Aspergillus flavus was isolated from the haemocoel of worker bees. Observations on the metabolomic profile of this strain showed kojic acid to be the dominant product in cultures on Czapek-Dox broth. However, an accurate review of papers documenting secondary metabolite production in A. flavus also showed that an isomer of kojic acid, identified as 5-(hydroxymethyl)-furan-3-carboxylic acid and named flufuran is reported from this species. The spectroscopic data of kojic acid were almost identical to those reported in the literature for flufuran. This motivated a comparative study of commercial kojic acid and 5-(hydroxymethyl)-furan-3-carboxylic acid, highlighting some differences, for example in the 13C-NMR and UV spectra for the two compounds, indicating that misidentification of the kojic acid as 5-(hydroxymethyl)-furan-3-carboxylic acid has occurred in the past.In the course of investigations on the complex phenomenon of bee decline,  Fungi have evolved the capability to produce a great number of secondary metabolites involved in the improvement of their ecological fitness, and many of them play important biological roles as virulence factors, chemical defense agents, developmental regulators, insect attractants, and chemical signals for communication with other organisms. On these properties is founded the pharmacological exploitation of many products as antibiotic, antiviral, antitumor, antihypercholesterolemic, and immunosuppressant agents ,2,3,4,5.Aspergillus, well-known for its ubiquity and cosmopolitan distribution  is hydrogenionic concentration, CH is the total acid concentration, CL is the compound concentration and Kw is ionic product . Experimental data were processed with Hyperquad softare +, 125 [M-OH]+, 113 [M-CHO]+, 97 [M-COOH]+, 69 [M-CH2OH-COO]+. Kojic acid (2). UV λmax nm (log ε): (H2O) 240 (3.39); (MeOH) 240 (3.38); (pH 2.5) 243 (2.97); (pH 3.0) 243 (3.07); (pH 4.0) 243 (3.07); (pH 5.0) 243 (3.12). MALDI TOF/MS: m/z 143 [M+H]+, 125 [M-OH]+, 113 [M-CHO]+, 97 [M-COOH]+.5-(Hydroxymethyl)furan-3-carboxylic acid ] were dissolved in MeOH (1.5 mL); an ethereal solution of CH2N2 was slowly added until a yellow color became persistent. The reaction mixtures were stirred at room temperature for 4 h. The solvent was evaporated under a N2 stream at room temperature. Residues of each reaction were analyzed by TLC on silica gel; 6, was evidenced at Rf 0.37 by eluting with EtOAc-MeOH (9:1), while Rf 0.54 and 0.82 corresponded to 7 and 9 respectively, as eluted with CHCl3-i-PrOH (92:8).Fifteen milligrams of samples , dissolved in pyridine (30 μL), were converted into the corresponding acetyl derivatives  by acetylation with Ac2O (30 μL) at room temperature overnight. The reaction was stopped by addition of MeOH, and the azeotrope formed by addition of benzene was evaporated in a N2 stream at 40 °C. Residues of each reaction were analyzed by TLC on silica gel; 5 was evidenced at Rf 0.44 by eluting with CHCl3-i-PrOH (95:5), while Rf 0.54 and 0.82 corresponded to 7 and 9 respectively, as eluted with CHCl3-i-PrOH (92:8).Ten mg of samples [KA, 5-(hydroxymethyl)furan-3-carboxylic acid, 5-


Upbringing in a high environmental risk locale increases the risk for schizophrenia by 122%. Individuals living in a high gene-by-environmental risk locale have a 78% increased risk compared to those who have the same genetic liability but live in a low-risk locale. Effects of specific locales vary substantially within the most densely populated city of Denmark, with hazard ratios ranging from 0.26 to 9.26 for environment and from 0.20 to 5.95 for gene-by-environment. These findings indicate the critical synergism of gene and environment on the etiology of schizophrenia and demonstrate the potential of incorporating geolocation in genetic studies.Spatial mapping is a promising strategy to investigate the mechanisms underlying the incidence of psychosis. We analyzed a case-cohort study ( Schizophrenia (SCZ) risk is influenced by genetic and environmental factors. Here, the authors develop a statistical method for analyzing gene-by-environment effects in SCZ risk across Denmark with fine spatial resolution. Take as an example one of the best-established environmental risks for schizophrenia, childhood upbringing in an urban area. Persons born and raised in urban areas have an approximately twofold increased risk of schizophrenia compared to those born and raised in rural areas5. Researchers have examined potentially causal elements of urban upbringing, such as accessibility to health care6, selective migration of individuals8, air-pollution9, infections10, and socioeconomic inequality13. Yet none of these factors have substantially explained the risk associated with urbanicity14, nor are they highly correlated with instruments used in defining urbanicity, such as population density15. The conditional relationships between genetic liabilities and putative environmental factors are even harder to detect despite some cohort studies suggesting an interaction between urban upbringing and family history of schizophrenia20.For public mental health, it is critical to know which environmental factors can be modified to mitigate the risk of psychiatric disorders. However, identifying modifiable environmental factors has been a contentious issue21, the candidate environment approach suffers from the “spotlight effect”, ignoring the likely complexity of many environmental factors interacting with each other and with genetic liabilities to determine overall risk for illness. The environmental impact can even be a joint holistic effects from multiple environmental factors3. Measurement of the specific environmental factor may also be imprecise, masking its relationship to the illness. For example, many instruments have been devised to characterize socioeconomic inequality, yet have not shown consistent effects on incidence of schizophrenia. Given the complexity of real-life socioeconomic forces, lack of association with schizophrenia could be caused by instrument measurement error or because the instrument does not capture the relevant social-economic factors12.The difficulty in isolating specific environmental risk elements underlying urbanicity effects on schizophrenia incidence exemplifies a serious methodological challenge. The process for discovering environmental risk factors typically relies on a hypothesis-driven “candidate environmental factor” approach. Researchers need to formulate a carefully constructed environmental hypothesis, measure it, and then determine if it associates with risk of the disease. Analyses is usually performed in a study of selected participants not necessarily representative of the entire population of interest. Similar to the candidate gene approach before the dawning of genome-wide association studies (GWAS)22, identifying spatially localized disease “hot spots” can assist in the discovery of latent environmental factors. Advanced methods for disease mapping have been developed within the field of geostatistics, particularly in applying spatial random effect models to infer latent environmental variation in causal risk factors23. As the urbanicity-related increase in risk for schizophrenia was first noted through spatial clustering of disease incidence24, inferring risk hot spots to a finer resolution may provide insight into potential risk-modulating environmental elements before investing substantial resources in active measurement.An alternative to the candidate environment approach is to assess spatial patterns of disease risk without directly measuring environmental factors. As with John Snow isolating the environmental source of cholera outbreak via mapping the cases27, our method differs by utilizing spatial fine-mapping and enabling the partition of risk into E and GxE components without the need for candidate environmental factors.With this concept in mind, we develop a disease mapping strategy to address the need for discovering environmental factors without direct measurement. We use spatial random effects to map the geographic distribution of genetic liabilities (G), locale of upbringing (E), and their synergistic effects (GxE) on disease risk. By treating E and GxE as “latent random fields” on the map of Denmark, we avoid methodological issues inherent in the candidate environment approach. Although several studies have utilized random effect models to examine spatially localized risk for schizophreniaAs a proof of concept, we examine geospatial variation in schizophrenia risk across Denmark. To do so, we apply this novel analytical approach to data from a population-based case-cohort study that includes subject genotyping and detailed residential information from birth up to age 7 years. We are thus able to assess locale of upbringing effects on schizophrenia risk with a resolution beyond conventionally defined levels of urbanicity, allowing us to assess variation in spatial risk, and to ask whether spatially localized environmental factors modulate genetic liability of risk for schizophrenia.We utilize the entire population cohort of iPSYCH, excluding cases, to derive locales. The resulting map contains 186 non-overlapping locales, with the number of cohort members ranging from 65 to 197 individuals in each locale (median = 105). Figure 5. The inclusion of spatial random effects (E) reduces the urbanicity effect to hazard ratio = 1.64 with confidence interval encompassing 1. Model 3 with both E and GxE effects significantly contributes explanatory power to the variation in risk for schizophrenia (Log-likelihood ratio tests p < 2 × 10−16), while the urbanicity effect is further reduced (hazard ratio = 1.46). Due to the concerns of residual confounds from interaction effects, Model 3 contains full pairwise interaction terms of fixed-effect covariates included in the model, i.e., PRS, genetic principal components, gender, and family history1. Median hazard ratios for E and GxE components, defined as the median absolute difference in hazard ratios for all possible combinations of pairs of locales28, are 2.22 and 1.78, respectively, representing a 122 and 78% expected change in risk if living in a high-risk locale.Table The geographical distribution of E and GxE are shown in Fig. Our novel spatial mapping analysis strategy transforms the "candidate environment” approach for disease risk into a search for environmental hot