Diabetic retinopathy(DR)is a leading cause of vision loss among working-age populations,with early screening significantly reducing the risk of blindness.However,resource-limited regions often face challenges in DR sc...Diabetic retinopathy(DR)is a leading cause of vision loss among working-age populations,with early screening significantly reducing the risk of blindness.However,resource-limited regions often face challenges in DR screening due to a shortage of ophthalmologists.This study reports the implementation and outcomes of the Chinese local standard DB52/T 1726-2023,Regulations for the application of diabetic retinopathy screening artificial intelligence,in Cambodian healthcare institutions.A pilot DR screening program with independent operational capability is established by providing a non-mydriatic fundus camera and deploying a localized diabetic retinopathy artificial intelligence(DR-AI)screening platform at the Cambodia-Kingdom Friendship Hospital in Phnom Penh,along with comprehensive training.From January to August 2025,a total of 565 patients with type 2 diabetes were screened,yielding a DR detection rate of 26.0%(147 cases).Research findings demonstrate that applying mature Chinese DR-AI screening standards and technological solutions through international collaboration in regions with a scarcity of ophthalmic professionals is both feasible and effective.This project serves as a reference for promoting DR-AI in resource-constrained countries and regions,highlighting its significant potential to leverage AI in addressing the global burden of chronic diseases and advancing the modernization of health systems.展开更多
The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the pot...Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.展开更多
Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo developm...Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.展开更多
Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing me...Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.展开更多
Soft rot is a destructive disease that inflicts significant losses on agricultural production and the economy post-harvest.Biocontrol strategies based on antagonistic microorganisms have a broad application prospect t...Soft rot is a destructive disease that inflicts significant losses on agricultural production and the economy post-harvest.Biocontrol strategies based on antagonistic microorganisms have a broad application prospect to fight against plant pathogens.This study utilized fluorescence-activated droplet sorting(FADS)technology as an alternative to traditional plate culture methods to isolate microorganisms with antagonistic activity against the soft rot pathogen Erwinia carotovora Ecc15.Initially,the culture performance of the FADS platform was evaluated by analyzing bacterial diversity in droplet culture samples and agar plate culture samples,our data showed that droplet culture exhibited higher species richness and diversity than plate culture,and more than 95%of the operational taxonomic units(OTUs)in the droplet samples belonged to the rare biosphere.Additionally,we developed a green fluorescent protein(GFP)-Ecc15-based FADS screening system,which achieved an enrichment ratio of up to 148.Using this system,we successfully screened 32 antagonistic bacteria from rhizosphere soil sample of healthy konjac plants,and some may be novel microbial resources,including the genera Lelliottia,Buttiauxella and Leclercia.Notably,strain D-62 exhibited the strongest antibacterial ability against Ecc15,with an inhibition zone diameter of(20.86±1.56)mm.In vivo experiments conducted on the corms of Amorphophallus konjac demonstrated that strain D-62 could effectively reduce the infection ability of Ecc15 to the corms,indicating that strain D-62 has the potential to be developed as a biocontrol agent.Our findings suggested that the FADS screening system showed a screening efficiency approximately 3×10^(3)times higher than plate screening system,while significantly reducing costs of infrastructure,labor and consumables,it provides theoretical guidance for the screening of other plant pathogen biocontrol bacteria.展开更多
The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combinat...The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).展开更多
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr...For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.展开更多
Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compound...Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.展开更多
It is established that different stresses cause signal-specific changes in cellular Ca2 ~ level, which function as messengers in modulating diverse physiological processes. These calcium signals are important for stre...It is established that different stresses cause signal-specific changes in cellular Ca2 ~ level, which function as messengers in modulating diverse physiological processes. These calcium signals are important for stress adaptation. Though numbers of downstream components of calcium signal cascades have been identified, upstream events in calcium signal remain elusive, specifically components required l＇~~r calcium signal generation due to the lack of high-throughput genetic assay. Here, we report the development of an easy and efficient method in a forward genetic screen for Ca2＋ signals-deficient mutants in Arahidopsis thaliana. Using this method, 121 mutants with disordered NaCI- and H=O2-induced Ca2＋ signals are isolated.展开更多
