Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due ...Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.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
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
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
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
Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient...Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient to meet regulatory requirements.Objective:To construct a rapid and effective non-targeted screening method for the identification of risk substances,and to provide a high-throughput method for toxicity assessment.Methods:Molecular networking was utilized for the non-targeted screening of risk substances in facial skincare products,and the toxicity of these risk substances was evaluated through molecular docking and quantitative structure-activity relationship(QSAR)models.Results:Through molecular networking,we identified seven known prohibited ingredients,six of which were confirmed using standard substances.In addition,17 potential risk substances were discovered within molecular clusters containing prohibited ingredients,including antibiotics,antihistamines,and phthalates,etc.Notably,chloramphenicol base and N-desmethyl chlorpheniramine exhibited stronger binding affinity to keratin 5/14 than chloramphenicol and chlorpheniramine through molecular docking,respectively.Additionally,toxicity prediction results indicated that the carcinogenicity of antibiotics presented gender differences in mice and rats,and two chlorpheniramine derivatives also showed carcinogenicity in mice.Moreover,of the 24 compounds,11 showed skin sensitization,while 14 caused skin irritation.Furthermore,half of these compounds demonstrated potential developmental toxicity,and only 4-nitrobenzenethiol was found to be mutagenic.Conclusion:In this study,we developed a visualization strategy for non-targeted screening of risk substances and a high-throughput method for initial toxicity assessment of risk substances.展开更多
Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening ...Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening we identified a lead molecule that selectively targets PI3K and BRAF^(V600E) kinases.Computational screening,Molecular dynamics simulation and MMPBSA calculations were performed.PI3K and BRAF^(V600E) kinase inhibition was done.A375 and G-361 cells were used for in vitro cellular analysis to determine antiproliferative effects,annexin V binding,nuclear fragmentation and cell cycle analysis.Computational screening of small molecules indicates compound CB-006-3 selectively targets PI3KCG(gamma subunit),PI3KCD(delta subunit)and BRAF^(V600E).Molecular dynamics simulation and MMPBSA bases binding free energy calculations predict a stable binding of CB-006-3 to the active sites of PI3K and BRAF^(V600E).The compound effectively inhibited PI3KCG,PI3KCD and BRAF^(V600E)kinases with respective IC50 values of 75.80,160.10 and 70.84 nM.CB-006-3 controlled the proliferation of A375 and G-361 cells with GI50 values of 223.3 and 143.6 nM,respectively.A dose dependent increase in apoptotic cell population and sub G0/G1 phase of cell cycle were also observed with the compound treatment in addition to observed nuclear fragmentation in these cells.Furthermore,CB-006-3 inhibited BRAF^(V600E),PI3KCD and PI3KCG in both melanoma cells.Collectively,based on the computational modeling and in vitro validations,we propose CB-006-3 as a lead candidate for selectively targeting PI3K and mutant BRAF^(V600E) to inhibit melanoma cell proliferation.Further experimental validations,including pharmacokinetic evaluations in mouse models will identify the druggability of the proposed lead candidate for further development as a therapeutic agent for treating melanoma.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
Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne mate...Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne materials can offer stable adsorption sites for single metal atoms.To investigate the influence of the sp/sp^(2)hybrid carbon ratio on the electrocatalytic NRR performance of graphyne,a high-throughput screening of 81 catalysts,with27 transition metals loaded on graphyne(GY1),graphdiyne(GY2),and graphtriyne(GY3),was conducted using firstprinciples calculations.The results of the screening revealed that Ti@GY3 exhibits the lowest energy barrier for the rate-determining step(0.32 eV)in NRR.Further,to explore the impact of different sp/sp^(2)-hybridized carbon ratios on the catalytic activity of SACs,the mechanism of nitrogen(N_(2))adsorption,activation,and the comprehensive pathway of NRR on Ti@GY1,Ti@GY2,and Ti@GY3 was systematically investigated.It was found that the ratio of sp/sp^(2)-hybridized carbon can significantly modulate the d-band center of the metal,thus affecting the energy barrier of the rate-determining step in NRR,decreasing from Ti@GY1(0.59 eV)to Ti@GY2(0.49 eV);and further to Ti@GY3(0.32 eV).Additionally,the Hall conductance was found to increase with the bias voltage in the range of 0.4-1 V,as calculated by Nanodcal software,demonstrating an improvement in the conductivity of the SAC.In summary,this work provides theoretical guidance for modulating the electrocatalytic nitrogen reduction activity of SACs by varying the ratio of sp/sp^(2)hybrid carbon,with Ti@GY3 showing potential as an excellent NRR catalyst.展开更多
Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect cat...Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect catalytic performance in the vast catalyst space remains challenging for people.Herein,to accurately identify the factors that affect the performance of N2 reduction,we apply interpretable machine learning(ML)to analyze high-throughput screening results,which is also suited to other surface reactions in catalysis.To expound on the paradigm,33 promising catalysts are screened from 168 carbon-supported candidates,specifically single-atom catalysts(SACs)supported by a BC_(3)monolayer(TM@V_(B/C)-N_(n)=_(0-3)-BC_(3))via high-throughput screening.Subsequently,the hybrid sampling method and XGBoost model are selected to classify eligible and non-eligible catalysts.Through feature interpretation using Shapley Additive Explanations(SHAP)analysis,two crucial features,that is,the number of valence electrons(N_(v))and nitrogen substitution(N_(n)),are screened out.Combining SHAP analysis and electronic structure calculations,the synergistic effect between an active center with low valence electron numbers and reasonable C-N coordination(a medium fraction of nitrogen substitution)can exhibit high catalytic performance.Finally,six superior catalysts with a limiting potential lower than-0.4 V are predicted.Our workflow offers a rational approach to obtaining key information on catalytic performance from high-throughput screening results to design efficient catalysts that can be applied to other materials and reactions.展开更多
Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensivel...Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensively drug resistant TB cases.It is very urgent to find some novel high-confidence drug targets in Mtb for discovering the effective anti-TB agents.Thioredoxin reductase(TrxR)has been identified to be a highly viable target for anti-TB drugs for its important role in protecting the pathogen from thiol-specific oxidizing stress,regulating intracellular dithiol/disulfide homeostasis and DNA replication and repair.In the present work,a near-infrared(NIR)fluorescent probe DDAT was developed for the detection of TrxR activity and used to high-throughput screen the TrxR inhibitors from natural products.Two screened TrxR inhibitors from Sappan Lignum and microbial metabolites that were further used to inhibit Mycobacterium tuberculosis.All the results indicate that DDAT is a practical fluorescent molecular tool for the discovery of potential anti-TB drugs.展开更多
One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both prote...One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both proteinDNA as well as protein–protein interactions for the regulatory network.To detect such interactions in CBC resistant regulation,a citrus high-throughput screening system with 203 CBC-inducible transcription factors(TFs),were developed.Screening the upstream regulators of target by yeast-one hybrid(Y1H)methods was also performed.A regulatory module of CBC resistance was identified based on this system.One TF(CsDOF5.8)was explored due to its interactions with the 1-kb promoter fragment of CsPrx25,a resistant gene of CBC involved in reactive oxygen species(ROS)homeostasis regulation.Electrophoretic mobility shift assay(EMSA),dual-LUC assays,as well as transient overexpression of CsDOF5.8,further validated the interactions and transcriptional regulation.The CsDOF5.8–CsPrx25 promoter interaction revealed a complex pathway that governs the regulation of CBC resistance via H2O2homeostasis.The high-throughput Y1H/Y2H screening system could be an efficient tool for studying regulatory pathways or network of CBC resistance regulation.In addition,it could highlight the potential of these candidate genes as targets for efforts to breed CBC-resistant citrus varieties.展开更多
Objective:We propose a solution that is backed by cloud computing,combines a series of AI neural networks of computer vision;is capable of detecting,highlighting,and locating breast lesions from a live ultrasound vide...Objective:We propose a solution that is backed by cloud computing,combines a series of AI neural networks of computer vision;is capable of detecting,highlighting,and locating breast lesions from a live ultrasound video feed,provides BI-RADS categorizations;and has reliable sensitivity and specificity.Multiple deep-learning models were trained on more than 300,000 breast ultrasound images to achieve object detection and regions of interest classification.The main objective of this study was to determine whether the performance of our Al-powered solution was comparable to that of ultrasound radiologists.Methods:The noninferiority evaluation was conducted by comparing the examination results of the same screening women between our AI-powered solution and ultrasound radiologists with over 10 years of experience.The study lasted for one and a half years and was carried out in the Duanzhou District Women and Children's Hospital,Zhaoqing,China.1,133 females between 20 and 70 years old were selected through convenience sampling.Results:The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value were 93.03%,94.90%,90.71%,92.68%,and 93.48%,respectively.The area under the curve(AUC)for all positives was 0.91569 and the AUC for all negatives was 0.90461.The comparison indicated that the overall performance of the AI system was comparable to that of ultrasound radiologists.Conclusion:This innovative AI-powered ultrasound solution is cost-effective and user-friendly,and could be applied to massive breast cancer screening.展开更多
Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown th...Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.展开更多
In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stabili...In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stability at the interface effectively.LiTi_(2)(PO_(4))_(3),a fast ion conductor with high ionic conductivity approaching 10^(-3)S·cm^(-1),is adopted as the coating materials in this study.The crystal and electronic structures,as well as the Li^+ion migration properties are evaluated for LTP and its doped derivatives based on density functional theory(DFT)and bond valence(BV)method.Substituting part of Ti sites with element Mn,Fe,or Mg in LTP can improve the electronic conductivity of LTP while does not decrease its high ionic conductivity.In this way,the coating materials with both high ionic conductivities and electronic conductivities can be prepared for all-solid-state lithium batteries to improve the ion and electron transport properties at the interface.展开更多
The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer...The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer cells. To attain this goal, the authors utilize many drugs to interact with mitogen-activated protein kinase kinase-1 （MEK1） in MAPK, and use computer aided drug design （CADD） to analyze the ligand activities of proteins in MEKL The results show that in these drugs, the aromatic group in the terminal of the protein and the PHE209 will induce the stacking force, which is highly related to the actual activities of these drugs.展开更多
The revolutionary development of machine learning(ML),data science,and analytics,coupled with its application in material science,stands as a significant milestone of the scientific community over the last decade.Inve...The revolutionary development of machine learning(ML),data science,and analytics,coupled with its application in material science,stands as a significant milestone of the scientific community over the last decade.Investigating active,stable,and cost-efficient catalysts is crucial for oxygen evolution reaction owing to the significance in a range of electrochemical energy co nversion processes.In this work,we have demonstrated an efficient approach of high-throughput screening to find stable transition metal oxides under acid condition for high-performance oxygen evolution reaction(OER)catalysts through density functional theory(DFT)calculation and a machine learning algorithm.A methodology utilizing both the Materials Project database and DFT calculations was introduced to assess the acid stability under specific reaction conditions.Building upon this,OER catalytic activity of acid-stable materials was examined,highlighting potential OER catalysts that meet the required properties.We identified IrO_(2),Fe(SbO_(3))_(2),Co(SbO_(3))_(2),Ni(SbO_(3))_(2),FeSbO_(4),Fe(SbO_(3))4,MoWO_(6),TiSnO_(4),CoSbO_(4),and Ti(WO_(4))_(2)as promising catalysts,several of which have already been experimentally discovered for their robust OER performance,while others are novel for experimental exploration,thereby broadening the chemical scope for efficient OER electrocatalysts.Descriptors of the bond length of TM-O and the first ionization energy were used to unveil the OER activity origin.From the calculated results,guidance has been derived to effectively execute advanced high-throughput screenings for the discovery of catalysts with favorable properties.Furthermore,the intrinsic correlation between catalytic performance and various atomic and structural factors was elucidated using the ML algorithm.Through these approaches,we not only streamline the choice of the promising electrocatalysts but also offer insights for the design of varied catalyst models and the discovery of superior catalysts.展开更多
Colorectal cancer(CRC)has high incidence and mortality rates,and the em-ergence and application of CRC screening have helped us effectively control the occurrence and development of CRC.Currently,common international ...Colorectal cancer(CRC)has high incidence and mortality rates,and the em-ergence and application of CRC screening have helped us effectively control the occurrence and development of CRC.Currently,common international screening methods include tests based on feces and blood,and examination methods that allow for visualization,such as sigmoidoscopy and colonoscopy.Some methods have been widely used,whereas others such as multi-target stool RNA test are still being explored and developed,and are expected to become front-line screening methods for CRC in the future.The choice of screening method is affected by external conditions and the patients'situation,and the clinician must choose an appropriate strategy according to the actual situation and the patient's wishes.This article introduces various CRC screening methods and analyzes the factors relevant to the screening strategy.展开更多
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
文摘Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.