spots, localizing where environmental factors appear to have a strong impact. The flexibility of this approach enables the estimation of the amount variance accounted for by E and GxE effects without direct measurement of environmental risk factors. Both simulations and empirical application demonstrate the utility of this strategy as an alternative to the candidate environment approach.Applying this strategy to nationwide, population-based longitudinal data enriched with genetic information, we recapitulate the well-known urban-rural gradient in schizophrenia risk based on the residential information alone. Furthermore, we show that locale of upbringing significantly contributes to the risk for schizophrenia even after controlling for population density. Both E and GxE spatial effects demonstrate substantial variation within city boundaries and account for a higher proportion of schizophrenia risk than simple urban-rural contrasts. In terms of schizophrenia risk, results indicate that the locale an individual was born and raised in is more important than urban-rural differences per se, even within the confines of a single city. Our patterns of E and GxE across Denmark can be regarded as reference distribution. The partitioned risk contour serves as an initial guide to find the true risk element. Further comparisons with putative environmental factors can reveal the underlying elements that are highly relevant for the etiology of schizophrenia.29. Thus, the PRS we used may be biased toward older patients, reducing the predictive power of the already weak biological instrument. Third, the diagnostic uncertainty of very early-onset schizophrenia (onset age lesser than 13-years-old) can impact observed associations. However, a recent validation study of schizophrenia diagnoses using the Danish registry has shown good reliability in both early-onset (age 13 years to 18 years) and very early-onset (age < 13 years) schizophrenia, with diagnostic concordance greater than 82 percent30. Another concern with the relatively young age of the iPSYCH sample is the inclusion of cohort members younger than 10-years-old who have very low-risk of being diagnosed as schizophrenia. These subjects are handled in the Cox proportional hazards model by treating their potential future diagnoses as right-censored outcomes, and hence have little impact on the model outputs. To verify this, we performed a sensitivity analysis on Model 3. We removed anyone younger than age 10 at study end and re-ran Model 3. As expected, the results are almost identical, with the E component on-average increasing risk by 127 percent  and GxE component on-average increasing the risk by 77 percent . Fourth, as shown in our simulations, the size of the GxE effect depends upon the predictive accuracy of the G effect. Because the PRS is a weak instrument of G, the true size of the GxE effect is probably several times larger than our current estimate, as suggested by our simulations. Fifth, we did not examine the impact of migration on locale effects. Since we cannot differentiate GxE from the gene by environment correlation introduced by migration, we restricted our analyses to individuals who have Danish parents and defined the locales as the place of birth. Although by this we intended to reduce the influence of migration, migration itself can be an important contributor for spatially-embedded risk8, as many migrants tend to live in clusters, especially in urban areas. A recent study on community samples across several countries shown that individuals with higher genetic risks of schizophrenia tend to migrate to urban area8. However, the spatial patterns we observe are unlikely due to the confounding effects of within generational drift4 since locale of upbringing was assessed before age 7, at which age no one had yet been diagnosed with schizophrenia. Inter-generational drift might still cause spatial aggregation of individuals with high genetic liabilities. A Swedish family-based study suggested urbanicity effects on schizophrenia can be explained by familial aggregation of risk13. Nevertheless, familial risk might not be the result of genetic liability but shared environmental risks within families. Danish registry studies using a cohort independent of our sample showed no evident urban aggregation of polygenic risk20, and the polygenic risk scores associated with incidence of schizophrenia independent of family history31. Therefore, there is little evidence to suggest that the identified spatial patterns is driven by inter-generational drift of families with high genetic liability for schizophrenia. Finally, we did not investigate a variety of possible socioeconomic factors in our current analyses. The potential importance such factors mandates in-depth examination in the future research; however, obtaining, validating, and analyzing socioeconomic variables as potential candidate environmental factors in the iPSYCH sample needs to be handled carefully and is beyond the scope of current paper.As a proof of concept study, our current analysis is not without limitations. First, the average age of the iPSYCH case-cohort is younger than the expected incidence peak of schizophrenia. Although the age range of our cohort is 8–32 years, encompassing the incidence peak of schizophrenia, some cohort members are still at risk for schizophrenia. Right-censoring among cohort members reduces the power of statistical analyses. However, by analyzing the case-cohort with age-adjusted RR’s and survival analyses with inverse probability of sampling weights, we obtain unbiased estimates of incidence proportions. Second, our case-cohort is relatively young, while existing GWAS of schizophrenia tend to recruit more chronic patients in middle age7. Given the uncertainty involved, invalid constructs or measurement error could be contributors to low power to detect risk associations with specific environmental factors. Our spatial mapping strategy is an alternative approach, since finding high-risk locales does not depend on correct specification of a purported environmental risk factor.Despite these caveats, we demonstrate that locale effects and modulating effects of locale on genetic risk account for a substantial proportion of urbanicity effects in Demark. Living in a locale with a high E component increases the risk for schizophrenia by as much as 122 percent, independent of genetic liability and family history. Meanwhile, living in a locale with a high GxE component can increase risk due to genetic liability for schizophrenia by as much as 78 percent. Because our results demonstrate risk variation with finer resolution and stronger effects than urban-rural demarcation, there must be specific factors underlying previously observed urban effects. However, identification of factors explicating urban risk has been unsuccessful to dateIn the nineteenth century, epidemiology pioneer John Snow mapped high-density regions of cholera cases onto London streets and thus identified the water source as the key infectious medium. By demonstrating that the locale of upbringing significantly contributes to risk and modulates genetic susceptibility to schizophrenia, we hope this is the first step in isolating the source of spatial risk variation, facilitating the design of future public health interventions for severe mental disorders.Our spatial mapping approach follows three steps: (1) defining neighboring locales to characterize the latent environment field, (2) estimating random effects associated with each locale, and (3) mapping the spatial distribution based on the realized effects on locales. These three steps are calibrated to ensure a good balance between fine spatial resolution and adequate statistical power. Furthermore, the modeling strategy partitions observed effects on risk for schizophrenia into different components: locale of upbringing (E), genetics (G), and the synergistic effects of spatial locale and genetics (GxE).32, ensuring each defined locale has a sufficient number of study subjects to be well-powered while achieving a fine spatial resolution . The Voronoi tessellation partitions the whole map into smaller units based on individuals’ coordinates on the map, making sure every point in a given unit area is closer to its centroid than any other. Their neighborhood relationships are defined simultaneously because the centroids are connected by the dual of Voronoi tessellation, i.e., Delaunay triangulation. After defining neighborhood relationships, individuals are grouped with their closest neighbors, making the locale growing in size, until the number of individuals in the defined locale reaches a pre-defined range , we obtain an unbiased estimation of spatial effects (E), while GxE effects are conservatively bounded by the predictive power of the genetic instrument  of psychiatric disorders have lacked information on locale of upbringing, while population registry studies with detailed residential locales have not yet implemented polygenic data analyses. By linking with the Danish Civil Registration System, iPSYCH has a nationally representative sample with whole-genome genotyping and detailed chronological residential information. Altogether with the case-cohort design17, these characteristics of iPSYCH enable us to obtain nationally representative estimates of the locale effects and the modulating effects of locale on genetic risk.We demonstrate the feasibility of our spatial mapping approach by characterizing E and GxE effects of schizophrenia in the Danish population. To map the synergistic effects of locale of upbringing and schizophrenia genetic liability, chronological residential information and genotyping data from the same population-based cohort is needed. The Danish Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort study provides a unique opportunity for this aim34. The aim of the iPSYCH study was to combined biobank and national registry to comprehensively examine the genetic and environmental risk factors of mental illness34. Cohort members  were randomly sampled individuals from the entire Danish population born between 1981 and 2005 and surviving past 1 year of age . Individuals with a diagnosis of selected mental disorders were ascertained through the Danish Psychiatric Central Research Register, using diagnostic classifications based on the International Classification