scale Bar = 80 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>A</bold>. Immunohistochemical reaction for CD4+ T-lymphocyte CD4 seen perivascularly on a lung of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. × 250. <bold>B</bold>. CD4+ T-cell volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups. * = p &lt; 0.01 versus air exposed, + = &lt; 0.05 versus smoke exposed, ++ = &lt; 0.01 versus smoke exposed. Scale Bar = 80 μm.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>A</bold>. Immunohistochemical reaction for CD8+ T-lymphocyte CD8-α seen organized in a lymphoid follicle on a lung of a C57Bl/6J mouse after a 6 month cigarette smoke exposure. <bold>B</bold>. CD8+ T-cell volume density in the lung of C57BL76J mice exposed either to room air or to cigarette smoke for 6 months and treated or not with roflumilast at 2 doses. Air = air exposure; CS = cigarette smoke exposure; R1 = treated with roflumilast at the dose 1 mg/kg po; R5 = treated with roflumilast at the dose 5 mg/kg po; N = 5 in all groups. * = p &lt; 0.01 versus air exposed, ++ = &lt; 0.01 versus smoke exposed. Scale Bar = 80 μm.</p></caption></fig>" ]

[]

[]

[]

[]

[]

[]

[]

[]

[ "<graphic xlink:href=\"1471-2466-8-17-1\"/>", "<graphic xlink:href=\"1471-2466-8-17-2\"/>", "<graphic xlink:href=\"1471-2466-8-17-3\"/>", "<graphic xlink:href=\"1471-2466-8-17-4\"/>", "<graphic xlink:href=\"1471-2466-8-17-5\"/>", "<graphic xlink:href=\"1471-2466-8-17-6\"/>" ]

[]

{ "acronym": [], "definition": [] }

[]

[]

[]

[]

[ "<title>Conclusion</title>", "<p>It is obvious that SDQ will gain increasing popularity world wide, and an accurate translated Chinese version is important for researchers, clinicians and educationists who work in the Chinese population. There is an urgent need to review the translation of the Chinese SDQ version before more studies use it in the field. A more complete set of Chinese SDQ versions in both traditional and simplified Chinese forms of writing should be made available on the SDQ website.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<p>Strengths and Difficulties Questionnaire (SDQ) is a brief behavioural screening questionnaire for children and teenagers aged 3 to 16 years. It is available in 66 languages, and gaining more popularity world wide. Chinese translation of SDQ is available and has been used in clinical practice and research. We undertook the exercise to back-translate the current Chinese translation and it showed a number of differences compared to the original English SDQ. The differences and concerns include: (1) the flow and grammar of Chinese translation as well as wrongly written Chinese characters; (2) translated words that have deviated from the original meaning; (3) significant numbers of wording that are somewhat different from the original English version; (4) addition of auxiliary verbs that do not exist in original English version; and (5) the current Chinese SDQ is a general questionnaire for all age groups that does not observe the differences of wording that exist in the English versions.</p>", "<p>An accurate translated Chinese version is important for researchers, clinicians and educators who work in the Chinese communities. There is an urgent need to review the translation of the Chinese SDQ version before more studies use it in the field.</p>" ]

[ "<title>Full Text</title>", "<p>The results of a study in China on the validity, reliability and normative scores of a Chinese translation of the Strengths and Difficulties Questionnaire (SDQ) were recently published in your online journal on 29 April 2008 by Du <italic>et al </italic>[##REF##18445259##1##]. Findings on psychometric properties were mixed, especially in the areas of peer problems and self-rating by adolescents. Concern was also raised about the validity of the Chinese translation. This does not surprise us because we believe the answers lie in the Chinese translation of the SDQ.</p>", "<p>The SDQ is a brief behavioural screening questionnaire for children and teenagers aged 3 to16 years [##UREF##0##2##]. It was first tested in the United Kingdom and copy-righted by Goodman in 1997 [##REF##9255702##3##]. Several versions are available and each version may include one to three of the following: a) 25-item psychological attributes, b) 5-question impact supplement, and c) seven follow-up questions. It is available in 66 languages, which include three English versions for the USA, United Kingdom and Australia that differ slightly in the wording used and age specification <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.sdqinfo.com/b3.html\"/>[##UREF##0##2##].</p>", "<p>The Centre for Clinical Trials and Epidemiological Research at the Chinese University of Hong Kong and Iris Tan Mink had contributed greatly in the translation, back-translation and validation of the Chinese version <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.sdqinfo.com/d4a.html\"/>[##UREF##0##2##]. Currently the Chinese translation has three versions available for parent, teacher and student respectively and each version consists of the 25-item psychological attributes and impact supplement only. They were presumably translated from the United Kingdom's English version because the wording matches more closely than the other English versions [##UREF##0##2##]. It is available in traditional form of Chinese writing, commonly used in Hong Kong and Taiwan. Chinese communities in China and South East Asian countries use the simplified form of writing.</p>", "<p>Kou J, Du Y and Xia L published an article in Chinese in 2005 which concluded that the Chinese SDQ can be used to assess children and adolescents in Shanghai. This was derived from a validity and reliability study involving parents of 2128 students, using the three versions of Chinese SDQ and a retest 6 weeks later involving 47 of these parents [##UREF##1##4##].</p>", "<p>Despite reported findings by Du Y and Kou J [##REF##18445259##1##,##UREF##1##4##], we feel strongly that the current Chinese translation of SDQ has a number of differences compared to the original English SDQ. It is challenging and unscientific to compare any finding as a result of using two questionnaires with different languages and meaning. We therefore question the conclusion by Du Y <italic>et al </italic>about the use of Chinese version of SDQ in China.</p>", "<p>We recognize that translation of scientific and clinical materials is not an easy task. We believe much effort has been put forward in the first translation by people in the Chinese University of Hong Kong and Iris Tan Mink. Their contribution should be recognized and appreciated. However, the current Chinese translation of SDQ should be critically appraised and reviewed to provide a more accurate translated Chinese version of SDQ that is reliable for its users in the field.</p>", "<p>An exercise was undertaken by two authors of this letter (Toh TH and Ting TH) to back-translate the current Chinese SDQ independently. Ting TH had no prior knowledge of the SDQ before the translation. Both back-translations were similar, and they are presented in Additional files ##SUPPL##0##1##, ##SUPPL##1##2## and ##SUPPL##2##3##. The differences and concerns we found are as follow:</p>", "<p>1. The flow and grammar of the current Chinese SDQ are not smooth, with wrongly written Chinese characters.</p>", "<p>2. Some translated word has deviated from the original meaning.</p>", "<p>3. Significant numbers of wording, which include the word \"<italic>True</italic>\", used as the answer of all the 25 items, are somewhat different from the original UK English version.</p>", "<p>4. Auxiliary verb \"<italic>will</italic>\", \"<italic>can</italic>\" and \"<italic>very</italic>\" were added in many of the 25-item psychological attributes and the significance of adding these verbs is unclear.</p>", "<p>5. The current Chinese SDQ is a general questionnaire for all age groups, and does not observe some differences of wording that exists in the English versions.</p>", "<p>Examples and explanation of these major differences and concerns are included in Table ##TAB##0##1##.</p>", "<p>An online search on 12 June 2008, involving PsycINFO 1806, Ovid MEDLINE(R) 1996, CINAHL 1982 and EMBASE 1996 using \"SDQ or Strengths and Difficulties Questionnaire\" and \"Chinese or Mandarin or China or Taiwan or Hong Kong\" as key words have shown numerous publications quoting the use of SDQ Chinese translations in China and Hong Kong. It was used as a measurement tool for interventional trials [##UREF##2##5##,##REF##14979223##6##] and descriptive epidemiological studies [##REF##17439441##7##,##REF##18247298##8##]. Clinicians have also used it as a screening tool to prioritise psychiatry services [##UREF##3##9##] and to compare findings on psychometric properties of parent ratings on the Chinese version of the Swanson, Nolan, and Pelham IV scale [##REF##18286459##10##].</p>", "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>Back-translation of the Chinese SDQ was performed by Toh TH and Ting TH. In addition all authors have contributed towards the writing and approval of this letter.</p>", "<title>Availability &amp; requirements</title>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.sdqinfo.com/b3.html\"/></p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.sdqinfo.com/d4a.html\"/></p>", "<title>Supplementary Material</title>" ]

[]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Summary of differences found between original english (UK) SDQ and Chinese translation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"left\">Major Differences and Concerns</td><td align=\"left\">Affected Items/Questions &amp; Examples</td><td align=\"left\">Implications/<break/>Suggestions</td></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">Chinese grammar/flow and wrongly written Chinese characters</td><td align=\"left\">○ Items 2, 7, 12 &amp; 23 in Parent/Teacher version<break/>○ Items 2, 12, 14, 17 &amp; 23 in Student version<break/>○ Question 1 to 4 of the impact supplement in all three versions<break/>○ Two wrongly written Chinese characters (Item 15 in Student version and Question 4 in impact supplement, Parent/Teacher versions)</td><td align=\"left\">Can be improved and rephrased to a more comprehensible language and more easily understood by a lay audience</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">2</td><td align=\"left\">Deviation of translated word</td><td align=\"left\">○ Items 4, 7, 9, 12 &amp; 17 in Parent/Teacher version*<break/>○ Items 4, 8, 9, 10, 11, 12, 20 &amp; 25 in Student version*<break/>○ Question 1, 3 &amp; 4 of the impact supplement in all three versions*<break/>○ Introductory paragraph of the Student version*</td><td align=\"left\">These words need to be reviewed and matching the original English version</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\" colspan=\"\">3</td><td align=\"left\">Translated word that is \"somewhat different\"</td><td align=\"left\">○ The answers to the 25 items, \"<italic>true</italic>\"^†<break/>○ Items 3, 5, 6, 8, 13, 24 &amp; 25 in Parent/Teacher version^‡<break/>○ Items 6, 18 &amp; 23 in Student version^‡<break/>○ Question 1 of the impact supplement in all three versions^‡</td><td align=\"left\">These words require further consideration and the significance of the differences is unclear.</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">4</td><td align=\"left\">Addition of auxiliary verbs (\"<italic>will\", \"can\" </italic>and <italic>\"very\"</italic>)</td><td align=\"left\">○ Items 16, 21 &amp; 22 in Parent version<break/>○ Items 16 &amp; 21 in Teacher version<break/>○ Items 16, 17, 21, 22 &amp; 24 in Student version</td><td align=\"left\">The significance of these verbs is unclear, ideally they should be removed</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\">5</td><td align=\"left\">Age-unspecific versions</td><td align=\"left\" colspan=\"2\">The English versions are divided into different age groups, with some differences in wording. E.g., \"<italic>often argumentative with adults</italic>\" in the 3–4 years old group is represented by \"<italic>often lies or cheats</italic>\" in the 4–16 years old group. Current Chinese SDQ does not observe these differences because one version is used for all age groups. In this example, the item concerned was translated as \"<italic>often lies or cheats</italic>\" only.</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Appendix A.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Appendix B.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>Appendix C.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>* For examples, instead of \"<italic>fights</italic>\", it was translated as \"<italic>quarrel</italic>\" and \"<italic>argue</italic>\"; instead of \"upset\", \"<italic>unwell</italic>\" and \"<italic>sad</italic>\" were used. \"<italic>I have one good friend or more</italic>\", was translated as \"<italic>I have one or a few good friends</italic>\"; and \"<italic>do the difficulties upset or distress your child?</italic>\" became \"<italic>are these difficulties perplexing/puzzling/disturbing you?</italic>\"</p><p>^†\"<italic>Not True</italic>\", \"<italic>Somewhat True</italic>\" and \"<italic>Certainly True</italic>\" – the answers to the 25 items, \"<italic>true</italic>\" was translated as \"<italic>tallying/accord or keeping with</italic>\"</p><p>^‡For examples \"<italic>often seems worried</italic>\" was translated as \"<italic>often exhibit/display sign of anxiety</italic>\"; \"<italic>tearful</italic>\" was translated as \"<italic>crying</italic>\".</p></table-wrap-foot>" ]

[]

[ "<media xlink:href=\"1753-2000-2-23-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1753-2000-2-23-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1753-2000-2-23-S3.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>The Ministry of Health and Social Services in the province of Quebec, Canada, has established the following breastfeeding targets for 2007: 85% of infants breastfed at hospital discharge; 70%, 60% and 50% of infants breastfed at two, four and six months respectively; and 20% of infants breastfed at one year [##UREF##0##1##]. A recent report indicated that the prevalence of any breastfeeding in Quebec in 2005 was close to these goals, with a rate of 85% at hospital discharge and 47% at six months [##UREF##1##2##]. Breastfeeding rates for the Greater Quebec City area were similar to those for the province as a whole [##UREF##1##2##]. However, these rates were still far from those of other industrialized countries such as Norway (80% at six months) and Sweden (70% at six months) [##REF##15705244##3##]. In addition, exclusive breastfeeding rates for the province of Quebec (3% at six months) [##UREF##1##2##] remain far below the 10% goal set by the Ministry [##UREF##0##1##].</p>", "<p>Health is a provincial jurisdiction in Canada, which means Quebec is in charge of determining which health services it offers, including those related to breastfeeding. Since Quebec has a public healthcare system and public health insurance, most health services are provided free of direct charge or at minimal cost. Breastfeeding services normally available in Quebec include prenatal courses and systematic one-time postnatal home visits by nurses from local community services centers. In some regions, including Greater Quebec City and Trois-Rivières, nurses may make more than one visit if necessary, for example in the event of breastfeeding difficulties. Breastfeeding support groups are also active in most regions of Quebec. Lastly, several newly created breastfeeding clinics staffed by lactation consultants and general practitioners have been established in the province (Lapointe and Martel, regional breastfeeding health officers, personal communication, 2008).</p>", "<p>A study of 407 women in the Greater Quebec City area in the late 1990s revealed that many women experienced problems including cracked nipples, low milk supply, latching difficulties or breast refusal, blocked ducts, hungry baby, frequent feedings, frequent baby crying, mastitis, and sore nipples [##UREF##2##4##]. Among the main reasons given by these women for cessation of breastfeeding were problems such as milk insufficiency (perceived or real), weight issues of baby (insufficient weight gain), lack of time for the mother, and breast problems [##UREF##2##4##].</p>", "<p>Different programs and interventions aim to promote breastfeeding or overcome breastfeeding difficulties. Scientific evidence indicates that among the interventions shown to be beneficial for prolonging breastfeeding duration, breastfeeding support by skilled peers and professionals is effective when provided to women in a proactive way. A combination of information, support and guidance, as well as unrestricted mother-baby contact and unrestricted feeding are other effective interventions [##UREF##3##5##, ####REF##11847902##6##, ##REF##15023925##7##, ##UREF##4##8##, ##REF##14629324##9####14629324##9##].</p>", "<p>Few studies of breastfeeding clinics in industrialized countries have been identified [##REF##11461023##10##, ####REF##11845734##11##, ##REF##17244353##12##, ##REF##16881907##13##, ##REF##9429364##14##, ##REF##16356608##15##, ##REF##18405394##16##, ##REF##18333766##17####18333766##17##]. These clinics aim to increase breastfeeding duration and diminish the prevalence of difficulties [##REF##11461023##10##,##REF##11845734##11##,##REF##9429364##14##]. According to the research findings, women were satisfied with these clinics. They felt that the clinics provided valuable knowledge about breastfeeding and could help them prolong the duration of breastfeeding and find solutions to the difficulties they experienced [##REF##11461023##10##,##REF##11845734##11##,##REF##9429364##14##,##REF##16356608##15##].</p>", "<p>At the time of this study, there was one breastfeeding clinic in Quebec City, located at the <italic>Centre Hospitalier Universitaire de Québec </italic>(CHUQ). It was established in 2004 by the Quebec City regional public health department and the CHUQ at the request of field workers who wanted to provide better support to women with acute breastfeeding problems. At that time, the clinic was funded in part by the regional public health department and in part by the CHUQ [##UREF##5##18##]. Referrals are mandatory to access the services of the clinic. Women using the facility are seen by an International Board Certified Lactation Consultant (IBCLC) and a physician. According to the satisfaction forms collected in 2004–2005, women were highly satisfied with the clinic for various reasons, including a warm reception, waiting time, usefulness of the information and treatments received, and overall satisfaction with their experience at the clinic [##UREF##5##18##].</p>", "<p>This paper aims to describe the breastfeeding experience of women experiencing major breastfeeding difficulties and in particular, the experience of women using the services of the Quebec City Breastfeeding Clinic.</p>" ]

[ "<title>Methods</title>", "<title>Design</title>", "<p>This descriptive study conducted in 2006 used a mixed methodology. The quantitative component comprised a telephone questionnaire and statistical analysis of the results while the qualitative component consisted of individual semi-structured interviews and a content analysis of the verbatim interview transcripts. This study was part of a larger research project which aimed to evaluate the effects of the Quebec City Breastfeeding Clinic on breastfeeding duration and satisfaction among women in comparison with women who did not receive clinic services [##UREF##6##19##].</p>", "<title>Sample</title>", "<p>This study was conducted with French speaking women aged 20 years or older having experienced major breastfeeding difficulties. These women were from two regions – the Greater Quebec City area and Trois-Rivières – where breastfeeding rates are similar [##UREF##1##2##]. The women living in the Greater Quebec City area had used the services of the Quebec City Breastfeeding Clinic. The women from Trois-Rivières, a town located 200 km southwest of Quebec City, had had access to standard breastfeeding services, as described in the background section above, but not to a breastfeeding clinic.</p>", "<p>To be included in the study, women had to be primiparous, have given birth to a healthy, full-term baby, and have experienced major problems with breastfeeding during the first two months of their baby's life. Problems were considered major if they were serious enough to compromise ongoing breastfeeding and if all steps had been taken in the course of normal follow-up to try to solve them. Examples included excessive pain during latching (possible causes: thrush, cracked nipples, vasospasms, breast infections); infant weight loss that could potentially compromise baby's health (possible causes: low milk supply, improper latching, breast refusal, difficulty staying latched); and baby's inability to breastfeed (possible causes: all of the above, as well as other problem situations such as tongue tie (ankyloglosia)). Women from Quebec City had to have given birth between July 1, 2004, and August 31, 2005. Given the smaller population of Trois-Rivières, the period was extended from May 1, 2004, to December 31, 2005, for women from this city. Women who had given birth to an infant born with an abnormality or major illness were not included in the study.</p>", "<p>Women from Quebec City were recruited by means of a systematic sampling method with a random start: an initial record was randomly chosen from the list of all the records of children having attended the breastfeeding clinic in the given period, followed by every fourth record in sequence, stratified for the locations (2) where the clinic was held. Once eligibility criteria were checked, a member of the research team (MSP) phoned the mothers to invite them to participate in the study. For Trois-Rivières, the women were identified from all birth records for the eligibility period kept at local community service centers. All those who satisfied the selection criteria were contacted by phone by a member of the research team (MSP). It was also determined at this time whether they had experienced major breastfeeding difficulties. All the women from Trois-Rivières who met the eligibility criteria and agreed to participate were included in the study.</p>", "<p>The subsample of women who participated in semi-structured interviews in both cities was selected using a purposeful sampling method designed to maximize variations in breastfeeding duration (0 to 12 months and more) and the education level of participants (vocational diploma or less to university degree or more).</p>", "<p>The sample for the study, which was conducted as part of a Master's Degree program, is relatively small: approximately 50 women per group for the telephone survey and 6 women per group for the interviews.</p>", "<title>Instruments and data collection</title>", "<title>Telephone questionnaire</title>", "<p>The questionnaire was pre-tested with five women from the Greater Quebec City area. After readjustments, it was administered to women from both cities. The questionnaire comprised 80 questions and examined sociodemographic, economic, clinical, and psychosocial characteristics, as well as the support respondents received, their breastfeeding experience, and their experience at the Quebec City Breastfeeding Clinic. The majority of questions were drawn up specifically for the study. However, the wording for certain questions like those on sociodemographic characteristics of the mother were based on those used by major Canadian and Quebec studies [##UREF##7##20##, ####UREF##8##21##, ##UREF##9##22##, ##UREF##10##23##, ##UREF##11##24##, ##UREF##12##25####12##25##]. Other questions, notably those on breastfeeding, were based on a telephone questionnaire used in an earlier study conducted in the Greater Quebec City area in 1998 [##UREF##2##4##]. Questions on the respondents' level of satisfaction with their breastfeeding experience, the healthcare professionals involved, and the interventions they received were measured on a scale of one to five (1 = highly dissatisfied, 5 = highly satisfied). See additional file ##SUPPL##0##1##: <italic>telephone questionnaire </italic>for themes from the questionnaire and for sample questions. A survey firm administered the telephone questionnaire to all the women. It was decided to use a survey firm to minimize the length of the data collection period. The firm chosen (SOM Surveys, Opinion Polls and Marketing) has a good reputation in the Quebec health research field. Interviewers received training on the study context and the questionnaire in the presence of a member of the research team (CL). Administering the telephone questionnaires took around 20 minutes per respondent.</p>", "<title>Semi-structured interview</title>", "<p>In this study, data from the qualitative component provided information that allowed for a better understanding of the breastfeeding experience [##UREF##13##26##]. The interview scenario included 17 questions on the respondent's personal history of breastfeeding, facilitating factors and obstacles to breastfeeding, social support, the experience at the Breastfeeding Clinic, the respondent's opinion about a potential clinic for Trois-Rivières and other relevant information related to the breastfeeding experience (see additional file ##SUPPL##1##2##: Interview grid). The individual interviews where conducted by a member of the research team (CL) at Université Laval for the women in Quebec City, and at a local health and community services center for the women of Trois-Rivières. The one hour interviews were taped and transcribed.</p>", "<title>Ethical considerations</title>", "<p>Before administering the telephone questionnaire, interviewers explained the study to the women. A consent form was read aloud and women who wanted to participate gave their verbal consent. The same process applied to the semi-structured interviews, but with written consent. The study was approved by the Clinical Research Ethics Committee at Centre Hospitalier de l'Université Laval. Ethical approval was also obtained from the Health and Social Services Center in Trois-Rivières.</p>", "<title>Data analysis</title>", "<p>The responses to the telephone questionnaire were described using frequency tables. Chi-square and Fisher's exact tests were employed to compare proportions of general characteristics of participants (age, marital status, education, and income) by their city of origin. A probability level of &lt; 0.05 was used to establish statistical significance. SPSS 13.0 software for Windows 2004 [##UREF##14##27##] was used to perform the quantitative analysis.</p>", "<p>The semi-structured interviews were fully transcribed, then subjected to a content analysis [##UREF##15##28##]. This aimed to determine the meaning of the message studied, and consisted of classifying the transcribed elements and codifying them in various categories in order to bring out the different characteristics and achieve better understanding of the exact meaning. L'Écuyer general procedures for content analysis were applied [##UREF##15##28##]: 1) preliminary reading and establishment of a list of statements; 2) choice and selection of units of classification; 3) categorization and classification; 4) quantification and statistical processing of the data; 5) scientific description; and 6) interpretation of the results. In the framework of this study, step four was omitted. Step three involved mixed categories, with pre-determined categories based on scientific literature and others based on emerging data. NVivo 2.0 software, 2002 [##UREF##16##29##] was used to help code the data. An intracoder reliability measure was performed using the Miles and Huberman formula [##UREF##17##30##]. This showed a percentage of 74% and after discussion, a percentage of 100%.</p>", "<p>Conceptual benchmarks were used to support the analysis. The theory of planned-based behavior had already been found useful for studying breastfeeding determinants [##REF##15767196##31##, ####REF##9835488##32##, ##REF##15811106##33####15811106##33##]. According to this theory [##UREF##18##34##], behavior is determined by intention and perceived behavioral control. Intention is self-determined by attitude, subjective norms, and perceived behavioral control. Two other concepts of this model, facilitating factors and reinforcing factors, were added by Godin [##UREF##19##35##, ####UREF##20##36##, ##UREF##21##37####21##37##]. For this study, Godin's conceptual framework (Figure ##FIG##0##1##) served to develop interview questions that would help identify factors influencing women's experience of breastfeeding. It subsequently served to organize the interview data and also facilitated understanding of the influencing factors in the discussion of interview results.</p>" ]

