Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of...Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of complex diseases,with some even achieving clinical translation.Changes in the overall size,shape,boundary,and other morphological features of organoids provide a noninvasive method for assessing organoid drug sensitivity.However,the precise segmentation of organoids in bright-field microscopy images is made difficult by the complexity of the organoid morphology and interference,including overlapping organoids,bubbles,dust particles,and cell fragments.This paper introduces the precision organoid segmentation technique(POST),which is a deep-learning algorithm for segmenting challenging organoids under simple bright-field imaging conditions.Unlike existing methods,POST accurately segments each organoid and eliminates various artifacts encountered during organoid culturing and imaging.Furthermore,it is sensitive to and aligns with measurements of organoid activity in drug sensitivity experiments.POST is expected to be a valuable tool for drug screening using organoids owing to its capability of automatically and rapidly eliminating interfering substances and thereby streamlining the organoid analysis and drug screening process.展开更多
Nasopharyngeal carcinoma(NPC)is a malignant tumor prevalent in southern China and Southeast Asia,where its early detection is crucial for improving patient prognosis and reducing mortality rates.However,existing scree...Nasopharyngeal carcinoma(NPC)is a malignant tumor prevalent in southern China and Southeast Asia,where its early detection is crucial for improving patient prognosis and reducing mortality rates.However,existing screening methods suffer from limitations in accuracy and accessibility,hindering their application in large-scale population screening.In this work,a surface-enhanced Raman spectroscopy(SERS)-based method was established to explore the profiles of different stratified components in saliva from NPC and healthy subjects after fractionation processing.The study findings indicate that all fractionated samples exhibit diseaseassociated molecular signaling differences,where small-molecule(molecular weight cut-offvalue is 10 kDa)demonstrating superior classification capabilities with sensitivity of 90.5%and speci-ficity of 75.6%,area under receiver operating characteristic(ROC)curve of 0:925±0:031.The primary objective of this study was to qualitatively explore patterns in saliva composition across groups.The proposed SERS detection strategy for fractionated saliva offers novel insights for enhancing the sensitivity and reliability of noninvasive NPC screening,laying the foundation for translational application in large-scale clinical settings.展开更多
Insects represent emerging sources of bioactive peptides and functional materials.Mantidis Oötheca(Sang-Piao-Xiao in Chinese,SPX)serves as an insect-derived medicine for treating kidney disease.This study demonst...Insects represent emerging sources of bioactive peptides and functional materials.Mantidis Oötheca(Sang-Piao-Xiao in Chinese,SPX)serves as an insect-derived medicine for treating kidney disease.This study demonstrated that supernatant(SPX)improved kidney function in adriamycin(ADR)-induced nephropathy mice model.Transcriptomic analysis revealed that SPX inhibited complement activation by targeting the MASP1-C3/C3a receptor(C3aR)pathway.Peptidomic analysis identified 304 peptides from SPX,with 49 peptides selected for evaluation using prediction tools and molecular docking with complement core protein C3.Three peptides(PMGFPFDR,FNDPK,AAQFFNR)exhibiting docking scores below-8.0 were synthesized to verify complement inhibition and anti-fibrotic activities.The synthetic peptide AAQFFNR demonstrated complement inhibitory activity,with an inhibitory complement hemolytic 50%(ICH_(50))value of 24.54μmol·L^(-1),and exhibited superior protective effects in ADR-induced HK-2 cells.Surface plasmon resonance(SPR)assay revealed direct interaction between AAQFFNR and complement C3 with K_(d)value of 16.8μmol·L^(-1).The reno-protective effect of AAQFFNR was subsequently verified in ADR-induced mice.This research provides initial evidence that complement C3-inhibiting peptides from insects demonstrate potential in preventing nephropathy through in silico and in vivo validation approaches.展开更多
