Along with the development of science and technology, lanthanide‐doped upconversion nanostructures as a new type of materials have taken their place in the field of nanomaterials. Upconversion luminescence is a nonlinear optical phenomenon, which absorbs two or more photons and emits one photon. Compared with traditional luminescence materials, upconversion nanostructures have many advantages, such as weak background interference, long lifetime, low excitation energy, and strong tissue penetration. These interesting nanostructures can be applied in anticounterfeit, solar cell, detection, bioimaging, therapy, and so on. This review is focused on the current advances in lanthanide‐doped upconversion nanostructures, covering not only basic luminescence mechanism, synthesis, and modification methods but also the design and fabrication of upconversion nanostructures, like core–shell nanoparticles or nanocomposites. At last, this review emphasizes the application of upconversion nanostructure in detection and bioimaging and therapy. Learning more about the advances of upconversion nanostructures can help us better exploit their excellent performance and use them in practice. Through adjusting the relative intensity of these particular emission bands, the emission from green to red can be obtained. The two characteristic emission bands of Tm3+ are respective about 800 and 480 nm, and blue light was apparent because the light of 800 nm is not visible. Ho3+ possesses similar characteristic emission bands to those of Er3+. As another kind of dopants, sensitizers are responsible for the absorption of energy from excitation source and then transferring it to activators. Yb3+ and Nd3+ are the most commonly used sensitizers.3+ and Nd3+ not only has large absorption cross‐section at 980 and 808 nm, respectively, but also could be in resonance with activators. In addition to dopant, host matrix provides a platform for energy transfer.Because of the different luminescence mechanism of upconversion materials against the traditional fluorescent ones, many research teams were committed to the study of their luminescence mechanism, which leads to a developing understanding of their luminescence mechanism. In most cases, upconversion luminescence (UCL) was derived from more than one fundamental mechanism. Among the numerous fundamental mechanisms, excited state absorption (ESA), energy transfer upconversion (ETU) are the most significantly influential factor. Dopants and matrices are the essential elements for upconversion. Activators act as dopant, to absorb and then release the energy in the form of fluorescence. The common activators for upconversion are ErSynthesis plays a critical role in determining the structure, composition and properties of resulting materials. The resulting upconversion nanostructures may be either hydrophobic or hydrophilic, which have their merits and demerits, though the former surface feature is more common. For example, the upconversion nanostructures with controllable shape and size can be prepared by thermal decomposition, high temperature co‐precipitation and solvothermal method.Utilizing newly developed materials for particular applications is the ultimate goal of scientific research, which applies to the upconversion fluorescent nanomaterials. Given low background noise and excitation located in the IR region, lanthanide‐doped upconversion nanostructures can be used in many aspects, such as physics, chemistry, biology, and medicine, especially, as a probe for detection, bioimaging, and therapy.This review aims to discuss the existing advances in the reasonable design and synthesis of lanthanide‐doped upconversion nanostructures. To begin with, we attempt to introduce the mechanism of lanthanide‐doped upconversion nanostructures from host matrices to dopants in Section 2UCL is an anti‐Stokes optical phenomenon. Simple upconversion nanostructures normally contain dopants and host matrices that are the key factors determining luminescence efficiency. Dopants, including sensitizers and activators, provide a luminescence center, while host matrices supply a platform for energy transfer between the dopants and drive them into optimal position.2.1n5s25p6 (n varies from 0 to 14) electronic configuration. The partially filled 4f electronic shell that is critically relevant to photoluminescence is protected by outer 5s and 5p electronic shells from external environmental disturbances.n between 0 and 14 elicits lanthanide ions energy‐enriched levels, which contributes greatly to broadband spectrum. Upconversion is a nonlinear optical phenomenon, whose fundamental mechanisms consist of ESA, ETU, photon avalanche (PA), cooperative energy transfer, and cross‐relaxation. Of them, ESA and ETU are responsible for UCL efficiency.It is well known that lanthanide ions exhibit a 4f Figure3+, Tm3+, and Ho3+, commonly play an activating role in single‐doped systems, which can be explained by ESA. For single‐doped systems, Er3+ has a relatively high quantum yield given the high similarity of ≈980 nm in the energy gaps between 4I11/2 and 4I15/2 states and between 4I11/2 and 4F7/2  generated by 3H4–3H6 transition, which is favorable for biological tissues because of the deep tissue penetration and low heat effect. Three additional primary upconversion emission bands stay around 350, 450, and 479 nm corresponding to the transitions 1D2–3H6, 1D2–3F4, and 1G4–3H6, respectively. In terms of Ho3+ ions, there are two main upconversion emission bands, including the red centered at 650 nm originated from the transition 5F5–5I8, and the green centered at 540 nm originated from the transitions 5S2/5F4–5I8. Low doping concentration is common in single‐doped system (less than 3% Er3+ and no more than 1% Tm3+) to avoid concentration fluorescence quenching that can be incurred by increase in harmful nonradiative transitions derived from high doping concentration.ESA, normally doped with low Lanthanide ion concentration <1%), is responsible for the single ion based process. As depicted in %, is resUnlike ESA based on single ions, ETU always occurs in two neighboring ions regardless of their chemical nature.3+ ions with a simple energy level structure are typical sensitizer, given to their large absorbing cross‐section about 980 nm corresponding to 2F7/2–2F5/2 transition, and matched energy well with a large number of f–f transitions of the typical activators . The doping concentration of Yb3+ ions should be controlled at a medium level (20%–40%) to eliminate the hazardous concentration quenching. Selection of various dopants or doping concentrations will lead to diverse colors of upconversion emissions. Liu and co‐workers utilized Yb3+/Er3+ and Yb3+/Tm3+ co‐doped NaYF4 NCs to yield a series of colors of light.3+, Nd3+ sensitizer also has increasingly been sought. Compared to Yb3+, the thermal effect of Nd3+ is lower, and more importantly, unlike the centered at 980 nm absorption peak of Yb3+, the absorption peak of Nd3+ does not overlap the absorption peak of water, which is more suitable for biological applications. In some cases, Nd3+ ions and Yb3+ ions act jointly as sensitizers.3+ ions are excited metastable level 4F5/2 from ground level 4I9/2 by absorbing a pump photon, reaches energy level 4F3/2 by nonradiation transition, and then transfers the energy to Yb3+ ion, and finally, Yb3+ ion transfers the energy to activator. However, for the sake of improvement in UCL efficiency and feasibility for further applications, the upconversion systems doped with two sensitizers will have a complicated reaction mechanism, like core/shell structures,Dopant ions can be categorized into activators and sensitizers. As Figure 2.22+,2+,2+,2+,2+,4+,4,4,4,4,5,5,UCL efficiency is closely related to host matrices, given their critical role in determining the surrounding environments of dopant ions, such as spatial distance, coordination numbers, and energy transfer efficiency. Selection of proper host materials is of paramount importance in which a few basic requirements are highly demanded, including optical stability and resembling ionic size to that of the dopant ions. Thus, the inorganic compounds containing alkaline earth ions, for instance Ca4 whose UCL efficiency is substantially reinforced due to the transformation from α to β phase with a more asymmetry. Symmetry of rare earth doped host crystal field could be tailored to change the spatial distance between the luminescent centers and lead to some other energy transfer processes.In general, radiative transitions of rare earth ions are forbidden by quantum mechanical selection rules. However, such a forbidden nature can be broken by the crystal field of host matrix. When lanthanide doping ions are introduced into an asymmetrical crystal field, their 4f state shall mix with higher electronic configurations, leading to a higher degree of asymmetry of the host matrix and consequently a better UCL efficiency. A good example can be seen in lanthanide doped β‐NaYF3+ ions in NaYF4 facilitates the crystal phase transition from cubic to hexagonal.+ ions that are optically inert have been extensively used to modify the host crystal field.+ ions having the smallest cationic radius are expected to enter lattice sites or interstices randomly, which makes Li+ ions more suitable to modify the host crystal field. Zhang and co‐workers reported a significant enhancement (by 25 times) of the visible upconversion emissions in Y2O3:Yb,Er nanoparticles through Li+ doping for the first time.