With the continuous emergence and rapid spread of multidrug-resistant and extensively-drug-resistant Mycobacterium tuberculosis strains, it is imperative to develop novel therapies against this bacterium. The intrins...With the continuous emergence and rapid spread of multidrug-resistant and extensively-drug-resistant Mycobacterium tuberculosis strains, it is imperative to develop novel therapies against this bacterium. The intrinsic β-lactam resistance of M. tuberculosis is primarily due to the production of an Ambler class-A β-lactamase BlaC, which limits the application of β-lactam antibiotics in the treatment of tuberculosis. Therefore, the inhibitors of BlaC could be novel anti-tuberculosis drug synergistic agents to recover the sensibility of M. Tuberculosis to the β-lactam antibiotics. In the present study, BlaC of M. tuberculosis was expressed and purified to establish a screening model of the BlaC inhibitors. The screening conditions were determined, and the screening model was evaluated to fit for the high throughput screening. A total of 22 BlaC inhibitors were screened out from 26 400 compound samples with a positive rate of 0.083%. Taken together, our findings lay the foundation for the discovery of novel anti-tuberculosis drug synergistic agents in clinic.展开更多
Colorectal cancer(CRC)is a prevalent malignancy worldwide,posing a significant public health concern.Mounting evidence has confirmed that timely early screening facilitates the detection of incipient CRC,thereby enhan...Colorectal cancer(CRC)is a prevalent malignancy worldwide,posing a significant public health concern.Mounting evidence has confirmed that timely early screening facilitates the detection of incipient CRC,thereby enhancing patient prognosis.Obviously,non-participation of asymptomatic individuals in screening programs hampers early diagnosis and may adversely affect long-term outcomes for CRC patients.In this letter,we provide a comprehensive overview of the current status of early screening practices,while also thoroughly examine the dilemmas and potential solutions associated with early screening for CRC.In response to these issues,we proffer a set of recommendations directed at governmental authorities and the general public,which focus on augmenting financial investment,establishing standardized screening protocols,advancing technological capabilities,and bolstering public awareness campaigns.The importance of collaborative efforts from various stakeholders cannot be overstated in the quest to enhance early detection rates and alleviate the societal burden of CRC.展开更多
Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and...Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.展开更多
To identify the desired hypertherrnophilic variants within a mutant esterase library for the resolution of （R, S）-2- octanol acetate, a simple, reliable, and versatile method was developed in this study. We built a ...To identify the desired hypertherrnophilic variants within a mutant esterase library for the resolution of （R, S）-2- octanol acetate, a simple, reliable, and versatile method was developed in this study. We built a screening strategy including two steps, first we selected agar plate with substrate to screen the enzymatic activity; secondly we used a pH indicator to screen the enantioselectivity. This method could rapidly detect favorable mutants with high activity and enantioselectivity. A total of 96. 2% of tedious screening work can be precluded using this screening strategy. It is an effective screening for alkyl ester and can be applied to relative screening researches. The four improved mutants were screened from the mutant esterase library. Their enantioselectivities, activities, and structures were investigated at different temperatures.展开更多
Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of m...Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.展开更多
The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the G...Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.展开更多
Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state b...Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.展开更多
Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite thei...Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.展开更多
基金funded by the Chronic Disease Management Research Project of National Health Commission Capacity Building and Continuing Education Center 2025(GWJJMB202510024146)the Post-Subsidy Project for Standard Development of Guizhou Provincial Market Supervision and Administration Bureau 2025(DB52/T1726-2023)the Guizhou Provincial Health Commission Science and Technology Fund Project(gzwkj2024-076,gzwkj2026-146).