of Diseases, 10th revision, Diagnostic Criteria for Research . The use of these samples is protected under strict regulation with the Danish legislation. The informed consent was obtained from all participants. The study is approved by the Danish Scientific Ethics Committee, the Danish Health Data Authority, the Danish data protection agency and the Danish Neonatal Screening Biobank Steering Committee. Here, we focused on a subset of cases who were diagnosed with schizophrenia. A flow chart of the recruitment can be found in the Supplementary Information .For this analysis, we extracted genotyped schizophrenia cases and a population random sample cohort from the iPSYCH study36 and with both parents born in Denmark based on Danish registry information. The final analyses include 24,028 case-cohort members  who met above criteria and passed genotyping quality controls. Supplementary Table To prevent confounds due to recent emigration/immigration and large-scale ethnic differences, we restrict our analyses to unrelated individuals who are of European descent, as determined by genetic ancestry37. Next, we implement the spatial mixed effects model to identify sources of variation in the observed risk across locales. Given the concern of potential confounds, all models include fixed effects of gender, the first three genetic principal components, and family history as covariates. Genetic principal components were covaried to reduce the potential for spatial confounds due to population history35. Family history of psychosis was also covaried to avoid clustering of high-risk families and unmodeled rare genetic mutations31. Family history was obtained by querying parents’ records in the registry. Survival models were used to account for age distribution34 and observations were weighted by the inverse of each subject’s sampling probability38 for inclusion in iPSYCH. Time-to-event is defined as age at first hospital contact for schizophrenia for cases, and the minimum of age of death, disappearance, emigration or age at date of registry information collection (31 December 2013) for cohort members without schizophrenia. Because locale of upbringing, especially place at birth, has been consistently associated with a twofold increase in schizophrenia risk17, we defined the locale based on the place at birth in our analysis. To reduce the effects of potential confounding caused by differences in time residing in the defined locale, we added the duration of residence in the same locale as a stratifying factor in models, so that only subjects residing the same time in a given locale are compared (5 years or 7 years due to the sampling time frames). For comparison purposes, we also fit a model with fixed-effect of the covariates and no random effects (Model 1).We performed our analysis of iPSYCH case-cohort based on a sequence intend to demonstrate the magnitude of partitioned E and GxE in the context of well-researched urbanicity effect. First, we examined the risk distribution through our algorithm for locale definition without multilevel modeling. This represents an overall risk distribution without partitioning the risks into different components. We use the Mantel-Haenszel approach for estimating risk ratios (RR) while correcting for age differences4, the effect measure for population density is contrasted between 55 person/km2  and 5220 person/km2 (urban category). Sensitivity analyses indicate the effect measures remain the same if we use locale at age 5 or 7 years instead of locale at birth.As a byproduct of our locale defining algorithm, the population density of each locale is also automatically calculated, since the size of each locale is inversely proportional to the population density. In the statistical analyses, population density is a continuous instrument, derived by dividing the number of individuals by the area of the defined locale, using the locale at birth for population density. To determine whether we reproduce the urbanicity effects previously reported in Danish cohorts39 and IMPUTE2 was used for imputation40. The reference panel was 1000 genomes project phase 341.Eleven million single-nucleotide polymorphisms (SNPs) were imputed based on genotyped SNPs that pass the following criteria: minor allele frequencies greater than 1 percent; frequencies in Hardy–Weinberg Equilibrium; SNPs autosomal and bi-allelic. SHAPEIT3 was used for phasing36 to perform the calculation because of its computational speed. By including the leading PCs in the models, it reduces the risk of spurious findings emerging due to population stratification35. Here, we used first three genetic principal components in our analysis since none of the remaining genetic principal components show associations with schizophrenia in iPSYCH sample.To control for potential confounds due to distant shared ancestry within the sample, we calculated genetic principal components (PCs) for iPSYCH samples. Genetic PCs were derived based on principal component analysis with a set of 43,769 independent SNP that are genotyped and passed quality control. We used flashPCA42. The PRS is the sum of the products of effect sizes of SNPs estimated from this independent GWAS and the dosage of those SNPs from the iPSYCH case-cohort. The included SNPs were pruned to ensure independence, while no significance threshold was set to filter SNPs. Parameters for calculating PRS include clumping , and pruning . Nonetheless, PRS is inherently a weak genetic instrument, so our estimate on GxE is as a conservative lower bound of interaction effects  using the summary statistics for 34,129 cases and 45,512 controls from the Psychiatric Genomics Consortium (PGC) Schizophrenia GWAShttps://chunchiehfan.shinyapps.io/iPSYCH_geo_tess_SZ/]. The interactive version of the disease mapping is shown on the web portal while all the relevant codes can be downloaded on it. All analyses are implemented in R43. R packages employed include spatstat 44and coxme45. The geographical visualization is done with ggmap46, which extracts geographical information from Google Maps. An interactive version of the risk map is generated using leaflet47 and shiny48.The code used for simulations, empirical analysis, and visualization can be found at [Supplementary InformationPeer Review FileSource DataReporting Summary


There is limited information available regarding the clinical management of intravenous immunoglobulin-resistant Kawasaki disease (KD). We aimed to evaluate the optimal treatment options for patients with refractory KD by presenting an indirect-comparison meta-analysis.PubMed, EMBASE, Web of Science, and the Cochrane Database were searched on August 31, 2018. Unpublished studies were also searched in ProQuest Dissertations & Theses and through manual retrieval strategies. Randomized concurrent controlled trials (RCTs), high-quality non-randomized concurrent controlled trials (non-RCTs), and retrospective studies associated with AEs were included. The quality of all eligible studies was assessed using Cochrane collaboration’s tool and non-randomized study guidelines. Risk ratios (RR) with 95% confidence intervals (CIs) for dichotomous outcomes were estimated in our analysis. GRADE profiler 3.6.1 was used to assess the evidence profile.Twelve studies involving 372 immunoglobulin-resistant KD patients were identified and analyzed. Neither infliximab nor intravenous pulse methylprednisolone (IVMP) was significantly more effective than second IVIG infusion with respect to lowering coronary artery lesions (CALs)  and treatment resistance . No significant differences were found between infliximab and IVMP in the incidence rate of CALs , the treatment resistance , the rates of coronary artery aneurysm  and the coronary artery dilatation . Furthermore, compared with second IVIG infusion, both infliximab and IVMP showed significant effectiveness in antipyretic effects . However, Infliximab was noninferior to IVMP on antipyretic effects . IVMP treatment showed significant association with fewer AEs than second IVIG infusion  and infliximab . No significant differences were noted between infliximab treatment and second IVIG infusion .Infliximab, IVMP, and second IVIG infusion showed no significant differences in the cardioprotective effect or the rate of treatment resistance. Infliximab and IVMP treatment were more effective than second IVIG infusion regarding antipyretic effects. IVMP treatment may have an advantage due to its lower total rate of AEs associated with drug infusion.CRD42016039693).The study has been registered on PROSPERO (The online version of this article (10.1186/s12887-019-1504-9) contains supplementary material, which is available to authorized users. Kawasaki disease (KD) is an acute self-limited systemic vasculitis that occurs mainly in infants and children . KD invoIntravenous pulse methylprednisolone  is the most commonly used steroid regimen, which rapidly inhibits inflammation and suppresses cytokine levels in KD patients. Several clinical trials have investigated the efficacy of steroids in IVIG nonresponders –12, but Currently, infliximab, IVMP, and second IVIG infusion are the conventional care for immunoglobulin-resistant KD patients who have failed the initial standard therapy. However, the efficacy of and adverse effects (AEs) associated with these drug administrations are not well known. In the absence of any trials directly assessing the efficacy and AEs of infliximab and methylprednisolone treatment for immunoglobulin-resistant KD, one method to evaluate efficacy and AEs is to conduct an adjusted indirect comparison of data from existing trials with a common control .An indirect comparison is an ideal method by which to resolve issues when there is no direct evidence from current clinical trials. If direct evidence of both α versus γ and β versus γ is available, an indirect comparison of α versus β is conducted using the same intervention γ as a common comparator. The meta-analysis defined second IVIG infusion as the common comparator. This adjusted indirect comparison meta-analysis aimed to evaluate the safety and effectiveness of these three therapies for children with immunoglobulin-resistant KD in the hope of providing evidence-based clinical advice.Ethical approval was not required because this was a meta-analysis of previously published trials and no real patients were included. The