[ "<title>Results</title>", "<title>Description of the sample</title>", "<p>One hundred and forty women were selected to take part in this study. Of the 72 women selected from the Greater Quebec City area, 13 could not be reached, five refused to participate for reasons unknown, and two were excluded because they did not meet eligibility criteria. This left a subtotal of 52 women, including the five women who took part in the pretest; their responses were counted, except for answers to five questions that had been considerably modified after the pretest. For Trois-Rivières, 68 women were selected for the study. Of this number, 27 could not be reached, including 20 whose eligibility for the study was unknown. Three women refused to participate and four others were excluded, leaving a total of 34 participating women. Of the 86 women who completed the study, 12 took part in the semi-structured interviews, six from Greater Quebec City and six from Trois-Rivières. The final refusal and loss rate was 28% for Greater Quebec City and 50% for Trois-Rivières.</p>", "<p>The sociodemographic and economic characteristics of the participants, namely age, marital status, education level, and family income, shown in Table ##TAB##0##1## suggest no baseline differences between the two groups.</p>", "<title>Description of the breastfeeding experience</title>", "<p>According to the data collected with the telephone questionnaire, women reported experiencing several types of breastfeeding difficulties as presented in Table ##TAB##1##2##. Painful nipples/breasts, low milk supply, insufficient infant weight gain, absence of infant bowel motions, and latching problems and breast refusal were the most frequent breastfeeding problems identified by women.</p>", "<p>Reasons for cessation of breastfeeding were also similar for women: latching problems or breast refusal, low milk supply, and pain were the most frequent reasons (Table ##TAB##2##3##). Other important reasons for cessation were the return to work, school, or daycare and the attainment of breastfeeding objectives or the belief that the infant was old enough to stop breastfeeding.</p>", "<p>Information gathered during the 12 individual interviews (see Table ##TAB##3##4## for a list of the main categories) also showed that some women experienced other, more specific problems. In certain cases, these affected them personally. Examples included fatigue, anemia, and significant postpartum pain: \"I'd had a big episiotomy, I had anemia [. . .] and I was really weak. I don't think that was much help either\" (QC6-82 – 10 days. Quote is our translation as are all subsequent quotes in this paper, and the period refers to the baby's age at the time of breastfeeding cessation). In other cases, infant health problems were the issue: \" [. . .] he was too weak. His little heart was weak, his breathing weak, I didn't have a choice. I was feeding five minutes per breast, then I had to stop and quickly give him bottled milk\" (QC5-21 – 3 months). Many of the women who experienced these difficulties also affirmed having felt sadness, discouraged and concern at the time: \"The breastfeeding wasn't going all that great, and I felt really sad because I didn't want to give up.\" (QC1-16 – 15 months) Potential links between the difficulties they experienced and their physical well-being were not addressed by the women.</p>", "<p>In addition, although some women were satisfied with their experience and expressed no regrets for having ceased breastfeeding, many of those interviewed expressed disappointment, sadness, and regret in having stopped: \" [. . .] I was sad, I cried a lot. It lasted almost a month. A good four weeks after I'd stopped breastfeeding, I cried. At night, I'd go to bed and shed a little tear\" (QC5-86 – 3 months). For others, cessation came as relief, since with bottle feeding, infants would gain weight and women would be less tired: \"It was really a big relief [. . .] and it was overnight. Once I made my decision, everything was fine afterwards. I felt better\" (TR3-56 – 6 months).</p>", "<p>Satisfaction with regards to the breastfeeding experience differed among the women who took part in the interviews. For almost half of them, it was a wonderful experience and they were very satisfied. As one woman said: \"I'm totally satisfied, and if I have another child, I'll do it again for sure\" (QC5-70 – 3 months). Others, especially those unable to overcome their difficulties, found the experience difficult and felt dissatisfied and disappointed: \"But that's the thing, you see, part of me was dissatisfied because [. . .] my problem never really got solved\" (TR6-42 – 6 weeks). Half of the women even felt guilty for ceasing breastfeeding or perceived cessation as a failure, as the following accounts show: \"But you feel really guilty, too, because you've read everywhere that it's the best thing, so it's really tough. You say to yourself, man, and you feel guilty\" (QC6-12 – 10 days). \"I took it as a failure, because I wanted to give this child the best of everything. For me, it was a failure not to live up to my ideal\" (TR2-43 – 2 months).</p>", "<title>Personal influences</title>", "<p>During the interviews, three women affirmed that they themselves were the most important person influencing their own breastfeeding experience: \"I'd have to say I was [the most important person]\" (TR5-116-118 – 6 months). In fact, a wide variety of personal characteristics or aspects could influence a woman's experience. First of all, intention to breastfeed was a major factor. From the beginning, certain women firmly intended to breastfeed their infant, sometimes even having a set goal in mind for the duration: \"I had this idea in mind that I would breastfeed her for six months\" (QC2-70 – 8 months). The firmness of these women's intentions gave them the motivation to traverse their difficulties and reach their goals. As one woman put it: \"No, I wanted it so much (laugh). Everything that looked like an obstacle, I got rid of it. For me, breastfeeding came first and everything else was secondary, so, I don't know what else could have stopped me from breastfeeding\" (QC5-162 – 3 months). Other women, however, were less certain regarding their intention to breastfeed and were clearly not as motivated: \"Anyway, when I was pregnant, I wasn't sure I wanted to breastfeed\" (TR1-40 – 3 days).</p>", "<p>Women's attitudes toward breastfeeding were also important. Almost all the women mentioned the benefits of breastfeeding for society, infants, and women. They also mentioned the practical aspects of breastfeeding and its low cost, as well as other factors influencing the intention to initiate or continue breastfeeding as expressed in this statement: \"It's always ready, it's always at the right temperature, there's nothing to sterilize. No matter where you are, you can always breastfeed\" (QC1-12 – 15 months).</p>", "<p>In addition, in light of what women said during the interviews, determination and perseverance appear to have influenced their experience: \" [. . .] I told myself, 'Hey, I can do this, too. I want to breastfeed, I've got enough milk, the baby's feeding well, there's no reason to stop\"' (TR6-65 – 6 weeks). Determination helped certain women to continue breastfeeding, even though some of them had told themselves at the beginning that they would not persist if they found it was not working: \"It wasn't really working for me, but I really stuck with it\" (TR2-39 – 2 months). Their determination and perseverance helped them overcome the effects of health problems and tiredness. One woman said, \"Because of how tired I was, I wouldn't have been able to handle breastfeeding any longer. I was exhausted\" (QC6-71 – 10 days). Hope that problems would cease and that breastfeeding would become easier over time helped other women to continue breastfeeding: \"At the start, what really kept me going was the constant hope that things would get better, and that it wouldn't hurt as much\" (TR6-34 – 6 weeks). Some women expressed discomfort and shyness that sometimes led them to refrain from breastfeeding in public: \"I'm not necessarily all that comfortable about breastfeeding in public\" (TR3-100 – 2 weeks).</p>", "<p>Most women really appreciated the contact, closeness, and bonding with their infant during breastfeeding. For some women, this contact was a motivation to pursue breastfeeding as this statement shows: \"I liked the contact with the baby [. . .]. So that's why I kept at so long, because if I had listened to myself, just from a physical standpoint, I would have breastfed for one week, than stopped\" (TR6-34 – 6 weeks). However, for one woman, the contact was spoiled by some major difficulties and ceased to be a motivation factor: \"So I'd reposition the baby, bring it back to the breast, try again, and all that time I'd forget about contact [. . .]. That lovely moment became pretty technical, and that took away some of the charm\" (QC6-36 – 10 days).</p>", "<title>Social influences</title>", "<p>Apart from aspects directly related to the women themselves, other factors such as social support contributed to their breastfeeding experience. According to the telephone questionnaires, as shown in Table ##TAB##4##5##, women's partners were the ones who encouraged and supported them the most throughout their experience. They were followed by nurses from local community services centers who visited the women in their homes, by clinicians at the breastfeeding clinic (named only by women from Quebec City) and then by mothers, friends, and hospital nurses.</p>", "<p>According to the semi-structured interviews, social support – whether formal (health professionals) or informal (partner, family and friends) – included both moral and physical support. Moral support was expressed through encouragement, reassurance, listening and a positive attitude, all of which helped reinforce the women's determination to pursue breastfeeding. For example, one woman said: \"It was because she was a nurse who really believed in breastfeeding. She'd say, 'Don't give up.' She would encourage us all the time and she'd push us to continue\" (TR4-32 – 3 weeks). However, men could undermine the women's determination if they did not support their partner in the pursuit of breastfeeding as suggested by this following account: \"My husband was not all that encouraging, because like I said before, he wanted to participate and was looking forward to giving the bottle\" (TR1-59 – 3 days). Health professionals could also have a negative influence when their comments and attitudes were discouraging or made women feel guilty, or when their attitudes were too pro-breastfeeding or lacked tact. One woman made the following remark which also hints at the fragility of women at this particular time of their life: \"Sometimes they (the nurses) can be a bit insensitive, I found they weren't always tactful\" (TR1-67 – 3 days).</p>", "<p>Physical support included advice and tips related to breastfeeding, help with breastfeeding management, and help with housework (cleanup, cooking, etc.), as described in statements like these: \"They (the hospital nurses) helped at the beginning, you know, with positions for feeding, right away at the hospital\" (TR3-66 – 2 weeks). \"My mom came to the house to give me a hand. It could be a bit overwhelming at times, so she'd clean up, do the wash, do a bit of cooking. It was a big help\" (QC2-97 – 8 months). Nevertheless, in cases where health professionals did not detect a problem or gave conflicting or erroneous advice, they hampered the breastfeeding experience, as the following comment suggests: \"One (nurse at the hospital) has her technique, another has hers. So you do what the last one told you, and then you're told it's wrong\" (TR1-67 – 3 days).</p>", "<p>Furthermore, two women felt that they had been left to themselves after returning home, or did not use the services available. This may have had a negative effect on their experience. One of them said: \"No one came to see me to give me tips, help out, or show me positions. I was kind of left to myself, but I didn't ask for help either\" (TR1-59 – 3 days).</p>", "<p>In addition to the influence of support on the breastfeeding experience, the interviews also revealed that women felt significant social pressure to breastfeed. Some women explained that it was mostly the positive aspects of breastfeeding that were promoted, and that the more difficult aspects were not always addressed. For almost half the women, there was so much information related to breastfeeding that they felt obligated to breastfeed and hesitated to stop because of all the pressure. One women said: \"I felt that I was not a good mother if I was not breastfeeding [. . .] I found there was a lot of pressure. Social pressure\" (TR1-28 – 3 days). However, this pressure was never mentioned in relation to the breastfeeding clinic.</p>", "<title>Breastfeeding clinic influences</title>", "<p>Breast or nipple pain, latching difficulties or breast refusal, low milk supply, and insufficient weight gain and sucking difficulties were the main reasons evoked by the study participants for consulting the Quebec City Breastfeeding Clinic, as shown in Table ##TAB##5##6##.</p>", "<p>Women seemed highly satisfied with the clinic. As presented in Table ##TAB##6##7##, the telephone questionnaire shows that the majority (over 85%) of women were satisfied or highly satisfied with the services and interventions provided by the clinic and the clinicians, either the IBCLC or the physician. The participants also believed that the clinic had helped them to reach (75%) and even surpass (48%) their breastfeeding objectives (Table ##TAB##6##7##). In addition, they believed that it had increased their satisfaction with their overall breastfeeding experience (85%).</p>", "<p>During the semi-structured interviews, participants noted that there were two kinds of services offered at the breastfeeding clinic. The first was the identification of the problems that led women to visit the clinic as reported by this woman: \"When you arrive, they ask you why you've come. You explain your problem, then they ask you to show them how your baby feeds\" (QC4-162 – 3 months). The second was the interventions themselves and the breastfeeding tips given. These included practical advice as well as encouragements, reassurance and explanations related to breastfeeding problems and their possible solutions. For example, women would recount: \"He gave me a suggestion to help the baby. It was a little bottle with a tube that I would slip in at the edge of her mouth while she was feeding, because she was drinking less and less milk [. . .] So with that, she had more milk, and her appetite came back\" (QC2-10 – 8 months); \"It still wasn't working, but at the clinic, they told me 'She's starting, it's not so bad to take the breast away every once in a while at the start of a feeding or in the middle. Don't be discouraged\"' (QC3-44 – 4 months).</p>", "<p>According to these women, the visits to the clinic had a positive influence on the breastfeeding experience in two ways. The first was in terms of physical support, which included the identification of problems and their resolution or temporary solution. As reported by one participant: \"If this advice had not worked, she wouldn't have gained back her weight and I would have put her on the bottle for sure\" (QC2-186 – 8 months). The second was in terms of moral support, which included encouragements, reassurance and the positive way in which the clinicians presented the breastfeeding experience. As one woman said: \"At the breastfeeding clinic, it was like there was no problem [. . .] They were really reassuring on this. It was 'try, try, everyday [. . .] and you will succeed.' They were really confident\" (QC3-79 – 4 months).</p>", "<p>In the semi-structured interviews, the participants again expressed their satisfaction with the clinic: \"I couldn't have asked for anything more. I found it very suitable, it was perfect for me\" (QC5-252 – 3 months). However, women did show some hesitation regarding various organizational aspects, including parking, waiting time, and the fact that the clinic is located in a hospital setting: \"There were waits sometimes. You think about the parking when that happens\" (QC2-203 – 8 months). However, waiting also had its advantages: \"You're never rushed. So the disadvantage of not having your appointment 'on time,' so to speak, works out to your advantage when it's your turn, because you're not hurried and they take time to really listen\" (QC3-160 – 4 months). Participants also talked about their satisfaction with the clinicians, who were greatly appreciated for their kindness, empathy, listening skills, warmth, and dedication, as well as for all the information they gave.</p>", "<p>The women who attended the clinic unanimously agreed that it was a useful service. They also felt it would be useful for other women experiencing breastfeeding difficulties. As one woman put it: \"They were such a big help. It seems to me that if anyone else had breastfeeding problems, it would be much easier for her to consult them. She'd get lots of information and help, plus good support\" (QC2-212 – 8 months).</p>", "<p>Interestingly, women from Trois-Rivières thought a breastfeeding clinic would be useful for their region because of the staff's specialized expertise and because of the wide range of breastfeeding problems they were familiar with. They felt that there were gaps in the breastfeeding services in their region that required a specialized service like a breastfeeding clinic. One woman said: \"For me, I think it would be a good idea to have centers like this in various areas. If we want to continue to promote breastfeeding, it takes support. I mean, there are resources and things here, I'm not trying to say there's nothing, but something a bit more specialized wouldn't hurt\" (TR6-129 – 6 weeks).</p>" ]

[ "<title>Discussion</title>", "<p>The women who participated in this study are comparable in terms of age and marital status to a larger group of over 4,000 Quebec women who gave birth in 2005 [##UREF##1##2##]. However, they appear to be more educated than Quebec mothers on average, with 55% holding university degrees compared to 35% at the provincial level. Family income was also higher, with 70% having a family income exceeding $50,000 compared to 47% for Quebec households in general [##UREF##1##2##].</p>", "<p>The major breastfeeding difficulties experienced by women, such as breast and nipple pain, low milk supply, latching problems, and so on, were similar to those mentioned in a study conducted in the Greater Quebec City area in the late 1990s [##UREF##2##4##]. In addition, in our study, the reasons for ceasing breastfeeding coincided with the difficulties experienced by other women. These reasons, along with the others mentioned (return to work or school, infant health problems), are comparable to the ones found in other studies in Canada [##REF##16190322##38##], the province of Quebec [##UREF##22##39##,##REF##16113021##40##], and the Greater Quebec City area [##UREF##2##4##].</p>", "<p>Intentions and attitudes regarding breastfeeding appear to be significant factors influencing the experience. In fact, firm intentions to breastfeed gave women the motivation they needed to face difficulties. According to different studies, prenatal breastfeeding intention is an important determinant of both breastfeeding initiation and duration [##REF##15811106##33##,##REF##11843016##41##, ####REF##10197366##42##, ##REF##15296585##43##, ##REF##8568056##44####8568056##44##]. The moment the decision is made, intentions regarding duration seem to be linked with breastfeeding duration [##REF##11843016##41##, ####REF##10197366##42##, ##REF##15296585##43####15296585##43##]. Positive attitudes toward breastfeeding have also been associated with the initiation and longer duration of breastfeeding [##REF##15811106##33##,##REF##11843016##41##]. Moreover, these elements correspond to certain concepts from our conceptual framework (Figure ##FIG##0##1##), which holds that attitudes toward a behavior are predictive of intentions to adopt the behavior, and that those intentions are in turn predictive of actual adoption, i.e., breastfeeding continuation. In addition, determination and perseverance to overcome breastfeeding challenges and difficulties are other notions that have been addressed in other studies [##REF##11843016##41##].</p>", "<p>With the exception of the clinicians at the breastfeeding clinic, the sources of social support mentioned by women in this study were similar to those mentioned by women in other studies included in a meta-analysis of qualitative studies [##REF##16504899##45##] and by women in the Greater Quebec City area [##UREF##2##4##]. These sources include partners, nurses from local community services centers, mothers, friends and hospital nurses. Moreover, a study conducted in the province of Quebec found that women's entourages influenced their decision to breastfeed, and that women generally perceived their entourage as being in favor of breastfeeding [##UREF##22##39##]. In addition, informal sources of support (partner, family, friends, peers) and formal sources (lactation consultants, nurses, physicians) have been shown to affect both initiation and continuation of breastfeeding [##UREF##22##39##,##REF##11843016##41##,##UREF##23##46##].</p>", "<p>Unfortunately, as mentioned by some participants in this study, health care professionals can sometimes be a negative influence when they provide women with inconsistent, inaccurate, inadequate, or conflicting breastfeeding information and recommendations [##REF##11843016##41##,##REF##16504899##45##,##REF##11281933##47##, ####REF##12746032##48##, ##REF##7699527##49####7699527##49##]. It is therefore important to ensure that health professionals are properly trained with respect to breastfeeding and that women have access to optimal services consistent with the <italic>Baby Friendly Hospital Initiative </italic>and with <italic>The Baby Friendly Initiative in the Community </italic>recommendations [##UREF##24##50##,##UREF##25##51##].</p>", "<p>Sources of social support and the way they influence the breastfeeding experience are analogous with some of the items of the conceptual framework (Figure ##FIG##0##1##). In fact, positive support from family and health professionals is similar to the perceived subjective norm influencing intentions to initiate and continue breastfeeding. Advice and interventions provided by a woman's entourage and by health professionals, as well as help with housework, are other facilitating factors, while encouragement and reassurance are reinforcing factors.</p>", "<p>The influence of social pressure on the breastfeeding experience was alluded to by three women. In other studies, women have reported feeling pressure both to start and continue breastfeeding against their own wishes [##REF##11281933##47##]. In a qualitative study conducted in England, women also described feeling unprepared for the realities of breastfeeding and said they would have liked to have had more information about the possible inconveniences [##REF##16128971##52##]. Greiner considers that priority should be given to protective and supportive strategies for breastfeeding, rather than to promotion strategies. In fact, he notes that in general, \"protective programs put pressure on government and industry, supportive strategies put pressure on the health care system, on networks of women and on employers, while promotion strategies [. . .] can [not easily] avoid putting pressure directly on women themselves\" [##UREF##26##53##]. Because of this, some women in our study may have felt obligated to breastfeed and hesitated to stop. In addition, some women felt guilty for stopping breastfeeding sooner than they planned and perceived this cessation as a failure, as was the case elsewhere [##REF##10810844##54##]. Similarly, an Australian qualitative study found that women may feel confusion, self-doubt and guilt when confronted with incompatible expectations between themselves and other people [##REF##12746032##48##].</p>", "<p>Satisfaction rates for the Quebec City Breastfeeding Clinic indicate that over 80% of women in our study were satisfied or highly satisfied with the clinic's staff and services and felt it had helped them increase their satisfaction with their breastfeeding experience. The high satisfaction rates were similar to those recorded for women attending other breastfeeding clinics. At one Canadian breastfeeding clinic in Ontario, over 90% of the 164 respondents reported satisfaction ratings of good or excellent [##REF##11461023##10##]. The clinic helped them feel more confident and positive with regards to their breastfeeding experience, enhance their knowledge of breastfeeding, and prevent or overcome difficulties. Over 70% of the respondents also believed that the clinic had helped them to breastfeed for a longer period [##REF##11461023##10##]. At another Canadian breastfeeding clinic in Saskatchewan, 100% of the 43 respondents were satisfied with the interpersonal aspects of the center and over 90% with the information and support they received. Respondents attributed their satisfaction to the advice given, the participative approach, the quality of information provided, the support, encouragement and reassurance received, and the knowledgeable staff [##REF##11845734##11##]. Similarly, mothers using a breastfeeding clinic in British Columbia, Canada, gave the facility an average rating of 8.7 out of 10 (10 = extremely satisfied) [##REF##9429364##14##]. In an Australian clinic, satisfaction survey showed that most respondents were satisfied with the clinic and felt that the service quality was better than expected [##REF##18405394##16##]. They also responded the staff were professional and knowledgeable in their field of work [##REF##18405394##16##].</p>", "<p>A considerable number of women also said that the Quebec City Clinic allowed them to reach or surpass their breastfeeding objectives. They gave the same reasons as those mentioned in other studies [##REF##11461023##10##,##REF##11845734##11##,##REF##16881907##13##, ####REF##9429364##14##, ##REF##16356608##15####16356608##15##] to explain the influence of the clinic on the breastfeeding experience, namely, the identification of problems, the solutions found, and the encouragement and reassurance received.</p>", "<p>However, it is important to point out that the Quebec City Breastfeeding Clinic does not operate entirely the same way as the majority of the other clinics studied. For example, these clinics employ IBCLC and nurses [##REF##11461023##10##,##REF##11845734##11##,##REF##9429364##14##] or midwives [##REF##16881907##13##,##REF##16356608##15##] while the Quebec City Clinic employs IBCLC and physicians. Also, at the other clinics [##REF##11461023##10##,##REF##11845734##11##,##REF##16356608##15##], women are free to use the services as they wish, while at the Quebec City clinic, women are referred by field workers. Although there are other clinics in Canada that operate in similar ways to the one in Quebec, no scientific papers on their services have been published yet.</p>", "<p>One limitation of this study is the small number of participants. Indeed, the number of semi-structured interviews conducted did not allow us to reach content saturation. Another possible limitation is the voluntary interview participation, which may have biased the results in a positive way. The telephone questionnaire and semi-structured interviews used for the study are both retrospective tools that relied on participants' memories. Participants may have forgotten information, which could have biased the results. Furthermore, the two research tools were tested, but not validated.</p>", "<p>More research is needed to better understand the breastfeeding experience of women grappling with major difficulties and to better understand why some are able to overcome these difficulties while others are not. It would also be relevant to study how social pressure may positively and/or negatively affect the breastfeeding experience. In addition, more qualitative and quantitative research is needed on women's experience at breastfeeding clinics throughout Canada and in other industrialized countries to better understand the influence of these clinics on breastfeeding issues such as duration and satisfaction.</p>" ]