文摘Diabetic retinopathy(DR)is a leading cause of vision loss among working-age populations,with early screening significantly reducing the risk of blindness.However,resource-limited regions often face challenges in DR screening due to a shortage of ophthalmologists.This study reports the implementation and outcomes of the Chinese local standard DB52/T 1726-2023,Regulations for the application of diabetic retinopathy screening artificial intelligence,in Cambodian healthcare institutions.A pilot DR screening program with independent operational capability is established by providing a non-mydriatic fundus camera and deploying a localized diabetic retinopathy artificial intelligence(DR-AI)screening platform at the Cambodia-Kingdom Friendship Hospital in Phnom Penh,along with comprehensive training.From January to August 2025,a total of 565 patients with type 2 diabetes were screened,yielding a DR detection rate of 26.0%(147 cases).Research findings demonstrate that applying mature Chinese DR-AI screening standards and technological solutions through international collaboration in regions with a scarcity of ophthalmic professionals is both feasible and effective.This project serves as a reference for promoting DR-AI in resource-constrained countries and regions,highlighting its significant potential to leverage AI in addressing the global burden of chronic diseases and advancing the modernization of health systems.
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金supported by the National Key Research and Development Program of China(No.2021YFB3702102)support from the“Initiation Program for New Teachers”(No.AF0500207)+1 种基金Shanghai Jiao Tong Universitysupport from the Changsha Science and Technology Plan International and Regional Cooperation Project(No.kh2304002)。
文摘Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.
基金supported by National Natural Science Foundation of China (32172747 and 32425052)
文摘Background Early embryo development plays a pivotal role in determining pregnancy outcomes,postnatal development,and lifelong health.Therefore,the strategic selection of functional nutrients to enhance embryo development is of paramount importance.In this study,we established a stable porcine trophectoderm cell line expressing dual fluorescent reporter genes driven by the CDX2 and TEAD4 gene promoter segments using lentiviral transfection.Results Three amino acid metabolites—kynurenic acid,taurine,and tryptamine—met the minimum z-score criteria of 2.0 for both luciferase and Renilla luciferase activities and were initially identified as potential metabolites for embryo development,with their beneficial effects validated by qPCR.Given that the identified metabolites are closely related to methionine,arginine,and tryptophan,we selected these three amino acids,using lysine as a standard,and employed response surface methodology combined with our high-throughput screening cell model to efficiently screen and optimize amino acid combination conducive to early embryo development.The optimized candidate amino acid system included lysine(1.87 mmol/L),methionine(0.82 mmol/L),tryptophan(0.23 mmol/L),and arginine(3 mmol/L),with the ratio of 1:0.43:0.12:1.60.In vitro experiments confirmed that this amino acid system enhances the expression of key genes involved in early embryonic development and improves in vitro embryo adhesion.Transcriptomic analysis of blastocysts suggested that candidate amino acid system enhances early embryo development by regulating early embryonic cell cycle and differentiation,as well as improving nutrient absorption.Furthermore,based on response surface methodology,400 sows were used to verify this amino acid system,substituting arginine with the more cost-effective N-carbamoyl glutamate(NCG),a precursor of arginine.The optimal dietary amino acid requirement was predicted to be 0.71%lysine,0.32%methionine,0.22%tryptophan,and 0.10%NCG for sows during early gestation.The optimized amino acid system ratio of the feed,derived from the peripheral release of essential amino acids,was found to be 1:0.45:0.13,which is largely consistent with the results obtained from the cell model optimization.Subsequently,we furtherly verified that this optimal dietary amino acid system significantly increased total litter size,live litter size and litter weight in sows.Conclusions In summary,we successfully established a dual-fluorescent high-throughput screening cell model for the efficient identification of potential nutrients that would promote embryo development and implantation.This innovative approach overcomes the limitations of traditional amino acid nutrition studies in sows,providing a more effective model for enhancing reproductive outcomes.
基金supported by the Shandong Provincial Key Research and Development Program(Major Key Technology Project)(2021CXGC010514)the National Natural Science Foundation of China(22008173).