meta-analysis conformed to standard guidelines and was written according to the PRISMA statement . This reWe searched PubMed, EMBASE, Web of Science, and the Cochrane Database for articles published from each database’s date of inception to August 31, 2018, using a combination of basic text and MeSH terms. Specifically, we performed a MeSH search using ‘mucocutaneous lymph node syndrome’ and a keyword search using the phrase ‘Kawasaki disease’ and terms related to intravenous immunoglobulin . This search strategy was modified to fit each database. In addition, unpublished studies were searched in ProQuest Dissertations & Theses and following manual retrieval strategies; we reviewed (1) references from published articles to identify additional relevant studies, (2) conference proceedings likely to contain trials relevant to the analysis, and (3) unpublished data or incomplete trials for relevant trial authors. All searches included non-English language literature  RCTs and high-quality non-randomized concurrent controlled trials (non-RCTs); retrospective studies  associated with AEs were reviewed; (2) studies whose patient populations included children with immunoglobulin-resistant KD according to the criteria of the Japanese Ministry of Health and Welfare  or the A RCTs andStudies were selected by 2 independent reviewers (H. You and H. Chi) according to the above inclusion criteria, and disputes regarding the studies were resolved by H. Chan. Data extracted from each study included the publication year, age, setting, design, number of cases, initial course of the disease, initial treatment, retreatment, and the follow-up time points at which echocardiographic assessments were performed. The primary outcomes were CALs and the rate of treatment resistance. The secondary outcomes were AEs associated with drug infusion and antipyretic effects.http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp) under the three main categories [The methodological quality of the included RCTs was assessed using the Cochrane collaboration tool to assess the risk of bias ; The Mettegories .The overtegories .I2 test and considered significant at I2 > 50% or P < 0.1. GRADE profiler 3.6.1 was used to assess the evidence profile [A traditional pair-wise meta-analysis was conducted. All statistical analyses were performed using Stata 14.0 software  . The ris profile ., of which, nine studies were RCTs, while remaining trials were non-RCTs, according to the Cochrane Handbook. Those two non-RCTs trials . The indirect comparison relative risk (RR) of the total incidence rate of CALs for infliximab versus IVMP was 0.70. No significant difference between infliximab and IVMP was found in the rate of coronary artery aneurysm  or coronary artery dilatation .Neither infliximab nor IVMP treatment was significantly more beneficial than second IVIG infusion with respect to reducing the total incidence rate of CALs in patients with immunoglobulin-resistant KD . Therefore, no significant difference in treatment resistance was found between infliximab and IVMP.The rate of treatment resistance was not higher in the infliximab group than in the second IVIG infusion group . The indirect comparison RR of antipyretic effects for infliximab versus IVMP was 1.18 , indicating that the antipyretic effects of infliximab and IVMP were not significantly different.Infliximab was associated with significant antipyretic effects than second IVIG infusion . The indirect comparison RR of the total rate of AEs for infliximab versus IVMP was 2.34. The result showed that the total rate of AEs associated with drug infusion was lower for IVMP treatment than for infliximab treatment.Compared to second IVIG infusion, IVMP treatment was associated with fewer AEs  and the rate of treatment resistance (I2 = 78%) in the IVMP treatment group. As shown in Figs. Significant heterogeneity was observed among the included studies in terms of antipyretic effects I2 = 6% and theStrengthened by the GRADE system, the working group grades of evidence were high for CALs in the infliximab group, moderate for CALs in the IVMP group, high for the rate of treatment resistance in the infliximab group, moderate for the rate of treatment resistance in the IVMP group, moderate for antipyretic action in both groups, moderate for the total rate of AEs associated with drug infusion in the infliximab group, and low for the total rate of AEs associated with drug infusion in the IVMP group. The indirect comparison suggested evidence grades of moderate for CALs between infliximab versus IVMP, low for treatment resistance between infliximab versus IVMP, moderate for antipyretic action between infliximab versus IVMP, and low for AEs associated with drug infusion among infliximab, IVMP, and second IVIG infusion .Tests for funnel plot asymmetry and meta-regression analyses weren’t conducted in the meta-analysis since the number of included studies in pair-wise meta-analysis was < 10, according to Cochrane Handbook .TNF-α is elevated in the acute phase of KD and may be a contributing factor in patients who subsequently develop a coronary artery aneurysm. Infliximab, which is a chimeric monoclonal antibody against TNF-α, has been used to treat patients with immunoglobulin-resistant KD for the past 10 years. Several studies have suggested that treatment with infliximab results in faster fever resolution, shorter hospitalization, and even improved coronary artery outcomes compared to second IVIG infusion , 27 and A previous traditional pair-wise meta-analysis of IVMP was published by Yang et al. in 2015 . This anOur meta-analysis suggested that IVMP and infliximab may have limited ability to prevent or treat CALs in immunoglobulin-resistant KD patients, as they showed the same cardioprotective effects as second IVIG infusion. Neither initial IVIG nonresponders nor patients treated with early initial IVIG with methylprednisolone pulse therapy are at a lower risk for coronary artery abnormalities . A retroThe results revealed that transient hepatomegaly was most likely associated with infliximab treatment , 16. HowMillar et al. suggested that corticosteroid use in the acute phase of KD in patients with evolving coronary artery aneurysms might be associated with worsened aneurysms and impaired vascular remodeling . AccordiCertain laboratory parameters in KD patients are considered useful markers of inflammation that may reflect disease severity and treatment effects; such parameters include leukocyte and platelet counts, erythrocyte sedimentation rate, and the levels of hemoglobin, C-reactive protein, albumin, TNF-α, monocyte chemoattractant protein-1 (MCP-1), aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Previous studies revealed that IVIG nonresponders have a higher neutrophil differential, higher C-reactive protein levels, and lower cholesterol levels than responders, and there was a high risk of CALs in patients with more severe and persistent inflammation , 47. AddCardiovascular manifestations and complications are closely connected to morbidity and mortality associated with severe KD, during both acute illness and long-term follow-up. Early diagnosis and early IVIG infusion in incomplete KD patients could reduce the risk of CALs , 49. RisTo date, because few clinical trials have assessed the efficacy of medications other than second IVIG treatment, neither the AHA nor the Research Committee of the Japanese Society of Pediatric Cardiology (RCJSPC) reached consensus on the treatment options for IVIG-resistant KD. Both the AHA and RCJSPC recommend mostly a second IVIG treatment as the best reasonable therapy in IVIG-resistant patients , secondly as IVMP , then as infliximab treatment  , 26, 50.Nevertheless, this meta-analysis had several limitations. First, the use of an indirect comparison might have created differences in the clinical outcomes assessed herein. However, in the absence of sufficient head-to-head data pertaining to different treatments, an adjusted indirect comparison of the treatments in question can produce reasonable results. Some clinicians have even argued that adjusted indirect comparisons produce less bias than direct comparisons , 51. UntNeither infliximab nor IVMP was associated with cardioprotective effects or decreases in the rate of treatment resistance compared with second IVIG infusion, and both treatments were more effective than second IVIG infusion due to their antipyretic effects. Additionally, IVMP may have an advantage due to its lower total rate of AEs associated with drug infusion. However, the results of this meta-analysis should be interpreted with caution due to the presence of potential limitations. Until data from direct clinical trials comparing infliximab with IVMP are available, our meta-analysis provides preliminary evidence for the optimal management of immunoglobulin-resistant KD patients.Additional file 1:Search strategy. (DOCX 16 kb)