[ "<title>Conclusion</title>", "<p>This study showed that women's breastfeeding experiences may be influenced by the moral and physical support provided by family and friends, health professionals, and breastfeeding clinic clinicians as well as their own personal traits. These results may be useful for better understanding women's experiences and determining the best ways to help them overcome their difficulties. They may also prove useful in showing the relevance of such clinics for improving the breastfeeding experience.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Many women experience breastfeeding difficulties. Sometimes these difficulties lead to breastfeeding cessation. Breastfeeding clinics provide support for women facing such problems. This study aims to describe the breastfeeding experience of women, particularly those who use the services of the breastfeeding clinic located in the Greater Quebec City area.</p>", "<title>Methods</title>", "<p>This is a descriptive study based on information gathered through telephone questionnaires that were administered in 2006 to a sample of 86 women and semi-structured interviews conducted with 12 of these women.</p>", "<title>Results</title>", "<p>Painful nipples/breasts, low milk supply and latching difficulties were the three most frequent major breastfeeding problems identified by women. Their personal characteristics as well as the moral and physical support provided by family and friends and by health professional and clinicians at the breastfeeding clinic were the factors identified most often as having a positive influence on the breastfeeding experience.</p>", "<title>Conclusion</title>", "<p>The results suggest that breastfeeding clinics have a critical role to play in improving the breastfeeding experience of women with major difficulties.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>This study is part of CL's Masters Degree. She performed all the research steps of this study. AMH participated in the design of the study and supervised all the research steps and writing. MSP participated in the design and coordination of the study. All authors read, commented, and approved the final manuscript.</p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to thank the clinicians at the Quebec City Breastfeeding Clinic, namely Marie-Josée Santerre, IBCLC, Cécile Fortin, IBCLC, Jean-Claude Mercier, IBCLC, PhD, attending pediatrician and public health pediatrician, and Martin Lalinec-Michaud, PhD, MDCM, as well as the members of the orientation committee, the statistician Stéphanie Camden, the SOM survey firm, and all the participants in this study. We would like to thank the reviewers for their thoughtful comments on an initial version of this paper. This project was made possible by a joint grant from the Quebec Minister of Health and Social Services and the Capitale-Nationale Health and Social Services Agency through the public health grant program for research and evaluation projects.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p>Conceptual framework.</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Sociodemographic characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Characteristics</bold></td><td align=\"center\"><bold>Total (n = 86) </bold>n (%)</td><td align=\"center\"><bold>Québec (n = 52) </bold>n (%)</td><td align=\"center\"><bold>Trois-Rivières (n = 34) </bold>n (%)</td><td align=\"center\"><bold>p value</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Maternal age</bold></td><td/><td/><td/><td align=\"center\">0.94**</td></tr><tr><td align=\"left\"> 20 to 29 years</td><td align=\"center\">48 (56)</td><td align=\"center\">29 (56)</td><td align=\"center\">19 (56)</td><td/></tr><tr><td align=\"left\"> 30 to 34 years</td><td align=\"center\">24 (28)</td><td align=\"center\">14 (27)</td><td align=\"center\">10 (29)</td><td/></tr><tr><td align=\"left\"> 35 years and more</td><td align=\"center\">14 (16)</td><td align=\"center\">9 (17)</td><td align=\"center\">5 15)</td><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Marital status</bold></td><td/><td/><td/><td align=\"center\">0.15*</td></tr><tr><td align=\"left\"> Married/common-law</td><td align=\"center\">84 (98)</td><td align=\"center\">52 (100)</td><td align=\"center\">32 (94)</td><td/></tr><tr><td align=\"left\"> Divorced</td><td align=\"center\">1 (1)</td><td align=\"center\">0 (0)</td><td align=\"center\">1 (3)</td><td/></tr><tr><td align=\"left\"> Single/never married</td><td align=\"center\">1 (1)</td><td align=\"center\">0 (0)</td><td align=\"center\">1 (3)</td><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Education</bold></td><td/><td/><td/><td align=\"center\">0.40*</td></tr><tr><td align=\"left\"> Vocational diploma or less</td><td align=\"center\">11 (13)</td><td align=\"center\">7 (13)</td><td align=\"center\">4 (12)</td><td/></tr><tr><td align=\"left\"> College diploma</td><td align=\"center\">28 (33)</td><td align=\"center\">14 (27)</td><td align=\"center\">14 (41)</td><td/></tr><tr><td align=\"left\"> University diploma</td><td align=\"center\">47 (55)</td><td align=\"center\">31 (60)</td><td align=\"center\">16 (47)</td><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Family income</bold></td><td/><td/><td/><td align=\"center\">0.39*</td></tr><tr><td align=\"left\"> &lt; 30 000$</td><td align=\"center\">9 (10)</td><td align=\"center\">4 (8)</td><td align=\"center\">5 (15)</td><td/></tr><tr><td align=\"left\"> 30 000 to &lt; 50 000$</td><td align=\"center\">17 (20)</td><td align=\"center\">9 (17)</td><td align=\"center\">8 (24)</td><td/></tr><tr><td align=\"left\"> ≥50000$</td><td align=\"center\">60 (70)</td><td align=\"center\">39 (75)</td><td align=\"center\">21 (62)</td><td/></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Breastfeeding difficulties experienced</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Difficulties**</bold></td><td align=\"center\"><bold>Total (n = 79)* </bold>n (%)</td></tr></thead><tbody><tr><td align=\"left\">Painful breast/nipple</td><td align=\"center\">70 (89)</td></tr><tr><td align=\"left\">Milk insufficiency/insufficient weight gain/stool absence</td><td align=\"center\">51 (65)</td></tr><tr><td align=\"left\">Latching/breast refusal</td><td align=\"center\">37 (47)</td></tr><tr><td align=\"left\">Sucking difficulties</td><td align=\"center\">12 (15)</td></tr><tr><td align=\"left\">Frequent baby crying</td><td align=\"center\">8 (10)</td></tr><tr><td align=\"left\">Inverted nipple</td><td align=\"center\">5 (6)</td></tr><tr><td align=\"left\">Other</td><td align=\"center\">3 (4)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Reasons for ceasing breastfeeding</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Reasons**</bold></td><td align=\"center\"><bold>Total (n = 75)* </bold>n (%)</td></tr></thead><tbody><tr><td align=\"left\">Latching difficulties/breast refusal</td><td align=\"center\">29 (39)</td></tr><tr><td align=\"left\">Low milk supply</td><td align=\"center\">28 (37)</td></tr><tr><td align=\"left\">Pain</td><td align=\"center\">20 (27)</td></tr><tr><td align=\"left\">Return to work/school or start of daycare</td><td align=\"center\">15 (20)</td></tr><tr><td align=\"left\">Breastfeeding objective attained/child old enough</td><td align=\"center\">14 (19)</td></tr><tr><td align=\"left\">Inconvenience/tired from breastfeeding</td><td align=\"center\">10 (13)</td></tr><tr><td align=\"left\">Child's health/weight loss</td><td align=\"center\">10 (13)</td></tr><tr><td align=\"left\">Lack of time/need for autonomy/freedom</td><td align=\"center\">5 (7)</td></tr><tr><td align=\"left\">Health problem in mother/medication</td><td align=\"center\">4 (5)</td></tr><tr><td align=\"left\">Desire to drink alcohol/varied diet</td><td align=\"center\">2 (3)</td></tr><tr><td align=\"left\">Child's desire or choice</td><td align=\"center\">2 (3)</td></tr><tr><td align=\"left\">Person's opinion</td><td align=\"center\">1 (1)</td></tr><tr><td align=\"left\">Effect of bottle</td><td align=\"center\">3 (4)</td></tr><tr><td align=\"left\">Other linked to woman's morale</td><td align=\"center\">3 (4)</td></tr><tr><td align=\"left\">Other</td><td align=\"center\">10 (13)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>List of principal content analysis categories, illustrated with verbatim excepts</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Breastfeeding history</bold></td></tr><tr><td align=\"left\"> <bold>Breastfeeding difficulties</bold></td></tr><tr><td align=\"left\">  <italic>\"The third week at home, she was having trouble latching on to the breast.\" (QC1-16)*</italic></td></tr><tr><td align=\"left\"> <bold>Breastfeeding duration</bold></td></tr><tr><td align=\"left\">  <italic>\"I breastfed full time for ten days.\"(TR3-8)</italic></td></tr><tr><td align=\"left\"> <bold>Satisfaction with the breastfeeding experience</bold></td></tr><tr><td align=\"left\">  <italic>\"As far as the length of time is concerned, I'm very satisfied\" (QC2-12)</italic></td></tr><tr><td align=\"left\"> <bold>Cessation of breastfeeding</bold></td></tr><tr><td align=\"left\">  <italic>\"The only reason I stopped was because of the pain.\" (TR6-77)</italic></td></tr></thead><tbody><tr><td align=\"left\"><bold>Influencing factors</bold></td></tr><tr><td align=\"left\"> <bold>Human</bold></td></tr><tr><td align=\"left\">  <bold>Formal </bold>(e.g. nurses, physician, others)</td></tr><tr><td align=\"left\">  <italic>\"The nurses are there and they help you.\" (QC1-81)</italic></td></tr><tr><td align=\"left\">  <bold>Informal </bold>(e.g. partner, mother, friends, others)</td></tr><tr><td align=\"left\">  <italic>\"My mother helped me a lot.\" (QC5-97)</italic></td></tr><tr><td align=\"left\"> <bold>Factors relative to the mother </bold>(e.g. intention, personality, others)</td></tr><tr><td align=\"left\">  <italic>\"I was really determined to breastfeed my baby.\" (TR2-18)</italic></td></tr><tr><td align=\"left\"> <bold>Social pressure</bold></td></tr><tr><td align=\"left\">  <italic>\"Because I really wanted to breastfeed, because everyone was talking about it and pushing me.\" (TR1-12)</italic></td></tr><tr><td align=\"left\"> <bold>Others </bold>(e.g. maternity/paternity leave, locations and facilities, others)</td></tr><tr><td align=\"left\">  <italic>\"There are nursing rooms everywhere.\" (QC1-42)</italic></td></tr><tr><td colspan=\"1\"><hr/></td></tr><tr><td align=\"left\"><bold>Breastfeeding clinic</bold></td></tr><tr><td align=\"left\"> <bold>Services and interventions received</bold></td></tr><tr><td align=\"left\">  <italic>\"That's it, they watched how I put E to the breast.\" (CQ1-162)</italic></td></tr><tr><td align=\"left\"> <bold>Satisfaction with the clinic</bold></td></tr><tr><td align=\"left\">  <italic>\"The staff was friendly and efficient.\" (QC5-240)</italic></td></tr><tr><td align=\"left\"> <bold>Utility of the breastfeeding clinic</bold></td></tr><tr><td align=\"left\">  <italic>\"They were such a big help. It seems to me that if anyone else had breastfeeding problems, it would be much easier for her to consult them.\" (QC2-212)</italic></td></tr><tr><td align=\"left\"> <bold>Influence of the clinic on the breastfeeding experience</bold></td></tr><tr><td align=\"left\">  <italic>\"How did it influence me to continue, yeah, that's it, with those medications. To see if it would stimulate my milk let-down.\" (QC4-190)</italic></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Persons who had most supported and encouraged women throughout breastfeeding experience</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Persons**</bold></td><td align=\"center\"><bold>Total </bold><break/><bold>(n = 81)* </bold><break/>n (%)</td></tr></thead><tbody><tr><td align=\"left\">Partner</td><td align=\"center\">54 (67)</td></tr><tr><td align=\"left\">Nurse from local community services centers</td><td align=\"center\">32 (40)</td></tr><tr><td align=\"left\">Personnel of breastfeeding clinic</td><td align=\"center\">25 (31)</td></tr><tr><td align=\"left\">Mother</td><td align=\"center\">21 (26)</td></tr><tr><td align=\"left\">Hospital nurse</td><td align=\"center\">20 (25)</td></tr><tr><td align=\"left\">Friend</td><td align=\"center\">19 (23)</td></tr><tr><td align=\"left\">Volunteer from a breastfeeding group</td><td align=\"center\">13 (16)</td></tr><tr><td align=\"left\">Physician (other than breastfeeding clinic one)</td><td align=\"center\">11 (14)</td></tr><tr><td align=\"left\">Family member (not partner or mother)</td><td align=\"center\">10 (12)</td></tr><tr><td align=\"left\">Midwife</td><td align=\"center\">1 (2)</td></tr><tr><td align=\"left\">Other</td><td align=\"center\">6 (7)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Reasons for consultation at the breastfeeding clinic</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Reasons for consultation**</bold></td><td align=\"center\"><bold>Greater Quebec City (n = 47)* </bold>n (%)</td></tr></thead><tbody><tr><td align=\"left\">Painful breast/nipple</td><td align=\"center\">30 (64)</td></tr><tr><td align=\"left\">Latching problems/breast refusal</td><td align=\"center\">24 (52)</td></tr><tr><td align=\"left\">Milk insufficiency/insufficient weight gain</td><td align=\"center\">14 (30)</td></tr><tr><td align=\"left\">Sucking difficulties</td><td align=\"center\">10 (21)</td></tr><tr><td align=\"left\">Frequent baby crying</td><td align=\"center\">4 (9)</td></tr><tr><td align=\"left\">Inverted nipples</td><td align=\"center\">2 (4)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T7\"><label>Table 7</label><caption><p>Women's satisfaction with the breastfeeding clinic and the effect of the clinic on attainment of their objectives and their satisfaction</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Greater Quebec City (n = 52) </bold>n (%)</td></tr></thead><tbody><tr><td align=\"left\"><bold>Satisfaction* with the services and interventions of the clinic</bold></td><td/></tr><tr><td align=\"left\"> Very dissatisfied/dissatisfied (1–2)</td><td align=\"center\">2 (4)</td></tr><tr><td align=\"left\"> Moderately satisfied (3)</td><td align=\"center\">4 (8)</td></tr><tr><td align=\"left\"> Satisfied/very satisfied (4–5)</td><td align=\"center\">46 (88)</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Satisfaction with the physicians of the clinic</bold></td><td/></tr><tr><td align=\"left\"> Very dissatisfied/dissatisfied (1–2)</td><td align=\"center\">2 (4)</td></tr><tr><td align=\"left\"> Moderately satisfied (3)</td><td align=\"center\">4 (8)</td></tr><tr><td align=\"left\"> Satisfied/very satisfied (4–5)</td><td align=\"center\">43 (88)</td></tr><tr><td align=\"left\"> Missing data: 1</td><td/></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Satisfaction with the lactation consultants of the clinic</bold></td><td/></tr><tr><td align=\"left\"> Very dissatisfied/dissatisfied (1–2)</td><td align=\"center\">1 (2)</td></tr><tr><td align=\"left\"> Moderately satisfied (3)</td><td align=\"center\">2 (4)</td></tr><tr><td align=\"left\"> Satisfied/very satisfied (4–5)</td><td align=\"center\">44 (94)</td></tr><tr><td align=\"left\"> Missing data: 5</td><td/></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Clinic allowed them to reach their breastfeeding objectives</bold></td><td/></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">39 (75)</td></tr><tr><td align=\"left\"> No</td><td align=\"center\">12 (23)</td></tr><tr><td align=\"left\"> Doesn't know</td><td align=\"center\">1 (2)</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Clinic allowed them to surpass their breastfeeding objectives</bold></td><td/></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">25 (48)</td></tr><tr><td align=\"left\"> No</td><td align=\"center\">14 (27)</td></tr><tr><td align=\"left\"> Doesn't apply to</td><td align=\"center\">12 (23)</td></tr><tr><td colspan=\"2\"><hr/></td></tr><tr><td align=\"left\"><bold>Clinic allowed them to increase overall satisfaction with their breastfeeding experience</bold></td><td/></tr><tr><td align=\"left\"> Yes</td><td align=\"center\">44 (85)</td></tr><tr><td align=\"left\"> No</td><td align=\"center\">8 (15)</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Description of the Telephone Questionnaire. Themes from the questionnaire and sample questions.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Interview Grid. Wording of questions of the interview.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>* Fisher's exact test</p><p>** Chi-square test</p></table-wrap-foot>", "<table-wrap-foot><p>* Data are missing for 5 women from the pretest (wording of the pretest question was different and we have decided not to keep their answers) and for 2 women who did not answer this question but indicated that they had breastfeeding difficulties in another question.</p><p>** Each woman could provide from 1 to 3 difficulties.</p></table-wrap-foot>", "<table-wrap-foot><p>* Data are missing for 5 women from the pretest (wording of the pretest question was different and we have decided not to keep their answers) and for 4 women who had not ceased breastfeeding at the time the questionnaire was conducted.</p><p>** Woman could provide from 1 to 3 reasons.</p></table-wrap-foot>", "<table-wrap-foot><p>Quote is our translation as are all subsequent quotes in this table.</p></table-wrap-foot>", "<table-wrap-foot><p>* Data are missing for women (5) from the pretest (wording of the pretest question was different and we have decided not to keep their answers).</p><p>** Woman could provide from 1 to 3 people.</p></table-wrap-foot>", "<table-wrap-foot><p>* Data are missing for 5 women from the pretest (wording of the pretest question was different and we have decided not to keep their answers).</p><p>** Each woman could provide from 1 to 3 reasons.</p></table-wrap-foot>", "<table-wrap-foot><p>* Satisfaction was measured on a scale of one to five (1 = highly dissatisfied, 5 = highly satisfied).</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1746-4358-3-17-1\"/>" ]

[ "<media xlink:href=\"1746-4358-3-17-S1.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1746-4358-3-17-S2.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Evidence-based practice (EBP) has been defined as the 'conscientious, judicious and explicit use of current best evidence available in making decisions about the care of individual patients', integrating individual clinical expertise, the needs and values of the individual patient and the best available research [##UREF##0##1##,##REF##8555924##2##].</p>", "<p>The understanding, accessing and implementing of EBP can provide appropriate and effective care in pregnancy, childbirth and the postnatal period for women and their babies [##UREF##0##1##]. However the wider application of EBP depends on the progress made in educating health professionals on accessing evidence-based research [##REF##11720947##3##], evaluating and correctly interpreting research studies, the provision of quick, easy and free access to evidence [##REF##14641194##4##] and an understanding on how to implement the findings into clinical practice [##REF##15012583##5##].</p>", "<p>Each year there are over half a million maternal deaths world-wide with 98% of these occurring in low and middle income countries. For women in Asia the lifetime risk of maternal death is one in 65 compared with one in 1,800 for women in high income countries [##UREF##1##6##]. Access to scientifically valid and up-to-date information is a prerequisite for providing evidenced-based care [##REF##14641194##4##].</p>", "<p>In the South East Asia Optimising Reproductive and Child Health In Developing countries (SEA-ORCHID) project, the three phases of the study included audit of the baseline rates and clinical care practice, an educational intervention to improve evidence-based care followed by an audit of change of rates and quality of clinical practice [##REF##17892586##7##]. As part of the initial data collection in the four South East Asian (SEA) countries; Malaysia, Indonesia, Thailand and The Philippines, all clinical staff at the maternity, child health and newborn services of the nine participating hospitals were invited to participate in a survey of current knowledge, perceptions, activities, enablers and barriers to evidence-based practice.</p>" ]

[ "<title>Methods</title>", "<title>Eligibility, sampling and time frame</title>", "<p>The EBP survey was conducted among staff in the nine hospitals participating in the SEA-ORCHID project. These hospitals were situated in four South East Asian countries; Malaysia, Indonesia, Thailand and the Philippines. Of the nine hospitals, seven were tertiary referral institutions with regional referrals of women with a high risk pregnancy, one was a provincial institution and one was a district institution. The SEA-ORCHID project settings and methods have been published elsewhere [[##REF##17892586##7##] and see Additional file ##SUPPL##0##1##].</p>", "<p>All maternal and child health staff working on roster at the nine participating hospitals across South-East Asia were invited to participate in the EBP survey during August to December 2005. The EBP survey was approved by all relevant Ethics Committees at the SEA-ORCHID participating sites.</p>", "<p>The SEA-ORCHID project was interested in obtaining information about the knowledge and access of on-line evidence-based information. The Cochrane Library [##UREF##2##8##] is one such on-line resource, reliable for obtaining evidence-based clinical information and up-to-date systematic reviews in health care. The World Health Organization (WHO) Reproductive Health Library (RHL) [##UREF##3##9##] is another on-line evidence-based resource. It aims to put the best available evidence into a practical context so that it can be used to improve health outcomes. RHL started in 1997 and is prepared by an editorial team based in the WHO department of reproductive health and research and other international partner institutions. The audit sought detail on the involvement of participants with clinical practice change and possible barrier and enabler identification in their clinical area.</p>", "<p>At each site the distribution of the questionnaires was managed by the local SEA-ORCHID study researcher. Instructions on how to administer the survey and how the data was to be entered on-line were emailed to all local study researchers, who instructed the field workers as to the correct on-line data entry. The instructions were also posted on-line for easy access on the SEA-ORCHID web site (please see Availability &amp; requirements for more information) that was protected by a password for access. Zoomerang software (please see Availability &amp; requirements for more information) was used for on-line data entry and entered data was converted into Excel for data checking and analyses.</p>", "<title>The survey questionnaire</title>", "<p>The survey consisted of 39 questions and was developed and piloted by one of the SEA-ORCHID clinical educators (RM) with feedback from SEA and Australian investigators [see Additional file ##SUPPL##1##2##]. The pilot data were not included in the analyses. The survey development was assisted by having access to and permission for use of a WHO RHL survey tool [##REF##14723792##10##].</p>", "<p>Most survey questions needed to be answered by writing a number in a box next to listed responses, 1 indicating no, 2 indicating yes and 3 indicating maybe. Most questions gave the opportunity to specify additional information. The survey comprised seven sections. The first section collected demographic data and IT technology available at the participant's work place. The second assessed the health information sources used by participants, how often they consulted such sources and how much time was spent reading health information. EBP beliefs were addressed in section three as well as whether the participant was an author of a systematic review. Section four and five sought information about participant's knowledge of the Reproductive Health Library (RHL) [##UREF##3##9##] and The Cochrane Library [##UREF##2##8##]. Section six explored participant's involvement and experiences with clinical practice change including barrier identification and how to overcome these. Finally participants identified workshops they would like to attend for enhancing their understanding of EBP and what would prevent them from attending such workshops.</p>", "<title>Statistical analysis</title>", "<p>Data analysis was conducted using pivotTables in Microsoft Office Excel 2003 calculating frequency and corresponding percentages to describe the responses to the survey questions for all participating health professionals and combining the data for all four SEA countries. Two response questions were presented as a list and frequency of occurrence rather than linked to health professionals or given as percentages.</p>", "<title>Ethical approval</title>", "<p>The SEA-ORCHID project was approved by the local ethics committees of each hospital and by the ethics committee of the University of Sydney, the administering institution in Australia.</p>" ]