文摘Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.
基金supported by the Guizhou Province High-level Innovative Talent Project(Qiankehe Platform Talent-GCC[2022]027-1)the National Key Research and Development Program of China(2019YFA0904800).
文摘Soft rot is a destructive disease that inflicts significant losses on agricultural production and the economy post-harvest.Biocontrol strategies based on antagonistic microorganisms have a broad application prospect to fight against plant pathogens.This study utilized fluorescence-activated droplet sorting(FADS)technology as an alternative to traditional plate culture methods to isolate microorganisms with antagonistic activity against the soft rot pathogen Erwinia carotovora Ecc15.Initially,the culture performance of the FADS platform was evaluated by analyzing bacterial diversity in droplet culture samples and agar plate culture samples,our data showed that droplet culture exhibited higher species richness and diversity than plate culture,and more than 95%of the operational taxonomic units(OTUs)in the droplet samples belonged to the rare biosphere.Additionally,we developed a green fluorescent protein(GFP)-Ecc15-based FADS screening system,which achieved an enrichment ratio of up to 148.Using this system,we successfully screened 32 antagonistic bacteria from rhizosphere soil sample of healthy konjac plants,and some may be novel microbial resources,including the genera Lelliottia,Buttiauxella and Leclercia.Notably,strain D-62 exhibited the strongest antibacterial ability against Ecc15,with an inhibition zone diameter of(20.86±1.56)mm.In vivo experiments conducted on the corms of Amorphophallus konjac demonstrated that strain D-62 could effectively reduce the infection ability of Ecc15 to the corms,indicating that strain D-62 has the potential to be developed as a biocontrol agent.Our findings suggested that the FADS screening system showed a screening efficiency approximately 3×10^(3)times higher than plate screening system,while significantly reducing costs of infrastructure,labor and consumables,it provides theoretical guidance for the screening of other plant pathogen biocontrol bacteria.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11304079,11404094,and 11504088)Science and Technology Research Project of Henan Science and Technology Department(Grant No.182102410076)。
文摘The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2022R1F1A1074339)。
文摘For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.
基金supported by the Ministry of Science and Technology, PRC in Mega-projects of Science Research During the 10th Five-Year Plan Period (No. 2004AA2Z38784)National Natural Science Foundation of China (No. 30472026).
文摘Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.
基金supported by the National Funds for Distinguished Young Scientists in China(Grant No.31025003) to Y.Guo
文摘It is established that different stresses cause signal-specific changes in cellular Ca2 ~ level, which function as messengers in modulating diverse physiological processes. These calcium signals are important for stress adaptation. Though numbers of downstream components of calcium signal cascades have been identified, upstream events in calcium signal remain elusive, specifically components required l＇~~r calcium signal generation due to the lack of high-throughput genetic assay. Here, we report the development of an easy and efficient method in a forward genetic screen for Ca2＋ signals-deficient mutants in Arahidopsis thaliana. Using this method, 121 mutants with disordered NaCI- and H=O2-induced Ca2＋ signals are isolated.
基金Fundamental Research Funds for Central Public Welfare Research Institutes(Grant No.2015PT350001)National Major Scientific and Technological Special Project for “Significant New Drugs Development”(Grant No.2015ZX09102007-009)
文摘With the continuous emergence and rapid spread of multidrug-resistant and extensively-drug-resistant Mycobacterium tuberculosis strains, it is imperative to develop novel therapies against this bacterium. The intrinsic β-lactam resistance of M. tuberculosis is primarily due to the production of an Ambler class-A β-lactamase BlaC, which limits the application of β-lactam antibiotics in the treatment of tuberculosis. Therefore, the inhibitors of BlaC could be novel anti-tuberculosis drug synergistic agents to recover the sensibility of M. Tuberculosis to the β-lactam antibiotics. In the present study, BlaC of M. tuberculosis was expressed and purified to establish a screening model of the BlaC inhibitors. The screening conditions were determined, and the screening model was evaluated to fit for the high throughput screening. A total of 22 BlaC inhibitors were screened out from 26 400 compound samples with a positive rate of 0.083%. Taken together, our findings lay the foundation for the discovery of novel anti-tuberculosis drug synergistic agents in clinic.