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 Scientific and technological innovation project of Guangdong Provincial Drug Administration(ZA20230069,2024ZDZ04)the Science and Technology Plan Project of Guangdong Provincial(2023A1111120025).
文摘Background:Risk substances in cosmetics have long been associated with adverse reactions.However,as risk substances become more concealed and diversified,conventional targeted analysis methods are no longer sufficient to meet regulatory requirements.Objective:To construct a rapid and effective non-targeted screening method for the identification of risk substances,and to provide a high-throughput method for toxicity assessment.Methods:Molecular networking was utilized for the non-targeted screening of risk substances in facial skincare products,and the toxicity of these risk substances was evaluated through molecular docking and quantitative structure-activity relationship(QSAR)models.Results:Through molecular networking,we identified seven known prohibited ingredients,six of which were confirmed using standard substances.In addition,17 potential risk substances were discovered within molecular clusters containing prohibited ingredients,including antibiotics,antihistamines,and phthalates,etc.Notably,chloramphenicol base and N-desmethyl chlorpheniramine exhibited stronger binding affinity to keratin 5/14 than chloramphenicol and chlorpheniramine through molecular docking,respectively.Additionally,toxicity prediction results indicated that the carcinogenicity of antibiotics presented gender differences in mice and rats,and two chlorpheniramine derivatives also showed carcinogenicity in mice.Moreover,of the 24 compounds,11 showed skin sensitization,while 14 caused skin irritation.Furthermore,half of these compounds demonstrated potential developmental toxicity,and only 4-nitrobenzenethiol was found to be mutagenic.Conclusion:In this study,we developed a visualization strategy for non-targeted screening of risk substances and a high-throughput method for initial toxicity assessment of risk substances.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Small Groups Project under Grant No.R.G.P.1/191/43.
文摘Malignant melanoma is characterized by both genetic and molecular alterations that activate phosphoinositide 3-kinase(PI3K),and RAS/BRAF pathways.In this work,through diversity-based high-throughput virtual screening we identified a lead molecule that selectively targets PI3K and BRAF^(V600E) kinases.Computational screening,Molecular dynamics simulation and MMPBSA calculations were performed.PI3K and BRAF^(V600E) kinase inhibition was done.A375 and G-361 cells were used for in vitro cellular analysis to determine antiproliferative effects,annexin V binding,nuclear fragmentation and cell cycle analysis.Computational screening of small molecules indicates compound CB-006-3 selectively targets PI3KCG(gamma subunit),PI3KCD(delta subunit)and BRAF^(V600E).Molecular dynamics simulation and MMPBSA bases binding free energy calculations predict a stable binding of CB-006-3 to the active sites of PI3K and BRAF^(V600E).The compound effectively inhibited PI3KCG,PI3KCD and BRAF^(V600E)kinases with respective IC50 values of 75.80,160.10 and 70.84 nM.CB-006-3 controlled the proliferation of A375 and G-361 cells with GI50 values of 223.3 and 143.6 nM,respectively.A dose dependent increase in apoptotic cell population and sub G0/G1 phase of cell cycle were also observed with the compound treatment in addition to observed nuclear fragmentation in these cells.Furthermore,CB-006-3 inhibited BRAF^(V600E),PI3KCD and PI3KCG in both melanoma cells.Collectively,based on the computational modeling and in vitro validations,we propose CB-006-3 as a lead candidate for selectively targeting PI3K and mutant BRAF^(V600E) to inhibit melanoma cell proliferation.Further experimental validations,including pharmacokinetic evaluations in mouse models will identify the druggability of the proposed lead candidate for further development as a therapeutic agent for treating melanoma.