[ "<title>Results</title>", "<title>Demographics</title>", "<p>A total of 660 staff across the four SEA-ORCHID countries were surveyed. Professions represented included 80 obstetrics and gynaecology (O&amp;G) specialists, four neonatologists, 36 paediatricians, 158 postgraduate medical trainees, 263 nurses, and 119 midwives (nurses with midwifery qualifications included).</p>", "<p>The participants were identified as 564 (85%) female and 96 (15%) male across the four participating SEA countries (Table ##TAB##0##1##). The female gender dominated for all professions surveyed, with nurses represented by 263 (100%) females, closely followed by midwives with 118 (99%). The age range varied among the professions with an overall mean age of 36 ± 9 years. A mean of 9 ± 8 years practicing in participants' respective profession was represented (Table ##TAB##0##1##).</p>", "<title>In-service training</title>", "<p>Of the overall participants, 368 (56%) commented that the type of in-service training usually offered at their institution was of technical or professional nature, rather than managerial or administrative. No in-service training was indicated by 66 (10%) and 13 (2%) did not know if training was offered. However, 201 (30%) indicated that both types (managerial or administrative and technical or professional) of in-service training were offered at their institution.</p>", "<title>Access to IT services</title>", "<p>In answer to the question of easy access to a computer at the workplace, 301 participants across all four SEA countries (46%) responded that they had access with broadband internet connection while 139 (21%) indicated that they had no access. However there were great variations between the countries. In Indonesia, 63 (50%) of all participants reported no access to computers and of the participants that did, 26 (21%) could not access the internet through their computer. Thailand had the highest reported access where 127 (84%) participants had easy access to a computer at work with broadband connection (Table ##TAB##1##2##).</p>", "<p>Of all the SEA participants with no easy access to a computer at their workplace, 114 (50%) indicated that the greatest difficulty was a limited supply of computers. The 'other' option was chosen by 14 (6%) participants where 7 (50%) described that the difficulty they had was due to their limited knowledge of how to use the computer or the available software on the computer.</p>", "<title>Health Information and Resources</title>", "<p>Participants across all four SEA countries indicated that the reason for consulting health information sources 'frequently' were for patient care (377, 57%), for teaching (216, 33%), for personal study (219, 33%) and for research (179, 27%).</p>", "<p>Resources 'frequently' used for health information were text books (359, 54%), colleagues (212, 32%), journals (157, 24%) and resources from pharmaceutical companies (30, 5%). Resources 'sometimes' used were resources from pharmaceutical companies (438, 66%), journals (380, 57%), colleagues (347, 52%) and textbooks (278, 42%).</p>", "<p>The internet was used as a resource for gaining health information by 409 participants (62%), who listed 46 websites, with the most popular website being <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.google.com\"/> 129 (20%), closely followed by <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.pubmed.nl\"/> 69 (10%), then <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.pubmedcentral.nih.gov\"/> 62 (9%) and <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.yahoo.com\"/> 50 (8%) (Table ##TAB##2##3##). Across SEA, nurses were the least likely to use the internet for health information with 136 (52%) indicating 'never', followed by nurse-midwives and postgraduate medical trainees. When asked how much time participants actually spent reading health information on an average weekly basis, 180 (27%) indicated less than one hour, 290 (44%) 1–2 hours and 195 (29%) indicated 3 or more hours a week.</p>", "<title>Evidence-Based Practice</title>", "<p>All participants were asked if they had ever heard about evidence-based practice, evidence-based medicine or evidence-based care. Of the total number of survey participants, 385 (58%) had heard about the concept. This result differed considerably between countries and the health professions, with the data from individual countries showing that 114 (75%) of Thailand's clinicians had heard about EBP, 71 (66%) from the Philippines, 142 (51%) from Malaysia and 60 (48%) from Indonesia.</p>", "<p>Among SEA health professionals the different groups who identified that they had heard about EBP were 94 (36%) nurses, 48 (40%) midwives, 134 (85%) postgraduate medical trainees, 71 (90%) O&amp;G specialists, 34 (97%) paediatricians and 4 (100%) neonatologists (Table ##TAB##3##4##). Of the participants that had heard about EBP, 291 (76%) opted to write down their personal definition. The answers varied considerably between participants; however the majority of responses indicated a lack of understanding of the EBP concept identifying it as clinical practice guidelines or something to do with research.</p>", "<title>The Cochrane Library</title>", "<p>In relation to having heard about The Cochrane Library, 307 (47%) participants indicated that they had (Table ##TAB##3##4##) with 156 (51%) of these having access to it. This is obviously related to on-line computer access and whether a subscription had been paid. However, of the participants that had access to The Cochrane Library, 28 (18%) indicated that they never used it, 30 (19%) used it once a year, 65 (42%) used it once a month, 28 (18%) used it once a week and 12 (8%) used it more than once a week. This was a consistent result across all four SEA countries. A question relating to whether participants found The Cochrane Library helpful was answered by 140 participants with 83 (59%) indicating they found it a helpful tool. The usefulness related to accessing systematic reviews (29, 47%) and to retrieving information for clinical practice guideline development (11, 18%). Of all the survey participants 311 (70%) indicated they had not attended a Cochrane Library workshop and 571 (81%) expressed interest in attending such a workshop. This was consistent across all four countries with a range of 79–85%.</p>", "<title>The Reproductive Health Library (RHL)</title>", "<p>Within the survey participants 177 (27%) had heard about the RHL and of these 83 (47%) had access to it (Table ##TAB##3##4##). Knowing about the RHL varied considerably between countries. In Indonesia, 6 (5%) health professionals had heard about this on-line resource, in the Philippines 23 (21%), in Malaysia 25 (9%) and in Thailand 46 (30%). RHL is a free resource to low and middle income countries.</p>", "<p>Only 70 participants answered the question on whether RHL tool is helpful in their practices of which 57% answered that it is useful but 43% answered it is useful sometimes. Both groups indicated the most useful section in the RHL were the systematic reviews (42, 60%). Of these 70 participants, 28 (40%) had attended a RHL workshop, mainly in Thailand. No participants in the Philippines or Malaysia and only two from Indonesia had attended a RHL workshop. Overall 572 (87%) of health professionals across SEA indicated an interest in attending a RHL workshop. This was consistent in all four countries with a range of 80–89%.</p>", "<title>Clinical Practice Change</title>", "<p>Of the survey participant 230 (35%) responded as having been involved in changing an established clinical practice. These results varied between the four SEA countries however with participant from Thailand indicating 112 (74%) had been involved, 36 (29%) in Indonesia, 72 (26%) in Malaysia and 10 (9%) in The Philippines. These participants were then asked to identify who initiated this change with 75 (33%) identifying that the change was initiated by the Head of the Department, followed by the respondent themselves (54, 23%), senior staff (46, 20%) and colleagues (37, 16%) (Table ##TAB##4##5##).</p>", "<p>Participants were asked about their understanding of why the change was made. Across SEA, 125 (54%) participants responded that the change was initiated because of new evidence, 70 (30%) identified the change was made because new health technology was made available, 15 (7%) indicated the change was made due to a new pharmaceutical drug and 16 (7%) did not know the reason for the initiated clinical practice change. Minor and major resistance to changing clinical practice was reported by 158 (69%) participants with the major reason being no discussion at implementation stage (67, 42%). This was followed by identifying additional resistance to change as no or little consultation (39, 25%), difficulty in accessing new clinical guidelines (28, 18%) and the observation that people did not like change or held on to their different clinical opinions and beliefs (15, 9%).</p>", "<p>Participants were invited to identify possible enablers to overcome the barriers that were identified in the previous question. The major recommended action was discussion groups within professional groups (76, 48%) from inception right through to implementation. Easy access to clinical practice guidelines were identified by 31 (20%) participants and multidisciplinary workshops by 30 (19%). Overall, a local language was not identified as needed for enabling change or overcoming barriers. However, 16 (10%) of Thailand's participants indicated that translation of clinical practice guidelines would be useful.</p>", "<title>Professional Development Indication</title>", "<p>Participants were invited to indicate their interest in attending workshops on evidence-based health care and to provide suggestions for workshop topics as this could assist their professional development. Across all four SEA countries the majority of health professionals surveyed were interested in attending such workshops with a range from 550 (83%) to 578 (88%) (Table ##TAB##5##6##). Additional topics for workshops were suggested by 9 participants, mainly related to computing skills and internet searching.</p>", "<p>It is of interest to the SEA-ORCHID project to understand if there are reasons that would prevent participants from attending the workshops for professional development. The survey data showed that 211 (32%) participants had no concerns, 353 (53%) had concerns and 101 (15%) indicated that maybe there were concerns. Of those that identified concerns, 271 (41%) indicated they needed financial support but none was available, 260 (39%) felt they were too busy with their clinical workload and 182 (28%) indicated language as a barrier. Other barriers were indicated by 14 people with the two main reasons being difficulty in obtaining permission from Head of Department and difficulty in changing shifts.</p>" ]

[ "<title>Discussion</title>", "<p>Our findings provide a useful foundation from which to plan future interventions and directions for EBP among maternal and child health professionals in SEA. The survey adds to the hospital data available from South East Asian countries on EBP knowledge amongst health professionals. The sample size of the study was limited to sites participating in the SEA-ORCHID project that may not be representative of all hospitals within each of the countries. Investigators at the hospitals that were chosen for the study were interested in EBP, so it is likely that these sites had more exposure to EBP. The survey results, therefore, would be likely to over-estimate EBP, knowledge and clinical change in reference to South East Asia as a whole.</p>", "<title>IT Access</title>", "<p>Less than half of participants had easy access to computers with broadband internet connections although an additional 13% were able to access the internet via a dial-in (telephone) connection. Across the participating SEA countries dial-in can be difficult to access on-line information, as the phone connections experience frequent interruptions. IT access varied widely between participating countries. Easy internet access is fundamental to inform EBP and to access EBP resources. It is an important tool to use for up-to-date information and latest research findings. Easy on-line access ensures busy clinicians are able to inform their practice through accessing peer-reviewed journals and updated research summary evidence such as those available through The Cochrane Library and The RHL [##REF##11280690##11##].</p>", "<p>Major barriers to accessing knowledge include difficulties with internet access, high costs of mailing and subscriptions [##REF##15262109##12##]. These difficulties are greater for health workers outside research settings involved mainly in routine care [##REF##17010115##13##].</p>", "<p>Our data shows the more senior the health professional the more likely it was for the IT access to be easy. For all the SEA participants that indicated they had no easy access to a computer at their workplace, half indicated that the greatest difficulty was a limited supply of computers. For some participants the difficulty they had was due to their limited knowledge of how to use the computer. This indicates an area where resources, training and assistance need to be allocated and planned in the workplace. Similar indications were found in an EBP survey among American physical therapists [##REF##12940766##14##] where physical therapists that had easy access to online resources were likely to perform data searches more frequently and tended to read more articles [##REF##12940766##14##].</p>", "<title>Health Information, Resources and EBP understanding</title>", "<p>EBP resources are growing fast. For health professionals to access these not only do they need to be able to have easy online access but also a knowledge about databases and how to search, as well as critical appraisal skills to interpret the information. Survey participants were asked how often and how much time they would spend consulting health information resources. Overall, the participants indicated that they consult any health information primarily for patient care. Textbooks were almost universally used with other highly used sources to inform clinical practice including colleagues, journals and information from pharmaceutical companies. Text books however, are quickly outdated, colleagues, while well experienced staff may be more opinion-based in their care rather then evidence-based and information from pharmaceutical companies may be biased towards their own research and products.</p>", "<p>The internet was used by two thirds of participants with the most popular URL being <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.google.com\"/>, which is not necessarily an evidenced-based database. Nurses and nurse-midwives were the least likely to use the internet for health information, followed by postgraduate medical trainees. All this information is useful in shaping future education programs within the SEA-ORCHID hospitals.</p>", "<p>Wider application of EBP in clinical practice will largely depend on the progress made in the area of educating health professionals in accessing peer reviewed evidence and the provision of quick and easy access to evidence, in particular if the evidence is formatted into clinical summaries [##REF##11280690##11##,##UREF##4##15##]. The lack of awareness of databases of pre-appraised evidence and the lack of access to these databases are recognized as barriers to practicing EBP [##REF##9487174##16##].</p>", "<p>Although half of the survey participants were aware of The Cochrane Library and one third of RHL, less than one-third actually used them on a regular basis. However the majority of participants were unaware of the existence of The Cochrane Library or RHL.</p>", "<p>The majority of participants indicated that they read health information for 1–2 hours a week. This level of attention to reading literature may not necessarily mean substandard care. Experienced health professionals who provide care frequently on a daily basis for a similar patient population may not need to refer to the literature as often. Three quarters of our participants consulted journals for informing their clinical practice. Most peer reviewed journals are published monthly or less frequent and maybe this level of reading on a weekly basis could be adequate. This of course relates to the actual material read and whether it is evidence-based [##REF##12940766##14##,##REF##8555924##2##].</p>", "<p>Only half of our participants had heard about the concept of EBP. This significant finding highlights the importance of readily accessible resources and opportunities for professional development workshops on EBP for busy health professionals.</p>", "<title>Involvement in and Barrier and Enabler Identification for Clinical Practice Change</title>", "<p>Over one third of participants had been involved in changing an established clinical practice. Relatively few participants did not know the reason for the change indicating good communication when implementing clinical practice change across the surveyed SEA sites. However, many participants reported resistance of differing degrees, with the main reason being no discussion at the implementation stage. Eccles and Grimshaw [##REF##15012581##17##] indicated there are 'no magic bullets' but involving people to change clinical behaviour rather than 'telling people to change' is an important factor for success.</p>", "<p>Barrier analysis can assist people with the planning and implementation of clinical practice change. Efforts can then be focused on interventions tailored to address specific barriers and identified enablers [##REF##17824862##18##] and is a recommended practice. In the literature it has been noted that barriers to change can occur across different levels of health care and analysis therefore needs to include policy makers and other stake holders, such as patients [##REF##15012583##5##,##REF##14568747##19##,##REF##14764503##20##].</p>", "<p>Enablers for clinical practice change were identified by participants. Overwhelmingly participants stated that discussion groups within professional groups from inception right through implementation would be the most effective way of ensuring sustainable clinical practice change. Easy access to evidence-based clinical practice guidelines was also identified. It is known that the 'barriers' reported as preventing implementation are less important than the context and underlying social relations that have given cause to them [##UREF##5##21##]. While it was difficult to assess from our survey what the context of clinical practice change was and what the underlying social relations were, participants indicated that they wanted to have discussions within their individual professional groups rather than multidisciplinary groups. This may be because of important underlying social relations.</p>", "<title>Identified Professional Development Needs and Identified Challenges</title>", "<p>Participants were able to identify their professional development needs and how these might be met. The majority requested training in the use of RHL and The Cochrane Library, Clinical Practice Guideline development and how to implement evidence into clinical practice. Other workshop suggestions were computer skill courses and how to search the internet. This was fairly consistent across all countries and among all health professional groups surveyed. Difficulty in attending workshops or training programmes, such as due to lack of available financial support and busy clinical workload would need to be overcome. These are echoed in the literature [##UREF##6##22##,##REF##17615076##23##] and are always a challenge to overcome.</p>" ]

[ "<title>Conclusion</title>", "<p>In conclusion, this EBP survey across four SEA countries indicates that a concerted effort by those promoting EBP are needed to ensure all clinicians, including nurses, midwives and other allied health professionals, are able to practice EBP. This will raise their awareness of evidence-based clinical practice guidelines and access to EBP resources on-line. In particular the lack of awareness of databases of pre-appraised evidence and the lack of access to these databases highlights some of the issues of practicing EBP effectively.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Evidence-based practice (EBP) can provide appropriate care for women and their babies; however implementation of EBP requires health professionals to have access to knowledge, the ability to interpret health care information and then strategies to apply care. The aim of this survey was to assess current knowledge of evidence-based practice, information seeking practices, perceptions and potential enablers and barriers to clinical practice change among maternal and infant health practitioners in South East Asia.</p>", "<title>Methods</title>", "<p>Questionnaires about IT access for health information and evidence-based practice were administered during August to December 2005 to health care professionals working at the nine hospitals participating in the South East Asia Optimising Reproductive and Child Health in Developing countries (SEA-ORCHID) project in Indonesia, Malaysia, Thailand and The Philippines.</p>", "<title>Results</title>", "<p>The survey was completed by 660 staff from six health professional groups. Overall, easy IT access for health care information was available to 46% of participants. However, over a fifth reported no IT access was available and over half of nurses and midwives never used IT health information. Evidence-based practice had been heard of by 58% but the majority did not understand the concept. The most frequent sites accessed were Google and PubMed. The Cochrane Library had been heard of by 47% of whom 51% had access although the majority did not use it or used it less than monthly. Only 27% had heard of the WHO Reproductive Health Library and 35% had been involved in a clinical practice change and were able to identify enablers and barriers to change. Only a third of participants had been actively involved in practice change with wide variation between the countries. Willingness to participate in professional development workshops on evidence-based practice was high.</p>", "<title>Conclusion</title>", "<p>This survey has identified the need to improve IT access to health care information and health professionals' knowledge of evidence-based health care to assist in employing evidence base practice effectively.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Availability &amp; requirements</title>", "<p>SEA-ORCHID web site: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.seaorchid.org\"/></p>", "<p>Zoomerang software: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.zoomerang.com\"/></p>", "<p>Google: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.google.com\"/></p>", "<p>PubMed NL: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.pubmed.nl\"/></p>", "<p>PubMed Central: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.pubmedcentral.nih.gov\"/></p>", "<p>Yahoo: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.yahoo.com\"/></p>", "<title>Authors' contributions</title>", "<p>All authors contributed to the study design, interpretation of the data and preparation of the drafts of the manuscript. In addition all authors coordinated the trial and the collection of data. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>The SEA-ORCHID study is jointly funded by an International Collaborative Research Grant from the National Health and Medical Research Council of Australia (No. 307703) and Wellcome Trust, United Kingdom (071672/Z/03/Z). All authors were funded individually by their respective university/institution for the preparation of the project proposal.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2393/8/34/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>We would like to acknowledge the following persons and institutions participated in the SEA-ORCHID Project Evidence-based Practice Staff Survey:</p>", "<p>Writing committee:</p>", "<p>R. Martis, JJ. Ho, CA. Crowther.</p>", "<p>Data management and administration:</p>", "<p>R. Martis, V. Ball, H. Dent, M. Thomas, N. Narash, M. Ewens.</p>", "<p>SEA-ORCHID Evidence Based Practice Staff Survey Group:</p>", "<p><underline>Indonesia</underline></p>", "<p><italic>Country Investigator: </italic>M. Hakimi.</p>", "<p><italic>Dr. Sardjito Hospital and Sleman District Hospital: </italic>Detty Nurdiati for administering the survey and for data entry.</p>", "<p><underline>Malaysia</underline></p>", "<p><italic>Country Investigator: </italic>JJ. Ho.</p>", "<p><italic>Universiti Sains Malaysia and Hospital Ipoh: </italic>Hans Van Rostenberghe and Japaraj Robert Peter for administering the survey and Sivasangari Subramaniam for data entry.</p>", "<p><underline>Thailand</underline></p>", "<p><italic>Country Investigator: </italic>P. Lumbiganon.</p>", "<p><italic>Sinagarind Hospital (Khon Kaen University), Khon Kaen Regional Hospital and Kalasin Hospital: </italic>Jadsada Thinkhamrop, Piangjit Tharnprisan, Ussanee Swadpanich, Janyaporn Ratanakosol, Bunpode Suwannachat and Bussarin Khianman for administering the survey and Natthaleeya Narash and Rabieb Poombankor for data entry.</p>", "<p><underline>The Philippines</underline></p>", "<p><italic>Country Investigator</italic>: MR. Festin.</p>", "<p><italic>Philippine General Hospital and Dr. Jose Fabella Memorial Hospital: </italic>Mario Festin, Geraldine Assumption Castillo-Torralba and Cynthia Ubaldo-Anzures for administering the survey and Jacelyn Magsipoc for data entry.</p>", "<p><underline>Australia</underline></p>", "<p><italic>Country Investigators: </italic>D. Henderson-Smart, S. Green, CA. Crowther.</p>", "<p><italic>Project Coordinator: </italic>SJ. McDonald.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Demographics: gender, age range and years practicing in profession across all four SEA countries (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Profession</bold></td><td align=\"right\"><bold>Total</bold></td><td align=\"center\" colspan=\"2\"><bold>Gender </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>Age</bold></td><td align=\"right\"><bold>Years practicing</bold></td></tr><tr><td colspan=\"2\"/><td colspan=\"2\"><hr/></td><td colspan=\"2\"/></tr><tr><td/><td/><td align=\"right\"><bold>Male</bold></td><td align=\"right\"><bold>Female</bold></td><td align=\"right\"><bold>Mean ± S.D.</bold></td><td align=\"right\"><bold>Mean ± S.D.</bold></td></tr></thead><tbody><tr><td align=\"left\">O &amp; G specialist</td><td align=\"right\">80</td><td align=\"right\">38 (48)</td><td align=\"right\">42 (53)</td><td align=\"right\">39 ± 10</td><td align=\"right\">9 ± 9</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">4</td><td align=\"right\">1 (25)</td><td align=\"right\">3 (75)</td><td align=\"right\">41 ± 5</td><td align=\"right\">11 ± 6</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">36</td><td align=\"right\">14 (39)</td><td align=\"right\">22 (61)</td><td align=\"right\">39 ± 8</td><td align=\"right\">9 ± 8</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">158</td><td align=\"right\">42 (27)</td><td align=\"right\">116 (73)</td><td align=\"right\">29 ± 3</td><td align=\"right\">3 ± 2</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">263</td><td align=\"right\">0 (0)</td><td align=\"right\">263(100)</td><td align=\"right\">35 ± 8</td><td align=\"right\">10 ± 7</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">119</td><td align=\"right\">1 (1)</td><td align=\"right\">118 (99)</td><td align=\"right\">42 ± 8</td><td align=\"right\">13 ± 9</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>660</bold></td><td align=\"right\"><bold>96 (15)</bold></td><td align=\"right\"><bold>564 (85)</bold></td><td align=\"right\"><bold>36 ± 9</bold></td><td align=\"right\"><bold>9 ± 8</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Access to computers and IT services by participating SEA countries and by profession (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"right\"><bold>No access </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>Yes, without internet connection </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>Yes, with phone internet connection </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>*Yes, with broadband internet connection </bold><break/><bold>n (%)</bold></td></tr></thead><tbody><tr><td align=\"left\"><bold>Country</bold></td><td/><td/><td/><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">Malaysia</td><td align=\"right\">42 (15)</td><td align=\"right\">83 (30)</td><td align=\"right\">41 (15)</td><td align=\"right\">110 (40)</td></tr><tr><td align=\"left\">Indonesia</td><td align=\"right\">63 (50)</td><td align=\"right\">26 (21)</td><td align=\"right\">5 (4)</td><td align=\"right\">32 (25)</td></tr><tr><td align=\"left\">Thailand</td><td align=\"right\">6 (4)</td><td align=\"right\">8 (5)</td><td align=\"right\">10 (7)</td><td align=\"right\">127 (84)</td></tr><tr><td align=\"left\">Philippines</td><td align=\"right\">28 (26)</td><td align=\"right\">15 (14)</td><td align=\"right\">32 (30)</td><td align=\"right\">32 (30)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>139 (21)</bold></td><td align=\"right\"><bold>132 (20)</bold></td><td align=\"right\"><bold>88 (13)</bold></td><td align=\"right\"><bold>301 (46)</bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Profession</bold></td><td/><td/><td/><td/></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\">O&amp;G Specialist</td><td align=\"right\">5 (6)</td><td align=\"right\">9 (11)</td><td align=\"right\">10 (13)</td><td align=\"right\">56 (70)</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">4 (100)</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">2 (6)</td><td align=\"right\">0 (0)</td><td align=\"right\">5 (14)</td><td align=\"right\">29 (81)</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">19 (12)</td><td align=\"right\">22 (14)</td><td align=\"right\">43 (27)</td><td align=\"right\">74 (47)</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">76 (29)</td><td align=\"right\">58 (22)</td><td align=\"right\">23 (9)</td><td align=\"right\">106 (40)</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">37 (31)</td><td align=\"right\">43 (36)</td><td align=\"right\">7 (6)</td><td align=\"right\">32 (27)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>139 (21)</bold></td><td align=\"right\"><bold>132 (20)</bold></td><td align=\"right\"><bold>88 (13)</bold></td><td align=\"right\"><bold>301 (46)</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>The four web sites used mostly for health information access by profession across SEA (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>*Profession</bold></td><td align=\"right\"><bold>Google </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>PubMednl </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>PubMed Central </bold><break/><bold>n (%)</bold></td><td align=\"right\"><bold>Yahoo </bold><break/><bold>n (%)</bold></td></tr></thead><tbody><tr><td align=\"left\">O&amp;G Specialist</td><td align=\"right\">18 (23)</td><td align=\"right\">17 (21)</td><td align=\"right\">14 (18)</td><td align=\"right\">11 (14)</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">3 (75)</td><td align=\"right\">4(100)</td><td align=\"right\">4(100)</td><td align=\"right\">0 (0)</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">14 (39)</td><td align=\"right\">11 (31)</td><td align=\"right\">11 (31)</td><td align=\"right\">4 (11)</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">32 (20)</td><td align=\"right\">33 (21)</td><td align=\"right\">30 (19)</td><td align=\"right\">13 (8)</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">54 (21)</td><td align=\"right\">3 (1)</td><td align=\"right\">2 (1)</td><td align=\"right\">18 (7)</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">8 (7)</td><td align=\"right\">1 (1)</td><td align=\"right\">1 (1)</td><td align=\"right\">4 (3)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>129 (20)</bold></td><td align=\"right\"><bold>69 (10)</bold></td><td align=\"right\"><bold>62 (9)</bold></td><td align=\"right\"><bold>50 (8)</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Heard about EBP, The Reproductive Health Library and The Cochrane Library by profession across SEA (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Profession</bold></td><td align=\"right\"><bold>Reproductive Health Library</bold></td><td align=\"right\"><bold>The Cochrane Library</bold></td><td align=\"right\"><bold>EBP</bold></td></tr><tr><td/><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td></tr></thead><tbody><tr><td align=\"left\">O&amp;G Specialist</td><td align=\"right\">46 (82)</td><td align=\"right\">71 (89)</td><td align=\"right\">71 (90)</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">4(100)</td><td align=\"right\">4(100)</td><td align=\"right\">4(100)</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">9 (35)</td><td align=\"right\">32 (89)</td><td align=\"right\">34 (97)</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">69 (83)</td><td align=\"right\">121 (77)</td><td align=\"right\">134 (85)</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">44 (32)</td><td align=\"right\">63 (24)</td><td align=\"right\">94 (36)</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">5 (4)</td><td align=\"right\">16 (13)</td><td align=\"right\">48 (40)</td></tr><tr><td colspan=\"4\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>177 (27)</bold></td><td align=\"right\"><bold>307 (47)</bold></td><td align=\"right\"><bold>385 (58)</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T5\"><label>Table 5</label><caption><p>Who initiated changing an established clinical practice by profession across four SEA countries (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Profession</bold></td><td align=\"right\"><bold>Team</bold></td><td align=\"right\"><bold>You</bold></td><td align=\"right\"><bold>Colleague</bold></td><td align=\"right\"><bold>Senior Staff</bold></td><td align=\"right\"><bold>Head of Department or Management </bold></td><td align=\"right\"><bold>Don't know </bold></td><td align=\"right\"><bold>Total</bold></td></tr><tr><td/><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td></tr></thead><tbody><tr><td align=\"left\">O&amp;G Specialist</td><td align=\"right\">3 (8)</td><td align=\"right\">14 (36)</td><td align=\"right\">8(21)</td><td align=\"right\">6(15)</td><td align=\"right\">7 (18)</td><td align=\"right\">1 (3)</td><td align=\"right\">80 (12)</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">1(25)</td><td align=\"right\">3 (75)</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">4 (1)</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">1 (4)</td><td align=\"right\">14 (58)</td><td align=\"right\">1 (4)</td><td align=\"right\">1 (4)</td><td align=\"right\">7 (29)</td><td align=\"right\">0 (0)</td><td align=\"right\">36 (5)</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">1 (4)</td><td align=\"right\">2 (7)</td><td align=\"right\">1 (4)</td><td align=\"right\">13 (46)</td><td align=\"right\">10 (36)</td><td align=\"right\">1 (4)</td><td align=\"right\">158 (24)</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">8 (7)</td><td align=\"right\">20 (18)</td><td align=\"right\">26 (23)</td><td align=\"right\">19 (17)</td><td align=\"right\">38 (34)</td><td align=\"right\">1 (1)</td><td align=\"right\">263 (40)</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">0 (0)</td><td align=\"right\">0 (0)</td><td align=\"right\">1 (4)</td><td align=\"right\">7 (28)</td><td align=\"right\">13 (52)</td><td align=\"right\">4 (16)</td><td align=\"right\">119 (18)</td></tr><tr><td colspan=\"8\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>14 (6)</bold></td><td align=\"right\"><bold>54 (23)</bold></td><td align=\"right\"><bold>37 (16)</bold></td><td align=\"right\"><bold>46 (20)</bold></td><td align=\"right\"><bold>75 (32)</bold></td><td align=\"right\"><bold>7 (3)</bold></td><td align=\"right\"><bold>660</bold></td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T6\"><label>Table 6</label><caption><p>Workshops interested in attending by health professionals across four SEA countries (n = 660)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Profession</bold></td><td align=\"right\"><bold>RHL</bold></td><td align=\"right\"><bold>Cochrane</bold></td><td align=\"right\"><bold>EBP</bold></td><td align=\"right\"><bold>CPG</bold></td><td align=\"right\"><bold>Use of evidence </bold></td></tr><tr><td/><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td><td align=\"right\"><bold>n (%)</bold></td></tr></thead><tbody><tr><td align=\"left\">O&amp;G Specialist</td><td align=\"right\">74 (93)</td><td align=\"right\">71 (88)</td><td align=\"right\">72 (90)</td><td align=\"right\">69 (88)</td><td align=\"right\">72 (90)</td></tr><tr><td align=\"left\">Neonatologist</td><td align=\"right\">3 (75)</td><td align=\"right\">3 (75)</td><td align=\"right\">3 (75)</td><td align=\"right\">3 (75)</td><td align=\"right\">3 (75)</td></tr><tr><td align=\"left\">Paediatrician</td><td align=\"right\">25 (69)</td><td align=\"right\">30 (83)</td><td align=\"right\">31 (86)</td><td align=\"right\">30 (83)</td><td align=\"right\">31 (86)</td></tr><tr><td align=\"left\">Postgraduate medical trainee^a</td><td align=\"right\">141 (89)</td><td align=\"right\">135 (85)</td><td align=\"right\">137 (87)</td><td align=\"right\">138 (87)</td><td align=\"right\">137 (87)</td></tr><tr><td align=\"left\">Nurse</td><td align=\"right\">228 (87)</td><td align=\"right\">211 (80)</td><td align=\"right\">210 (80)</td><td align=\"right\">227 (86)</td><td align=\"right\">229 (87)</td></tr><tr><td align=\"left\">Midwife^b</td><td align=\"right\">97 (82)</td><td align=\"right\">97 (82)</td><td align=\"right\">95 (80)</td><td align=\"right\">100 (84)</td><td align=\"right\">102 (87)</td></tr><tr><td colspan=\"6\"><hr/></td></tr><tr><td align=\"left\"><bold>Total</bold></td><td align=\"right\"><bold>568 (86)</bold></td><td align=\"right\"><bold>547 (83)</bold></td><td align=\"right\"><bold>548 (83)</bold></td><td align=\"right\"><bold>567 (86)</bold></td><td align=\"right\"><bold>574 (87)</bold></td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>Sea-orchid protocol. Optimizing reproductive and child health outcomes by building evidence-based research and practice in South East Asia (SEA-ORCHID): study protocol</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>Staff survey. Evidence-Based Practice Survey</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>^aIdentified as Resident or RMO in Thailand, Indonesia, The Philippines and Medical Officer in Malaysia</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>", "<table-wrap-foot><p>*Identified as easy access</p><p>^aIdentified as Resident or RMO in Thailand, Indonesia and The Philippines and Medical Officer in Malaysia</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>", "<table-wrap-foot><p>*Please note that some professions might have indicated more than one option</p><p>^aIdentified as Resident or RMO in Thailand, Indonesia and The Philippines and Medical Officer in Malaysia</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>", "<table-wrap-foot><p>^aIdentified as Resident or RMO in Thailand, Indonesia and The Philippines and Medical Officer in Malaysia</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>", "<table-wrap-foot><p>^aIdentified as Resident or RMO in Thailand, Indonesia and The Philippines and Medical Officer in Malaysia</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>", "<table-wrap-foot><p>^aIdentified as Resident or RMO in Thailand, Indonesia and The Philippines and Medical Officer in Malaysiam</p><p>^bNurse with midwifery training included</p><p>All figures are rounded to the nearest whole number</p></table-wrap-foot>" ]