+ doping produces a more than 30‐fold increase in upconversion emission for NaYF4:Yb,Er upconversion nanoparticles (UCNPs)  Figure2a.48 I2F7 host material adopts an orthorhombic crystallographic structure to construct a “dopant ions spatial separation” structure at the sub‐lattice level with enhanced UCL efficiency . KYb2F7 material plays a dual role of host matrix and sensitizer, which is favorable for the generation of multiphoton upconversion.In general, concentrated luminescence centers shorten the spatial distances between luminescence centers, which leads to the development of some detrimental energy transfer and luminescence quenching effect. As such, concentrations of activators and sensitizers have to be strictly controlled to perform their desirable functions. However, a latest report claims that the use of a new class of KYb3 was adopted as host matrix to obtain pure single band upconversion .2+ ions within the host matrix and the dopants ions and a pure single‐band upconversion emission concentered on the red and NIR spectral regions was obtained. In addition to the host materials containing Mn2+, red single band can be observed in NaScF4, NaSc2F7, and YOF host materials.The color derived from upconversion emission is normally adjusted through controlling concentration or species of the doping rare earth ions. In some particular cases, the host materials, nevertheless, also have an influence on the upconversion emission color, as indicated by the latest report of Liu's group, where KMnFFurthermore, crystal grain size of host matrix is one of primary factors affecting the luminescence efficiency. For upconversion materials a smaller grain size gives rise to a lower UCL efficiency, which is attributed to the higher density of surface defects and more serious energy transfer loss associated with smaller grain size.2.3Energy transfer, a great physical concept, applies well to all upconversion process. Here, we discuss energy transfer process from three main contents, i.e., energy transfer in core@shell nanostructures, localized surface plasmon resonance (LSPR) assisted energy transfer, and luminescence resonance energy transfer (LRET).4:Yb,Er@KYF4,4:Yb,Er(Tm)@NaGdF44:Ln@CaF24:Tm@CaF24:Yb,Er@NaYF4:Yb,Tm was reported to that of NaYF4:Yb,Er,Tm.Figure 3+ ions, and accumulated by Tm3+ ions in the core area. Afterward, the energy transfer from Tm3+ ions to Gd3+ ions in the intermediate layer, and finally is captured by X3+ ions in outer shell for UCL under 980 nm irradiation. Apart from the host matrix containing Gd3+ ions, Yb3+ doped host materials also have a similar property. Zhao and co‐workers designed an Nd3+‐sensitized core–shell–shell nanostructure of NaYF4:Yb,X@NaYF4:Yb@NaNdF4:Yb. The Nd3+ ions in the outer shell was excited by 800 nm irradiation, and with an aid of Yb3+ ions, energy migrates from Nd3+ ions to X3+ ions.Shell layers in core@shell nanostructures are either active and inactive in terms of UCL.4:Yb,Tm NCs with plasmonic gold nanostructures.4:Yb,Tm NCs, emission intensities of 1D2‐3F4 and 1G4‐3H6 transitions were increased more than 150%, while an increase of only ≈50% was observed in 1G4‐3F4 transition. The enhancement could be attributed to the increase in radiative decay rate and emission efficiency. On the contrary, a quenching effect may be caused by the considerable scattering of excitation irradiation, when NaYF4:Yb,Tm nanocrystals was embraced by gold shells. As Figure 3+ ions to Er3+ ions, which is enhanced at least 6 folds on fabricated gold pyramid pattern.In recent years, noble metals have been extensively studied due to their excellent optical properties, such as strong visible light absorbing and scattering. LSPR can occur between noble metals, like Ag or Au, and phosphors, when the confined free electrons of noble metals are resonant with frequencies close to those of the passing photons. In general, the enhancement effect of LSPR derives from increases in excitation and emission rate. The excitation rate is elevated by the amplification of local incident electromagnetic fields when the excitation band of upconversion nanostructure couples with the LSPR band of noble metals. The increase in emission rate, when the emission band upconversion nanostructure is resonant with the LSPR frequencies of noble metals, would not only promote radiative decay rate but also promote nonradiative decay rate, which can give rise to emission quenching. In recent years, various nanostructures of noble metals, including nanoparticles, nanowires, and nanoarrays, have been employed to investigate the effect of LSPR. Zhang et al. reported a modulation of upconversion emission through hetero‐integration of NaYF4:Yb,Er nanoheterostructures (CSNY), where the CdSe nanoparticles act as an acceptor absorbing green upconversion band and emitting red light under 980 nm excitation , referring to energy donor and acceptor, requires a certain degree of overlapping between absorption band of acceptor and emission band of donor, and a close spatial distance between donor and acceptor for energy transfer. In UCNPs based LRET nanocomposites, UCNPs are usually used as energy donor, while a number of dyes, quantum dots (QDs) or metal nanoparticles act as acceptor. UCL was absorbed by acceptor and subsequently produced new emission colors. Perepichka and co‐workers reported a novel CdSe/NaYFn Figure e,f.67 In3Due to the development of nanoscience and nanotechnology, synthesis of UCNPs with controllable size, crystalline phase and composition has gradually become mature. Synthetic UCNPs can be divided into the oil‐dispersible and water‐dispersible based on their decentralized nature. Oil‐dispersible UCNPs are produced through employing oleic acid (OA) and oleylamine (OM) as surfactant. Such hydrophobic UCNPs exhibit excellent dispersibility, uniform size distribution, high crystallinity, and superior UCL properties. However, some particular UCL related applications including bioimaging and theropies, require water‐dispersible UCNPs, which inspires studies of converting hydrophobic UCNPs into hydrophilic counterparts. In order to facilitate biological applications, direct synthesis of water‐dispersible UCNPs has been developed. Surface of water‐dispersible UCNPs is normally covered by hydrophilic polymer or molecules to achieve sufficient stability in service. In this section, we will discuss the synthesis and modification of UCNPs from three aspects: synthesis of hydrophobic UCNPs, direct synthesis of hydrophilic UCNPs, and conversion of hydrophobic UCNPs to hydrophilic UCNPs.3.1Considerable efforts have been devoted to synthesis of hydrophobic UCNPs with controllable shapes, sizes and phase, which delivers a great impact on upconversion emission efficiency and their applications.3 triangular nanoplates via decomposing La(CF3COO)3 precursors in a OA/ODE solution at high temperature.4:Yb,Er and NaYF4:Yb,Tm UCNPs by thermal decomposition of sodium and lanthanides trifluoroacetates in OM,4 and NaYF4:Yb,Er/Tm NCs with controllable size in OA/OM/ODE.4:Yb,Er UCNPs, they proposed a scheme of the nucleation stages combining transmission electron microscopy, X‐ray diffraction and upconversion emission spectroscopy.Figure4:Yb,Er from their α counterparts was depicted in Figure 4:Yb,Er precursors dissolve in the beginning period, and Ostwald‐ripening process is enhanced during the α → β phase transition, owing to the broad size distribution of the dissolved α‐NaYF4:Yb,Er. In terms of route B, addition of CF3COONa in this system suppresses Ostwald‐ripening, a nucleation process initiating at low temperature and regrowth at high temperature, which is ascribed to the high concentration of monomers. At the stage of α → β phase transition, the size increases uniformly. Murray et al. obtained highly uniform β‐NaYF4 UCNPs with a diverse family of morphologies  by adjusting the synthetic conditions, including the reaction time, the ratio of OA and ODE, and the concentration of precursors  and high crystallinity nanocrystals will be synthesized by Ostwald‐ripening. For example, Zhang et al. reported the synthesis of lanthanide‐doped pure hexagonal‐NaYF4 UCNPs via high‐temperature coprecipitation.4‐based UCNPs with different shapes could be obtained via adjusting OA and ODE  to hexagonal phase (NaScF4) would be achieved. The raw materials of rare earth chlorides could be replaced by other rare earth inorganic salts. Recently, Liu's group reported the preparation of lanthanide‐doped NaGdF4 nanoparticles by a similar process, which just uses acetates counterparts as starting materials thermal synthesis.4 (M = Rare earth).3)3 as precursors and OA as a stabilizing agent and obtained nanostructured arrays that were composed of hexagonal nanotubes with lengths of ≈500 nm and outer diameters of ≈250 nm thermal synthesis has attracted much attention for synthesizing high quality NCs with well controlled size and shape, due to its low cost. At a certain temperature and pressure, water or other solvents is at a critical or supercritical state, which leads to an elevated reaction activity. So, the physical and chemical properties of the substances in the solvents were altered greatly. The most popular procedure to prepare hydrophobic NCs is the liquid−solid‐solution (LSS) process that was proposed by Li's group Figure6a.87 ASome other synthetic methods have also been developed to obtain hydrophobic UCNPs, such as ionic liquid‐based,3.2Regarding bioapplications, UCNPs with high water solubility is desired, as such secondary modifications are essential to convert hydrophobic UCNPs into hydrophilic ones, which inspires study of direct synthesis of hydrophilic UCNPs. Direct synthesis of hydrophilic UCNPs often employs water or polyol as solvent and hydrophilic polymers and molecules as surfactant. The capping ligands of the finally obtained hydrophilic UCNPs normally contain special reactive groups and can further conjugate with biomolecules or functional groups.Figure4:Yb,Er,4:Yb/Er upconversion phosphors with carboxyl‐functionalized surfaces, to prepare hydrophilic NaYF4:Yb/Er upconversion phosphors via one‐step hydrothermal method.4:Yb/Er upconversion phosphors can be controlled. Furthermore, the carboxyl‐functionalized hydrophilic NaYF4:Yb/Er upconversion phosphors can directly conjugate antibodies for biodetection. Our group also has conducted some investigations in terms of preparation of hydrophilic lanthanide‐doped UCNPs.4 UCNPs were obtained via a fast, simple, and environ‐mentally friendly microwave‐assisted modified polyol process with PEI as surfactant.4 pure phase transition from cubic to hexagonal was achieved by modulating the ratio of Gd3+:F−. The upconversion emission from visible to near‐IR, even white light, was tuned via adjusting the doping concentrations of the rare earth luminescent centers.The above mentioned hydro(solvo)‐thermal synthesis is a typical synthetic method, which is applicable to direct synthesis of hydrophilic UCNPs.4:Yb,Er upconversion nanospheres were fabricated by using Y(OH)CO3:Yb,Er nanospheres as sacrificial templates via a surface‐protected “etching” and hydrothermal ion‐exchange process by Lin's group.3:Yb,Er precursors. After addition of NaBF4, the as‐obtained solution was transferred into a Teflon autoclave for a certain time period under a certain temperature. At high temperature and pressure, the fluoride source, i.e., NaBF4, can gradually release H+ and F− ions. The H+ ions corroded Y(OH)CO3 nanospheres and resulted in a large quantity of Y3+ ions. Na+, Y3+ and F− ions reacted to generate α‐NaYF4. PEI coated on the surface of Y(OH)CO3 can effectively protect them against rapid dissolution incurred by H+ ions, as a result, α‐NaYF4:Yb,Er upconversion nanospheres with hollow structure were obtained. Furthermore, FA was conjugated on the surface of α‐NaYF4:Yb,Er nanospheres, due to the presence of free amine groups. Using the identical synthetic process, hollow CaF2, GdVO4, and NaREF4  microspheres can be fabricated.2O3:Yb,Er hollow spheres with uniform morphology and controllable inner structure via hydrothermal method followed by temperature‐programmed calcination 4) to replace the original organic ligands of nanocrystal surface. Such strategy does not work well on other diazonium tetra‐fluoroborate compounds.4− anions attaching weakly to the surface after replacement can render NCs easily a high dispersibility in various polar, hydrophilic solvents with a