Real‐world evidence of second‐line treatment and beyond with immune checkpoint inhibitors (ICIs) in Chinese patients is lacking. Here, we aimed to assess the efficacy, responses, and immune‐related side effects of anti‐PD‐1 agents in real‐life practice.We retrospectively analyzed consecutive patients who received nivolumab or pembrolizumab monotherapy at Peking Medical College Hospital. We collected baseline characteristics, evaluated treatment efficacy, and categorized immune‐related adverse effects (irAEs). Predictive factors of treatment response were also determined.The study included 97 patients with a median age of 64 years. The majority of patients were male, with nonsquamous histological type and advanced stage tumor, and had a history of smoking. Most patients received ICIs as second‐line therapy. Expression of PD‐L1 was detected in 34.11% patients. Overall response rate (ORR) and disease control rate (DCR) were 16.49% and 60.82%, respectively. None of the patients achieved complete response (CR). The median PFS and OS were150 days and 537 days, respectively. The incidence of immune‐related toxicities was similar to the one previously reported. Patients with driver gene mutations had shorter PFS than patients without, while patients who encountered irAE had relatively longer PFS.The real‐world clinical outcome of ICIs in second‐ and further‐line NSCLC therapy is promising. Several characteristics may have predictive value for efficacy. Occurrence of irAEs during treatment was acceptable and could be an independent positive predictive for PFS.Efficacy and safety profile of ICIs as second‐line treatment or above for patients with NSCLC are promising in real world circumstancesIncidence and median time to the occurrence of irAEs vary between organsDriver gene mutations are associated with lower progression‐free survivalOccurrence of irAEs is associated with higher progression‐free survival Advances in immuno‐oncology have caused a dramatic shift in the treatment landscape of advanced non‐small cell lung cancer (NSCLC) in recent years. Immune checkpoint inhibition therapy, which has a profoundly different cure mechanism from target therapy or chemotherapy, restoring the efficacy of tumor‐specific T cells within the tumor microenvironment thereby enhance immune response and has shown promising outcomes in NSCLC.Although significant responses of NSCLC to PD‐1 inhibitors have been demonstrated in clinical trials, there is a paucity of data in real‐world. In real‐world settings, patient cohorts are more heterogeneous, and some patients are unsuitable for clinical trials. Real‐world evidence (RWE) includes data from patients of different background and can help improving management of individual patients. The aim of this study was to assess the efficacy, responses, and immune‐related side effects of anti‐PD‐1 agents in real‐life practice after the approval of anti‐PD‐1 therapy in China. We also analyzed treatment alternatives to PD‐1 inhibitors after tumor progression. To our knowledge, this study is the largest single site retrospective study of real‐world in China.This study was conducted in Peking Union Medical College Hospital (PUMCH). Patients were collected from a prospective cohort data base (CAPTRA‐Lung Study).During the treatment cycles, disease assessments were performed every six weeks. The Response Evaluation Criteria in Solid Tumors (RECIST) criteria v 1.1 were used to evaluate disease responses. Progression‐free survival (PFS) was calculated from the beginning of anti‐PD‐1 treatment to date of progression of disease or death. Overall survival (OS) was calculated from the beginning of anti‐PD‐1 treatment to death.Adverse effects (AEs) with an immunological basis were defined immune‐related adverse effects (irAEs). All irAEs were classified and graded according to the National Cancer Institute Common Toxicity Criteria for Adverse Events .We conducted descriptive analyses on clinical and pathological variables. We compared variables that might be associated with clinical efficacy using univariate and multivariate Cox proportional hazards regression. Progression‐free survival (PFS) and overall survival (OS) data are presented as Kaplan‐Meier curves. Statistical analyses were performed with SPSS 20 and GraphPad Prism 8.0.Every patient in the study had signed their informed consent. The retrospective analysis was approved by the ethic board of PUMCH.A total of 2430 patients received treatment at the lung cancer center of PUMCH from 1 April 2017 to 31 December 2019. Among these, 97 patients had received anti‐PD‐1 treatment as second‐line therapy or beyond. The majority of these patients were men (men: women ratio = 2.03:1), and their median age was 64 years.Most patients had nonsquamous histology type (59.79%) and metastatic disease (77.32%). The most frequent metastatic site was contralateral lung, followed by bone, liver, and adrenal. Most patients had smoking history (58.76%). Checkpoint inhibitor was given a second‐line treatment in 72 patients (74.23%) and third or fourth line in 25 patients (25.77%). Nivolumab was given to the majority of patients (63.92%). The patients' characteristics are summarized in Table EGFR mutations, ALK fusions, ROS1 fusions, MET‐14 skipping, RET rearrangement, and KRAS oncogene had been tested by next generation sequencing or amplification refractory mutation system PCR in 74 patients . The analysis showed that 21 patients had driver gene mutations, including 15 cases (15.46%) of EGFR 19‐del or 21‐L858R mutations, three cases (3.09%) of ROS1 fusion, two cases (2.06%) of RET rearrangement, and one case (1.03%) of MET‐14skipping. KRAS was detected in eight patients (8.25%) , ranged between one and 49% in 23 patients (23.71%), and was negative in 31 patients (31.96%)  experienced irAEs. Of these, 19 patients had irAEs involving more than one organ. The organ most commonly involved was the skin, followed by endocrine system and liver.The median time from immunotherapy to first irAEs was 63 days. Moreover, the median time to occurrence of irAEs varied between organs and systems Fig .Most irAEs were limited to grade 2, whereas grade 3 or 4 irAEs occurred in nine cases (9.4%). Patients were given systemic glucocorticoids for the treatment of irAEs greater than grade 3, except for endocrine irAEs, for which replacement therapies were given. Cyclosporin A, cyclophosphamide, anti‐IL‐6 antibody, and anti‐TNFα antibody were given to selected patients with critical and refractory diseases. The incidence and grades of irAEs are reported in Table Nine patients had dose interruptions, and six patients permanently stopped immunotherapy due to myocarditis (two cases), pneumonia (two cases), myocarditis plus pneumonia (one case), and grade 4 bulla (one case). Most patients experienced improvement or resolution of toxicity. Three patients died presumably as a consequence of irAEs. The causes of death were myocarditis, pneumonia, and pneumonia plus myocarditis and hepatitis.The median follow‐up time for all patients was 249 days. During this time, 72 patients (74.22%) had disease progression and 42 patients (43.30%) died. The median PFS and OS were150 days and 537 days, respectively . The regimens included single‐drug chemotherapy (23.71%), continued immunotherapy (15.46%), and targeted therapy (15.46%). The most used mono‐chemotherapies were docetaxel (12.37%), gemcitabine (4.12%), or paclitaxel (3.09%). Targeted therapies were only used in patients who were positive to driver gene mutations, and consisted of second‐ or third‐generation tyrosine‐kinase inhibitors (TKIs) and rechallenge of first‐generation TKIs. Eight of the patients who continued immunotherapy had concurrent local treatment such as radiofrequency ablation, localized radiotherapy, and interventional embolotherapy.We further investigated the clinicopathological factors that might affect the efficacy of PD‐1 inhibitors. Univariate analysis showed that median PFS was significantly increased in patients with Eastern Cooperative Oncology Group (ECOG) performance status (PS) score 0‐1who experienced irAEs during therapy Fig . InsteadPatients with recurrent or advanced NSCLC for whom first‐line chemotherapy and/or targeted therapy fail generally have a poor prognosis. ICIs, which have the ability to restore the patient's antitumor immunity, are becoming the new choice for these patients. In several clinical trials, ICIs have shown a significantly higher response rate and durable clinical response than chemotherapy in patients with advanced NSCLC.However, most of the evidence to date comes from clinical trials and cannot be generalized to real‐world patients. There are only a few retrospective analyses that, however, include smaller cohorts of Chinese patients.This study retrospectively analyzed the efficacy, outcomes, side effects, and clinical factors associated with prognosis in a longitudinal cohort of real‐world patients with NSCLC receiving monotherapy of ICIs as second‐line treatment and above. To the best of our knowledge, this is one of the largest comprehensive retrospective studies of real‐world patients from mainland China who were treated with second‐line PD‐1 inhibitor monotherapy.In published clinical trials, the ORR of second‐line ICI monotherapy ranged from 18 to 37%.The incidence of total irAEs, ≥ grade 3 irAE, and median time to irAEs in our study were comparable to those in previous reports.EGFR‐sensitive mutations and ALK fusion did not respond well to ICI therapy.EGFR mutations activate PD‐L1 expression and induce immune escape,EGFR or ALK‐mutated patients receiving ICIs are scarce. A retrospective study showed that only one in 28 EGFR‐mutant or ALK‐positive patients achieved PR as best response.EGFR or ALK‐mutated patients were not significant. Recently, a systemic analysis showed no benefit on OS by using second‐line nivolumab, pembrolizumab, and atezolizumab treatment in EGFR‐mutated patients against docetaxel.Previous studies found that patients with IrAEs, with an incidence of 40% to 51%,Furthermore, the pattern of follow‐up therapies revealed that most patients had further‐line therapies, including chemotherapy, and a few patients continued immunotherapy beyond progression. The latter group of patients had oligoprogressive diseases and had been treated with localized therapy along with maintenance ICIs. Although the therapeutic regimen might prolong the PFS2 of driver gene mutated NSCLC with CNS and/or limited systemic disease progression on targeted therapies,EGFR mutations in this study had only received first‐generation TKI therapy. The efficacy of ICIs in patients resistant to third‐line TKIs still needs to be defined. Third, tumor mutation burden, which may affect the efficacy of nivolumab, was not tested in most patients. It would be interesting to collect these data for future studies. Cases from different cancer centers should also be collected and analyzed comprehensively in the future.There are several limitations of this study. First, this is a retrospectively designed, nonrandomized study conducted in a single center. Therefore, the patient number is limited, and biases could exist in patients' inclusion criteria and efficacy evaluations. Second, most patients with In conclusion, in heterogeneous real‐world settings, ICI monotherapy showed promising clinical outcomes and acceptable side effects as second‐ and further‐line treatment for patients with advanced NSCLC. Clinical factors such as driver gene mutations and appearance of irAEs were independent predictive factors for PFS. Further prospective studies are required to understand the underlying mechanism and relationship between clinical factors and ICI response in patients.The authors declare no potential conflicts of interest.Table S1 The treatment choice of all the 97 patients.Click here for additional data file.