[]

[ "<media xlink:href=\"1471-2393-8-34-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-34-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Background</title>", "<p>Pre-eclampsia (PET) and small for gestational age (SGA) remain significant causes of perinatal death and childhood disability [##REF##9093303##1##, ####UREF##0##2##, ##REF##2475158##3####2475158##3##]. PET has significant health implications for the mother with complications including adult respiratory distress syndrome, coagulopathy, renal and liver failure and stroke. Babies affected by SGA on reaching adulthood are at greater risk of developing cardiovascular disease, hypertension, and non-insulin dependent diabetes [##REF##10068385##4##,##REF##15702667##5##]. Both PET and SGA are characterized by a failure of the trophoblast invasion (at 16–22 weeks) into the spiral arteries.</p>", "<p>Second trimester serum screening for Down's syndrome is routinely offered to women in the United Kingdom and United States, either with the triple test (alpha-fetoprotein (AFP), human chorionic gonadotrophin (HCG) and unconjugated estriol) or with the addition of inhibin A as the quadruple test. More recently first trimester screening with fetal nuchal translucency, HCG and pregnancy associated plasma protein A (PAPP-A) has provided an earlier, more effective screening method [##UREF##1##6##]. Due to their origin and sites of metabolism these biochemical markers may be useful in the prediction of PET and SGA, there are however conflicting reports in the literature. Maternal serum levels of these analytes have been shown to be associated with adverse outcome [##REF##10521763##7##,##REF##10940198##8##] with low levels of PAPP-A having been suggested as a marker for impaired placental function and placentation [##REF##11028579##9##]. There are studies however reporting contrasting views [##REF##9516016##10##].</p>", "<p>Reliable antenatal identification of PET and SGA is crucial to judicious allocation of monitoring resources and use of preventative treatment [##REF##17512048##11##] with the prospect of improving maternal and perinatal outcome. The variation in the design of research on accuracy of tests for prediction of PET and SGA, the scatter of this research across many databases and languages, and the dearth of clear collated up-to-date summaries of this literature contribute to the uncertainty about the best screening and monitoring strategies [##UREF##2##12##]. Systematic reviews of the literature can improve our ability to identify those pregnancies at increased risk of developing PET and SGA making additional use of test results already obtained for Down syndrome screening.</p>", "<p>The purpose of our review was to investigate the accuracy of serum biochemical markers used in first and second trimester Down syndrome serum screening in predicting PET and/or SGA. We systematically reviewed the available literature and meta-analysed the data.</p>" ]

[ "<title>Methods</title>", "<p>The systematic review was based on our previously published prospective protocols [##REF##17052339##13##,##REF##17346337##14##] designed using widely recommended methods [##UREF##3##15##, ####REF##11463691##16##, ##REF##8135452##17##, ##REF##11267714##18####11267714##18##]. The protocols are available as Additional files ##SUPPL##0##1## and ##SUPPL##1##2##.</p>", "<title>Data sources and searches</title>", "<p>Electronic searches were performed by experienced clinical librarians targeting the prediction of PET and SGA. We searched Medline, Embase, the Cochrane Library (2006;4) and Medion from inception until February 2007. The search strategies are detailed in the published protocols [##REF##17052339##13##,##REF##17346337##14##] and in Additional file ##SUPPL##2##3##. The reference lists of all included primary and review articles were examined to identify cited articles not captured by electronic searches. No language restrictions were applied.</p>", "<title>Study selection</title>", "<p>The first stage of study selection was the scrutinizing of the database by two reviewers to identify articles from title and/or abstract. In a second stage, a search based on keywords for each of the analytes under review was performed within the Reference Manager database. The results of this search were scrutinized by a second reviewer. In the final stage of study selection the full papers of identified articles were obtained with final inclusion or exclusion decisions made after independent and duplicate examination of the papers. We included studies that reported on singleton pregnancies at any level of risk in any healthcare setting using any serum biochemical test used in Down syndrome serum screening before the 25^thweek of gestation. Test accuracy studies allowing generation of 2 × 2 tables were included.</p>", "<title>Data extraction and Study Quality Assessment</title>", "<p>Further details on inclusion and exclusion criteria and extracted clinical, methodological and statistical data can be found in the published protocols.</p>", "<p>Acceptable reference standards for PET were: persistent systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg with proteinuria ≥ 0.3 g/24 hours or ≥ 1+ dipstick (= 30 mg/dl in a single urine sample), new after 20 weeks of gestation. Severe PET was defined as SBP ≥ 160 mmHg or DBP ≥ 110 mmHg with proteinuria ≥ 2.0 g/24 hours or ≥ 3+ dipstick, or of early onset &lt; 34 weeks gestation. Superimposed PET was defined as the development of proteinuria ≥ 0.3 g/24 hours or ≥ 1+ dipstick after 20 weeks gestation in chronically hypertensive patients [##REF##12044323##19##]. Acceptable reference standards for SGA included birth weight &lt; 10^thcentile adjusted for gestational age and based on local population values and absolute birth weight threshold &lt; 2500 g. Severe SGA was defined as birth weight &lt; 5^thor &lt; 3^rdcentile or &lt; 1750 g or and preterm SGA for SGA leading to delivery &lt; 37 weeks. Neonatal ponderal index &lt; 10^thcentile, skin fold thickness, and mid-arm circumference/head circumference were also assessed [##REF##16045513##20##, ####REF##12118644##21##, ##REF##1872765##22##, ##REF##15576272##23##, ##REF##4029053##24####4029053##24##].</p>", "<p>Disagreements were resolved by consensus or arbitration of a third reviewer. For multiple/duplicate publication of the same data set, the most recent and/or complete study was included only.</p>", "<p>All included manuscripts were assessed by at least one reviewer for study and reporting quality using validated tools [##REF##14606960##25##, ####REF##16519814##26##, ##REF##12511463##27##, ##REF##10493205##28##, ##REF##16477057##29##, ##REF##15193208##30####15193208##30##]. Methodological quality was defined as the confidence that the study design, conduct and analysis have minimized biases in addressing the research question, thereby focusing on the internal validity (i.e. the degree to which the results of an observation are correct for the patients being studied). Items considered important for a good quality paper were prospective design with consecutive recruitment, full verification of the test result with reference standard (&gt; 90%), adequate description of the index test and use of appropriate reference standard, and application of any preventative treatments. Additional quality items were assessed for SGA papers; whether they excluded cases of PET from the results, whether fetuses with chromosomal and structural anomalies were excluded and whether stillbirths and intrauterine deaths were excluded from the results. Further explanation of the quality assessment can be found in Additional file ##SUPPL##3##4##.</p>", "<p>We excluded from the statistical analysis any paper with a case-control design as this type of design in diagnostic test accuracy studies has been shown to be associated with bias and over/under estimation of accuracy [##REF##16477057##29##].</p>", "<title>Data synthesis and Analysis</title>", "<p>From the 2 × 2 tables the following were calculated with their 95% confidence intervals for individual studies; sensitivity (true positive rate), specificity (true negative rate) and the likelihood ratios (LR, the ratio of the probability of the specific test result in people who do have the disease to the probability in people who do not). LRs indicate by how much a given test result raises or lowers the probability of having the disease and have been recommended by Evidence-based Medicine Groups [##UREF##4##31##,##REF##8309035##32##]. Results were pooled among groups of studies with similar characteristics, the same threshold for the index test (PET and SGA), same reference standard threshold for (SGA) and the same trimester for testing. Where 2 × 2 tables contained zero cells, 0.5 was added to each cell to enable calculations.</p>", "<p>Sub-groups were defined at the start of the review based on clinical criteria known to affect prognosis, method of index test or study quality: level of risk of population (high or low based on authors assessment and calculated incidence rates from results); type of assay used for index test; whether babies with chromosomal anomalies were excluded from the results; use of preventative treatment; quality of study. Sub-group analyses were performed where there were at least 3 studies with similar characteristics within that group.</p>", "<p>Heterogeneity was assessed graphically by looking at the distribution of the sensitivities and specificities in the receiver operating characteristic (ROC) space and LRs as a measurement of accuracy size using a Forest plot. The loglikelihood and X²test were used to assess for heterogeneity statistically. When X²p value &gt; 0.05 (homogenous data) the fixed effect pooling method was used; where there was heterogeneity random effects pooling was used. Summary ROC plots were produced (data not shown). Sensitivity analysis was performed to check the robustness of our results. A p value of &lt; 0.05 was used throughout for statistical significance.</p>", "<p>All statistical analyses were performed using Meta-Disc software <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.hrc.es/investigacion/metadisc.html\"/> and Statsdirect for drawing the Forest plots.</p>", "<title>Clinical application</title>", "<p>The clinical impact of estimates of accuracy for a screening test depend on how the results of the test alter the patient's pre-test probability of disease, based on disease prevalence. The post-test probability can then be combined with estimates of effectiveness for known treatments [##REF##9332996##33##]. From this data we can then calculate the number of women needed to be tested (number needed to test- NNTest), using a particular serum marker, to prevent one case of SGA with a particular treatment and the number needed to treat (NNTreat), the number of test positive women needed to be treated to prevent one case of SGA. In this review clinical application will be assessed using aspirin as this is the only treatment with any level of effectiveness for PET and SGA [##REF##17512048##11##,##REF##9027913##34##].</p>" ]

[ "<title>Results</title>", "<title>Literature identification, study characteristics, and quality</title>", "<p>Figure ##FIG##0##1## summarises the process of literature identification and selection. Tables detailing the individual study characteristics of the included studies are available in Additional file ##SUPPL##4##5##. There were twenty studies that reported on both PET and SGA.</p>", "<title>Pre-eclampsia</title>", "<p>There were 44 included studies for pre-eclampsia [##REF##10521763##7##,##REF##11028579##9##,##REF##12601840##35##, ####REF##12576244##36##, ##REF##12393965##37##, ##REF##12224070##38##, ##REF##11932314##39##, ##REF##11422967##40##, ##REF##11015703##41##, ##REF##10920109##42##, ##REF##10875882##43##, ##REF##10865185##44##, ##REF##10847238##45##, ##REF##10739512##46##, ##REF##10548639##47##, ##REF##10215068##48##, ##REF##9611000##49##, ##REF##9598944##50##, ##REF##9127156##51##, ##REF##9065195##52##, ##REF##8994249##53##, ##REF##8885920##54##, ##REF##8960614##55##, ##REF##8694072##56##, ##REF##8559526##57##, ##REF##8730421##58##, ##REF##8610755##59##, ##REF##2475017##60##, ##REF##1373447##61##, ##REF##9166297##62##, ##REF##14758802##63##, ##REF##15608460##64##, ##REF##15539871##65##, ##REF##15507981##66##, ##REF##16055573##67##, ##REF##16029293##68##, ##REF##16263599##69##, ##REF##16325185##70##, ##REF##16086443##71##, ##UREF##5##72##, ##REF##16700087##73##, ##REF##17221926##74##, ##REF##9491867##75####9491867##75##] reporting on 169,637 women (4376 preeclamptic women, incidence 2.6%). Among these 44 studies, there were 35 cohort studies and nine case-control studies [##REF##11015703##41##,##REF##10875882##43##,##REF##10865185##44##,##REF##10215068##48##,##REF##9127156##51##,##REF##8960614##55##,##REF##14758802##63##,##UREF##5##72##,##REF##16700087##73##]. There were nine prospective studies, 10 retrospective and 25 were unclearly designed. Calculated incidence rates of PET ranged from 0.6–44%. Incidence rates of PET correlated poorly with descriptions of \"high\" or \"low\" risk study populations. Four of the studies were in \"high-risk\" populations (one in IVF patients, one in patients with abnormal uterine artery Doppler and two in patients with chronic hypertension) and in three of these studies the incidence of PET was &gt; 4%. However in 15 of the \"low-risk\" studies the incidence was &gt; 4% and in one study in which the inclusion criteria were unclearly reported. The remaining 25 studies were in low risk, screening populations with a calculated incidence of PET &lt; 4%.</p>", "<p>Ten studies were performed in the first trimester, 32 studies at a mean gestation between 15 to 20 weeks and two studies 20 to 24 weeks.</p>", "<p>The quality assessment of included studies for PET is summarized in Figure ##FIG##1##2##. There was poor reporting of patient selection criteria, description of index and reference tests and blinding of the reference test. Only two studies reported clearly whether preventative treatment had been used. The nine case control studies were excluded from the final meta-analysis, leaving 35 cohort studies for analysis.</p>", "<title>Small for gestational age</title>", "<p>There were 86 included studies for SGA [##REF##10521763##7##,##REF##11028579##9##,##REF##12393965##37##,##REF##11932314##39##,##REF##10548639##47##,##REF##9127156##51##,##REF##8994249##53##, ####REF##8885920##54##, ##REF##8960614##55####8960614##55##,##REF##8559526##57##,##REF##8610755##59##, ####REF##2475017##60##, ##REF##1373447##61####1373447##61##,##REF##15608460##64##, ####REF##15539871##65##, ##REF##15507981##66##, ##REF##16055573##67####16055573##67##,##REF##16263599##69##,##REF##17221926##74##,##REF##8737299##76##, ####REF##8559527##77##, ##REF##1370124##78##, ##REF##12796932##79##, ##REF##7529457##80##, ##REF##7524321##81##, ##REF##2467849##82##, ##REF##6158993##83##, ##REF##6209381##84##, ##REF##2459638##85##, ##REF##9376009##86##, ##REF##2417618##87##, ##REF##12237660##88##, ##REF##9494919##89##, ##REF##8728745##90##, ##REF##8725757##91##, ##UREF##6##92##, ##REF##2440547##93##, ##REF##9419747##94##, ##REF##12932863##95##, ##REF##14526308##96##, ##REF##6202356##97##, ##REF##2422642##98##, ##REF##1603504##99##, ##REF##86301##100##, ##REF##6194484##101##, ##REF##2425844##102##, ##REF##2439965##103##, ##REF##2580253##104##, ##REF##1385554##105##, ##REF##12044318##106##, ##REF##10191802##107##, ##REF##12580835##108##, ##REF##16519620##109##, ##REF##10817024##110##, ##REF##16147728##111##, ##REF##15507982##112##, ##REF##12874670##113##, ##REF##14712947##114##, ##REF##2423067##115##, ##REF##12748511##116##, ##REF##8317532##117##, ##REF##9219457##118##, ##REF##8823604##119##, ##REF##11125251##120##, ##REF##8606883##121##, ##REF##2409736##122##, ##REF##11332414##123##, ##REF##16841275##124##, ##REF##10694681##125##, ##REF##7542379##126##, ##REF##1717806##127##, ##REF##2420339##128##, ##REF##16394054##129##, ##REF##16146246##130##, ##REF##12798540##131##, ##REF##7531210##132##, ##REF##16643816##133##, ##REF##14663836##134##, ##REF##69879##135##, ##REF##6158991##136##, ##REF##1720619##137##, ##REF##1281964##138##, ##REF##6083800##139##, ##REF##1384333##140##, ##REF##9848697##141####9848697##141##], reporting on 382,005 women (20339 cases of SGA, incidence 5.32%). Among these studies, there were 61 cohort studies and 25 case control studies [##REF##8994249##53##,##REF##8960614##55##,##REF##8737299##76##,##REF##8559527##77##,##REF##2467849##82##, ####REF##6158993##83##, ##REF##6209381##84##, ##REF##2459638##85####2459638##85##,##REF##12237660##88##,##REF##9494919##89##,##REF##9419747##94##,##REF##14526308##96##,##REF##6202356##97##,##REF##2580253##104##,##REF##12874670##113##,##REF##12748511##116##,##REF##8823604##119##,##REF##11332414##123##, ####REF##16841275##124##, ##REF##10694681##125####10694681##125##,##REF##16146246##130##,##REF##12798540##131##,##REF##16643816##133##,##REF##69879##135##,##REF##1384333##140##]. Thirty-one studies were prospective, 17 retrospective and 38 of unclear design. Calculated incidence rates of SGA correlated well with the threshold used in 78 of studies and poorly in 8, incidence range for birth weight &lt; 10^thcentile was 1.2–63%. Three of the studies were performed in high risk populations, whereas the remainder were performed in low risk or screening populations. Due to the inclusion criteria of the studies the majority of tests were performed between 15 to 20 weeks. There were ten studies reporting on first trimester screening. Fifty studies reported on birth weight &lt; 10^thcentile, 13 on birth weight &lt; 5^thcentile, 27 on birth weight &lt; 2500 g, 1 on birth weight &lt; 1500 g, 1 on birth weight &lt; 15^thcentile and 12 reported no threshold.</p>", "<p>The quality assessment of included studies for SGA revealed deficiencies (Figure ##FIG##1##2##). Only 40 studies contained an adequate description of the performance of the index test. None of the studies reported clearly on the performance of the reference standard. Blinding of the reference test was also poorly reported as was the use of any treatment in between the index test and reference standard. These items of quality of study design are important in diagnostic accuracy reviews.</p>", "<p>Four papers only distinguished between SGA with PET and SGA alone; intrauterine deaths and stillbirths were excluded from the results for SGA in only 16 papers, in the remainder it was unclear; chromosomal and structural anomalies were excluded from 62 studies, unclear in 24</p>", "<p>Twenty-five case control studies and eight studies [##REF##1370124##78##,##REF##7524321##81##,##REF##2422642##98##,##REF##1385554##105##,##REF##2409736##122##,##REF##1717806##127##,##REF##16394054##129##,##REF##1281964##138##] in which thresholds for SGA were not defined were excluded from the final meta-analysis, leaving 53 studies.</p>", "<title>Data analysis</title>", "<p>For both analysis for PET and analysis for SGA, there was significant heterogeneity in all results. As a consequence of this the random effects model was used throughout the study.</p>", "<title>Maternal serum alpha fetoprotein (AFP)</title>", "<p>The results for AFP are summarized in Figure ##FIG##2##3##, all studies were performed in the second trimester. For PET there were sixteen studies included in the meta-analysis. Thresholds that were most commonly used were &gt; 2.0MoM (multiples of median) (10 studies) and &gt; 2.5MoM (6 studies). The most accurate predictor was AFP&gt;2.0 MoM; LR+ 2.36 (1.46,3.83), LR- 0.96 (0.95,0.98). (One study had a better positive LR however this threshold was chosen from receiver operating curve analysis AFP&gt;1.28MoM; LR+ 3.30 (2.00,5.43), LR- 0.44(0.22,0.90)).</p>", "<p>For SGA there were thirty studies included in the meta-analysis. The commonest threshold used were &gt; 2.0MoM (10 studies) and &gt; 2.5MoM (5 studies) to predict birth weight &lt; 10^thcentile. The best predictor for birth weight &lt; 10^thcentile was AFP&lt;10^thcentile; LR+ 8.80 (5.57,13.91), LR- 0.02 (0.00,0.34), this was a single study. For birth weight &lt; 5^thcentile and birth weight &lt; 2500 g, AFP&gt;3.0MoM was the most accurate predictor. The most accurate predictor overall was AFP&gt;2.0MoM to predict severe SGA (birth weight &lt; 10^thcentile with birth &lt; 37 weeks): LR+ 27.96 (8.02,97.48), LR- 0.78 (0.55, 1.11).</p>", "<title>Maternal serum human chorionic gonadotrophin (HCG)</title>", "<p>The results for HCG are summarized in Figure ##FIG##3##4##. There were forty seven studies overall evaluating HCG, nine for free β-HCG, eight total β-HCG and 30 total HCG. For PET there were 21 included studies in the meta-analysis, 3 looked at testing in the first trimester. The commonest thresholds used were HCG&gt;2.0MoM (12 studies), HCG&gt;2.5MoM (4 studies) and HCG&gt;3.0MoM (3 studies). The most accurate predictor was HCG&gt;2.0MoM with second trimester testing; LR+ 2.45 (1.57,3.84), LR- 0.89 (0.83,0.96). There was one study looking at severe PET as the outcome, results showed no improvement in prediction.</p>", "<p>For SGA there were 22 included studies in the meta-analysis, 5 looked at testing in the first trimester. The commonest thresholds used were HCG&gt;2.0MoM (7 studies) and HCG&gt;2.5MoM (4 studies) for birth weight &lt; 10^thcentile. The most accurate predictor for birth weight &lt; 10^thcentile was HCG&gt;2.0MoM; LR+ 1.74 (1.48,2.04), LR- 0.95 (0.93,0.96). For birth weight &lt; 5^thcentile HCG&gt;2.0MoM in the second trimester was the most accurate and for birth weight &lt; 2500 g HCG&gt;2.5MoM.</p>", "<title>Maternal serum unconjugated Estriol</title>", "<p>The results for unconjugated estriol are summarized in Figure ##FIG##4##5##, all studies were performed in the second trimester. For PET there were 4 included studies, the commonest threshold being estriol&lt;0.5MoM (2 studies), this was also the most accurate predictor; LR+ 1.50 (1.02,2.19), LR- 0.99 (0.97,1.00).</p>", "<p>For SGA there were 7 included studies, the commonest threshold was estriol&lt;0.75MoM (2 studies) for birth weight &lt; 10^thcentile. The most accurate predictor for birth weight &lt; 10^thcentile was estriol&lt;0.75MoM; LR+ 2.54 (1.54,4.19), LR- 0.75 (0.63,0.89). For birth weight &lt; 5^thcentile there were 2 studies for estriol&lt;0.5 MoM; LR+ 6.54 (0.98,43.91), LR- 0.59 (0.03,13.28).</p>", "<title>Maternal serum pregnancy associated plasma protein A (PAPP-A)</title>", "<p>The results for PAPP-A are summarized in Figure ##FIG##5##6##. For PET there were 16 included studies, all performed in the first trimester, the commonest threshold was PAPP-A&lt;5^thcentile (5 studies) and PAPP-A&lt;10^thcentile (3 studies). The most accurate predictor was PAPP-A&lt;5^thcentile; LR+ 2.10 (1.57,2.81), LR- 0.95 (0.93,0.98).</p>", "<p>For SGA there were 10 included studies, 7 were performed in the first trimester, the commonest thresholds were PAPP-A &lt; 5^thcentile (4 studies), PAPP-A&lt;10^thcentile (5 studies) for birth weight &lt; 10^thcentile. The most accurate predictor for birth weight &lt; 10^thcentile was PAPP-A&lt;1^stcentile; LR+ 3.50 (2.53,4.82), LR- 0.98 (0.97,0.99). For birth weight &lt; 5^thcentile, the most accurate predictor was again PAPP-A&lt;1^stcentile; LR+ 4.36 (3.27,5.80), LR- 0.97 (0.96,0.98).</p>", "<title>Maternal serum inhibin A</title>", "<p>The results for inhibin A are summarized in Figure ##FIG##6##7##. For PET there were 6 included studies, 1 performed in the first trimester, the commonest threshold being inhibin A&gt;2.0MoM (2 studies) with a LR+ 6.00 (5.12,7.03), LR- 0.72 (0.48,1.09). The most accurate predictor for PET was inhibin A&gt;2.79MoM; LR+ 19.52 (8.33,45.79), LR- 0.30 (0.13,0.68), however this result was derived from one study using a receiver operating characteristic curve to determine threshold.</p>", "<p>For SGA there was only one study, looking at second trimester testing, using a cut-off of inhibin A&gt;2.0MoM, the results for prediction of birth weight &lt; 10^thcentile were LR+ 4.45 (3.92,5.06), LR- 0.92 (0.91,0.93) and birth weight &lt; 5^thcentile; LR+ 4.91 (4.20,5.73), LR- 0.89 (0.87,0.91).</p>", "<title>Triple test (serum AFP, HCG and unconjugated estriol)</title>", "<p>There were no included studies for PET. For SGA there were 2 studies, second trimester testing, with different cut-offs for prediction of birth weight &lt; 10^thcentile: triple test &gt; 1:190 LR+ 1.07 (0.60,1.91), LR- 0.98 (0.82,1.17) and triple test&gt;1:250 LR+ 2.71 (1.77,4.17), LR- 1.19 (0.01,2.47).</p>", "<title>Gestation of testing</title>", "<p>Table ##TAB##0##1## shows the different results achieved where testing was performed in both the first and second trimester. Overall for HCG, testing in the second trimester was more accurate.</p>", "<title>Sub-group and sensitivity analysis</title>", "<p>For sub group analysis, a sub-group had to include at least three studies within each analyte and threshold and thus was only possible for calculated incidence of disease. The results for sub-group analysis are shown in Table ##TAB##1##2##. There was no significant difference between the subgroups.</p>", "<p>Most of the studies included in the review excluded fetuses with other structural or chromosomal anomalies from the results and included live births only thus subgroup analysis could not be performed in these areas. Sensitivity analysis including only those studies with these characteristics showed no significant difference. The same was true for the assessment of study quality i.e. most studies were of a similar quality to make sub-group analysis impossible but sensitivity analysis showed no difference when extremely low quality studies were excluded.</p>", "<p>Forest plots of sensitivity and specificity are shown in Additional file ##SUPPL##5##6##. Summary receiver operating characteristic curves are available from the authors on request.</p>", "<title>Clinical application with aspirin</title>", "<p>The results for clinical application with aspirin for SGA are shown in Table ##TAB##2##3## and for PET in Table ##TAB##3##4##. The results show that by testing with inhibin A for PET or SGA in a low risk population we can reduce the number of women needed to treat to prevent one case of SGA from 90 to 30 and for PET from 323 to 27, having to test 909 and 469 women respectively.</p>" ]