marginal impact on the particle size and shape. This approach is widely applicable to a great number of NCs with varying shape and size. This method is of importance because the obtained ligand‐free NCs can be stored in solvents over a long time period without evident aggregation.When an acidic pH is applied, oleate is protonated completely and detached from the UCNPs surface. The charge repulsion on the surface stabilize UCNPs. Liu's group adopted a similar strategy to prepare bare sandwich‐structured UCNPs with short spatial distance for energy transfer.3.3.32MA‐co‐SEMA) copolymers as the new capping ligand.2 in the ligands exchange procedure, the luminescence intensity would be reinforced.Ligand exchange is an effective technique to replace the original hydrophobic ligand coating on the UCNPs surface with hydrophilic ones. The process is easy to operate, and exhibits a negligible effect on the morphology of the yielded UCNPs. The driving force behind this reaction is that hydrophilic ligand has a stronger coordination ability to lanthanide ions than original hydrophobic ligand. A variety of organic molecules or polymers, such as PAA,3.3.4Ligands interaction can be categorized into ligands layer‐by‐layer assembly and ligands attraction. This approach would bring a hydrophilic shell coating on the OA‐capped UCNPs for conversion of hydrophobic UCNPs into hydrophilic ones.2 groups could attach to biotin for further fluorescence resonant energy transfer. Li and co‐workers developed water dispersible UCNPs by self‐assembly interaction between the host molecule alpha‐cyclodextrin (α‐CD) and the guest molecules OA , PSS = poly(styrene sulfonate)).A Figure e.119 ThiA Figure f.23 In tAbove all, the modifications of converting hydrophobic UCNPs into hydrophilic ones have merits and drawbacks. Some properties of UCNPs, including morphology, monodispersity, and UCL, may be affected more or less. The perfect modifications with the control of particle size and homogeneity and the preserved UCL need to be developed.44@NaYF4 of core or some other substances whose lattice is similar to host matrices of cores, like α‐NaYF4@CaF2. As Section For the upconversion nanostructures, it is important to improve their UCL efficiency. So far, numerous efforts have devoted to improving UCL efficiency of upconversion nanostructures, such as seeking optimal matrices, tuning the doping concentration, constructing core–shell nanostructures, and so on. Core–shell nanostructures play an important role in upconversion nanomaterials, which can not only improve the optical properties but also combine discrete functional units together. Core–shell structures are generally divided into two classes: epitaxial core–shell nanostructures, and nonepitaxial ones. Shell of the epitaxial core–shell nanostructures must have low lattice mismatch with the core, which could decrease surface defects and improve UCL efficiency. The shell layer could be host matrx, like NaYF4:Yb,Tm Nanocrystals through thermal decomposition.4 nanoparticles via heating‐up method was reported by Liu et al.Heating‐up method is a commonly used synthetic method to obtain core–shell structures through seed‐mediated epitaxial growth.Figure4:Yb,Er/NaYF4 UCNPs was achieved by successive layer‐by‐layer method. However, quantum yield was 0.47 ± 0.05% for the heterogeneous doping NaGdF4:Yb,Er/NaYF4 UCNPs. The upconversion emission of NaGdF4:Yb,Tm/NaGdF4:A  was also improved 20%–30% by successive layer‐by‐layer method. Chen's group reported the synthesis of LiLuF4:Ln3+ core/shell UCNPs through successive layer‐by‐layer method and high absolute upconversion quantum yields were achieved 5.0% and 7.6% for LiLuF4:Er and LiLuF4:Tm core–shell structures, respectively.Heating‐up method has a few shortcomings, such as volatile solvent removal, prolonged heating and the centrifugation and washing of core nanoparticles, as such hot‐injection technique was developed to obtain upconversion core–shell nanostructures.4 NCs via thermal decomposition. Then SNCs as shell precursors were injected into a hot solution of core NCs (defocusing) and dissolved and deposited on the larger core NCs (self‐focusing). Therefore, core–shell nanostructures would be obtained. If the cycle process of defocusing and self‐focusing was repeated, multilayer core–shell nanostructures could form  are dissolved and deposited on the surface of nanocrystal cores with larger size due to their high surface energy. Veggel and co‐workers synthesized core–shell nanostructures through this method.m Figure e–i. The 4:Yb,Er@NaGdF4 multilayer core–shell UCNPs were synthesized for the first time . The size of NaYF4:Yb,Er core upconversion nanocrystals was about 16.3 nm. Diameter of NaYF4:Yb,Er@NaGdF4 core–shell nanocrystals with 4‐layer NaGdF4 shell increased to ≈30 nm. With the shell growth, the uponversion optical property was optimized and improved under the same excitation power. Doping luminescent centers in shells, the core–shell nanostructures could realize up‐down conversion dual‐mode luminescence.The prior three methods are generally used to prepare hydrophobic core–shell upconversion nanostructures. Our group synthesized hydrophilic lanthanide‐doped core–shell UCNPs by microwave assisted polyol processes.2 and TiO2 are the most common inorganic shell materials. The reverse microemulsion method is suitable to coat SiO2 shell on the oleate or OM‐capped UCNPs. Numerous functional groups can be encapsulated in SiO2 shells or be connected to the surface of SiO2 shells for further applications.N‐hydroxysuccinimide ester groups.2) has also attracted massive attention owing to their large surface area and tunable pore size. The nanocomposites combining mSiO2 and UCNPs are very promising for biological imaging, drug delivery PDT and chemical detection. For example, Shi and Bu synthesized azobenzene‐modified UCNP@mSiO2, and load anticancer drug doxorubicin (DOX) into mesopores silica.2 shell on the hydrophobic UCNPs via reverse microemulsion method, and then further coated another dense SiO2 shell via water‐phase regrowth method. Hot water etching, with PVP as protecting agents, is conducted to obtain upconversion core/hollow porous silica shell nanostructures (UCSNs). UCSNs are very conducive in terms of drug delivery. TiO2 shell is also coated on the surface of UCNPs for some particular applications, such as photocatalysis2 layer on UCNPs after modification with a surfactant layer.4:Yb,Tm@TiO2 nanocomposites showed obvious photocatalytic activity under NIR light. Lin coated TiO2 on UCNPs for NIR light triggered PDT and Zhao et al. designed novel UCNP@SiO2@TiO2 nanocomposites for high‐performance dye sensitized solar cells.4:Yb,Tm hybrid nanostructures via a solution method.4:Yb,Er@Ag core/shell nanocomposites and demonstrated that they were a promising upconversion imaging and PTT agent.The shells of nonepitaxial core–shell structures, whose crystal lattices mismatch with those of cores, are usually inorganic materials or noble metals. SiO5In recent years, development of rare earth doped upconversion nanomaterials for various applications ranging from biomedical to electro‐optic field, especially bioapplications has been a research focus, in addition to the study of their light emission mechanism, synthesis routes and optical properties. First of all, the safety of upconversion nanostructures is our common concern. Not only for bioimaging and therapy, some detections also require upconversion nanostructures with biocompatibility and low biotoxicity. Therefore, at the beginning of this chapter, the biosafety of upconversion nanostructures is identified as an issue we need to consider, although it has been reviewed by Capobianco et al. and Li et al.5.1As previously mentioned, UCNPs with large anti‐Stokes shift, weak background interference, and no photobleaching are suitable to detect some target species, such as pH,5.1.14:20%Yb,1.6%Er,0.4%Tm UCNPs for detection and bioimaging of cyanide anion.− anions can change the absorption band of Ir1. When adding CN− anions in the LRET system, the energy transfer was blocked and the upconversion emission was recovered. By comparing the rations of UCL in the absence and presence of CN− anions, low detection limit of 0.18 μM CN− anions could be obtained. They also designed a LRET nanoprobe combining hCy7 (an organic dye) and UCNPs  to detect methylmercury (MeHg+), which would cause language and memory barriers , 540 nm (green), and 650 nm (red), respectively. The hCy7‐UCNPs could emit green and NIR emission in the absence of MeHg+. When meeting MeHg+, the hCy7 was converted into hCy7' that exhibits NIR absorption band (centered at 800 nm) rather than red absorption band (centered at 660 nm). Through detecting the ratiometric upconversion emission at 660 to 800 nm, MeHg+ could be monitored. Vetrone et al. developed a nanothermometer based on poly(N‐isopropylacrylamide) (pNIPAM) modified NaGdF4:Yb,Er UCNPs which combined an organic dye (FluoProbe532A) to detect the temperature at a subcellular level.2+,2+,2,2S,3+,2+,Organic dyes like chromophoric Ru(II) complex (N719) and Ir(III) complex (Ir‐9), which have an absorption band matched well with the upconversion emission, could play as energy acceptor for upconversion turn‐on probe.rs Figure10a.1635.1.24:Yb,Tm@NaYF4 UCNPs as energy donor and MnO2 nanosheet as energy acceptor. MnO2 nanosheet was deposited on the surface of UCNPs by reduction of potassium permanganate solution.2 nanosheet modified UCNPs was quenched due to the formation of LRET between Tm3+ ions and MnO2. But facing GSH, the MnO2 nanosheet was reduced to Mn2+ ions. MnO2‐induced UCL quenching effect was inhibited, and the LRET was terminated, thereby UCL was recovered. The recovered upconversion emission was a function of the concentration of GSH. Furthermore, they monitored the GSH levels in living cells. Liu's group reported a LERT probe for biothiols and few‐atom silver nanoclusters (Ag NCs) as energy acceptor of UCNPs, which was presented in Figure If the absorption bands of inorganic nanoparticles are match with the upconversion emission bands of UCNPs, the distance is suffciently close as well, the LRET process would occur.4 UCNPs for the detection of β‐hCG (an important disease marker)  Figure c.41 Firs5.23+ have two emission bands centered at 540 and 650 nm, separately. So single‐band red upconversion light (650 nm) is a purse for bioimaging.3+‐doped UCNPs with an upconversion emission peak centered at 800 nm under 980 nm, in which both excitation and emission bands are located in the “optical window,” provide a high penetration depth. Prasad et al. demonstrated high‐contrast UCL imaging of deep tissues (UCL was imaged through 3.2 cm pork tissue) based on α‐NaYbF4:Yb,Tm@CaF2 core−shell nanoparticles.3+ as sensitizer was introduced into upconversion nanostructures. Yan's group demonstrated that using shorter wavelength excitation band centered 808 nm rather than 980 nm could greatly minimize the tissue