文摘Colorectal cancer(CRC)is a prevalent malignancy worldwide,posing a significant public health concern.Mounting evidence has confirmed that timely early screening facilitates the detection of incipient CRC,thereby enhancing patient prognosis.Obviously,non-participation of asymptomatic individuals in screening programs hampers early diagnosis and may adversely affect long-term outcomes for CRC patients.In this letter,we provide a comprehensive overview of the current status of early screening practices,while also thoroughly examine the dilemmas and potential solutions associated with early screening for CRC.In response to these issues,we proffer a set of recommendations directed at governmental authorities and the general public,which focus on augmenting financial investment,establishing standardized screening protocols,advancing technological capabilities,and bolstering public awareness campaigns.The importance of collaborative efforts from various stakeholders cannot be overstated in the quest to enhance early detection rates and alleviate the societal burden of CRC.
基金the Science Challenge Project(TZ2018004)the National Natural Science Foundation of China(21875228 and 21702195)for financial support。
文摘Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.
基金Supported by the National Natural Science Foundation of China(Nos30400081, 30570405 and 20672045)the Key Tech-nology Research and Development Program of China(No2004BA713D03-04)
文摘To identify the desired hypertherrnophilic variants within a mutant esterase library for the resolution of （R, S）-2- octanol acetate, a simple, reliable, and versatile method was developed in this study. We built a screening strategy including two steps, first we selected agar plate with substrate to screen the enzymatic activity; secondly we used a pH indicator to screen the enantioselectivity. This method could rapidly detect favorable mutants with high activity and enantioselectivity. A total of 96. 2% of tedious screening work can be precluded using this screening strategy. It is an effective screening for alkyl ester and can be applied to relative screening researches. The four improved mutants were screened from the mutant esterase library. Their enantioselectivities, activities, and structures were investigated at different temperatures.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82373835,82304437,and 82173781)Regional Joint Fund Project of Guangdong Basic and Applied Basic Research Fund,China(Grant Nos.:2023A1515110417 and 2023A1515140131)+2 种基金Regional Joint Fund-Key Project of Guangdong Basic and Applied Basic Research Fund,China(Grant No.:2020B1515120033)the Key Field Projects of General Universities in Guangdong Province,China(Grant Nos.:2020ZDZX2057 and 2022ZDZX2056)Medical Scientific Research Foundation of Guangdong Province of China(Grant No.:A2022061).
文摘Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
基金the National Key R&D Program of China(No.2021YFA0715900)the National Natural Science Foundation of China(No.41831279)+2 种基金the Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks(No.ZDSYS20220606100604008)the Guangdong Province Bureau of Education(No.2020KCXTD006)the Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control(No.2023B1212060002).
文摘Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.
基金the National Key Research Program of China under granted No.92164201National Natural Science Foundation of China for Distinguished Young Scholars No.62325403+2 种基金Natural Science Foundation of Jiangsu Province(BK20230498)Jiangsu Funding Program for Excellent Postdoctoral Talent(2024ZB427)the National Natural Science Foundation of China(62304147).
文摘Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy,high safety,and high environmental adaptability.However,the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment,rendering performance prediction arduous and delaying large-scale industrialization.Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction.This review will systematically examine how the latest progress in using machine learning(ML)algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode,anode,and electrolyte materials suitable for solid-state batteries.Furthermore,the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed,among which are state of charge,state of health,remaining useful life,and battery capacity.Finally,we will summarize the main challenges encountered in the current research,such as data quality issues and poor code portability,and propose possible solutions and development paths.These will provide clear guidance for future research and technological reiteration.
基金supported by the State Key Laboratory of Natural and Biomimetic Drugs, Peking University。
文摘Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.