[ "<title>Discussion</title>", "<p>We evaluated the accuracy of five serum screening markers used in Down's syndrome screening. The results showed low predictive accuracy overall. For PET the best predictor was inhibin A&gt;2.79MoM. However, it is important to point out that this threshold was determined from a receiver operating characteristic curve and based on a single study. For SGA the best predictor overall for birth weight &lt; 10^thcentile was AFP&lt;10^thcentile while AFP&gt;3.0MoM was the best predictor of birth weight &lt; 5^thcentile. These results were both based on single studies. AFP and inhibin A showed improvements in predictive accuracy when looking at severe disease for SGA and PET respectively. HCG showed improved prediction when comparing second trimester to first trimester testing.</p>", "<p>The strength of our review and validity of its findings lies in the methodological strengths used. We complied with existing guidelines for the reporting of systematic reviews [##REF##11267714##18##] and also guidelines specific to the reporting of systematic reviews of observational studies [##REF##10789670##142##]. We performed extensive literature searches without language restrictions. We paid careful attention to assessment of quality of study design and reporting (The Quorum statement for this review is shown in Additional file ##SUPPL##6##7##).</p>", "<p>Previously published reviews in this area are restricted to a systematic review evaluating predictive tests for PET [##REF##15572504##143##]. This review concluded that the tests investigated had a low predictive value, the methodology of this review has however been criticized [##REF##15863566##144##] and was restricted in the thresholds and tests it reviewed. To our knowledge there are no previously reported systematic reviews in this area for SGA.</p>", "<p>We have primarily reported likelihood ratios in this review as they are thought to be more clinically meaningful than sensitivities and specificities, the use of likelihood ratios allowing us to determine post test probabilities of disease based on Bayes' theorem. Recent research suggests that independently pooled likelihood ratios should be interpreted with caution as positive and negative likelihood ratios are related statistics (just like sensitivity and specificity) [##UREF##7##145##]. We also pooled sensitivity and specificity and found no difference in the interpretation of the results. Bivariate meta-analysis is a new statistical technique that explicitly incorporates the correlation between sensitivity and specificity in a single model [##REF##16168343##146##], its use is however not yet widespread nor is it easily interpreted.</p>", "<p>Our assessment of study quality was hindered by lack of clear reporting, which is a common problem in diagnostic reviews as standards for quality and checklists for assessing it are fairly new. It has been previously reported that poor study design and conduct can affect the estimates of diagnostic accuracy [##REF##10493205##28##,##REF##16477057##29##] however, it is not entirely clear how individual aspects of quality may effect this and to what magnitude particularly in the area of Obstetrics. Application of quality scores has been shown to be of little value on diagnostic reviews [##REF##15918898##147##] however, due to the lack of clear reporting it was not possible to perform sub-group analysis based on individual quality criteria.</p>", "<p>One of the areas in which reporting was uniformly poor was in the details provided regarding performance of the reference standard. In PET definitions have changed over time with previous definitions including change increases in blood pressure. The measurement of blood pressure was poorly reported. It is important to record diastolic blood pressure with Korotkoff phase V as this is more reliably recorded and reflects true diastolic blood pressure [##REF##10925900##148##, ####REF##8544546##149##, ##REF##8092212##150####8092212##150##]. For SGA there is still no convincing evidence as to which is the best definition of the condition at birth nor which is the best predictor of future infant and childhood morbidity and mortality for term infants. Population based birth weight standards were the most commonly used, however it is important to realize that these do not distinguish between the small healthy infant and the compromised infant. Customised growth charts that are adjusted for sex, gestation, parity, maternal weight and height and ethnicity, have been shown to improve the detection of infants at risk of stillbirth [##REF##11510708##151##] while neonatal indices have been shown to identify the malnourished infant at risk of peripartum asphyxia [##REF##5910362##152##]. Unfortunately these were rarely used as outcome measures in the included reviews.</p>", "<p>Confounding factors in measurement of serum screening markers but mainly AFP is its association with intrauterine death, preterm labour and chromosomal and structural anomalies [##REF##8885920##54##,##REF##8559526##57##,##REF##2475017##60##]. Ideally all the included papers in this review should have included only women with live births and fetuses with no other chromosomal or structural anomalies, this however was not always clearly reported. Sensitivity analysis, including only studies that did report exclusion of these subjects showed no significant difference in estimates of test accuracy.</p>", "<p>In this review we have also assumed that the markers act independently but this may not be the case. The relationship between PET and SGA must also be taken into account. For HCG measurement the risk of SGA has been shown by logistic regression to be dependent on the presence of PET [##REF##1603504##99##]. Ideally included cases of SGA for this review would have been those where there was no PET but this was again poorly reported.</p>", "<p>When assessing the clinical relevance of these tests it is important to look at severe disease as this causes the majority of maternal, fetal and neonatal complications and thus prediction and prevention of this form of disease would have the greatest health impact. For the studies included in the meta-analysis there were only three that had results for either severe PET or SGA and these were insufficient to make an accurate assessment of the prediction of this form of disease.</p>", "<p>The calculations of NNTreat and NNTest show that we can reduce the number of women needed to treat with aspirin to prevent one case of SGA/PET if we first test with a serum screening marker and then only treat the test positives. As aspirin is not routinely used as a treatment these calculations serve to contextualize the predictive value of these markers as individual tests. The costs of introducing aspirin as a treatment would need to be balanced against the costs of the test, costs of failing to treat the women with a false negative result that then go on to develop disease and any patient costs in terms of anxiety from screening and over treatment in the false positive category. To thus calculate the true clinical effectiveness of these tests these results would need to be incorporated in to a full cost-effectiveness analysis.</p>", "<p>As PET and SGA are diseases with relatively low prevalence a clinically useful test would need to have a high positive LR (&gt; 10) and low negative LR (&lt; 0.10) [##REF##15258077##153##]. From the results of this review it is unlikely that any one serum screening marker in isolation will provide this. Future research should thus concentrate in two areas. The first should be to address the limitations within the primary literature as identified by this review; poor reporting, exclusion of intrauterine deaths and chromosomal and structural anomalies from the results, separation of PET and SGA, prediction of severe disease. This may not necessarily require further primary research as there are sufficient large, well designed cohort studies available but meta-analysis based on individual patient data. Secondly future research should focus on combinations of markers as predictors and combinations of tests such as serum screening markers and uterine artery Doppler [##REF##7485303##154##] to improve the predictive accuracy to a clinically useful value.</p>", "<p>As Down's serum screening is routinely performed in many developed countries the cost of implementing use of these results as a predictive test for PET and SGA would be small. However as aspirin is the only preventative treatment with any proven benefit in these conditions and has minimal adverse events this cost has to be compared to that of implementing aspirin treatment to all pregnant women.</p>" ]

[ "<title>Conclusion</title>", "<p>Down's serum screening analytes have low predictive accuracy for pre-eclampsia and small for gestational age. They may be a useful means of risk assessment or of use in prediction when combined with other tests.</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Reliable antenatal identification of pre-eclampsia and small for gestational age is crucial to judicious allocation of monitoring resources and use of preventative treatment with the prospect of improving maternal/perinatal outcome. The purpose of this systematic review was to determine the accuracy of five serum analytes used in Down's serum screening for prediction of pre-eclampsia and/or small for gestational age.</p>", "<title>Methods</title>", "<p>The data sources included Medline, Embase, Cochrane library, Medion (inception to February 2007), hand searching of relevant journals, reference list checking of included articles, contact with experts. Two reviewers independently selected the articles in which the accuracy of an analyte used in Downs's serum screening before the 25^thgestational week was associated with the occurrence of pre-eclampsia and/or small for gestational age without language restrictions. Two authors independently extracted data on study characteristics, quality and results.</p>", "<title>Results</title>", "<p>Five serum screening markers were evaluated. 44 studies, testing 169,637 pregnant women (4376 pre-eclampsia cases) and 86 studies, testing 382,005 women (20,339 fetal growth restriction cases) met the selection criteria. The results showed low predictive accuracy overall. For pre-eclampsia the best predictor was inhibin A&gt;2.79MoM positive likelihood ratio 19.52 (8.33,45.79) and negative likelihood ratio 0.30 (0.13,0.68) (single study). For small for gestational age it was AFP&gt;2.0MoM to predict birth weight &lt; 10^thcentile with birth &lt; 37 weeks positive likelihood ratio 27.96 (8.02,97.48) and negative likelihood ratio 0.78 (0.55,1.11) (single study). A potential clinical application using aspirin as a treatment is given as an example.</p>", "<p>There were methodological and reporting limitations in the included studies thus studies were heterogeneous giving pooled results with wide confidence intervals.</p>", "<title>Conclusion</title>", "<p>Down's serum screening analytes have low predictive accuracy for pre-eclampsia and small for gestational age. They may be a useful means of risk assessment or of use in prediction when combined with other tests.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>The following authors were responsible for the study concept and design: RKM, JSC, GtR, BWM, JAMvdP, JK, KSK, SCR. The following authors were responsible for acquisition of data: RKM, JSC, ML, BWM.</p>", "<p>Analysis and interpretation of data was performed by the following authors: RKM, JSC, KSK. Drafting of the manuscript was performed by: RKM, JSC, ML, GtR, BWM, JAMvdP, KSK, JK, SCR. Statistical analysis was performed by: RKM, JSC, KSK. All authors read and approved the final manuscript. </p>", "<p>RKM had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.</p>", "<title>Pre-publication history</title>", "<p>The pre-publication history for this paper can be accessed here:</p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.biomedcentral.com/1471-2393/8/33/prepub\"/></p>", "<title>Supplementary Material</title>" ]

[ "<title>Acknowledgements</title>", "<p>Faridi van Etten, Amsterdam Medical Center for help with searches. This study was supported by two project grants from Wellbeing of Women (NBTF626\\03) and NHS Health Technology Assessment UK (01/64). The funding sources had no role in the collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication.</p>" ]

[ "<fig position=\"float\" id=\"F1\"><label>Figure 1</label><caption><p><bold>Process from initial search to final inclusion for biochemical screening to predict pre-eclampsia/small for gestational age (up to February 2007).</bold> PET preeclampsia; PIH pregnancy induced hypertension; SGA small for gestational age.</p></caption></fig>", "<fig position=\"float\" id=\"F2\"><label>Figure 2</label><caption><p>Bar chart showing quality of evidence on biochemical screening markers to predict small for gestational age and pre-eclampsia.</p></caption></fig>", "<fig position=\"float\" id=\"F3\"><label>Figure 3</label><caption><p><bold>Forest Plot showing likelihood ratio of a positive and negative test result with 95% confidence intervals (95% CI) for studies of alpha feto-protein (AFP) to predict pre-eclampsia and small for gestational age (birth weight threshold as indicated).</bold> Results with diamonds are pooled results (number of studies as indicated), results with squares are single studies. The number of women included in the studies is shown, all studies second trimester testing.</p></caption></fig>", "<fig position=\"float\" id=\"F4\"><label>Figure 4</label><caption><p><bold>Forest Plot showing likelihood ratio of a positive and negative test result with 95% confidence intervals (95% CI) for studies of human chorionic gonadotrophin (HCG) to predict pre-eclampsia and small for gestational age (birth weight threshold as indicated).</bold> Results with diamonds are pooled results (number of studies as indicated), results with squares are single studies. The number of women included in the studies is shown. (^afirst trimester testing).</p></caption></fig>", "<fig position=\"float\" id=\"F5\"><label>Figure 5</label><caption><p><bold>Forest Plot showing likelihood ratio of a positive and negative test result with 95% confidence intervals (95% CI) for studies of estriol to predict pre-eclampsia and small for gestational age (birth weight threshold as indicated).</bold> Results with diamonds are pooled results (number of studies as indicated), results with squares are single studies. The number of women included in the studies is shown, all studies second trimester testing.</p></caption></fig>", "<fig position=\"float\" id=\"F6\"><label>Figure 6</label><caption><p><bold>Forest Plot showing likelihood ratio of a positive and negative test result with 95% confidence intervals (95% CI) for studies of pregnancy associated plasma protein A (PAPPA) to predict pre-eclampsia and small for gestational age (birth weight threshold as indicated).</bold> Results with diamonds are pooled results (number of studies as indicated), results with squares are single studies. The number of women included in the studies is shown. (^afirst trimester testing).</p></caption></fig>", "<fig position=\"float\" id=\"F7\"><label>Figure 7</label><caption><p>Forest Plot showing likelihood ratio of a positive and negative test result with 95% confidence intervals (95% CI) for studies of Inhibin A to predict pre-eclampsia and small for gestational age (birth weight threshold as indicated). Results with diamonds are pooled results (number of studies as indicated), results with squares are single studies. The number of women included in the studies is shown. (^afirst trimester testing).</p></caption></fig>" ]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Subgroup analyses of accuracy of biochemical screening to predict small for gestational age and pre-eclampsia (random effects pooling).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"5\"><bold><italic>Small for gestational age</italic></bold></td></tr></thead><tbody><tr><td align=\"left\"><bold><italic>Analyte </italic></bold><italic>Subgroup</italic></td><td align=\"left\"><bold><italic>Positive Likelihood Ratio (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Negative Likelihood Ratio (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Sensitivity (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Specificity (95% CI)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&gt;90^thcentile (BW&lt;10th centile)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Trimester</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">First</td><td align=\"left\">1.48 (0.57–3.81)</td><td align=\"left\">0.92 (0.72–1.17)</td><td align=\"left\">0.21 (0.06–0.46)</td><td align=\"left\">0.86 (0.79–0.91)</td></tr><tr><td align=\"left\">Second</td><td align=\"left\">1.68 (0.37–7.63)</td><td align=\"left\">0.97 (0.86–1.09)</td><td align=\"left\">0.08 (0.01–0.26)</td><td align=\"left\">0.95 (0.90–0.98)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&lt;10^thcentile (BW&lt;10th centile)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Trimester</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">First</td><td align=\"left\">1.29 (0.05–33.56)</td><td align=\"left\">1.14 (0.53–2.43)</td><td align=\"left\">0.13 (0.10–0.16)</td><td align=\"left\">0.60 (0.57–0.63)</td></tr><tr><td align=\"left\">Second</td><td align=\"left\">2.35 (0.80–6.92)</td><td align=\"left\">0.90 (0.76–1.08)</td><td align=\"left\">0.16 (0.05–0.36)</td><td align=\"left\">0.93 (0.88–0.97)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&gt;2.0MoM (BW&lt;5th centile)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Trimester</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">First</td><td align=\"left\">0.96 (0.55–1.68)</td><td align=\"left\">1.01 (0.88–1.17)</td><td align=\"left\">0.20 (0.10–0.34)</td><td align=\"left\">0.79 (0.77–0.81)</td></tr><tr><td align=\"left\">Second</td><td align=\"left\">2.08 (1.78–2.42)</td><td align=\"left\">0.94 (0.92–0.95)</td><td align=\"left\">0.12 (0.10–0.14)</td><td align=\"left\">0.94 (0.94–0.95)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>PAPPA&lt;10^thcentile (BW&lt;10^thcentile)</italic></bold></td></tr><tr><td align=\"left\"><italic>Trimester</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">First</td><td align=\"left\">1.68 (1.25–2.27)</td><td align=\"left\">0.93 (0.88–0.98)</td><td align=\"left\">0.17 (0.16–0.19)</td><td align=\"left\">0.90 (0.89–0.90)</td></tr><tr><td align=\"left\">Second</td><td align=\"left\">1.82 (0.95–3.50)</td><td align=\"left\">0.91 (0.75–1.05)</td><td align=\"left\">0.20 (0.10–0.33)</td><td align=\"left\">0.89 (0.85–0.92)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\" colspan=\"5\"><bold><italic>Pre-eclampsia</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&gt;2.0MoM</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Trimester</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">First</td><td align=\"left\">1.77 (1.07–2.92)</td><td align=\"left\">0.80 (0.60–1.07)</td><td align=\"left\">0.37 (0.19–0.58)</td><td align=\"left\">0.79 (0.77–0.81)</td></tr><tr><td align=\"left\">Second</td><td align=\"left\">2.45 (1.57–3.84)</td><td align=\"left\">0.89 (0.83–0.96)</td><td align=\"left\">0.19 (0.17–0.21)</td><td align=\"left\">0.93 (0.93–0.93)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Subgroup analyses of accuracy of biochemical screening to predict small for gestational age and pre-eclampsia (random effects pooling)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\" colspan=\"5\"><bold><italic>Small for gestational age</italic></bold></td></tr></thead><tbody><tr><td align=\"left\"><bold><italic>Analyte </italic></bold><italic>Subgroup</italic></td><td align=\"left\"><bold><italic>Positive Likelihood Ratio (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Negative Likelihood Ratio (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Sensitivity (95% CI)</italic></bold></td><td align=\"left\"><bold><italic>Specificity (95% CI)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>AFP&gt;2.0MoM (BW&lt;10th centile)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Incidence</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">&gt;10%</td><td align=\"left\">2.69 (1.36–5.31)</td><td align=\"left\">0.98 (0.96–1.00)</td><td align=\"left\">0.04 (0.02–0.08)</td><td align=\"left\">0.98 (0.98–0.99)</td></tr><tr><td align=\"left\">≤ 10%</td><td align=\"left\">3.71 (2.66–5.16)</td><td align=\"left\">0.93 (0.88–0.97)</td><td align=\"left\">0.06 (0.05–0.07)</td><td align=\"left\">0.98 (0.98–0.98)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&gt;2.0MoM(BW&lt;10th centile)</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Incidence</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">&gt;10%</td><td align=\"left\">1.53 (1.1–2.12)</td><td align=\"left\">0.89 (0.77–1.04)</td><td align=\"left\">0.29 (0.22–0.37)</td><td align=\"left\">0.79 (0.77–0.82)</td></tr><tr><td align=\"left\">≤ 10%</td><td align=\"left\">1.92 (1.72–2.13)</td><td align=\"left\">0.95 (0.94–0.96)</td><td align=\"left\">0.11 (0.1–0.12)</td><td align=\"left\">0.94 (0.94–0.95)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"center\" colspan=\"5\"><bold><italic>Pre-eclampsia</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>AFP&gt;2.0MoM</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Incidence</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">&gt;4%</td><td align=\"left\">0.85 (0.41–1.78)</td><td align=\"left\">1.01 (0.97–1.06)</td><td align=\"left\">0.06 (0.02–0.13)</td><td align=\"left\">0.93 (0.91–0.94)</td></tr><tr><td align=\"left\">≤ 4%</td><td align=\"left\">2.98 (1.77–5.03)</td><td align=\"left\">0.96 (0.95–0.97)</td><td align=\"left\">0.08 (0.06–0.09)</td><td align=\"left\">0.96 (0.96–0.96)</td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\" colspan=\"5\"><bold><italic>HCG&gt;2.0MoM</italic></bold></td></tr><tr><td colspan=\"5\"><hr/></td></tr><tr><td align=\"left\"><italic>Incidence</italic></td><td/><td/><td/><td/></tr><tr><td align=\"left\">&gt;4%</td><td align=\"left\">2.45 (0.65–2.93)</td><td align=\"left\">0.68 (0.42–1.1)</td><td align=\"left\">0.25 (0.21–0.3)</td><td align=\"left\">0.92 (0.91–0.93)</td></tr><tr><td align=\"left\">≤ 4%</td><td align=\"left\">2.36 (1.81–3.08)</td><td align=\"left\">0.89 (0.85–0.95)</td><td align=\"left\">0.18 (0.16–0.2)</td><td align=\"left\">0.93 (0.92–0.93)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Serum screening among pregnant women and number of women needed to be tested and treated with aspirin to prevent one case of SGA (birth weight &lt; 10^thcentile).</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Test result</bold></td><td align=\"right\"><bold>Prevalence SGA (%)</bold></td><td align=\"right\"><bold>Probability of SGA after testing positive (%)</bold></td><td align=\"center\"><bold>Risk of SGA after treatment*</bold></td><td align=\"center\"><bold>Probability of SGA after treatment</bold></td><td align=\"center\"><bold>NNTest¹</bold></td><td align=\"center\"><bold>NNTreat²</bold></td></tr></thead><tbody><tr><td align=\"left\">No test, no treatment³</td><td align=\"right\">10.0</td><td align=\"right\">10.0</td><td align=\"center\">-</td><td align=\"center\">10.0</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td align=\"left\">No test, treat all³</td><td align=\"right\">10.0</td><td align=\"right\">-</td><td align=\"center\">0.90</td><td align=\"center\">9.0</td><td align=\"center\">-</td><td align=\"center\">90</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Alpha feto-protein&gt;2.0MoM: Sensitivity 60%; Specificity 98%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">10.0</td><td align=\"right\">28.3</td><td align=\"center\">0.90</td><td align=\"center\">25.4</td><td align=\"center\">167</td><td align=\"center\">35</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Human chorionic gonadotrophin&gt;2.0MoM: Sensitivity 12%; Specificity 94%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">10.0</td><td align=\"right\">16.2</td><td align=\"center\">0.90</td><td align=\"center\">14.6</td><td align=\"center\">833</td><td align=\"center\">62</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Unconjugated estriol&lt;0.75MoM: Sensitvity 37%; Specifcitiy 88%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">10.0</td><td align=\"right\">22.0</td><td align=\"center\">0.90</td><td align=\"center\">19.8</td><td align=\"center\">270</td><td align=\"center\">45</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Pregnancy associated plasma protein A (PAPP-A)&lt;1^stcentile: Sensitivity 3%; Specificity 99%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">10.0</td><td align=\"right\">28.0</td><td align=\"center\">0.90</td><td align=\"center\">25.2</td><td align=\"center\">3333</td><td align=\"center\">36</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Inhibin A&gt;2.0MoM: Sensitivity 11%; Specificity 98%.</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">10.0</td><td align=\"right\">33.1</td><td align=\"center\">0.90</td><td align=\"center\">29.8</td><td align=\"center\">909</td><td align=\"center\">30</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Alpha feto-protein&gt;2.0MoM to predict severe FGR: Sensitivity 22%, Specificity 99%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">1.0</td><td align=\"right\">22.0</td><td align=\"center\">0.90</td><td align=\"center\">19.8</td><td align=\"center\">454</td><td align=\"center\">45</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T4\"><label>Table 4</label><caption><p>Serum screening among pregnant women and number of women needed to be tested and treated with aspirin to prevent one case of PET.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"left\"><bold>Test result</bold></td><td align=\"right\"><bold>Prevalence PET (%)</bold></td><td align=\"right\"><bold>Probability of PET after testing positive (%)</bold></td><td align=\"center\"><bold>Risk of PET after treatment*</bold></td><td align=\"center\"><bold>Probability of PET after treatment</bold></td><td align=\"center\"><bold>NNTest¹</bold></td><td align=\"center\"><bold>NNTreat²</bold></td></tr></thead><tbody><tr><td align=\"left\">No test, no treatment³</td><td align=\"right\">3.0</td><td align=\"right\">3.0</td><td align=\"center\">-</td><td align=\"center\">3.0</td><td align=\"center\">-</td><td align=\"center\">-</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">10.0</td><td/><td align=\"center\">10.0</td><td/><td/></tr><tr><td align=\"left\">No test, treat all³</td><td align=\"right\">3.0</td><td align=\"right\">-</td><td align=\"center\">0.9</td><td align=\"center\">2.8</td><td align=\"center\">-</td><td align=\"center\">323</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">-</td><td align=\"center\">0.9</td><td align=\"center\">9.0</td><td align=\"center\">-</td><td align=\"center\">90</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Alpha feto-protein&gt;2.0MoM: Sensitivity 7%; Specificity 96%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">3.0</td><td align=\"right\">7.3</td><td align=\"center\">0.9</td><td align=\"center\">6.1</td><td align=\"center\">4762</td><td align=\"center\">147</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">26.2</td><td align=\"center\">0.9</td><td align=\"center\">18.6</td><td align=\"center\">1429</td><td align=\"center\">48</td></tr><tr><td colspan=\"7\"><hr/></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Human chorionic gonadotrophin&gt;2.0MoM, second trimester: Sensitivity 19%; Specificity 93%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">3.0</td><td align=\"right\">7.5</td><td align=\"center\">0.9</td><td align=\"center\">6.3</td><td align=\"center\">1754</td><td align=\"center\">142</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">27.2</td><td align=\"center\">0.9</td><td align=\"center\">19.3</td><td align=\"center\">526</td><td align=\"center\">47</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Unconjugated estriol&lt;0.5MoM: Sensitvity 6%; Specifcitiy 96%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">3.0</td><td align=\"right\">4.6</td><td align=\"center\">0.9</td><td align=\"center\">4.0</td><td align=\"center\">5556</td><td align=\"center\">226</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">16.7</td><td align=\"center\">0.9</td><td align=\"center\">12.8</td><td align=\"center\">1667</td><td align=\"center\">70</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Pregnancy associated plasma protein A (PAPP-A)&lt;5th centile: Sensitivity 9%; Specificity 95%</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">3.0</td><td align=\"right\">6.5</td><td align=\"center\">0.9</td><td align=\"center\">5.5</td><td align=\"center\">3704</td><td align=\"center\">167</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">23.3</td><td align=\"center\">0.9</td><td align=\"center\">17.0</td><td align=\"center\">1111</td><td align=\"center\">53</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Inhibin A&gt;2.79MoM: Sensitivity 71%; Specificity 96%.</bold></td></tr><tr><td align=\"left\">Test all, treat test positives</td><td align=\"right\">3.0</td><td align=\"right\">6.0</td><td align=\"center\">0.9</td><td align=\"center\">3.4</td><td align=\"center\">469</td><td align=\"center\">27</td></tr><tr><td/><td align=\"right\">10.0</td><td align=\"right\">216.9</td><td align=\"center\">0.9</td><td align=\"center\">61.2</td><td align=\"center\">141</td><td align=\"center\">15</td></tr></tbody></table></table-wrap>" ]