overheating effect.4:Yb,Tm UCNPs and they fed C.elegans with the mixture of B‐growth media and NaYF4:Yb,Tm UCNPs.4 UCNPs for UCL bioimaging in a small black mouse.FigureBioimaging technology has attracted much attention given its ability of visualization. Fluorescence imaging, MRI, and CT are the most common bioimaging techniques. First, we talk about the fluorescent bioimaging based UCNPs. Compared to the traditional fluorescent probes, such as semiconductor quantum dots or organic dyes, UCNPs with some advantages, such as weak background autofluorescence, deep tissue penetration, low photobleaching, and large anti‐Stokes shifts, are good fluorescence agent for in vitro or in vivo imaging. Autofluorescence can be eliminated because bio‐samples do not have upconversion emission under NIR excitation. For bioimaging, it is optimal that excitation and emission wavelengths are in the NIR spectral range (700–1100 nm) and red region (600–700 nm) which is termed “optical window” of the biological tissues. The UCNPs containing Er3+ ions in UCNPs are of importance for some certain imaging techniques. This kind of UCNPs is an excellent multimodal imaging agent. Gd3+ ions with seven unpaired electrons in the ground state show large paramagnetic moment, which is commonly used as T1‐weighted MRI contrast agent. Gd3+‐based host materials, such as NaGdF4,4,4,53+ ions could exist as host matrix or just as a shell coated on core nanoparticles.3+ ions can also be incorporated into the host matrix as dopant. Li and co‐workers reported NaYbF4:Gd,Yb,Er nanophosphors with suitable magnetic properties (r1 = 0.41 s−1 Mm−1) for both MRI and upconversion imaging of Kunming mice.3+ ions by modification using gadopentetic acid (Gd‐DTPA). For example, Li's group obtained a core–shell UCNP‐based nanostructure with NaLuF4:Yb3+, Tm3+ as core SiO2 as shell and Gd complex of Gd‐DTPA as capping surfactant. These nanostructures had excellent UCL, high r1 value of 6.35 s−1 mM−1, and strong X‐ray attenuation, which display relatively low biotoxicity and are for upconversion/MRI/CT tri‐modal bioimaging.3+ or Co3+ ions, also can combine UCNPs as T2‐weighted MRI contrast agent.4:Yb,Tm@FexOy nanostructures which exhibit excellent UCL of NIR to NIR and a saturation magnetization of ≈12 emu g−1.2‐weighted MRI/upconversion bio‐imaging in vivo of the lymphatic system had been done. The design might be of great help to clinical lymph nodal study and diagnosis.In order to achieve the temporary and spatial sensitivity and accuracy of diagnosis, multimodal bioimaging was developed. Multimodal bioimaging based on UCNPs, which combines UCL imaging with other imaging technologies, like MRI and CT, could make up for their own shortcomings and tap their respective advantages. So the multimodal bioimaging has great contribution to further clinical treatment. In addition to UCL, some specific Lnx18F , it has been the most commonly used radionuclide for PET bioimaging. PET bioimaging, which could produce 3D imaging, is used for biodistribution investigation. Li et al. fabricated 18F labeled magnetic‐upconversion nanophosphors for in vivo upconversion/MRI/PET bioimaging.18F, 153Sm with a half‐time of 46.3 h is commonly incorporated into upconversion nanostructures as radionuclide for SPECT imaging. Li's group reported the synthesis of NaLuF4:153Sm,Yb,Tm nanoparticles. Nanoparticles were utilized for in vivo SPECT imaging with high sensitivity and the ex vivo biodistribution of nanoparticles was easily qualified by this method.The lanthanides, especially Lu, with higher atomic numbers than iodine show excellent X‐ray attenuation ability, which makes them an optimal option as CT contrast agent. Obviously, Au,4:Yb,Tm as core and 4 nm of 153Sm3+‐doped NaGdF4 as shell. In this nanostructure, Yb and Tm, Lu, Gd, and Sm153 were responsible for UCL, CT, MRI, and SPECT imaging, respectively. The combination of those four imaging modalities can provide detailed information, which shows its value in tumor angiogenesis imaging.4:Tm@NaYF4 UCNPs. The two active imaging components of PoP and UCNPs could be used in no less than six different imaging techniques, including fluorescence (FL), photoacoustic, Cerenkov luminescence (CL), PET, CT and UCL imaging , with a particle diameter of sub‐50 nm.2 layer via a water‐in‐oil reverse microemulsion technique. Furthermore, in order to improve the efficiency of loading photosensitizers, Zhang's group designed mesoporous silica coated UCNPs and incorporated ZnPc (photosensitizer) into the mesoporous silica shell. Under NIR 980 nm irradiation, the UCNPs converted NIR light to visible light which could further activate ZnPc to produce reactive singlet oxygen for killing cancer cells.−2 of 978 nm light for 45 min. The photosensitizer can also attach to the surface of UCNPs via covalent bonding.4:Yb,Er@CaF2@SiO2‐PS nanostructure for PDT in vitro, in which, photosensitizer (PS) was covalently grafted to mesoporous channels of mesoporous silica.1O2 production efficiency, the 660 nm upconversion emission of NaYF4:Yb,Er UCNPs was enhanced via doping 25% Yb3+ and the efficiency of energy transfer was improved because the distance of energy transfer was shortened via covalent assemblage. Liver tumor inhibitory ratio was ≈80.1% under 980 nm irradiation duration 15 min  has been designed by Shi's group.Compared to surgery, chemotherapy and radiotherapy, PDT is a noninvasive cancer treatment. PDT is involved, in which PDT drugs (photosensitizers) are activated by UV, visible light or NIR to generate cytotoxic reactive oxygen species (ROS) for killing the target cells. The organic molecules, such as methylene blue (MB), zinc(II) phthalocyanine (ZnPc), Chlorine6 (Ce6) and so on, and semiconductor nanomaterials are the most common photosensitizers for PDT. Because UV and visible light with low penetration ability limit the development of PDT, utilizing UV and visible light converted by UCNPs from NIR can overcome the limitation of low penetration ability.in Figure13a,b. 5.3.22, mesoporous SiO2 or polymer coated UCNPs with porous or hollow structure are good drug and siRNA carrier for chemotherapy.5:Yb/Tm UCNPs as drug carrier.2@DOX‐ZnO nanostructure.2. ZnO as a gatekeeper blocked the mesopores of SiO2 to the noneffective leakage of drugs. However, ZnO could be dissolved in acidic solution. So, drugs could be effectively released in the location of the tumor with very low side effects. The multimodality bioimaging including UCL, CT and MRI provided detailed and exact information for drug release. They demonstrated that higher amounts of HeLa cell death caused by UCNP@mSiO2@DOX‐ZnO nanostructures than DOX. Phototrigger‐induced chemotherapy based on UCNPs utilizing the visible or ultraviolet light converted by UCNPs from NIR to control drug release, which means that UCNPs are a switch of drug release. For example, Shi's group reported the synthesis of hollow mesoporous silica coated NaYF4:Yb/Tm@NaGdF4 (UCNP@hmSiO2) nanostructures.2  as drug carrier.Although chemotherapy is invasive, it is still an effective method for disease treatment. The chemotherapy based on UCNPs includes two aspects: imaging‐guided chemotherapy and phototrigger‐induced chemotherapy. Imaging‐guided chemotherapy could indirectly observe and monitor the extent of drug release by using the UCL of UCNPs. SiO2 Figure c,d. The 5.3.33O4 nanoparticles, and Au nanoparticles via layer‐by‐layer self‐assembly to be used for multifunctional bioimaging and PTT.xS were also used as photothermal agents for tumor therapy. Zhang et al. reported the synthesis of GO covalently grafted UCNPs and then loading ZnPc on GO, which could act as a theranostic platform for UCL bioimaging and PTT/PDT of cancer.2O3:Yb/Er−CuxS multifunctional nanostructures. DOX could be loaded into the nanostructures. Simultaneous bioimaging and chemotherapy/PTT could be achieved in this nanostructure, where CuxS acted as the photothermal functional section, DOX acted as the chemotherapeutic drugs and UCL acted as the part of bioimaging.  nanostructures, they utilized Au25(SR)18 clusters with size of 2.5 nm to produce PDT and PTT effect by receiving energy from the UCNPs and the pH/temperature‐responsive P(NIPAm‐MAA) could control DOX release. An in vivo anticancer therapy has been conducted, which demonstrated that this design could markedly improve the therapeutic efficacy.In many cases, these three treatments are used together.5.42 is a semiconductor, which is frequently used for solar energy harvesting. However, TiO2 with a high band gap (3.2 eV) can only absorb UV light and most of the solar energy is wasted. Therefore, incorporating upconversion materials and TiO2 into the system of solar energy harvesting, where TiO2 absorbs the visible or ultraviolet light converted by upconversion material from NIR, can increase the utilization of solar energy.t‐BOC‐coated α‐NaYF4:Yb/Er and α‐NaYF4:Yb/Tm UCNPs.4 upconversion microrods, which could act as multicolor barcoding for anticounterfeiting.4:Yb/Tm UCNPs to develop a new temporal‐domain approach to multiplexing.4:Yb,Er,Gd UCNPs and demonstrated that the UCNPs could be in 3D displays.In addition to the above applications demonstrated, upconversion nanostructures could also be used for solar energy harvesting,6In this review, we reviewed recent advances in upconversion nanostructures in terms of mechanism, design and synthesis, and some applications. We also provided a number of typical examples to demonstrate the various aspects of upconversion nanostructures in detail. Though, the development of upconversion nanostructures grows substantially in recent years, critical challenges remain, which impose great barriers to further optimize the upconversion nanostructures for commercialization. First, controllable preparation of upconversion nanostructures is highly desired, which includes both morphology and composition, and surface properties and the ability for chemical modifications. As one kind of optical materials, the main issue of upconversion nanostructures is that the fluorescence efficiency of the upconversion is far less sufficient, which largely limits their applications. One urgent task is to generate upconversion nanostructures with high fluorescence quantum yield. Obviously, upconversion is a nonlinear optical phenomenon, moreover, quantum yield is not applicable for characterizing their fluorescence efficiency. Therefore, it is required to establish a new and sound pathway to evaluate upconversion fluorescence efficiency. In addition to fluorescence efficiency, the color of upconversion emission, such as single‐band and full‐color emission, should be a research focus. On the other hand, the dispersibility, chemical stability, biocompatibility, and long‐term toxicity are still issues that should be well addressed in the development process. Last but not the least, the upconversion nanostructures should be combined with other functional materials to create new and promising structures and properties.