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 equilibrium dynamics and nonlinear rheology of unentangled polymer blends remain inadequately understood,especially regarding the influence of short-chain matrix length N_(S) on the structure and rheological behav...The equilibrium dynamics and nonlinear rheology of unentangled polymer blends remain inadequately understood,especially regarding the influence of short-chain matrix length N_(S) on the structure and rheological behavior of dispersed long chains.Using molecular dynamics simulations based on the Kremer-Grest model,we systematically explore the N_(S)-dependence of static conformations,equilibrium dynamics,and nonlinear shear responses in unentangled long-chain/short-chain polymer blends.Our results demonstrate a decoupling between the static and dynamic sensitivity to N_(S):while the static chain size,R_g,follows Flory theory with slight swelling at small N_(S) due to incomplete excluded volume screening,the diffusion coefficient,D,and the relaxation time,τ_(0),exhibit a strong,non-monotonic N_(S)-dependence,transitioning from monomeric friction dominance at small N_(S) to collective segmental rearrangement at large N_(S).Additionally,we observe partial decoupling between the viscous and normal stress responses:while the zero-shear viscosity,η,is strongly N_(S)-dependent,the first and second normal stress coefficients,Ψ_(1) and Ψ_(2),collapse onto universal curves when scaled by the dimensionless shear rate,γτ_(0),suggesting a common mechanism of orientation and stretching.Under shear,long chains compress in the vorticity direction λ_(z)~Wi^(-0.2),which reduces collision frequency and contributes to shear thinning,while the scaling of weaker orientation resistance m_(G)~Wi^(0.35)reflects hydrodynamic screening by the short-chain matrix.These findings highlight the limitations of single-chain models and emphasize the necessity of considering N_(S)-dependent matrix dynamics and flow-induced structural changes in understanding the rheology of unentangled polymer blends.展开更多
Background Frailty is common and significantly impacts prognosis in heart failure(HF). The Vulnerable Elders Survey-13(VES-13), widely used in oncogeriatrics and public health, remains unexplored as a frailty screenin...Background Frailty is common and significantly impacts prognosis in heart failure(HF). The Vulnerable Elders Survey-13(VES-13), widely used in oncogeriatrics and public health, remains unexplored as a frailty screening tool in HF outpatients. In this study, we prospectively evaluated VES-13 against a multimodal screening assessment in detecting frailty and predicting individual risk of adverse prognosis.Methods Frailty was assessed at the initial visit using both a multimodal approach, incorporating Barthel Index, Older American Resources and Services scale, Pfeiffer Test, abbreviated Geriatric Depression Scale, age > 85 years, lacking support systems,and VES-13. Patients scoring ≥ 3 on VES-13 or meeting at least one multimodal criterion were classified as frail. Endpoints included all-cause mortality, a composite of death or HF hospitalization, and recurrent HF hospitalizations.Results A total of 301 patients were evaluated. VES-13 identified 40.2% as frail and the multimodal assessment 33.2%. In Cox regression analyses, frailty identified by VES-13 showed greater prognostic significance than the multimodal assessment for allcause mortality(HR = 3.70 [2.15–6.33], P < 0.001 vs. 2.40 [1.46–4.0], P = 0.001) and the composite endpoint(HR = 3.13 [2.02–4.84], P< 0.001 vs. 1.96 [1.28–2.99], P = 0.002). Recurrent HF hospitalizations were four times more frequent in VES-13 frail patients while two times in those identified as frail by the multimodal assessment. Additionally, stratifying patients by VES-13 tertiles provided robust risk differentiation.Conclusions VES-13, a simple frailty tool, outperformed a comprehensive multimodal assessment and could be easily integrated into routine HF care, highlighting its clinical utility in identifying patients at risk for poor outcomes.展开更多
Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual pat...Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.展开更多
The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb...The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.展开更多
Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).Ho...Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).展开更多
Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are...Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.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