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financially supported by the National Natural Science Foundation of China(Nos.52301011,52231008,52142304,52177220,52101182 and U23A200767)Hainan Provincial Natural Science Foundation of China(No.524QN226)+2 种基金the Key research and development program of Hainan province(No.ZDYF2022GXJS006)the Starting Research Fund from the Hainan University(No.KYQD(ZR)23026)the International Science&Technology Cooperation Program of Hainan Province(No.GHYF2023007)。
文摘Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne materials can offer stable adsorption sites for single metal atoms.To investigate the influence of the sp/sp^(2)hybrid carbon ratio on the electrocatalytic NRR performance of graphyne,a high-throughput screening of 81 catalysts,with27 transition metals loaded on graphyne(GY1),graphdiyne(GY2),and graphtriyne(GY3),was conducted using firstprinciples calculations.The results of the screening revealed that Ti@GY3 exhibits the lowest energy barrier for the rate-determining step(0.32 eV)in NRR.Further,to explore the impact of different sp/sp^(2)-hybridized carbon ratios on the catalytic activity of SACs,the mechanism of nitrogen(N_(2))adsorption,activation,and the comprehensive pathway of NRR on Ti@GY1,Ti@GY2,and Ti@GY3 was systematically investigated.It was found that the ratio of sp/sp^(2)-hybridized carbon can significantly modulate the d-band center of the metal,thus affecting the energy barrier of the rate-determining step in NRR,decreasing from Ti@GY1(0.59 eV)to Ti@GY2(0.49 eV);and further to Ti@GY3(0.32 eV).Additionally,the Hall conductance was found to increase with the bias voltage in the range of 0.4-1 V,as calculated by Nanodcal software,demonstrating an improvement in the conductivity of the SAC.In summary,this work provides theoretical guidance for modulating the electrocatalytic nitrogen reduction activity of SACs by varying the ratio of sp/sp^(2)hybrid carbon,with Ti@GY3 showing potential as an excellent NRR catalyst.
基金supported by the National Key R&D Program of China(2022YFA1503103)the National Natural Science Foundation of China(22033002,92261112,22203046)+2 种基金the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY221128)the Six Talent Peaks Project in Jiangsu Province(XCL-104)the open research fund of Key Laboratory of Quantum Materials and Devices(Southeast University)
文摘Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect catalytic performance in the vast catalyst space remains challenging for people.Herein,to accurately identify the factors that affect the performance of N2 reduction,we apply interpretable machine learning(ML)to analyze high-throughput screening results,which is also suited to other surface reactions in catalysis.To expound on the paradigm,33 promising catalysts are screened from 168 carbon-supported candidates,specifically single-atom catalysts(SACs)supported by a BC_(3)monolayer(TM@V_(B/C)-N_(n)=_(0-3)-BC_(3))via high-throughput screening.Subsequently,the hybrid sampling method and XGBoost model are selected to classify eligible and non-eligible catalysts.Through feature interpretation using Shapley Additive Explanations(SHAP)analysis,two crucial features,that is,the number of valence electrons(N_(v))and nitrogen substitution(N_(n)),are screened out.Combining SHAP analysis and electronic structure calculations,the synergistic effect between an active center with low valence electron numbers and reasonable C-N coordination(a medium fraction of nitrogen substitution)can exhibit high catalytic performance.Finally,six superior catalysts with a limiting potential lower than-0.4 V are predicted.Our workflow offers a rational approach to obtaining key information on catalytic performance from high-throughput screening results to design efficient catalysts that can be applied to other materials and reactions.