In developing countries, Pakistan is one of the countries where access to health and health-related indicators is a major concern. Their improvement would reduce inequalities among various Communities/Districts or groups of Communities. A Community health index (CHI) in this regard is estimated to explore inequality ratio, inequality slope, and spatial analysis of inequalities among all Communities at regional and geographical levels.Data from Pakistan Social and Living Standard Measurement (PSLM) survey, Round-VI, 2014–15 were used to construct CHI. The index was constructed in two steps. In the first step, the study indicators were standardized while in the second step, the standardized indicators were aggregated into a single metric by applying non-linear Geometric Mean formula.The inequality ratio of 16.59 estimated for Pakistan was found to be higher than the ratio of Atlanta city, GA (5.92), whereas, a lower slope coefficient was estimated for Pakistan than Atlanta city, GA (0.38 < 0.54). This ratio of disparity was also found to be lower for urban regions as compared to rural (7.78 < 17.54). While the slope coefficient was slightly higher for urban regions (0.45 > 0.43). The results of the spatial analysis revealed different patterns of inequalities. A cluster of healthy districts was found in Punjab province, whereas districts from Baluchistan had made a bunch of deprived/unhealthy districts in terms of CHI scores. Besides, separate maps for all provinces showed that capital districts of all provinces were relatively well-off/developed.The instant results concluded that inequalities in access to health and health-related indicators exist across countries as well as across geographical regions. To reduce or eradicate these inequalities, government and public health workers are recommended to set priorities based on access to composite index.The online version contains supplementary material available at 10.1186/s12889-020-09870-4. Improvement towards equitable access to health and health-related determinants is a global concern and fundamental to the advancement of Sustainable Development Goals (SDGs) . Access Nations throughout the globe are lacking access to health and health-related indicators, but more in low- and middle-income countries. According to UNDP’s report, about 103 million of the world population has no literacy skills . ApproxiPakistan being a low- and middle-income country faces a lack of access to health and health-related socioeconomic indicators. About 39% of the population suffers from multi-dimensional poverty . ConsideIt could be viewed as access to health and health-related socioeconomic, housing, clean drinking water, and environmental factors, the government of Pakistan has made extraordinary progress in accessibility and sustainability towards these indicators since 2000 . HoweverThere are several approaches used to measure geographical disparities. One of these popular approaches is the recently developed Urban Health Index (UHI) . Though As the aim of the composite index  is to examine health/wellbeing disparities among districts at the geographical level, this paper can contribute to the existing literature from certain perspectives. First, the composite index is constructed very rarely and has not been constructed before in Pakistan. Second, in Pakistan, there has been no study found on district health/wellbeing disparities at the regional and geographical levels. Finally, spatial analysis of health inequalities has not been conducted in Pakistan and we have analyzed the data spatially through ArcGIS and GeoDa applications , 31.Before explaining the step-wise methodology of CHI, the selection of appropriate domains (and their sub-domains) was the main problem in index construction. Therefore, the dimensions were selected based on certain important grounds. First, based on previous literature these indicators have significantly influenced the health status , 32–40. To construct the Community Health Index (CHI), the WHO’s methodology was applied, recently used to measure the Urban Health . CHI wasThe selected indicators were standardized by taking the difference of the indicator’s actual value from its lowest value divided by the difference between the highest values to the lowest value. Lowest and highest values are also known as the minimum and maximum goalposts respectively. The mathematical derivation is given in Eq.  as underI = actual value of an indicator.Where; I) = maximum value of indictor I.Max (I) = minimum value of indicator I minus a small value or a chosen value.Min*  formulae. The Geometric Mean methodology is explained mathematically in Eq.  as underj” is the total number of indicators and “1/j” is the power of the product of all standardized indicators. The index score was calculated by multiplying the values of standardized indicators together for all communities (districts) and raising the product to the jth root. This simple Geometric Mean formula assigned equal weights to all sub-dimensions or simply it is known as Unweighted Geometric Mean. However, as in the present study, all dimensions (and not their sub-dimensions) were assumed to be weighted equally, the above simple Geometric Mean formula had been converted to the Weighted Geometric Mean formula. The mathematical expression of Weighted Geometric Mean is written in Eq.  was computed by taking the ratio of the mean of the upper 10% of the distribution (first decile) to the mean of the lower 10% of the distribution (last decile) of CHI scores. Mathematically we can write the formula as under;The disparity/inequality slope of the middle 80% of CHI scores was estimated by applying simple linear regression through the Ordinary Least Square (OLS) technique. These districts/communities were ranked in ascending order in terms of CHI scores. The CHI scores were regressed on the rank variable. Mathematically;i” is the index score of “ith” district and “Ranki” is the rank of that particular district. “f” shows a functional relationship between the dependent and independent variables. Equation (Where “CHIEquation  is econoβ” is the disparity slope that shows the average CHI heterogeneity between each adjacent district (Community) and is influenced by the ranking of districts/communities. As the number of communities was varied in different provinces, the rank variable was rescaled through dividing each area’s rank by the total number of units in the midsection and regressed the CHI scores again on the rescaled rank variable.In Eq. , “β” is The slope estimated through Eq.  can be uAs one of the objectives is to assess the patterns of spatial geographical disparities among districts of Pakistan, the CHI scores were displayed on choropleth maps. Spatial representation is useful because one can directly differentiate the extent of the health/well-being quality of various districts for different regions. Moreover, it provides essential information about different patterns of health (well-being) to public health workers and can make some useful planning in this regard. A step by step brief procedure of how to show CHI scores on maps is given in Additional file Data were extracted from Pakistan Social and Living Standard Measurement Survey (PSLM): Round-VI, 2014–15 conducted by the Pakistan Bureau of Statistics (PBS), Islamabad . This suFor analysis purposes, Excel spreadsheets , Statistical Package for Social Sciences (SPSS) version 20, Geographic Information System (ArcGIS), and GeoDa applications were used throughout the study , 31.As the study was based on the assumption that the selected indicators should be positively correlated with one another, Pearson’s Correlation Metrix is shown in Table The distribution of the Community Health Index (CHI) for 113 districts of Pakistan is shown in Fig. Figure Figure Figure There has been a significant improvement in access to health and health-related social indicators but inequalities exist across nations as well as across different geographical regions within the country. For instance, in our study, the disparity ratio (16.59) is higher than the ratio of 5.92 found for census tracks of city of Atlanta, state of Georgia, USA . ComparaThere is also a significant difference in disparity slopes across nations as well as across various geographical groupings within a country. Census tracks of city of Atlanta, GA are more heterogeneous and sensitive (with a slope of 0.54 ) than diSpatial analyses are useful in understanding the patterns of inequalities among various geographical regions. Figure To assess whether there exist variations in the spatial pattern of urban and rural regions of all districts, separated maps for both rural and urban regions have been constructed Fig. . From boA separate spatial analysis of each province provided information about where the clusters of healthier or unhealthier districts in terms of CHI scores exist. For instance, concentrating on the Punjab map (Panel A), Northern districts are making a bunch of relatively healthier districts , as the data set utilized in our study does not have rich information about other than the selected indicators. Secondly, the analysis was conducted only for 113 districts of Pakistan, and the rest of the districts were ignored either due to law and order situations or having fewer respondents (households) that could not show the real picture of the whole district. Finally, rich information was available on Islamabad district but in the present study, we have ignored this district. It is because Islamabad is the capital of Pakistan and after estimating the CHI score for that district, it was highly developed and was far away from all other study districts which made our results.To conclude here, spatial inequalities concerning access to health and health-related social indicators persist across countries and geographical regions within the country. In this regard, this study provides a foundation for measuring the extent of inequalities and heterogeneities within communities/districts. Besides, this analysis also offers a basis for assessing the spatial patterns of disparities across various geographical boundaries. Governments and public health researchers/practitioners can use such outcomes to set priorities and can eradicate the disparities as health-related socioeconomic attributes are integrated and improvement in any of these indicators especially in deprived/unhealthy regions will enhance the overall quality of health/wellbeing .Additional file 1. Steps of constructing choropleth map using ArcGIS application.Additional file 2:Table A. List of upper and lower decile districts of Pakistan with respect to CHI scores. Table B. Regression analysis for disparity slope . Table C. Region-wise list of upper and lower decile districts of Pakistan with respect to CHI scores. Table D. Regression analysis for disparity slope . Table E. Regression analysis for disparity slope (All provinces of Pakistan).Additional file 3:Figure A. Distribution of Community Health Index of districts in all Provinces. Figure B. Spatial distribution of CHI of districts in all provinces of Pakistan.