[]

[]

[]

[]

[]

[ "<supplementary-material content-type=\"local-data\" id=\"S1\"><caption><title>Additional file 1</title><p>\"Prediction of pre-eclampsia: a protocol for systematic reviews of test accuracy.\" Study protocol for pre-eclampsia systematic reviews.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S2\"><caption><title>Additional file 2</title><p>\"The value of predicting restriction of fetal growth and compromise of its wellbeing: Systematic quantitative overviews (meta-analysis) of test accuracy literature.\" Study protocol for fetal growth restriction systematic reviews.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S3\"><caption><title>Additional file 3</title><p>\"Search strategies for biochemical markers used in Down's serum screening to predict preeclampsia/small for gestational age.\" Electronic search strategies for systematic reviews.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S4\"><caption><title>Additional file 4</title><p>\"Guide to QUADAS for Down's syndrome markers to predict pre-eclampsia/small for gestational age.\" Guide to quality assessment of included papers in review using QUADAS tool.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S5\"><caption><title>Additional file 5</title><p>\"Study characteristics of studies of included studies for maternal serum biochemical (Down syndrome) screening to predict pre-eclampsia and small for gestational age.\"</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S6\"><caption><title>Additional file 6</title><p>\"Forest plots of sensitivity and specificity.\" Results of sensitivity and specificity displayed as Forest plots.</p></caption></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"S7\"><caption><title>Additional file 7</title><p>\"Improving the quality of reports of meta-analyses of randomised controlled trials: the Quorum Statement checklist.\" The Quorum statement checklist.</p></caption></supplementary-material>" ]

[ "<table-wrap-foot><p>(CI confidence intervals, AFP alpha feto-protein, HCG human chorionic gonadotrophin, BW birth weight, MoM multiple of median). Analyses according to gestation of testing of accuracy of biochemical screening to predict small for gestational age and pre-eclampsia (random effects pooling). (CI confidence intervals, HCG human chorionic gonadotrophin, BW birth weight, MoM multiple of median, PAPPA pregnancy associated plasma protein A)</p></table-wrap-foot>", "<table-wrap-foot><p>(CI confidence intervals, AFP alpha feto-protein, HCG human chorionic gonadotrophin, BW birth weight, MoM multiple of median)</p></table-wrap-foot>", "<table-wrap-foot><p>* RR 0.90 (95% CI 0.84–0.97) Askie et al. Antiplatelet agents for prevention of pre-eclampsia: meta-analysis of individual patient data. Lancet 2007;369:1791–98;¹¹.</p><p>¹NNTest is number needed to test and treat with aspirin to prevent one case of SGA calculated by 1/(proportion true positives (TP) – (proportion TP * RR)).</p><p>²NNTreat is number need to treat if only treat test positives with aspirin calculated by 1/(probability after testing positive – probability after treatment).</p><p>³Numbers are equal for all tests regardless of threshold, sensitivity and specificity.</p><p>MoM multiples of median</p><p>SGA small for gestational age</p></table-wrap-foot>", "<table-wrap-foot><p>* RR 0.90 (95% CI 0.81–1.01) Askie et al. Antiplatelet agents for prevention of pre-eclampsia: a meta-analysis of individual patient data. Lancet 2007;369:1791–98¹¹.</p><p>¹NNTest is number needed to test and treat with aspirin to prevent one case of FGR calculated by 1/(proportion true positives (TP) – (proportion TP * RR)).</p><p>²NNTreat is number need to treat if only treat test positives with aspirin calculated by 1/(probability after testing positive – probability after treatment).</p><p>³Numbers are equal for all tests regardless of threshold, sensitivity and specificity.</p><p>MoM multiples of median</p><p>PET pre-eclampsia</p></table-wrap-foot>" ]

[ "<graphic xlink:href=\"1471-2393-8-33-1\"/>", "<graphic xlink:href=\"1471-2393-8-33-2\"/>", "<graphic xlink:href=\"1471-2393-8-33-3\"/>", "<graphic xlink:href=\"1471-2393-8-33-4\"/>", "<graphic xlink:href=\"1471-2393-8-33-5\"/>", "<graphic xlink:href=\"1471-2393-8-33-6\"/>", "<graphic xlink:href=\"1471-2393-8-33-7\"/>" ]

[ "<media xlink:href=\"1471-2393-8-33-S1.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S2.pdf\" mimetype=\"application\" mime-subtype=\"pdf\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S3.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S4.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S5.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S6.doc\" mimetype=\"application\" mime-subtype=\"msword\"><caption><p>Click here for file</p></caption></media>", "<media xlink:href=\"1471-2393-8-33-S7.bmp\" mimetype=\"image\" mime-subtype=\"bmp\"><caption><p>Click here for file</p></caption></media>" ]

{ "acronym": [], "definition": [] }

[ "<title>Introduction</title>", "<p>Cigarette smoking is a well-established risk factor for vascular disease and stroke. Various mechanisms that link cigarette smoking to these risks have been described, including: vasomotor dysfunction [##REF##9887164##1##, ####REF##15145091##2##, ##REF##12920702##3####12920702##3##] modification of the lipid profile (notably increased oxidation of LDL) [##REF##9887164##1##,##REF##15145091##2##,##REF##2496857##4##], modification of prothrombotic effects, including altered platelet function [##REF##15145091##2##,##REF##2951895##5##], and deregulation of antithrombotic, prothrombotic, and fibrinolytic mechanisms [##REF##9887164##1##,##REF##15145091##2##]. The final common pathway shared by these mechanisms is heightened inflammation, which is also considered a potential risk mechanism [##REF##9887164##1##,##REF##15145091##2##,##REF##16339501##6##]. Each of the mechanisms is under the influence of multiple genes, therefore an individuals' susceptibility to the detrimental effects of cigarette smoke appears to be related to their pro-inflammatory versus anti-inflammatory gene-specific allele load. This hypothesis is supported by multiple studies that indicate pro-inflammatory gene-specific allele load is associated with enhanced inflammation and early atherosclerosis in smokers [##REF##15472098##7##, ####REF##15039035##8##, ##REF##16873708##9##, ##REF##9125293##10####9125293##10##]. Many inflammatory genes have been implicated in these relationships, specific to this study these include: interleukin-1A (<italic>IL1A; </italic>OMIM 147760), interleukin-1 receptor – type I precursor (<italic>IL1R1; </italic>OMIM 147810), interleukin-1B (<italic>IL1B; </italic>OMIM 147720), interleukin-6 (<italic>IL6; </italic>OMIM 147620), stromelysin-1 (<italic>MMP3; </italic>OMIM 185250), and monocyte endotoxin receptor (<italic>CD14; </italic>OMIM 158120). In this study, we analyze the relationships between various polymorphisms of these genes, ischemic stroke risk, and smoking status.</p>" ]

[ "<title>Research design and methods</title>", "<title>Study subjects</title>", "<p>The Stroke Prevention in Young Women Study 2 (SPYW2) is a population-based case-control study that was designed to examine genetic risk factors for ischemic stroke in young women. The term \"population-based\" indicates that the cases and the comparison control group were identified from the same population including all of Maryland (except the far Western panhandle), Washington DC, and the southern portions of both Pennsylvania and Delaware. Two hundred thirty nine female cases age 15 to 49 years of age with a first cerebral infarction were identified by discharge surveillance at 51 regional hospitals and through direct referral by regional neurologists. The methods for discharge surveillance, chart abstraction, and case adjudication have been described previously [##REF##7839396##11##, ####REF##8703181##12##, ##REF##9566368##13####9566368##13##]. We determined each subject's case-control status (i.e. determined subjects who had a stroke) blinded to genetic information. Strokes were classified as having a probable, possible or undetermined etiology [##REF##7839396##11##,##REF##8703181##12##]. Using predetermined exclusion criteria, modified from the Siblings With Ischemic Stroke Study (SWISS) protocol [##REF##11882254##14##], we excluded 15 cases with the following characteristics: sickle cell disease (n = 1), CNS vasculitis by angiogram and clinical criteria (n = 3), post-radiation arteriopathy (n = 1), endocarditis (n = 3), neurosyphillis (n = 1), mechanical prosthetic heart valves (n = 2), left atrial myxoma (n = 1), and cocaine use in the 48 hours prior to their stroke (n = 3). Controls subjects (212 women without a history of stroke), were identified by random digit dialing and were frequency matched to the cases by age and geographic region of residence. One control was excluded from analyses based on a history of sickle cell disease. Thus, the sample for genetic analyses consisted of 224 cases and 211 controls.</p>", "<p>Cases and controls were grouped into the following race-ethnic categories: Caucasian (non-Hispanic) (95 cases and 99 controls), African-American (105 cases and 91 controls), and other (including Hispanic, Asian, American-Indian, etc.) (24 cases and 21 controls). Because of the small size and heterogeneity of the latter group, it was not analyzed separately, but was included within the combined total study group (224 cases and 211 controls). Strokes were further classified by subtype: the atherosclerotic group included 27 cases with either probable or possible atherosclerotic mechanism, the cardiac group included 14 cases with a probable cardiac source of embolism, the probable dissection group included 13 cases confirmed by neuroimaging, the lacunar group included 45 cases of symptomatic small deep lesions on neuroimaging studies or classic lacunar syndromes regardless of other potential causes, and the probable hematologic group included 9 cases. These categories were not mutually exclusive. There were 125 non-lacunar stroke cases of undetermined etiology.</p>", "<title>Single Nucleotide Polymorphisms (SNPs) evaluated</title>", "<p>We identified genes and SNPs that influence inflammation through a literature review seeking an association of the genes and SNPs with vascular disease (stroke, myocardial infarction, peripheral vascular disease, or atherosclerosis). If the evidence suggested that smoking might modify the relationship between gene or SNP and stroke through a gene-environment interaction, a higher priority for inclusion in our analyses was assigned to that gene or SNP. Because we sought to evaluate common SNPs, only those SNPs with a minor allele frequency of 0.05 or greater among African-Americans or Caucasians as per the NCBI SNP website <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&amp;DB=snp\"/> were evaluated. After weighing these considerations, the final list of genes and SNPs analyzed in this study included: <italic>CD14 </italic>(rs2569190), <italic>IL1A </italic>(rs17561), <italic>IL1R1 </italic>(rs3917318), <italic>IL1B </italic>(rs3917365), <italic>IL6 </italic>(rs1800797, rs2069830, 2069832), and <italic>MMP3 </italic>(rs679620).</p>", "<title>Genotyping methods for the case/control population</title>", "<p>Genotyping was conducted on DNA isolated from whole blood using the QIAamp DNA Blood Maxi Kit (Qiagen, Valencia, CA). SNP genotyping was performed by one of two methods. The first method, developed for a SNP stream Ultra-High Throughput machine (Beckman Coulter, Inc., Fullerton, CA) is capable of genotyping up to 12-SNPs simultaneously. Sequences surrounding the SNPs were obtained from GenBank <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/Genbank/index.html\"/> and submitted to Autoprimer.com (Beckman Coulter, Inc.). For each SNP, three primers were designed, two for PCR amplification and an internal primer with a 5' DNA sequence tag. Pairs of primers were used to initiate PCR amplification. The free primers were removed by enzymatic digestion using Exonuclease I and Shrimp Alkaline Phosphotase (Beckman Coulter, Inc.). The internal primers were used to initiate a sequencing reaction that adds one labeled base for the alternative nucleotides of each SNP to have distinct labels. The labeled products are separated on a SNP-IT plate consisting of 384 mini-arrays with 16-spots each (Beckman Coulter, Inc.). For each individual DNA sample, 16 spots hybridized to the two homozygotes, the heterozygote, a negative control and the 12-labeled primers associated with the 12-SNPs. Thus, every PCR and labeling reaction had internal controls to confirm the success of the reactions and the appropriateness of the fluorescent outputs for each DNA sample. SNPs genotyped using this method include: <italic>IL1R1 </italic>(rs3917318); <italic>IL1B </italic>(rs3917365); <italic>IL6 </italic>(rs1800797, 2069832).</p>", "<p>The second genotyping method was Taqman (Applied Biosystems). This method is based on four primers, two flanking the SNP that are used to amplify the DNA surrounding the SNP and two, one for each alternative allele, that were labeled with different fluorescent dyes. The original form of the labeled primer has a quencher in close proximity to the dye. However, when the exonuclease activity of DNA polymerase disrupts the primer hybridized to the single strand DNA during the PCR, then quencher and the dye are released and the fluorescence can be measured. The reaction itself follows manufacturer's instructions included with each individual primer set. SNPs genotyped using this method include: <italic>CD14 </italic>(rs2569190); <italic>IL1A </italic>(rs17561); <italic>IL6 </italic>(rs2069830); <italic>MMP3 </italic>(rs679620).</p>", "<title>Analyses</title>", "<p>All statistical analyses were performed using SAS^®, Version 9.1 (SAS Institute, Cary, NC). We compared means by two-sided t-tests and proportions by χ²tests. All SNPs were verified to be in Hardy-Weinberg equilibrium. Adjusted odds ratios from logistic regression were used to determine whether the presence of the risk allele was associated with an increased risk for ischemic stroke after controlling for potential confounders.</p>", "<p>Two additive models were used to determine the relation between SNP and outcome. The first model (our primary analyses) was adjusted for age and race (when all subjects were included in the analysis) or only age when the analysis was stratified by race (i.e. African-Americans and Caucasians). The second model, (adjusted model) added history of hypertension, diabetes, smoking, oral contraceptive (OCP) use and angina pectoris or myocardial infarction (angina-MI), to age (or age and race) to the independent variables used in the first model. The results of the analyses were expressed as odds ratios which quantify the increased risk of ischemic stroke associated with each additional risk allele. Age, race, current cigarette smoking status, and OCP use were determined by subject reports (or proxy report, if a participant was unable to answer). Hypertension and diabetes mellitus were determined by asking study participants (or a proxy) if a physician had ever told them they had the condition. Current smoking was defined as having one or more cigarettes in the month (31 days) preceding their stroke, or for controls, in the month prior to their interview. Current oral contraceptive use was also defined as use in the prior month.</p>", "<p>In order to evaluate each SNP for a genotype by smoking interaction (as per our initial hypothesis), study participants were stratified by smoking status and evaluated in an age-, race-adjusted additive model. For those SNPs that demonstrated a potential genotype by smoking interaction the significance of the difference between the point estimates (i.e. the log odds ratios) in smokers and non-smokers was tested using a z-test. Lastly, SNPs with significant z-test results were additionally evaluated for potential race-specific smoking interactions in an age-adjusted additive model, with the SNP stratified by smoking status further stratified by race (Caucasian and African-American).</p>", "<p>In secondary analyses, significantly associated SNPs from the primary analyses (total population and race-stratified) underwent further analyses to evaluate groups stratified by other standard risk factors (age, hypertension, diabetes mellitus, OCP use, and history of angina/MI) and ischemic stroke subtype (atherosclerotic, cardiac, dissection, lacunar, hematologic, and stroke of unknown etiology (i.e. all other stroke)) with the later groups compared to all controls. Additionally, analyses consisting of dominant and recessive genetic models that included similar groups and covariates to the primary analyses were also performed. We did not adjust for multiple comparisons because our study was considered to be hypothesis generating.</p>" ]

[ "<title>Results</title>", "<title>Subject characteristics</title>", "<p>Demographic and risk factor characteristics by case-control status are described in Table ##TAB##0##1##. The mean age of the cases was 41.7 years and the mean age of control subjects was 39.6 years. Cases were significantly more likely than controls to have a history of hypertension (p &lt; 0.0001), diabetes (p = 0.0002), angina-MI (p = 0.0005), to currently smoke cigarettes (p &lt; 0.0001), and to report the use of oral contraceptive pills (OCP) within the month prior to their stroke (p = 0.032).</p>", "<title>Ischemic stroke risk</title>", "<p>Table ##TAB##1##2## gives p-values for the age-adjusted additive model and risk factor-adjusted additive model for the eight SNPs stratified by race and case-control status, and also provides each SNPs location, allelic variants, and genotype call rate. Of the SNPs analyzed, only the <italic>IL6 </italic>SNP rs2069832 (C allele; overall frequency: African-Americans = 92%, Caucasians = 55%) was found to be significantly associated with stroke, and this was only among African-Americans (Age-adjusted model: OR = 2.2, 95% CI = 1.0–5.0, p = 0.049; Risk Factor model: OR = 2.5, 95% CI = 1.0–6.5, p = 0.05). Dominant and recessive models did not strengthen the association (data not shown). Stratifying participants by other risk factors and evaluating stroke risk in relation to SNP rs2069832 genotype revealed no associations with stroke (data not shown). Stratifying participants by stroke subtype as compared to all controls and evaluating stroke risk in relation to SNP rs2069832 genotype revealed no significant associations (data not shown).</p>", "<title>Ischemic stroke risk as stratified by smoking status</title>", "<p>Table ##TAB##2##3## demonstrates the age- and race-adjusted additive model results for the SNPs stratified by smoking status. Two SNPs demonstrated a gene-environment interaction based upon smoking status. First, <italic>CD-14 </italic>SNP rs2569190 (C allele; frequency in total population = 39%) was found to be associated with increased risk of stroke among smokers (OR = 2.05, 95% CI = 1.09–3.87, p = 0.027), but not non-smokers (OR = 0.93, 95% CI = 0.62–1.39, p = 0.72). The two odds ratios were significantly different (p = 0.039). Secondly, <italic>IL6 </italic>SNP rs2069830 (T allele; frequency in total population = 5%) was found to be protective among non-smokers (OR = 0.30, 95% CI = 0.11–.082, p = 0.02), but not among smokers (OR = 1.63, 95% CI = 0.48–5.58, p = 0.43). The two odds ratios were significantly different (p = 0.036).</p>", "<title>Ischemic stroke risk as stratified by smoking status further stratified by race</title>", "<p>Results of the race-stratified smoking-genotype interaction analyses demonstrated no significant interactions. However, the race-stratified point estimates (ORs) remained similar to the combined population point estimates as detailed in the preceding paragraph. For CD-14 SNP rs2569190, similar ORs were seen among both smokers of both races (Caucasian OR = 2.21, p = 0.127; African-American OR = 1.91, p = 0.143) and non-smokers of both races (Caucasian OR = 1.18, p = 0.60; African-American OR = 0.83, p = 0.55). For IL-6 SNP rs2069830, among African-Americans, similar ORs as found in the combined population were seen among smokers (OR = 1.31, p = 0.71) and non-smokers (OR = 0.38, p = 0.10), consistent with a protective effect for the T allele among non-smokers. For IL-6 SNP rs2069830, among both Caucasian non-smokers and smokers, the logistic regression models did not converge due to the low frequency (2%) of the T allele.</p>" ]