基金the National Natural Science Foundation of China(Nos.81930112 and 82225048)Open Research Fund of the School of Chemistry and Chemical Engineering,Henan Normal University for support(No.2021YB07)Research on National Reference Material and Product Development of Natural Products(No.SG030801,Beijing Polytechnic)。
文摘Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensively drug resistant TB cases.It is very urgent to find some novel high-confidence drug targets in Mtb for discovering the effective anti-TB agents.Thioredoxin reductase(TrxR)has been identified to be a highly viable target for anti-TB drugs for its important role in protecting the pathogen from thiol-specific oxidizing stress,regulating intracellular dithiol/disulfide homeostasis and DNA replication and repair.In the present work,a near-infrared(NIR)fluorescent probe DDAT was developed for the detection of TrxR activity and used to high-throughput screen the TrxR inhibitors from natural products.Two screened TrxR inhibitors from Sappan Lignum and microbial metabolites that were further used to inhibit Mycobacterium tuberculosis.All the results indicate that DDAT is a practical fluorescent molecular tool for the discovery of potential anti-TB drugs.
基金funded by the National Key Research and Development Program of China(2022YFD1201600)the earmarked fund for the China Agriculture Research System(CARS-26)+1 种基金the Fundamental Research Funds for the Central Universities,China(SWU-XDJH202308)the Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJQN202001418)。
文摘One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both proteinDNA as well as protein–protein interactions for the regulatory network.To detect such interactions in CBC resistant regulation,a citrus high-throughput screening system with 203 CBC-inducible transcription factors(TFs),were developed.Screening the upstream regulators of target by yeast-one hybrid(Y1H)methods was also performed.A regulatory module of CBC resistance was identified based on this system.One TF(CsDOF5.8)was explored due to its interactions with the 1-kb promoter fragment of CsPrx25,a resistant gene of CBC involved in reactive oxygen species(ROS)homeostasis regulation.Electrophoretic mobility shift assay(EMSA),dual-LUC assays,as well as transient overexpression of CsDOF5.8,further validated the interactions and transcriptional regulation.The CsDOF5.8–CsPrx25 promoter interaction revealed a complex pathway that governs the regulation of CBC resistance via H2O2homeostasis.The high-throughput Y1H/Y2H screening system could be an efficient tool for studying regulatory pathways or network of CBC resistance regulation.In addition,it could highlight the potential of these candidate genes as targets for efforts to breed CBC-resistant citrus varieties.
文摘Objective:We propose a solution that is backed by cloud computing,combines a series of AI neural networks of computer vision;is capable of detecting,highlighting,and locating breast lesions from a live ultrasound video feed,provides BI-RADS categorizations;and has reliable sensitivity and specificity.Multiple deep-learning models were trained on more than 300,000 breast ultrasound images to achieve object detection and regions of interest classification.The main objective of this study was to determine whether the performance of our Al-powered solution was comparable to that of ultrasound radiologists.Methods:The noninferiority evaluation was conducted by comparing the examination results of the same screening women between our AI-powered solution and ultrasound radiologists with over 10 years of experience.The study lasted for one and a half years and was carried out in the Duanzhou District Women and Children's Hospital,Zhaoqing,China.1,133 females between 20 and 70 years old were selected through convenience sampling.Results:The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value were 93.03%,94.90%,90.71%,92.68%,and 93.48%,respectively.The area under the curve(AUC)for all positives was 0.91569 and the AUC for all negatives was 0.90461.The comparison indicated that the overall performance of the AI system was comparable to that of ultrasound radiologists.Conclusion:This innovative AI-powered ultrasound solution is cost-effective and user-friendly,and could be applied to massive breast cancer screening.
基金supported by the National Natural Science Foundation of China (22078004)the Research Development Fund from Xi’an Jiaotong-Liverpool University (RDF-16-02-03 and RDF15-01-23)key program special fund (KSF-E-03)。
文摘Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation.
基金Project supported by the National Natural Science Foundation of China(Grant No.51772321)the National Key R&D Program of China(Grant No.2017YFB0701602)the Youth Innovation Promotion Association,China(Grant No.2016005)。
文摘In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle performance.Cathode coatings are helpful to reduce the impedance and increase the stability at the interface effectively.LiTi_(2)(PO_(4))_(3),a fast ion conductor with high ionic conductivity approaching 10^(-3)S·cm^(-1),is adopted as the coating materials in this study.The crystal and electronic structures,as well as the Li^+ion migration properties are evaluated for LTP and its doped derivatives based on density functional theory(DFT)and bond valence(BV)method.Substituting part of Ti sites with element Mn,Fe,or Mg in LTP can improve the electronic conductivity of LTP while does not decrease its high ionic conductivity.In this way,the coating materials with both high ionic conductivities and electronic conductivities can be prepared for all-solid-state lithium batteries to improve the ion and electron transport properties at the interface.