The purpose of the study was to establish a mathematical model for correlating the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) with the total energy of Holmium laser lithotripsy.In this study, from March 2013 to February 2014, 180 patients with single urinary calculus were examined using ultrasonography and NCHCT before Holmium laser lithotripsy. The calculus location and size, acoustic shadowing (AS) level, twinkling artifact intensity (TAI), and CT value were all documented. The total energy of lithotripsy (TEL) and the calculus composition were also recorded postoperatively. Data were analyzed using Spearman's rank correlation coefficient, with the SPSS 17.0 software package. Multiple linear regression was also used for further statistical analysis.r = –0.565, P < 0.001), and there was a strong correlation between the calculus size and the TEL . The difference in the TEL between the calculi with and without AS was highly significant . The CT value of the calculi was significantly correlated with the TEL . A correlation between the TAI and TEL was also observed . Multiple linear regression analysis revealed that the location, size, and TAI of the calculi were related to the TEL, and the location and size were statistically significant predictors .A significant difference in the TEL was observed between renal calculi and ureteral calculi (A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. Thus, the Holmium laser has become the primary choice to fragment calculi.After being investigated and demonstrated to be safe and effective in 1960, a variety of laser techniques have been used in urological procedures. Because of its precision and strong decomposing power, the Holmium laser has become one of the most popular tools in urological procedures, including lithotripsy. One major advantage of the Holmium laser is that it can fragment urinary calculi efficiently, regardless of size, hardness, chemical composition, and physical consistency; accordingly, a high stone-free rate can be achieved. However, Dushinski and Lingeman have proposed that the mechanism of fragmentation should be explained by the photothermal effect on urinary calculi. Chan et al have also reported that the Holmium laser lithotripsy mechanism is primarily a photothermal effect through which the Holmium laser increases the temperature of the irradiated area, causing a chemical breakdown of the calculi and weakening the physical strength of the irradiated area, whereas interstitial water and vapor expansion merely facilitate the drainage of the fragments within the area.The mechanism of Holmium laser lithotripsy has been investigated for many years. Many studies have suggested that it might result from the photoacoustic effect generated by pulsed lasers. When pulsed lasers are fired, cavitation bubbles are produced at the water–calculus interface. Shock waves are produced by continuous rebound, and the bursting of the bubbles is transmitted to the calculus and can cause calculus fragmentation. have reported that the fragmentation rate does not increase when the frequency increases and that the pulse energy is constant. Chawla et al have shown that the fragmentation rate increases with the pulse energy, but it does not consistently increase with the pulse frequency. It has been reported that in cases of high density and fixed calculi, a higher pulse energy, and shorter pulse duration will lead to increased fragmentation efficacy. In an in vitro study, Peter and Olivier observed that a low frequency-high pulse energy setting is more efficient than a high frequency-low pulse energy setting at the same power levels; they also found linear correlations between the pulse energy and fragmentation size, as well as the fissure width and the depth.Several parameters that affect the fragmentation efficiency of Holmium laser lithotripsy have been assessed, including the pulse energy, pulse duration, frequency, and power setting. Sea et alDifferent energy is needed to fragment calculi with different characteristics. Unguided use of energy in laser lithotripsy has some disadvantages. Insufficient energy cannot fragment calculi effectively, whereas overused energy may lead to a higher incidence rate of complications and overconsumption. Preoperative evaluation of the total energy of Holmium laser lithotripsy can predict the operation difficulty, estimate the operation time, and make emergency program to high-risk patient in advance. Therefore, guiding the use of energy plays a key role in Holmium laser lithotripsy, and it may improve the safety and efficiency of laser lithotripsy and increase the cost-effectiveness of its operation.First introduced in the early 1990s, the mechanism of Holmium laser lithotripsy and the parameters for fragmentation efficiency have been frequently investigated. However, no in vivo studies have reported a correlation between the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) and the total energy of lithotripsy (TEL), particularly the potential role of ultrasonography in the assessment of TEL, such as twinkling artifact and acoustic shadowing (AS). The purpose of this study was to establish a mathematical model to correlate the combination of ultrasonography and NCHCT with the total energy of Holmium laser lithotripsy.22.1This study proposal was approved by the institutional review board. A total of 180 patients with a single renal or ureteral calculus were enrolled in the study from March 2013 to February 2014. All patients provided written informed consent prior to study enrollment.2.2All examinations were performed by a single ultrasonologist (with 7 years of experience) using a Philips iU22 ultrasound scanner  using a C5–1 curvilinear array probe. All patients underwent ultrasonography the day before lithotripsy. No special preparation was required for the patients with kidney or proximal/middle ureter calculi. Patients with calculi in the distal ureter were requested to moderately fill their bladders. Scanning started with gray-scale imaging to measure the calculus size and to confirm the calculus location and the presence or absence of AS  by calculating the number of color pixels in each artifact. In Adobe Photoshop CS5, the background gray pixels were deleted, the background was masked in black, and the images containing only color pixels from twinkling were saved. Image J, an image editing application for medical image processing, was then used to select a region of interest that included all color pixels in the artifact and some background pixels and to draw a histogram of the region. The number of color pixels in the artifact was calculated by subtracting the number of background pixels from the number of all pixels in the region. All data were obtained from measuring 5 different images, and the average of the 5 measurements was used as the final result.Philips DICOM Viewer R2.5L1-SP3 software was used for data processing. Five static images were randomly chosen from each cine loop replay for the statistical analysis. In gray-scale imaging, the calculus location was confirmed and classified as renal or ureteral. The maximum calculus size was measured and classified into 4 grades: smaller than 10 mm was grade 1; between 10 and 20 mm was grade 2; between 20 and 30 mm was grade 3; and larger than 30 mm was grade 4. AS was assessed and classified into 2 levels: calculus without AS was level 0 and calculus with AS was level 1. There are no uniform or strict criteria to evaluate the intensity of twinkling artifacts, which makes the evaluation subjective and operator-dependent. Referring to Gao et al2.32 regions of interest on each calculus. The average of the 3 measurements was used as the final CT value for each specific calculus. The CT values of the calculi were classified into 4 grades: below 400 Hu was grade 1, between 400 and 800 Hu was grade 2, between 800 and 1200 Hu was grade 3, and over 1200 Hu was grade 4.Immediately after undergoing ultrasonography, all patients were examined using noncontrast helical computerized tomography (NCHCT) with a Philips Brilliance iCT 256 scanner . The CT value of each calculus was generated, as follows: Hounsfield units were measured for 3 different 0.02 cm2.4All lithotripsies were performed by 2 surgical urologists (1 with 5 years of experience and the other with 7 years of experience) using a dual-wavelength Holmium laser therapeutic machine . The following laser settings were used: 200 μm laser fiber at output energy of 0.5/0.6 J and a pulse repetition rate of 20/35 Hz. During lithotripsy, fragments were targeted to obtain the smallest size possible. Using the laser fiber as a frame of reference, all fragments >4 mm were removed with a basket catheter. The total energy of each completed laser lithotripsy was recorded. The criterion for a completed laser lithotripsy was no residual fragment left, or, if any, the fragment size had to be ≤4 mm, and spontaneous excretion of the fragment was expected. The efficacy of lithotripsy was evaluated 1 to 2 days after the procedure through ultrasonography and plain film of the kidney–ureter–bladder.2.5After the completion of each laser lithotripsy, 1 fragment was randomly chosen for composition analysis through automatic infrared spectrophotometry with the Medical Automated FTIR Human Calculi Analysis System .2.6P-value of < 0.05 was considered to be statistically significant.Statistical analyses were performed with the SPSS 17.0 software package. Spearman's rank correlation analysis was used to assess the correlations between the TEL and the calculus location, size, AS level, TAI, and CT value, as well as the calculus composition. Multiple linear regression was performed to formulate a mathematical model to estimate the TEL. A 3Of the 180 patients who participated in the study from March 2013 to February 2014, 5 patients were excluded from the final analyses because their lithotripsies were evaluated as failed: in 2 cases, the renal calculi in the subrenal calyx were too secluded to be reached and fragmented effectively, and 3 patients had residual fragments >4 mm after the procedure. Therefore, valid data for this study were collected from 175 patients . Fifty-one patients had renal calculi, and 124 patients had ureteral calculi. The calculi had an average size of 14.7 ± 6.1 mm (6–41 mm), and 46 of them were grade 1, 101 were grade 2, 22 were grade 3, and 6 were grade 4. In terms of AS, 16 calculi were level 0, and 159 were level 1. In terms of CT values, 7 calculi were grade 1, 47 were grade 2, 72 were grade 3, and 49 were grade 4 , and the TEL for renal calculi was much higher than that required for ureteral calculi. Statistical analysis showed a strong correlation between the size of the calculus and the TEL , and larger calculi required a higher TEL. There was also a significant difference in the TEL between different levels of AS , and calculi with AS required more energy for fragmentation. TAI was strongly correlated with TEL , and a higher TEL was required for calculi with a greater TAI. A correlation between the CT value of the calculus and the TEL was also observed , and the energy required for lithotripsy was proportional to the CT value of the calculus. There were no statistically significant differences between the TEL values for the different calculi compositions . The equation shows that more energy is needed for lithotripsy in patients with larger calculi, renal calculi, or calculi with greater TAI.To further eliminate confounding factors and to estimate the TEL in patients with different characteristics, a multiple linear regression model was built with the following parameters: calculus location , AS level , size of calculus, TAI and CT value Table . After c4A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established in our study, and it may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. By providing an initial estimate of the total energy required in Holmium laser lithotripsy, the combination of ultrasonography and NCHCT is likely to improve the safety and efficiency of laser lithotripsy, as well as the cost-effectiveness of the procedure, by avoiding overconsumption of pulse energy during the operation. analyzed the differences in cumulative Holmium laser energy in different locations. They concluded that renal calculi required more energy than ureteral calculi. We reached a similar conclusion: the required TEL differed significantly between the kidney and the ureter. Although the exact mechanism is still not clear, 1 conceivable explanation for the phenomenon is that hydronephrosis or hydrocalycosis around the renal calculus makes it more mobilizable than ureteral calculi, and the total amount of contact between the calculus and the tip of the laser fiber is decreased. Therefore, more pulses are likely to be fired inefficiently, and more energy may be wasted during the fragmentation of renal calculi.In a previous retrospective study, Molina et al have performed a systematic review of Holmium laser use for calculus lithotripsy. They reported that the required cumulative energy of pulses increased with the calculus size and the