[ "<title>Discussion</title>", "<p>Our study did not demonstrate strong relationships between the inflammatory gene polymorphisms and ischemic stroke risk. Only <italic>IL6 </italic>(rs2069832) was found to be associated with stroke, and only among African-Americans. However, it did identify two polymorphisms that appear to influence stroke risk via a gene-environment interaction with cigarette smoking, IL6 rs2069830 and CD-14 rs2569190.</p>", "<p>IL-6 plays a key role in the acute inflammatory response and in regulation of the production of acute phase proteins such as C-reactive protein [##REF##16741147##15##,##REF##1689567##16##]. It contributes to the inflammatory response by activating endothelial cells [##REF##16741147##15##,##REF##9075932##17##] and stimulating the synthesis of fibrinogen [##REF##16741147##15##,##REF##8423785##18##]. In vivo exposure to cigarette smoke has been shown to increase the expression of proinflammatory cytokines including IL-6 [##REF##17071726##19##]. Furthermore, several studies have demonstrated that IL-6 polymorphisms may mediate carotid artery intima-media wall thickness [##REF##11988625##20##,##REF##11116068##21##], an intermediate marker of stroke risk. Our results, consistent with other studies, demonstrates that genetic variation in IL-6 may modify stroke risk [##REF##16741147##15##,##REF##16323614##22##], and that this increased risk may be due to synergistic effects between proinflammatory genotypes and smoking [##REF##15308783##23##].</p>", "<p>CD14 is a surface protein preferentially expressed on monocytes and macrophages that acts to bind lipopolysaccharide-binding protein (also called endotoxin). Endotoxin is a potent mediator of inflammation, and smokers have elevated plasma levels of endotoxin. Hence, it is believed that the risk of atherosclerosis from endotoxemia is increased in smokers [##REF##12624278##24##]. The <italic>CD14 SNP </italic>rs2569190 is a C &gt; T substitution in the proximal <italic>CD14 </italic>promoter GC box at position -260 from the translation start site and results in a <italic>Hae</italic>III restriction site [##REF##10385492##25##]. The results of studies which have tried to determine which allele mediates vascular risk have been variable. The T allele was associated with an increased risk of MI [##REF##10385492##25##, ####REF##10195920##26##, ##REF##14587643##27##, ##REF##17087609##28####17087609##28##] and two ischemic stroke subtypes including atherosclerosis of large arteries and microangiopathy [##REF##12140663##29##]. Contrary to these studies, the C allele was associated with a higher risk of carotid plaque formation [##REF##15292769##30##], and was found to act synergistically with other inflammatory SNPs to increase carotid IMT [##REF##15472098##7##,##REF##16873708##9##], specifically among smokers [##REF##15472098##7##]. Still other studies evaluating this SNP have found no association with stroke [##REF##11062291##31##,##REF##11935032##32##]. Our results support a gene-environment association between the C allele and ischemic stroke risk among smokers. Our findings replicate a prior study showing an interaction with smoking and the C allele of <italic>CD14 </italic>SNP rs2569190 [##REF##15472098##7##].</p>", "<p>Our study has several limitations. Most notably, we only evaluated a limited number of SNPs, which were not sufficient to comprehensively evaluate stroke risk or smoking interaction for any of the genes studied. Secondly, our study did not provide any mechanistic information regarding stroke risk or protection. Specifically, we did not determine if our SNPs were associated with increased or decreased protein activity. Furthermore, our study population is relatively small and is underpowered to detect modest effects, particularly in the stroke subtype analyses. Although we have attempted to minimize phenotypic heterogeneity through identifying ischemic stroke subtypes during adjudication, we recognize that residual phenotypic heterogeneity may exist. Lastly, though we performed numerous analyses, no correction was made for multiple comparisons. This allows for the possibility that our results could be attained through chance alone, although confirming CD-14 rs2569190 as a mediator of vascular risk, and specifically among smokers of both races, makes such a false positive association less likely.</p>" ]

[ "<title>Conclusion</title>", "<p>This study demonstrates that inflammatory gene SNPs may be associated with early-onset ischemic stroke among African-American women (<italic>IL6</italic>) and that cigarette smoking may modulate stroke risk through a gene-environment interaction (<italic>IL6 and CD14</italic>).</p>" ]

[ "<p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type=\"uri\" xlink:href=\"http://creativecommons.org/licenses/by/2.0\"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>", "<title>Background</title>", "<p>Although cigarette smoking is a well-established risk factor for vascular disease, the genetic mechanisms that link cigarette smoking to an increased incidence of stroke are not well understood. Genetic variations within the genes of the inflammatory pathways are thought to partially mediate this risk. Here we evaluate the association of several inflammatory gene single nucleotide polymorphisms (SNPs) with ischemic stroke risk among young women, further stratified by current cigarette smoking status.</p>", "<title>Methods</title>", "<p>A population-based case-control study of stroke among women aged 15–49 identified 224 cases of first ischemic stroke (47.3% African-American) and 211 age-comparable control subjects (43.1% African-American). Several inflammatory candidate gene SNPs chosen through literature review were genotyped in the study population and assessed for association with stroke and interaction with smoking status.</p>", "<title>Results</title>", "<p>Of the 8 SNPs (across 6 genes) analyzed, only <italic>IL6 </italic>SNP rs2069832 (allele C, African-American frequency = 92%, Caucasian frequency = 55%) was found to be significantly associated with stroke using an additive model, and this was only among African-Americans (age-adjusted: OR = 2.2, 95% CI = 1.0–5.0, p = 0.049; risk factor adjusted: OR = 2.5, 95% CI = 1.0–6.5, p = 0.05). When stratified by smoking status, two SNPs demonstrated statistically significant gene-environment interactions. First, the T allele (frequency = 5%) of <italic>IL6 </italic>SNP rs2069830 was found to be protective among non-smokers (OR = 0.30, 95% CI = 0.11–.082, p = 0.02), but not among smokers (OR = 1.63, 95% CI = 0.48–5.58, p = 0.43); genotype by smoking interaction (p = 0.036). Second, the C allele (frequency = 39%) of <italic>CD14 </italic>SNP rs2569190 was found to increase risk among smokers (OR = 2.05, 95% CI = 1.09–3.86, p = 0.03), but not among non-smokers (OR = 0.93, 95% CI = 0.62–1.39, p = 0.72); genotype by smoking interaction (p = 0.039).</p>", "<title>Conclusion</title>", "<p>This study demonstrates that inflammatory gene SNPs are associated with early-onset ischemic stroke among African-American women (<italic>IL6</italic>) and that cigarette smoking may modulate stroke risk through a gene-environment interaction (<italic>IL6 and CD14</italic>). Our finding replicates a prior study showing an interaction with smoking and the C allele of <italic>CD14 </italic>SNP rs2569190.</p>" ]

[ "<title>Competing interests</title>", "<p>The authors declare that they have no competing interests.</p>", "<title>Authors' contributions</title>", "<p>All authors certify that they participated in the conceptual design of this work, the analysis of the data, and the writing of the manuscript to take public responsibility for it. All authors reviewed the final version of the manuscript and approve it for publication. JWC, OCS, and SJK participated in the writing of the initial draft. OCS participated in the genotyping. JWC OCS, MAW, BJS, MJS, MD, LS, NZ, and SJK participated in DNA and data collection. JWC, DWB, WHG, JRO, BDM, JDS, and LJR participated in the data analysis. All authors provided critiques of the final manuscript.</p>", "<p>The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.</p>", "<title>Availability &amp; requirements</title>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&amp;DB=snp\"/></p>", "<p><ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/Genbank/index.html\"/></p>" ]

[ "<title>Acknowledgements</title>", "<p>We are indebted to the following members of the Stroke Prevention in Young Women research team for their dedication: Esther Berrent, Kathleen Caubo, Julia Clark, Mohammed Huq, Ann Maher, Tamar Pair, and Mary Simmons.</p>", "<p>The authors would like to acknowledge the assistance of the following individuals who have sponsored the Stroke Prevention in Young Women Study at their institution: Clifford Andrew, MD; Merrill Ansher, Brian Avin, MD; MD; Harjit Bajaj, MD; Robert Baumann, MD; Nicholas Buendia, MD, Young Ja Cho, MD; Kevin Crutchfield, MD; Terry Detrich, MD; Mohammed Dughly, MD; Boyd Dwyer, MD; Jerold Fleishman, MD; Stuart Goodman, MD, PhD; Adrian Goldszmidt, MD; Kalpana Hari Hall, MD; Walid Kamsheh, MD; John Kelly, MD; Harry Kerasidis, MD; Mehrullah Khan, MD; Ramesh Khurana, MD; Ruediger Kratz MD; Somchai Laowattana, MD; William Leahy, MD; Alan Levitt, MD; Bruce Lobar, MD; Paul Melnick, MD; Harshad Mody, MD; Seth Morgan, MD; Howard Moses, MD; Francis Mwaisela, MD; Sivarama Nandipati, MD; Maciej Poltorak, MD; Thaddeus Pula, MD; Phillip Pulaski, MD; Neelupali Reddy, MD; Perry Richardson, MD; Solomon Robbins, MD; Michael Sellman, MD, PhD; Barney Stern, MD; Jack Syme, MD; Richard Taylor, MD; Dean Tippett, MD; Michael Weinrich, MD; Roger Weir, MD; Richard Weisman, MD; Laurence Whicker, MD; Robert Wityk, MD; James Yan, MD and Manuel Yepes, MD.</p>", "<p>In addition, the study could not have been completed without the support from the administration and medical records staff at the following institutions: In Maryland: Anne Arundel Medical Center, Bon Secours Hospital, Calvert Memorial Hospital, Carroll County General Hospital, Chester River Hospital, Civista Medical Center, Department of Veterans Affairs Medical Center in Baltimore, Doctors Community Hospital, Dorchester Hospital, Franklin Square Hospital Center, Frederick Memorial Hospital, Good Samaritan Hospital, Greater Baltimore Medical Center, Harbor Hospital Center, Hartford Memorial Hospital, Holy Cross Hospital, Howard County General Hospital, Johns Hopkins Bayview, The Johns Hopkins Hospital, Kernan Hospital, Laurel Regional Hospital, Maryland General Hospital, McCready Memorial Hospital, Memorial Hospital at Easton, Mercy Medical Center, Montgomery General Hospital, North Arundel Hospital, Northwest Hospital Center, Peninsula Regional Medical Center, Prince George's Hospital Center, Saint Agnes Hospital, Saint Joseph Medical Center, Saint Mary's Hospital, Shady Grove Adventist Hospital, Sinai Hospital of Baltimore, Southern Maryland Hospital Center, Suburban Hospital, Union Hospital Cecil County, The Union Memorial Hospital, University of Maryland Medical System, Upper Chesapeake Medical Center, Washington Adventist Hospital and Washington County Hospital; in Washington DC: The George Washington University Medical Center; Georgetown University Hospital; Hadley Memorial Hospital; Howard University Hospital; National Rehabilitation Hospital; Providence Hospital; Sibley Memorial Hospital; and the Washington Hospital Center; in Pennsylvania: Gettysburg Hospital.</p>", "<p><bold>Funding acknowledgments</bold>: <bold>Dr. Cole </bold>was supported in part by the Department of Veterans Affairs, Baltimore, Office of Research and Development, Medical Research Service; the Department of Veterans Affairs Stroke Research Enhancement Award Program; the University of Maryland General Clinical Research Center (Grant M01 RR 165001), General Clinical Research Centers Program, National Center for Research Resources, NIH, and; an American Heart Association Beginning Grant-in-Aid (Grant 0665352U). <bold>Dr. Kittner </bold>was supported in part by the Department of Veterans Affairs, Baltimore, Office of Research and Development, Medical Research Service, and Geriatrics Research, Education and Clinical Center, and Stroke Research Enhancement Award Program; a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention; the National Institute of Neurological Disorders and Stroke and the NIH Office of Research on Women's Health; the National Institute on Aging Pepper Center (Grant P60 12583); and the University of Maryland General Clinical Research Center (Grant M01 RR 165001), General Clinical Research Centers Program, National Center for Research Resources, NIH. <bold>Dr. Sorkin </bold>was supported by the Baltimore VA Medical Center Geriatrics Research, Education, and Clinical Center; the University of Maryland Claude D. Pepper Older Americans Independence Center; the Clinical Nutrition Research Unit of the University of Maryland, and; the Baltimore VA Medical Center, Center for Excellence in Robotics.</p>" ]

[]

[ "<table-wrap position=\"float\" id=\"T1\"><label>Table 1</label><caption><p>Characteristics, by case-control status.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td/><td align=\"center\"><bold>Cases (N = 224)</bold></td><td align=\"center\"><bold>Controls (N = 211)</bold></td><td align=\"center\"><bold>p-value</bold></td></tr></thead><tbody><tr><td align=\"center\">Mean age (years)</td><td align=\"center\">41.7</td><td align=\"center\">39.6</td><td align=\"center\">0.0026</td></tr><tr><td align=\"center\">African-American (%)</td><td align=\"center\">47.3</td><td align=\"center\">43.1</td><td align=\"center\">0.579</td></tr><tr><td align=\"center\">Hypertension (%)</td><td align=\"center\">41.1</td><td align=\"center\">14.2</td><td align=\"center\">&lt;.0001</td></tr><tr><td align=\"center\">Diabetes mellitus (%)</td><td align=\"center\">17.9</td><td align=\"center\">6.2</td><td align=\"center\">0.0002</td></tr><tr><td align=\"center\">Current smokers (%)</td><td align=\"center\">47.8</td><td align=\"center\">23.7</td><td align=\"center\">&lt;.0001</td></tr><tr><td align=\"center\">Angina-MI (%)</td><td align=\"center\">11.6</td><td align=\"center\">2.8</td><td align=\"center\">0.0005</td></tr><tr><td align=\"center\">OCP (%)*</td><td align=\"center\">12.2</td><td align=\"center\">6.2</td><td align=\"center\">0.032</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T2\"><label>Table 2</label><caption><p>Proinflammatory SNPs stratified by race and case/control status demonstrating allelic variants, genotype call rate, minor allele frequencies and p-values for age-adjusted additive model and risk factor adjusted additive model.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Gene</bold></td><td align=\"center\"><bold>SNP rs number, location and function</bold></td><td align=\"center\"><bold>Alleles*</bold></td><td align=\"center\"><bold>Call Rate (%)</bold></td><td align=\"center\" colspan=\"4\"><bold>African-Americans</bold></td><td align=\"center\" colspan=\"4\"><bold>Caucasians</bold></td></tr></thead><tbody><tr><td/><td/><td/><td/><td align=\"center\"><bold>Cases</bold></td><td align=\"center\"><bold>Controls</bold></td><td align=\"center\" colspan=\"2\"><bold>p-value</bold></td><td align=\"center\"><bold>Cases</bold></td><td align=\"center\"><bold>Controls</bold></td><td align=\"center\" colspan=\"2\"><bold>p-value</bold></td></tr><tr><td colspan=\"12\"><hr/></td></tr><tr><td/><td/><td/><td/><td align=\"center\"><bold>Minor Allele Frequency/N</bold></td><td align=\"center\"><bold>Minor Allele Frequency/N</bold></td><td align=\"center\"><bold>Age-adjusted</bold></td><td align=\"center\"><bold>Risk factor adjusted**</bold></td><td align=\"center\"><bold>Minor Allele Frequency/N</bold></td><td align=\"center\"><bold>Minor Allele Frequency/N</bold></td><td align=\"center\"><bold>Age-adjusted</bold></td><td align=\"center\"><bold>Risk factor adjusted**</bold></td></tr><tr><td colspan=\"12\"><hr/></td></tr><tr><td align=\"center\"><italic>CD14</italic>^ψ</td><td align=\"center\">rs2569190, 5' promotor</td><td align=\"center\">C/<bold>T</bold></td><td align=\"center\">99%</td><td align=\"center\">0.38/77</td><td align=\"center\">0.42/62</td><td align=\"center\">0.57</td><td align=\"center\">0.66</td><td align=\"center\">0.49/65</td><td align=\"center\">0.40/75</td><td align=\"center\">0.13</td><td align=\"center\">0.30</td></tr><tr><td align=\"center\"><italic>IL1A</italic></td><td align=\"center\">rs17561, exon 4 nonsynonymous</td><td align=\"center\">G/<bold>T</bold></td><td align=\"center\">98%</td><td align=\"center\">0.18/102</td><td align=\"center\">0.18/90</td><td align=\"center\">0.83</td><td align=\"center\">0.73</td><td align=\"center\">0.27/93</td><td align=\"center\">0.31/94</td><td align=\"center\">0.32</td><td align=\"center\">0.80</td></tr><tr><td align=\"center\"><italic>IL1R1</italic></td><td align=\"center\">rs3917318, intron 10</td><td align=\"center\">A/<bold>G</bold></td><td align=\"center\">91%</td><td align=\"center\">0.33/97</td><td align=\"center\">0.29/88</td><td align=\"center\">0.44</td><td align=\"center\">0.23</td><td align=\"center\">0.33/92</td><td align=\"center\">0.36/92</td><td align=\"center\">0.53</td><td align=\"center\">0.24</td></tr><tr><td align=\"center\">ILIB</td><td align=\"center\">rs3917365, 3' near gene</td><td align=\"center\">C/<bold>T</bold></td><td align=\"center\">81%</td><td align=\"center\">0.21/97</td><td align=\"center\">0.17/83</td><td align=\"center\">0.34</td><td align=\"center\">0.36</td><td align=\"center\">0.08/86</td><td align=\"center\">0.08/89</td><td align=\"center\">0.85</td><td align=\"center\">0.87</td></tr><tr><td align=\"center\"><italic>IL6</italic></td><td align=\"center\">rs1800797, 5' near gene</td><td align=\"center\"><bold>A</bold>/G</td><td align=\"center\">91%</td><td align=\"center\">0.06/99</td><td align=\"center\">0.10/88</td><td align=\"center\">0.19</td><td align=\"center\">0.18</td><td align=\"center\">0.42/93</td><td align=\"center\">0.43/91</td><td align=\"center\">0.89</td><td align=\"center\">0.87</td></tr><tr><td/><td align=\"center\">rs2069830, exon 2 nonsynonymous</td><td align=\"center\">C/<bold>T</bold></td><td align=\"center\">91%</td><td align=\"center\">0.07/100</td><td align=\"center\">0.09/87</td><td align=\"center\">0.32</td><td align=\"center\">0.31</td><td align=\"center\">0.01/90</td><td align=\"center\">0.03/93</td><td align=\"center\">0.30</td><td align=\"center\">0.35</td></tr><tr><td/><td align=\"center\">rs2069832, intron 2</td><td align=\"center\">C/<bold>T</bold></td><td align=\"center\">89%</td><td align=\"center\">0.05/97</td><td align=\"center\">0.12/86</td><td align=\"center\"><bold>0.049</bold></td><td align=\"center\"><bold>0.05</bold></td><td align=\"center\">0.45/92</td><td align=\"center\">0.45/91</td><td align=\"center\">0.97</td><td align=\"center\">0.85</td></tr><tr><td align=\"center\"><italic>MMP3</italic></td><td align=\"center\">rs679620, exon 2 nonsynonymous</td><td align=\"center\">C/<bold>T</bold></td><td align=\"center\">89%</td><td align=\"center\">0.35/103</td><td align=\"center\">0.35/88</td><td align=\"center\">0.95</td><td align=\"center\">0.72</td><td align=\"center\">0.45/90</td><td align=\"center\">0.47/96</td><td align=\"center\">0.85</td><td align=\"center\">1.0</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"T3\"><label>Table 3</label><caption><p>Proinflammatory SNPs stratified by smoking status demonstrating the number of cases and controls, and Odds Ratio, 95%CI and p-values in an age-, race-adjusted additive model.</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><td align=\"center\"><bold>Gene</bold></td><td align=\"center\"><bold>rs number</bold></td><td align=\"center\" colspan=\"4\"><bold>Smokers</bold></td><td align=\"center\" colspan=\"4\"><bold>Non-Smokers</bold></td></tr></thead><tbody><tr><td/><td/><td align=\"center\"><bold>Cases/Controls</bold></td><td align=\"center\"><bold>OR*</bold></td><td align=\"center\"><bold>95% CI</bold></td><td align=\"center\"><bold>p-value</bold></td><td align=\"center\"><bold>Cases/Controls</bold></td><td align=\"center\"><bold>OR*</bold></td><td align=\"center\"><bold>95% CI</bold></td><td align=\"center\"><bold>p-value</bold></td></tr><tr><td colspan=\"10\"><hr/></td></tr><tr><td align=\"center\"><italic>CD14</italic></td><td align=\"center\">rs2569190</td><td align=\"center\">77/31</td><td align=\"center\"><bold>2.05</bold></td><td align=\"center\"><bold>1.09–3.87</bold></td><td align=\"center\"><bold>0.027</bold></td><td align=\"center\">82/121</td><td align=\"center\">0.93</td><td align=\"center\">0.62–1.39</td><td align=\"center\">0.72</td></tr><tr><td align=\"center\"><italic>IL1A</italic></td><td align=\"center\">rs17561</td><td align=\"center\">106/48</td><td align=\"center\">1.68</td><td align=\"center\">0.84–3.32</td><td align=\"center\">0.14</td><td align=\"center\">111/156</td><td align=\"center\">1.05</td><td align=\"center\">0.69–1.60</td><td align=\"center\">0.83</td></tr><tr><td align=\"center\"><italic>IL1R1</italic></td><td align=\"center\">rs3917318</td><td align=\"center\">102/45</td><td align=\"center\">1.138</td><td align=\"center\">0.67–1.94</td><td align=\"center\">0.64</td><td align=\"center\">108/155</td><td align=\"center\">1.07</td><td align=\"center\">0.74–1.54</td><td align=\"center\">0.72</td></tr><tr><td align=\"center\">IL1B</td><td align=\"center\">rs3917365</td><td align=\"center\">99/44</td><td align=\"center\">1.63</td><td align=\"center\">0.78–3.42</td><td align=\"center\">0.19</td><td align=\"center\">105/146</td><td align=\"center\">1.03</td><td align=\"center\">0.62–1.73</td><td align=\"center\">0.90</td></tr><tr><td align=\"center\"><italic>IL6</italic></td><td align=\"center\">rs1800797</td><td align=\"center\">104/43</td><td align=\"center\">1.28</td><td align=\"center\">0.66–2.46</td><td align=\"center\">0.46</td><td align=\"center\">110/155</td><td align=\"center\">1.05</td><td align=\"center\">0.67–1.64</td><td align=\"center\">0.83</td></tr><tr><td/><td align=\"center\">rs2069830</td><td align=\"center\">103/45</td><td align=\"center\">1.63</td><td align=\"center\">0.48–5.58</td><td align=\"center\">0.43</td><td align=\"center\">109/155</td><td align=\"center\"><bold>0.30</bold></td><td align=\"center\"><bold>0.11–0.82</bold></td><td align=\"center\"><bold>0.019</bold></td></tr><tr><td/><td align=\"center\">rs2069832</td><td align=\"center\">101/45</td><td align=\"center\">0.69</td><td align=\"center\">0.35–1.35</td><td align=\"center\">0.28</td><td align=\"center\">109/152</td><td align=\"center\">0.80</td><td align=\"center\">0.51–1.26</td><td align=\"center\">0.34</td></tr><tr><td align=\"center\"><italic>MMP3</italic></td><td align=\"center\">rs679620</td><td align=\"center\">103/46</td><td align=\"center\">0.98</td><td align=\"center\">0.58–1.65</td><td align=\"center\">0.93</td><td align=\"center\">110/157</td><td align=\"center\">1.01</td><td align=\"center\">0.71–1.43</td><td align=\"center\">0.97</td></tr></tbody></table></table-wrap>" ]