文摘The mitogen-activated protein kinase （MAPK） cell signal transduction pathways play a key role in determining the survival of cells. If these pathways can be controlled, they will prohibit the proliferation of cancer cells. To attain this goal, the authors utilize many drugs to interact with mitogen-activated protein kinase kinase-1 （MEK1） in MAPK, and use computer aided drug design （CADD） to analyze the ligand activities of proteins in MEKL The results show that in these drugs, the aromatic group in the terminal of the protein and the PHE209 will induce the stacking force, which is highly related to the actual activities of these drugs.
基金supported by the Soonchunhyang University Research Fundsupported by the Supercomputing Center/Korea Institute of Science and Technology Information with supercomputing resources(KSC-2022-CRE-0354)+5 种基金supported by the “Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2021RIS-004)a study on the“Leaders in INdustry-university Cooperation 3.0”Project,supported by the Ministry of Education and National Research Foundation of Koreafunded by BK 21 FOUR(Fostering Outstanding Universities for Research)(5199991614564)supported by the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(CRC-20-01-NFRI)supported by the research fund of Hanyang University(HY-2022-3095)supported by the Technology Innovation Program(20023140,Development of an integrated low-power,highperformance,cryogenic high-vacuum exhaust system for analyzing impurity concentrations in the process in real time)funded By the Ministry of Trade,Industry&Energy(MOTIE,Korea)。
文摘The revolutionary development of machine learning(ML),data science,and analytics,coupled with its application in material science,stands as a significant milestone of the scientific community over the last decade.Investigating active,stable,and cost-efficient catalysts is crucial for oxygen evolution reaction owing to the significance in a range of electrochemical energy co nversion processes.In this work,we have demonstrated an efficient approach of high-throughput screening to find stable transition metal oxides under acid condition for high-performance oxygen evolution reaction(OER)catalysts through density functional theory(DFT)calculation and a machine learning algorithm.A methodology utilizing both the Materials Project database and DFT calculations was introduced to assess the acid stability under specific reaction conditions.Building upon this,OER catalytic activity of acid-stable materials was examined,highlighting potential OER catalysts that meet the required properties.We identified IrO_(2),Fe(SbO_(3))_(2),Co(SbO_(3))_(2),Ni(SbO_(3))_(2),FeSbO_(4),Fe(SbO_(3))4,MoWO_(6),TiSnO_(4),CoSbO_(4),and Ti(WO_(4))_(2)as promising catalysts,several of which have already been experimentally discovered for their robust OER performance,while others are novel for experimental exploration,thereby broadening the chemical scope for efficient OER electrocatalysts.Descriptors of the bond length of TM-O and the first ionization energy were used to unveil the OER activity origin.From the calculated results,guidance has been derived to effectively execute advanced high-throughput screenings for the discovery of catalysts with favorable properties.Furthermore,the intrinsic correlation between catalytic performance and various atomic and structural factors was elucidated using the ML algorithm.Through these approaches,we not only streamline the choice of the promising electrocatalysts but also offer insights for the design of varied catalyst models and the discovery of superior catalysts.
基金Supported by Liaoning Province Applied Basic Research Program Joint Program Project,No.2022JH2/101500076Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program,No.RC200438Tree Planting Program of Shengjing Hospital,No.M1595.
文摘Colorectal cancer(CRC)has high incidence and mortality rates,and the em-ergence and application of CRC screening have helped us effectively control the occurrence and development of CRC.Currently,common international screening methods include tests based on feces and blood,and examination methods that allow for visualization,such as sigmoidoscopy and colonoscopy.Some methods have been widely used,whereas others such as multi-target stool RNA test are still being explored and developed,and are expected to become front-line screening methods for CRC in the future.The choice of screening method is affected by external conditions and the patients'situation,and the clinician must choose an appropriate strategy according to the actual situation and the patient's wishes.This article introduces various CRC screening methods and analyzes the factors relevant to the screening strategy.