mass. This finding is consistent with our finding that the correlation between the calculus size and the TEL is statistically significant.The characteristics of calculi play an important part in the laser lithotripsy procedure. In terms of size, a larger calculus requires more energy for fragmentation. Blomley et al observed that it was much denser and harder than plaster of Paris, and it was more difficult to fragment in SWL compared to plaster of Paris. In an in vitro study, Wezel et al reported that at all tested settings, the fragmentation efficiency was remarkably higher for soft calculi than for hard calculi. Kronenberg and Traxer compared the fragmentation efficiency among artificial calculi constructed from different materials. They found that the ablation rate was higher in calculi made of plaster of Paris than those made from BegoStone Plus. They also concluded that a hard calculus material was more difficult to ablate than a soft calculus material at the same laser lithotripter settings. According to these studies, it is reasonable to conclude that the energy required for calculus fragmentation through laser lithotripsy is proportional to the density of the calculus.Note that for the first time, our study demonstrated a significant difference between the TEL at different AS levels. This phenomenon has 2 explanations. First, acoustic impedance plays an important role in the intensity of AS. A larger difference in the acoustic impedance between materials will lead to a stronger reflection at the interface and a greater AS. The higher the calculus density, the larger its acoustic impedance and the greater its AS. Second, a higher density calculus requires more energy from laser lithotripsy for fragmentation. After investigating the characteristics of BegoStone, Liu and Zhong found a significant correlation between the twinkling artifact grade and the calculus size and deduced that a higher artifact grade should be expected for larger calculi. Considering that both TAI and TEL are correlated with calculus size, a correlation between TAI and TEL should also be reasonably expected.We also noticed a significant correlation between TAI and TEL that has not been previously reported. However, due to many potential influential factors from the twinkling artifact, we could not clearly define the correlation. One possible explanation is the correlation between the calculus size and TAI. In an in vitro study, Louvet divided patients into low and high attenuation coefficient groups based on the preoperative median absolute CT values for average calculus density, and they found the fragmentation efficiency was significantly higher in the low attenuation coefficient group compared to the high group. Molina et al have also reported that calculus size and hardness (measured by NCHCT) were important predictors for cumulative laser energy.In alignment with previous studies, a significant correlation between TEL and CT values of the calculus was also observed in our study. In a retrospective study, Ito et al observed that when the laser fiber and the energy level remained unchanged, the fragmentation efficiency of the Holmium laser varied among different calculus compositions. They attributed this phenomenon to the different temperature thresholds of different compositions. Molina et al reported that all calcium calculi require less energy compared with uric acid calculi in a univariate analysis. However, we failed to find a statistically significant difference in the TEL among different compositions of calculi. Although the reason for this observation is not clear, the possible explanations are as follows. First, only 1 fragment was collected per calculus for the composition analysis, which might not accurately represent the calculus as a whole. Second, although we could determine the composition of a calculus, we were unable to define the proportion of each component of the calculus because of the functional limit of the calculi analysis system that we used. Therefore, the statistical outcome of the correlation between the TEL and the calculus composition could be affected.The role that calculus composition plays in laser lithotripsy efficiency remains less defined. In an in vitro study, Teichman et alThis study has several limitations. First, a patient's BMI might affect the TAI because of the change of depth to the calculus, which we failed to consider in our study. Second, we could not pre-set and optimize the machine settings for evaluating the TAI more sensitively and specifically. In addition, we performed the study using equipment from only 1 manufacturer, and it is possible that different results could be obtained using different machines. The factors above may have caused deviations; thus, further investigation is needed.5A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus.This manuscript was edited for English language by American Journal Experts (AJE). The authors are particularly grateful to Yuanyuan Liu for her assistance with the statistical analysis. They also thank Mingjie Li and Xiangtao Wang for their technical advice about the Holmium laser lithotripsy.


A cyber-physical attack in the industrial Internet of Things can cause severe damage to physical system. In this paper, we focus on the command disaggregation attack, wherein attackers modify disaggregated commands by intruding command aggregators like programmable logic controllers, and then maliciously manipulate the physical process. It is necessary to investigate these attacks, analyze their impact on the physical process, and seek effective detection mechanisms. We depict two different types of command disaggregation attack modes: (1) the command sequence is disordered and (2) disaggregated sub-commands are allocated to wrong actuators. We describe three attack models to implement these modes with going undetected by existing detection methods. A novel and effective framework is provided to detect command disaggregation attacks. The framework utilizes the correlations among two-tier command sequences, including commands from the output of central controller and sub-commands from the input of actuators, to detect attacks before disruptions occur. We have designed components of the framework and explain how to mine and use these correlations to detect attacks. We present two case studies to validate different levels of impact from various attack models and the effectiveness of the detection framework. Finally, we discuss how to enhance the detection framework. A large-scale industrial Internet of Things (IIoT)  is deploHowever, with the wide openness of communication infrastructure which is used to improve efficiency, reliability, and sustainability of services  such as command disaggregation attack. The attack may result in disruptions of physical process. In this paper, we focus on the process of launching the command disaggregation attack and its detection method. Previous studies, such as [When commands reach sub-controllers, malicious entities remotely attack sub-controllers to generate wrong executed commands called  such as , introdu such as  can not Driven by the above considerations, we depict two different command disaggregation attack modes: (1) false command sequence; and (2) wrong command allocation. The former refers to the situation that attackers delay the disaggregation of some commands to disorder its logic, thereby resulting in disruptions of physical process; the latter refers to the situation that disaggregated commands are issued to other than the expected or planned actuators, causing the failure of control objective or physical damages. We also describe three attack models to implement command disaggregation attacks in two kinds of modes. When attackers manipulate the disaggregation of commands, they simultaneously inject false feedback data to confuse security detectors to ensure that the attack goes undetected. To deal with the threats above, we provide a detection framework based on correlations among two-tier command sequences, which collects two-tier commands including those issued from the central controller and the sub-commands executed by actuators. We design components of the detection framework and explain the method of mining correlations among commands and using the correlations to detect attacks. Finally, two cases are studied to demonstrate the different levels of impact from various attack models and the effectiveness of proposed detection framework.The rest of the paper is organized as follows. We introduce the related work and summarize our contributions in In this section, we first survey the state of the art of attacks that cause disruptions of physical process. Then, we review the works about attack detection.Three methods, namely, false command injection, false data injection, and time-delay attacks, can be used to disrupt the physical system. In ,16,17, aAlthough many detection methods have been proposed to detect anomalies caused by attacks, they are not effective to identify false command disaggregation attacks. For example, in , some co(i)We introduce two kinds of command disaggregation attack modes, namely, false command sequence and wrong command allocation.(ii)We describe three attack models to implement command disaggregation attacks in two modes. Attacks based on the three models can not be detected by the existing detection methods.(iii)We provide an effective detection framework based on correlations among two-tier command sequences. Detecting command disaggregation attacks with false feedback data injection is still an unexplored topic and our method is the first to effectively identify command disaggregation attacks before a disruption occurs.After summarizing the related work in attack and in detection, we clarify our contributions asIn this section, we first introduce a simplified model of IIoT control system. Second, we unveil two kinds of command disaggregation attack modes, including wrong command allocation and false command sequence, wherein we depict attack models.t. After multi-tier sub-controllers disaggregate these commands, sub-commands kth kind of command. t.ith sensor. ith sensor at time instant l. jth kind of state and k, k, and under normal circumstances, k.kth actuator. N means the number of actuators. An actuator only executes a sub-command in unit time, and a sub-controller only disaggregates one command from the upper-tier sub-controller during once outflow of the central controller. ith actuator. The system state at time t, t when current commands are issued and the time of its last outflow.AC(t−dt) , which cS. A disruption occurs when the system state is The system model is described using six-tuple:The model is based on the assumption that the information and physical systems have not yet been attacked, and all observed states and commands can be regarded as a representation of normal system behavior. From the above process, we can know that the accurate feedback data and commands are critical for the normal running of systems. When security mechanisms such as authentication  and crypWe also use To describe the attack models, we define two operations about sets, “−” and “+”. For any two sets In this section, we will disclose two kinds of attack modes and describe the corresponding attack models in details. During the implementation of the attack models, attackers usually inject false data into sensors or feed back false data to detectors to hide signs of attacks.When a command Next, we depict the attack models that implement the above two situations.(1) Attack model based on wrong command inner allocation (WCIA)• Information collectionAttackers first find a set of issued commands Equation .(4)ci∈C• False data injectionith sub-controllers, they also need to inject the same false feedback data to manipulate the corresponding (i + 1)th tier sub-controllers. The disaggregation of commands is influenced and the executed sub-commands are changed from When attackers discover that the current state is (2) Attack model based on wrong command outer allocation (WCOA)• Information collectionAttackers first find a set of issued commands Equation .(5)ci∈C• Command modificationWe use • False data injectionWhen disaggregated commands have been modified, attackers need to inject bad feedback data to the next-tier sub-controllers. Bad data informs the next-tier sub-controllers that the current state is When the sub-commands Under normal situations, if As shown in • Information collectionAttackers first find command sequence Equation .(6)ci∈C• Time-delay attackAttackers manipulate the sub-controllers to delay the disaggregation of • False data injectionCommands WCIA, WCOA, and FCS change executed commands during the process of disaggregation, meanwhile, inject false data to confuse detectors. The existing detection methods in The detection framework is in charge of collecting command sequences, mining correlations, and identifying anomalies. As shown in • Command Collectorith actuator. Data is then transferred to two other components, namely, correlation analyzer and exception detector.Command collector is responsible for collecting commands from IIoTs. Command collector gets commands from two sites, as shown in • Correlation AnalyzerCorrelation analyzer tries to discover whether correlations exist among commands and sub-commands. Correlation analyzer mines correlations by using the recently collected history data. Once in a while the analyzer will update the correlations in correlation database. We will discuss which correlations and how they are mined in the next subsection.