Early-psychosis researchers have documented that duration of untreated psychosis (DUP) is an important predictor of outcomes in first-episode psychosis. Very few cross-national studies have been conducted, and none have been carried out involving patients from both Mexico and the U.S. We collaborated to answer three questions: (1)Are DUP estimates similar in two very different settings and samples? (2)Are demographic variables, premorbid adjustment, and symptom severity similarly related to DUP in the two different settings? (3)Does the same set of variables account for a similar proportion of variance in DUP in the two settings?Data on sociodemographic characteristics, premorbid adjustment, symptom severity, and DUP were available for 145 Mexican and 247 U.S. first-episode psychosis patients. DUP was compared, and bivariate analyses and multiple linear regressions were carried out in each sample.DUP estimates were similar (medians of 35 weeks in Mexico and 38 weeks in the U.S.). In the Mexican sample, DUP was associated with gender, employment status, premorbid social adjustment, and positive symptom severity (explaining 18% of variance). In the U.S. sample, DUP was associated with age, employment status, premorbid social adjustment, and positive symptom severity (but in the opposite direction of that observed in the Mexican sample), accounting for 25% of variance.Additional cross-national collaborations examining key facets of early-course psychotic disorders, including DUP, will clarify the extent of generalizability of findings, strengthen partnerships for more internationally relevant studies, and support the global movement to help young people struggling with first-episode psychosis and their families. Studies on first-episode psychosis from around the world have consistently shown duration of untreated psychosis (DUP)—often defined as the time interval from onset of frank psychotic symptoms  to the first contact with a psychiatric facility to receive adequate pharmacological treatment—to be an important predictor of clinical and social outcomes in patients with first-episode psychosis . A longecauses poor outcomes or if individuals at risk for poor outcome receive specialized treatment long after the onset of symptoms [The specific mechanisms underlying the association between DUP and outcome variables are not yet clearly identified. It is still unknown if DUP symptoms . It is csymptoms , and thasymptoms –10.Although longer DUP can be considered a risk factor for poorer outcomes in patients with psychosis, little is known about the determinants of a prolonged DUP . Some stLower premorbid adjustment is reflected by a poorer adaptation to school, lower academic performance, and limited social relationships during childhood and adolescence. If an insidious illness onset begins during this time, early manifestations of the disorder, such as predominant negative symptoms, are often misattributed to other circumstances rather than a serious mental illness, such as substance use, difficulties at school, or simply behaviors considered to be characteristic of adolescence , 20–22. In this study, we leveraged a collaboration between Mexican and U.S. early psychosis researchers to study two samples with regard to key variables pertaining to first-episode psychosis. We specifically sought to answer three research questions about DUP. First, are DUP estimates similar or different in the two very different settings and samples? Second, are basic demographic variables, premorbid adjustment scores, and symptom severity scores similarly related to DUP in the two settings and samples? Third, does the same set of variables account for a similar portion of variance in DUP in the two different settings and samples?Patients in Mexico were consecutively recruited from both the inpatient and outpatient services of the Instituto Nacional de Psiquiatría Ramón de la Fuente Muñíz (INPRFM), a highly specialized mental health center in Mexico City, dedicated to research, education, and treatment of psychiatric patients. A total of 145 patients, enrolled from the prospective Mexican First-Episode Psychotic Study  were incWith regard to the settings from which the U.S. participant were drawn, as part of a project examining the effects of premorbid marijuana use on early-course psychosis , consecuStructured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) [At both sites, after a clinical interview with the patient and his or her relatives, a trained clinical researcher made a diagnosis using the (SCID-I) , to confPremorbid Adjustment Scale (PAS) [childhood (≤11 years), early adolescence (12–15 years), late adolescence (16–18 years), and adulthood (≥19 years). Functioning in each of these age periods is assessed across five major psychosocial domains that are rated from 0  to6 (severe impairment): sociability and withdrawal, peer relationships, scholastic performance, adaptation to school, and social-sexual functioning. Social-sexual functioning is not included as a psychosocial domain during the childhood period, while scholastic performance and adaptation to school are not measured during the adulthood period. The adulthood period was not assessed in the present study. Thus, in childhood, academic functioning includes scholastic performance and adaptation to school, and the social functioning encompasses sociability and withdrawal and peer relationships. In both early adolescence and late adolescence, academic functioning is comprised of scholastic performance and adaptation to school, and social functioning includes sociability and withdrawal, peer relationships, and social-sexual functioning. At both the Mexican and U.S. sites, functioning was not rated in a respective age period if prodromal or psychotic symptoms began during or within one year of that period, as described previously [The le (PAS)  assessesle (PAS) –32. Funceviously .Positive and Negative Syndrome Scale (PANSS) [Positive and negative symptom severity was assessed at both sites with the commonly used  (PANSS) . The PAN (PANSS) . At the At the Mexican site, DUP was measured following the criteria proposed by Larsen  and was Symptom Onset in Schizophrenia (SOS) inventory [At the U.S. site, age at onset of psychosis and DUP  were determined using the nventory . The SOSnventory , 38–40.2 tests of association for categorical variables, independent samples Student’s t tests for continuous variables with approximately normal distributions (based on examination of descriptive statistics and the Kolmogorov-Smirnov test), and Mann-Whitney U tests for continuous variables that were not normally distributed. Correlations were computed using Pearson and Spearman correlation coefficients as appropriate.Bivariate analyses for comparisons between the Mexican and U.S. samples of first-episode psychosis patients were carried out using χTo assess the independent effects of correlates of DUP in both samples, we computed a log transformation of DUP, ln(DUP+1), which normalized the distribution to allow for multiple linear regression models.z=3.99, p<0.001) and more likely to be unemployed (at a trend level). Patients in the U.S. sample had completed more years of education , were more likely to be male , and were more likely to be single .We first compared our two first-episode psychosis samples in terms of basic demographic variables. As shown in z=0.02, p=0.99); the distributions of DUP are shown in In terms of PAS scores, patients in the Mexican sample had lower PAS academic adjustment scores (indicating better premorbid academic adjustment) across all three age groups. However, PAS social adjustment scores did not differ. Also shown in p<0.01) and in the moderate range (the average of the three correlations was 0.46 in the Mexican sample and 0.49 in the U.S. sample). Correlations between the three social adjustment scores were also statistically significant  and larger (the average of the three correlations was 0.68 in the Mexican sample and 0.58 in the U.S. sample). On the other hand, correlations between the three academic adjustment scores and the three social adjustment scores were only modest  and 0.17 in the U.S. sample ).Inter-correlations among PAS subscale scores, in both samples, are shown in r=0.15 in Mexican patients and r=0.23 in U.S. patients), and negative symptom and general psychopathology symptom subscale scores were most correlated .With regard to inter-correlations among the three PANSS symptom severity scores, findings were again consistent in the Mexican and U.S. samples of first-episode patients . Specifip<0.001), though it was not associated with DUP in the Mexican sample . Also in the U.S. sample, employment status was associated with DUP at a trend level . In the Mexican sample, both gender  and employment status were associated with DUP .In terms of associations between DUP and the five demographic variables , and employment status), in the U.S. sample, age and employment status were associated with DUP. Age was directly correlated with DUP . In both samples, DUP was associated neither with negative symptom severity nor general psychopathology symptom severity. In the Mexican sample, longer DUP was associated with a lesser severity of positive symptoms , but in the U.S. sample, longer DUP was associated with a greater severity of positive symptoms .Correlations among DUP, PAS academic adjustment (an average score across the three age periods), PAS social adjustment , and PANSS scores are shown in . Similarly, in the model pertaining to the U.S. sample, the four independent variables  accounted for 25% of the variance in DUP .In each sample, multiple linear regressions were run, including variables found to be associated with DUP in the aforementioned bivariate tests. Results of these two models are shown in 4.social adjustment was related to DUP in both samples, though premorbid academic adjustment was not. Third, interestingly, positive symptom severity was associated with DUP in the two samples, but in contrasting ways. Fourth, we found that a similar set of four variables account for approximately one-fifth to one-quarter of the variance in DUP in the two different settings and samples.Several interesting findings emerged from this analysis, which represents one of the first cross-national comparisons of DUP and predictors/correlates of DUP, and the first to do so among first-episode samples in Mexico and the U.S. First, we found that the distributions of DUP—and the medians of DUP—were remarkably similar in these two very different settings and samples. Second, we observed similarities in variables associated with DUP; for example, premorbid With regard to the first of these findings, in our samples, the median DUP is around 8–9 months. This is consistent with findings in several other studies , 41. OneOur similarities in correlates of DUP add more evidence regarding the importance of poor premorbid social adjustment in understanding DUP. This variable may produce longer DUP as poor social adjustment is related to decreased social support –47 (incllesser severity of this kind of symptoms in the Mexican sample. However, a longer DUP was associated with greater positive symptom severity in the U.S. sample. This apparently contradictory finding could be explained by the exacerbation of stigma in the presence of positive symptoms [Regarding the relationship between DUP and positive symptoms, as expected due to the difficulty for the patient/family to recognize/accept a psychiatric disorder that needs to be evaluated and treated when positive symptoms are less severe or not present, a longer DUP was associated with symptoms  and conssymptoms . Additiosymptoms  pointed a priori that our two settings and samples were quite different; we view the findings as particularly informative in part because of this lack of similarity. In both samples, four predictors accounted for 18–25% of the variance in DUP.In comparing DUP estimates, predictors of DUP, and proportion of DUP explained by similar sets of predictors, we knew Several methodological limitations should be noted. First, this was a secondary analysis of two existing but similar datasets that were combined for the purposes of this collaborative analysis. As such, there were subtle differences in the exact measurement methods for key variables, including DUP. Second, as is true of any study of DUP, this is a difficult construct to measure as it inevitably relies on retrospective recall of patients and their family members. Third, and also related to the fact that this was a secondary analysis, there are a host of other variables that would have ideally been measured, and which could have explained more variance in DUP. Despite these limitations, our analysis reveals the value of cross-national collaborations in examining key facets of the early course of psychotic disorders, including DUP. Such studies will clarify the extent of broad generalizability of findings even in quite different samples; strengthen partnerships for more rigorous and internationally relevant studies; and support the now global movement to help young people struggling with early psychosis and their families, who must navigate complex systems of care while facing diverse social and psychological challenges.