• Correlation DatabaseCorrelation information is stored in the correlation database. Correlation information includes discovered correlations and the time and number of occurrences of commands and sub-commands. Correlation database provides the corresponding information when the correlation analyzer or exception detector requires.• Exception DetectorException detector examines anomalies of the input four-tuple based on correlation information. The exception detector directly utilizes correlations in database, instead of waiting for knowledge from the correlation analyzer, to identify anomalies. Therefore, the time that the detector spends in identifying anomalies is not related to correlation mining. The detector can provide the real-time result when a 4-tuple is input.We mainly mine two kinds of correlations including correlations between a command and sub-commands, and correlations between executed sub-commands.If executed sub-command Latter support ratio  denotes the ratio of the number of occurrences that kth actuator. The value of At the beginning of correlation mining, there exist many 4-tuples Phase I: verified correlation selection. In this phase, the correlation analyzer only needs to find a command C when correlation mining between sub-command Phase II: correlation validation. In the second phase, the correlation analyzer judges whether there exists a correlation between We use Equation , the corEquation , the corThe two phases are executed repetitively until set k) and x(k) indicate the number of occurrences that ith actuator and the number of occurrences that kth outflow. If Equation  is satisThe flowchart of correlation mining among sub-commands is given in The correlation analyzer can obtain Equation  by applyAfter computing ehaviors . At the Lastly, we introduce the detection process of the exception detector.Exception detector identifies anomalies based on broken correlations. For a sub-command In this section, we investigate two cases about tank system and energy trading system in the smart grid to illustrate the impact of attacks and the effectiveness of our detection framework.A tank system ,32 with We only describe a sub-system to illustrate the control process. turning on the pump that outputs ingredient A at time 0 s (turning off the pump that outputs ingredient A at time M s (turning on the pump that outputs ingredient B at time M + 60 s (turning off the pump that outputs ingredient B at time opening the valve that outputs liquid C at time closing the valve that outputs liquid C at time A plan of producing The above neutralization process depicted is simulated in Java, where the central controller, actuators, and sub-controllers are designed as components by using Java Class. Every switch and sensor are seen as attributes of related actuators. When some attributes occur a change, the central controller issues new commands. Some executed sub-commands can cause the changes of the attributes. Different components communicate with each other by function call with parameters. The parameters include commands and feedback data. The central controller automatically keeps running and issues commands based on the users’ input and the designed control process. During the operation of the system, values of sensors, sub-commands, and commands are written into different files per unit time. Moreover, every sub-controller component provides an interface for users. When users call the interface and input parameters, sub-controllers have been compromised and commands and feedback data can be modified.With the increasing proliferation of new energy, many users can become suppliers who sell energy to other users called consumers. Every supplier has an energy storage system that stores extra energy. When consumers need to buy energy, energy is routed to these consumers from suppliers based on energy routing schemes.A simplified model of energy trading system in the smart grid ,34 is shIn the model, there are 12 sub-commands and 6 sensors, which are shown in turning on the switch that outputs energy at time 0 s (turning on the switch that inputs energy at time 0 s (turning off the switch that outputs energy at time K s (turning off the switch that inputs energy at time K w energy, it will turn on the switch with the largest amount of energy until the output is equal to K w. If multiple users request power, the sub-controller will turn on other switches to output energy. The initial volume of every storage system is At the beginning of every circle, consumers sent their demands In this subsection, we introduce six attack cases based on WCOA, WCIA and FCS. Under normal circumstances of scenario 1, users randomly receive orders of goods including Six attack cases are described as follows:Attack case 1 in scenario 1: When the controller issues command Attack case 2 in scenario 1: At Attack case 3 in scenario 1: At Attack case 4 in scenario 2: When the controller issues command Attack case 5 in scenario 2: At Attack case 6 in scenario 2: At During the above attack processes, attackers also modify data of sensors to confuse the central controller and detectors, thereby resulting in sensory data same to those in The above six cases demonstrate that command disaggregation attacks can lead to disruptions of physical process and create great impact.We employed java to implement the detection framework described in We check whether the proposed detection framework can effectively identify six attack cases. Two kinds of correlations are obtained by analyzing data. In We also implement two other detection methods in ,35 to deTo better illustrate the performance of the proposed detection framework, we randomly launch attacks based on WCIA, WCOA, and FCA in scenario 1 and scenario 2. Every type of attack is launched many times at the different time. We find that attacks based on FCA and WCOA can be identified with 100% accuracy in two scenarios. Attacks based on WCIA in scenario 1 can be identified with 95% accuracy because some elaborately constructed attacks enable the correlation between two sub-commands not to be broken. An example will be described in The experiments demonstrate that the detection framework can effectively identify many command disaggregation attacks, and can find anomalies before disruptions of physical process occur.This section discusses further improvement measures for the defects of our detection framework.Difficulties of correlation mining. A large number of linear relationships exist among data of complex IIoTs [ex IIoTs , howeverex IIoTs  to identThe futility of detecting elaborately constructed attack sequences. Experiments in In this study, we focus on the command disaggregation attack and its detection method. We describe three attack models to implement command disaggregation attacks in two kinds of modes. The examples of the tank system and energy trading system demonstrate that command disaggregation attacks in two modes can cause severe damage to physical process and an effective detection method is necessary. We also provide a novel framework to detect command disaggregation attacks. The framework utilizes the correlations between commands and sub-commands to identify anomalies. The two cases demonstrate that our detection framework can identify undetected command disaggregation attacks by the existing detection methods with high accuracy if there exist corresponding correlations among commands and sub-commands. Besides that, our method can identify anomalies before a fault occurs. In future, we will strengthen the detection framework to detect command disaggregation attacks in more complex IIoTs.


Escherichia coli (ETEC) are bacterial pathogens that are frequently associated with diarrhoeal disease, and are a significant cause of mortality and morbidity worldwide. The Global Burden of Diseases, Injuries, and Risk Factors study 2016 (GBD 2016) is a systematic, scientific effort to quantify the morbidity and mortality due to over 300 causes of death and disability. We aimed to analyse the global burden of shigella and ETEC diarrhoea according to age, sex, geography, and year from 1990 to 2016.Shigella and enterotoxigenic We modelled shigella and ETEC-related mortality using a Bayesian hierarchical modelling platform that evaluates a wide range of covariates and model types on the basis of vital registration and verbal autopsy data. We used a compartmental meta-regression tool to model the incidence of shigella and ETEC, which enforces an association between incidence, prevalence, and remission on the basis of scientific literature, population representative surveys, and health-care data. We calculated 95% uncertainty intervals (UIs) for the point estimates.Shigella was the second leading cause of diarrhoeal mortality in 2016 among all ages, accounting for 212 438 deaths (95% UI 136 979–326 913) and about 13·2% (9·2–17·4) of all diarrhoea deaths. Shigella was responsible for 63 713 deaths (41 191–93 611) among children younger than 5 years and was frequently associated with diarrhoea across all adult age groups, increasing in elderly people, with broad geographical distribution. ETEC was the eighth leading cause of diarrhoea mortality in 2016 among all age groups, accounting for 51 186 deaths (26 757–83 064) and about 3·2% (1·8–4·7) of diarrhoea deaths. ETEC was responsible for about 4·2% (2·2–6·8) of diarrhoea deaths in children younger than 5 years.The health burden of bacterial diarrhoeal pathogens is difficult to estimate. Despite existing prevention and treatment options, they remain a major cause of morbidity and mortality globally. Additional emphasis by public health officials is needed on a reduction in disease due to shigella and ETEC to reduce disease burden.Bill & Melinda Gates Foundation. Escherichia coli .13According to recent global disease burden estimates, diarrhoea accounts for more than 1 million deaths and about 4% of the total global disability-adjusted life-years (DALYS) per year across all age groups.ETEC is one of the first symptomatic enteric illnesses for many children, causing several hundred million cases of diarrhoea each year, mostly in young children.Evidence before this studyEscherichia coli (ETEC) diarrhoea include population representative surveys, scientific literature, and health-care utilisation data. We searched PubMed, with no language restrictions, for studies published between Jan 1, 1990, and Dec 31, 2017, with the following search string: (diarrhoea [title] OR diarrhoea [MeSH terms] OR diarrhoea [title] OR diarrhoea [MeSH terms] AND (shigell* [title/abstract] OR enterotoxigenic e. coli [title/abstract]) AND (aetiolog* [title/abstract] OR aetiology [MeSH Terms] OR cause [title/abstract] OR pathogen [title/abstract]) NOT (colitis [title/abstract] OR enterocolitis [title/abstract] OR inflammatory bowel [title/abstract] OR irritable [title/abstract] OR Crohn* [title/abstract] OR HIV [title] OR treatment [title] OR therapy [title]) NOT (appendicitis [title/abstract] OR esophag* [title/abstract] OR surger* [title/abstract] OR gastritis [title/abstract] OR liver [title/abstract] OR case report [title] OR case-report [title] OR therapy [title] OR treatment [title]) AND humans [Mesh]). The Maternal and Child Epidemiology Estimation group (MCEE) estimated 42 000 deaths among children younger than 5 years due to ETEC and 28 000 deaths due to shigella. The MCEE modelling approach was categorical, meaning that if a pathogen was present in a diarrhoeal stool sample, diarrhoea was attributed to that pathogen, and used conventional bacterial culture methods for diagnostic detection. The Global Burden of Diseases, Injuries, and Risk Factors (GBD) study 2016 used molecular diagnostics.Sources for this analysis of the global burden of shigella and enterotoxigenic Added value of this studyOur analysis uses the GBD study to estimate shigella and ETEC incidence, disability-adjusted life-years, and mortality across every country for each sex and all ages from 1990 to 2016. We estimated that shigella was responsible for about 210 000 deaths among all ages, including about 63 700 among children younger than 5 years, and that ETEC was responsible for about 51 200 deaths among all ages and about 18 700 deaths in children younger than 5 years. Our results challenge some previous estimates with regard to the relative and absolute magnitude of the health burden associated with diarrhoea caused by shigella and ETEC.Implications of all the available evidenceOur study calls for a widespread improvement in the quality and quantity of data, including improved surveillance systems and utilisation of standard reporting mechanisms and case definitions. Refined burden estimates for the acute and long-term burden of shigella and ETEC are needed to guide funders and public health officials to make evidence-based decisions for the alleviation of diarrhoeal diseases, with particular attention to the development of effective and attainable vaccines. Data on the burden of diarrhoeal diseases caused by shigella and ETEC will help public health officials to identify proper age appropriate vaccination schedules and target regions where the burden of these pathogens is substantial.Although shigellosis occurs worldwide, the greatest burden is among children in low-income countries. Repeated infection is not uncommon because of the multiple serotypes associated with illness, and the decrease in the incidence of disease with increasing age shows that immunity eventually develops.Both shigella and ETEC are important causes of diarrhoea and dysentery in people older than 5 years, with an estimated 100 million episodes occurring annually among those aged 5–14 years.38Shigella spp are antigenically diverse, encompassing two toxins and over 25 colonisation factors for ETEC, and 50 serotypes or subtypes for shigella, which makes the development of vaccines challenging.Shigella flexneri 2a, 6, 3a, and Shigella sonnei.45Shigella and ETEC vaccine candidates are currently in various phases of research and development.To inform vaccine development priorities, the disease burdens of shigella and ETEC need to be characterised at regional and national levels. Co-infecting pathogens, asymptomatic infections, antigenic diversity, and variability of diagnostic methods can complicate the determination of diarrhoeal aetiology for children in LMICs.Detailed methods on the Global Burden of Disease (GBD) Study and on diarrhoea estimation in GBD have already been published.Diarrhoea-related mortality was modelled in the Cause of Death Ensemble model (CODEm) platform.Diarrhoea-related morbidity, including incidence and prevalence, was modelled in DisMod-MR (version 2.1).The cause of diarrhoea is estimated separately from mortality and morbidity.Shigella spp and for both heat stable (ST)-ETEC and heat labile (LT)-ETEC.Diarrhoea aetiologies are based on molecular diagnostic case definitions. We did a systematic reanalysis of the GEMS samples using real-time PCR. Our modelling strategy requires that the continuous real-time PCR test results be dichotomised into positive and negative results. To do this, we identified the lowest cycle threshold at which the diagnostic accuracy, defined as the ability to discriminate between cases and controls, was maximised. We fitted a Loess curve to each cycle threshold distribution of aetiology and the proportion of diarrhoea cases that were correctly identified .estA or eltB E coli genes in the primary GEMS laboratory results and the lower cycle threshold score for ST (both STh and STp genes) or LT gene targets in the real-time PCR reanalysis  and the highest rates of mortality due to shigella in this age group were in sub-Saharan Africa, where mortality rates were greater than 10 per 100 000 people per year in northern, western, eastern, and central regions . Under-5ETEC was the eighth leading cause of diarrhoea mortality in 2016 among all age groups globally, accounting for an estimated 51 186 deaths  and the global mortality rate among children younger than 5 years ranged from less than 0·1 per 100 000 in many regions to 8·8 per 100 000 (4·6–14·3) in eastern sub-Saharan Africa . The greThe burden of shigella and ETEC varied by geographical region . DiffereThe use of bacterial culture to detect shigella and ETEC in diarrhoeal stool samples is likely to miss a substantial proportion of infections.r2 −0·33, 95% UI −0·42 to −0·24). Shigella is strongly correlated  with a highly negative slope, indicating that these causes, shigella especially, are focused in low-income countries  and enterotoxin production within the small intestine. ETEC produce ST or LT enterotoxins, or both, which stimulate the release of fluid and electrolytes from the intestinal epithelium, resulting in watery diarrhoea.Campylobacter spp, and adenovirus.Diarrhoea early in childhood can impede the absorption of nutrients in the gut, leading to malnutrition.Shigella affects people of all ages and is a predominant cause of diarrhoea mortality throughout adolescence and adulthood. Our analysis shows that shigella was the leading cause of death among adults older than 70 years. Although routine immunisation programmes are an attractive option for the prevention of shigella, our results suggest that such programmes might miss a substantial burden of shigella mortality in this age group.The long-term solution for disease reduction is an integrated approach that includes improved water quality, sanitation and handwashing, optimised nutrition, better access to medical care, and vaccines. A combined shigella–ETEC vaccine is also being investigated, partly because both pathogens affect similar geographical settings and populations.30Our results differ from previous estimates in some respects. The Child Health Epidemiology Research Group—now called the Maternal and Child Epidemiology Estimation group (MCEE)A systematic reanalysisOur findings have several limitations. First, our estimates of mortality, morbidity, and aetiological attribution for shigella and ETEC are restricted by availability of data, particularly data sparsity in regions of the world with a high diarrhoea burden. In addition, scarce data are available for the neonatal age group. Although adjustment for factors such as maternal immunity might help to improve our model estimates, quantification of the effect of maternal immunity is restricted by the availability of data. We account for this limitation by including UIs with each of our estimates, and our modelling approach allows us to make inferences for places and times with little data, based on more reliable estimates from other periods and regions to generate the best possible estimates. There is also a general scarcity of data on diarrhoea among populations older than 5 years and, although we model causes for diarrhoea in these age groups, the ORs from the oldest age group in GEMS—under 5 years old—are assumed to be representative in older ages. Second, this analysis only accounts for the acute phase of diarrhoea in our YLD estimates for the two pathogens. Consequently, our DALY estimates severely underestimate diarrhoea-associated long-term sequaelae, such as stunting and cognitive impairment.In summary, our findings give an insight into the global burden of shigella and ETEC diarrhoea globally, spanning over 25 years for both sexes and all ages. Such refined burden estimates for the mortality, morbidity, and long-term effects of shigella and ETEC are needed to guide funders, public health officials, and policy makers. Refined burden estimates will help these individuals and organisations to make evidence-based decisions for the allocation of resources and the promotion of vaccine development and other effective strategies to reduce the unacceptable burden of diarrhoea worldwide.list of all GBD 2015 data sources for each country see http://ghdx.healthdata.org/gbd-2015/data-input-sourcesFor a online results see https://vizhub.healthdata.org/gbdcompare/ and https://ghdx.healthdata.org/gbd-2016/For code see http://ghdx.healthdata.org/global-burdendisease-study-2016-gbd-2016-causes-death-3For the


OF) conditions and, a high, by using greenhouses (GH). For OF, data belong to five municipalities of the Guanentá province (Santander department), while for GH, data belong to five municipalities of the Alto Ricaurte province (Boyacá department). The data presented here includes information on soil parental materials and climate variables (averages ± standard deviations) relevant from the agricultural point of view, which were calculated from historical climate series. Soils natural fertility data, obtained by sampling the production areas, are also presented. After filtering the data, 67 samples were obtained for OF and 70 for the GH. For GH, a dataset with the results of 38 soil samples taken inside greenhouses were paired with the results of samples taken outside these greenhouses in uncropped areas. In the case of these soil analyses, the data correspond to tables with the results reported by the laboratory for both, chemical and physical variables, for each location in which soil samples were taken. In this work, the main dataset is one that contains the inputs of fertilizers and water, and the corresponding yields of tomato production cycles managed by local growers. This information was collected through two data collection tools: surveys (SVY) to growers about these aspects in their last production cycle, and through detailed follow-ups of selected production cycles (FWU). For the OF, we collected data from 71 cycles through the surveys and 22 through the follow-ups, while for the GH, information from 138 to 38 tomato cycles was collected through surveys and follow-ups, respectively. A table with the results aggregated by tomato cycle is attached.Datasets presented here were employed in the main work “Understanding the heterogeneity of smallholder production systems in the Andean tropics – The case of Colombian tomato growers” Gil, et al., 2019. In this region, tomato crop is developed under two technological levels: low, carried out under open field ( The distance between the two production zones is 115 km. The landscape of the Guanentá province is formed by mountains and hills crossed by rivers, which in some sectors form small riverbanks . The solar radiation was estimated from the hours of bright sunshine (hours day−1) since this variable was not included in the original data. The incoming solar radiation was estimated from extraterrestrial solar radiation and relative sunshine hours, following the equation proposed by Angstrom −2 day−1); −2 day−1); −1); DL is the day length (hours). The coefficients For each production area, the elevation profiles were constructed with data extracted from Google Earth and supplemented with information about the soil parental materials obtained from previous studies 2.23), ammonium (N—NH4), phosphorus (P) and potassium (K) contents, pH, electrical conductivity (EC), soil organic carbon (SOC); and physical properties such as clay, silt and sand contents (%). Exchangeable N—NH4 and N—NO3 were determined by extraction with KCl, and the solution was analyzed as described by Bremner and Keeney 2O5 and K2O by multiplying them by 2.292 and 1.205, respectively.Initially, in each production area, 75 soils samples were collected at 30 cm depth on fallow plots between May and July 2015. Sampling spots were determined by a non-aligned random sampling procedure and adjusted once on the field to sample only uncropped soils. Based on the geographic coordinates of the sampling points, we determined the altitude and slope using a 30 m digital elevation model (DEM). Soil samples were processed at a certificated soils laboratory, and the analysis included chemical properties such as nitrate . The sampling sites were randomly selected based on satellite images on which GH locations were clearly identified. Samples were analysed including the same variables used to describe the soil natural fertility in a certified soils laboratory and following the aforementioned methods. We took 38 pairs of soil samples during June 2013.As part of the characterization, we determined the effect of 2.4SVY) and a direct follow-up observation procedure (FWU). SVY consisted on a questionnaire of closed-ended questions about technical aspects related to the last tomato growing cycle such as: cropped area, plant density, cycle length, type and amount of fertilizers applied, crop management practices, water input by irrigation and yield. Questions were redacted by the research team and subsequently were tested through a simulacrum on local growers to improve its comprehension. Once on the field, previously trained undergraduate students conducted the interviews. Between 2009 and 2010, a total of 80 and 174 surveys were carried out to randomly selected smallholder of the OF and GH technological levels, respectively.In the present work, two data collection tools were employed: surveys  for the OF and 30 months (from September 2010 to March 2013) for the GH. From both data collection tools, the data recorded were aggregated in order to obtain the total inputs (e.g. fertilizers) employed for the tomato production along with the total yield achieved. For commercial fertilizers, the nutrient elements contribution was obtained from the official information showed in the label. In the case of organic fertilizers, samples were taken and analyzed to determine the concentration of nitrogen, phosphorus and potassium.In GH fertilization strategies on the soils and the data about the management practices in relation to the fertilization are georeferenced. In each table, samples have associated the coordinates in decimal degrees taken in the official geodesic datum for Colombia (MAGNA-SIRGAS).The datasets of soil natural fertility, the effect of the