Ectopic expression of RUNX2 has been reported in several tumors. In melanoma cells, the RUNT domain of RUNX2 increases cell proliferation and migration. Due to the strong link between RUNX2 and skeletal development, we hypothesized that the RUNT domain may be involved in the modulation of mechanisms associated with melanoma bone metastasis. Therefore, we evaluated the expression of metastatic targets in wild type (WT) and RUNT KO melanoma cells by array and real-time PCR analyses. Western blot, ELISA, immunofluorescence, migration and invasion ability assays were also performed. Our findings showed that the expression levels of bone sialoprotein (BSP) and osteopontin (SPP1) genes, which are involved in malignancy-induced hypercalcemia, were reduced in RUNT KO cells. In addition, released PTHrP levels were lower in RUNT KO cells than in WT cells. The RUNT domain also contributes to increased osteotropism and bone invasion in melanoma cells. Importantly, we found that the ERK/p-ERK and AKT/p-AKT pathways are involved in RUNT-promoted bone metastases. On the basis of our findings, we concluded that the RUNX2 RUNT domain is involved in the mechanisms promoting bone metastasis of melanoma cells via complex interactions between multiple players involved in bone remodeling. SPP1 (secreted phosphoprotein 1 )gene product, OPN(osteopontin), was observed in bone metastases [Skeletal metastases occur when cancer cells from a primary tumor invade the bone. Generally, bone metastases are associated with breast, prostate and lung cancers . Bone metastases ; it was tastases . Importatastases . In parttastases . PTHrP wtastases  in head tastases . In additastases . Recentltastases . Conside2 and in RMPI  growth medium  containing 10% fetal bovine serum (FBS) (Sigma-Aldrich), supplemented with antibiotics (1% penicillin/streptomycin) and 1% glutamine. All cell lines were tested negative for mycoplasma using the LookOut Mycoplasma PCR Detection Kit (Sigma-Aldrich).We used A375  and MELHO (DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen) human melanoma cells. The RUNT KO cells were obtained using CRISPR/Cas9 as we previously described . Cell liOnce 80% confluence was reached, cells were harvested, washed and counted using a Burker haemocytometer for all experiments.gatatcTTCGCCTCACAAACAACC-3′) and the reverse primer Runx2R-XhoI (5′-ggacctcgagATATGGTCGCCAAACAGAT-3′); underlined nucleotides represent the restriction sites. The amplified fragment was inserted in the pCRTM2.1 cloning vector, then excised by EcoRV/XhoI digestion and finally cloned in pcDNA3-Flag-HA vector . The cloned fragment was sequenced at the BMR Genomics facility (http://www.bmr-genomics.it). RUNX-2 expression was validated by Western blot.The RUNX-2 gene was cloned into the pcDNA3 vector as previously described ,23. BrieThe exogenous PTHrp peptide  was added to A375, 3G8, MELHO and 1F5 melanoma cells seeded into 24-well plates at a concentration of 100 µg and incubated for 24 h. Treated cells were then harvested to perform expression analyses.A375 and MELHO melanoma cells were plated in 96-well plates at a density of 1000 cells per well and incubated overnight. Cells were then treated with ERK1/2 and AKT inhibitors  for 24 h at a final concentration of 2 µM in RPMI1640 10% FBS. Cultured media were collected to perform ELISA assays, while cells were stored for gene expression analysis.® Design and Analysis desktop software (Thermo Fisher Scientific).PCR arrays were performed using a TaqMan™ Human Tumor Metastasis Array  according to the manufacturer’s instructions. The amplification reaction and the results analysis were carried out using a QuantStudio™ 3 Real-Time PCR System equipped with QuantStudioVEGFA, Hs00900055_m1; VEGFR, Hs01052961_m1; CD31, Hs01065279_m1; IBSP, Hs00173720, OPN, Hs00167093_m1). Gene expression for MMP9  was tested using the Power SYBR® Green PCR Master Mix (Thermo Fisher Scientific). Gene expression was normalized to the housekeeping β2-microglobulin  gene, and the relative fold expression differences were calculated. TaqMan SDS analysis software was used to analyze the Ct values. Three independent experiments with three replicates for each sample were performed.Total RNA extraction and RT were performed as previously reported . PCRs we® TGXTM precast gradient 4–20% gels  and transferred onto polyvinylidene difluoride (PVDF) membranes (Thermo Fisher Scientific). PVDF membranes were then probed with the primary and secondary antibodies reported in RIPA buffer was used for protein extraction (Thermo Fisher Scientific) and protein concentrations were determined by BCA assay (Thermo Fisher Scientific). Protein samples were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) using mini-PROTEANSignals were detected using a chemiluminescence reagent , and images were acquired using an LAS4000 Digital Image Scanning System . Densitometric analyses were performed using the ImageJ software, and the relative protein band intensity was normalized to β-actin and expressed as the optical density (OD) ratio. The data were obtained from three independent experiments.® 488 anti-rabbit (Cat. #A-11034) secondary antibody, and nuclear staining was performed by using ProLong™ Gold Antifade Mountant with DAPI (Thermo Fisher Scientific). Images were captured using a Leica DM2500 microscope . In particular, four different fields were measured for each sample in three independent experiments, and each field contained approximately 80–100 total cells.Cells were fixed and processed according to the manufacturer’s protocols. BSP primary antibodies  were diluted (as reported in the datasheet) in Antibody Dilution Buffer and incubated overnight at 4 °C. The slides were then incubated with the Alexa Fluor4 cells were seeded onto the upper chamber of transwell plates of 8 µm diameter  in the presence of RPMI supplemented with 1% FBS for 24 h (migration assay) or 48 h (invasion assay). The invasion assays were performed by coating the upper chamber with Matrigel. The lower chamber was filled with medium with or without bone fragments . After 48 h, cells adherent to the upper surface of the membrane were removed. Thereafter, cells in the membrane underside were fixed with 4% of paraformaldeide and stained with DAPI. Cells were then visualized under a Leica DM 2500  to take pictures and to evaluate the number of adherent cells. Cells were counted in ten random fields at 40X magnification.To assess bone tropism, we first compared cells’ ability to migrate in the presence or absence of a bone fragment. Therefore, cells were seeded on a 6-well plate at a density of 500,000 per well. After adhesion, half of each well was scratched using a cell scraper, and the relative migration distance (RMD) was calculated in the absence or presence of a bovine bone slice  placed at the same distance in all samples. Cultures were carried out for 2 days using DMEM (Dulbecco’s Modified Eagle Medium) supplemented with 10% FBS and Glutamax  at 37 °C and 5% CO. The migration ability assay was conducted with an EVOS™ FL Auto Imaging System (Thermo Fisher Scientific) under time-lapse protocol for 48 h. Distances between the cell front and the bone slice or the signed blank space for every well were measured at the beginning and at the end of each experiment. Relative migration distances (RMDs) were calculated using the following formula: RMD = (t0–t1)/t0, where t0 is the distance between the cell front and the bone slice at time zero of the assay and t1 is the same distance at the end, as previously reported . The RMDFor PTHrP protein detection, we performed an ELISA . WT and RUNT KO cell lines were plated onto 96-well plates at a density of 10,000 cells/well. After 3 days of culture, the medium was collected and centrifuged at 1000 g for 20 min at 4 °C. Standards were prepared following the manufacturer’s instructions. Samples and standards were plated into the ELISA microplate, and the assay was conducted according to the manufacturer’s instructions.https://string-db.org) for independent inspection related to their predicted connections.RUNX2, PTHrP, AKT and ERK proteins were submitted to the STRING portal  for Windows, version 16.0 .Student’s paired t-test was used to compare the variation of variables between two groups. Differences were considered statistically significant at Then, we evaluated the metastatic gene expression profile in A375 and RUNX2 RUNT KO (RUNT KO) melanoma cells by using a Human Tumor Metastasis Array. The data showed lower expression of several genes involved in the metastatic process in RUNT KO cells compared to A375 cells . To valiWe then tested RUNT domain influence in driving melanoma cell migration to the bone by analyzing the expression of IBSP and SPP1 genes. As shown in As PTHrP expression is regulated by RUNX2, we measured PTHrP levels in WT and RUNT-KO melanoma cell culture media. Interestingly, we observed a significant reduction in PTHrP concentration in RUNT KO cells media compared to the WT cell media A, as welIn order to confirm the RUNT domain role in inducing PTHrP expression, we cultured KO cells in the presence of exogenous PTHrP (+exPTHrP). As shown in Considering the modulatory role of VEGFR2 in the ERK pathway, we then looked for ERK pathway modifications in KO cells. The observed reduced levels of ERK and pERK proteins expression in RUNT KO cells compared to WT cells suggested an activating role of the RUNT domain A. ERK anTo evaluate the interaction between RUNT and AKT/ERK signaling pathways, we treated WT cells with either AKT or ERK inhibitors. Our data showed that the inhibition of AKT and ERK pathways did not affect RUNX2 gene expression A. HoweveImportantly, inhibition of both the AKT and ERK pathways reduced the amount of PTHrP released in the WT melanoma cell medium D. AccordAt first, we evaluated the migration ability of cells either in the presence or in absence of bone fragments in vitro. In particular, we calculated the levels of the relative migration distance of WT versus RUNX2 KO cells in the presence or absence of bone fragments. We observed that RMD levels of, W.T.; normalized with the RMD of RUNX2 KO cells, were higher in the presence of bone fragments . TherefoTo further analyze the role of the RUNT domain in driving melanoma cell migration to bone fragments, we tested the migration and invasion ability of WT and RUNT-KO melanoma cells, respectively, in a transwell system. The migration ability in the absence of bone fragments was lower for RUNT-KO cells compared to WT A. In theThe bone microenvironment regulates complex and relevant processes such as hematopoiesis, osteogenesis and osteolysis . VariousTranscription factor RUNX2 is the master gene of osteogenic differentiation. Its expression is high in pre-osteoblasts and in early osteoblasts, but decreases in mature osteoblasts . HoweverRUNX2 involvement in regulating the epithelial–mesenchymal transition (EMT) process has been demonstrated in melanoma . RecentlIn lung cancers, RUNX2 overexpression was shown to promote EMT via direct regulation of vimentin along with other proteins ,37. ReceWe demonstrated that the RUNT domain promotes melanoma cell proliferation and migration . AccordiWe also observed a reduced expression of PTHrP, an autocrine/paracrine ligand involved in malignancy-induced hypercalcaemia and skeletal metastatic lesions, in RUNT KO cells . InteresTo evaluate the involvement of RUNX2 in osteotropic mechanisms, we performed in vitro experiments by using bone fragments as previously described by Mannavola and coworkers . EmploymFinally, since our results showed that the RUNT domain affects the expression and the activity of various molecules involved in bone metastasis, we conclude that RUNX2, via the RUNT domain, may promote bone metastasis of melanoma through a complex scenario affecting different and strongly associated pathways.