The exact worldwide prevalence of gastroesophageal reflux disease(GERD)re-mains uncertain,despite its recognition as a common condition.This conundrum arises primarily from the lack of a standardized definition for GE...The exact worldwide prevalence of gastroesophageal reflux disease(GERD)re-mains uncertain,despite its recognition as a common condition.This conundrum arises primarily from the lack of a standardized definition for GERD.The gold standard diagnostic tests for GERD,such as pH impedance testing and endo-scopy,are cumbersome and impractical for assessing community prevalence.Consequently,most epidemiological studies rely on symptom-based screening tools.GERD symptoms can be both esophageal and extraesophageal,varying widely among individuals.This variability has led to multiple symptom-based definitions of GERD,with no consensus,resulting in prevalence estimates ranging from 5%to 25%worldwide.Most systematic reviews define GERD as experi-encing heartburn and/or regurgitation at least once weekly,yielding a calculated prevalence of 13.98%.In 2017,the global age-standardized prevalence of GERD was estimated at 8819 per 100000 people(95%confidence interval:7781-9863),a figure that has remained stable from 1990 to 2017.Prevalence increases with age,leading to more years lived with disability.GERD significantly impairs quality of life and can lead to multiple complications.Additionally,it imposes a severe economic burden,with the United States alone estimated to spend around 10 billion dollars annually on diagnosis and treatment.In summary,GERD preva-lence varies greatly by region and even within different areas of the same province.Determining the exact prevalence is challenging due to inconsistent diagnostic criteria.However,it is well-documented that GERD poses a significant global burden,affecting the quality of life of individuals and creating a substantial healthcare cost.展开更多
The problem of gastric cancer(GC)prevention remains relevant for a long time.Various methods of population serological screening of atrophic gastritis and precancerous changes in the gastric mucosa have been created a...The problem of gastric cancer(GC)prevention remains relevant for a long time.Various methods of population serological screening of atrophic gastritis and precancerous changes in the gastric mucosa have been created at present.Modern endoscopic and morphological methods of verification of the diagnosis of precancerous diseases and changes in the gastric mucosa have been introduced into the practice of gastroenterologists and oncologists.GC risk stratification systems allow the formation of risk groups that require population screening.Practical hints for population serological screening of atrophic gastritis,endoscopic and morphological verification of precancerous changes and diseases of the stomach recommend using it:When developing state programs for the prevention of stomach cancer;when implementing preventive measures for stomach cancer by doctors of all specialties;the authors also offer the possibility of use by anyone over the age of 40,provided that they seek methodological help from their doctor;in the work of health schools in any medical and preventive institutions.The use of an assessment system of certain risk factor signatures with prognostic value would add significant assistance to preventive measures against GC.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
In the global transition towards sustainable energy sources,hydrogen energy has emerged as an indispensable pillar in reshaping the energy landscape,owing to its environmental sustainability,zero emissions,and high ef...In the global transition towards sustainable energy sources,hydrogen energy has emerged as an indispensable pillar in reshaping the energy landscape,owing to its environmental sustainability,zero emissions,and high efficiency.Nevertheless,the large-scale deployment of hydrogen energy is confronted with substantial technical barriers in storage and transportation.Although contemporary research has shifted focus to the development of highly efficient hydrogen storage materials,conventional material design concepts remain predominantly empirical,typically relying on trial-and-error methodologies.Importantly,the widespread application of artificial intelligence technologies in accelerating materials discovery and optimization has attracted considerable attention.This review provides a comprehensive overview of the latest advancements in hydrogen storage technologies,with an emphasis on the synergistic application of high-throughput screening and machine learning in solid-state hydrogen storage materials.These approaches demonstrate exceptional potential in accurately predicting hydrogen storage properties,optimizing material performance,and accelerating the development of innovative hydrogen storage materials.Specifically,we discuss in detail the essential role of artificial intelligence in developing hydrogen storage materials such as metal hydrides,alloys,carbon materials,metal–organic frameworks,and zeolites.Moreover,underground hydrogen storage is further explored as a scalable renewable energy storage solution,particularly in terms of optimizing storage parameters and performance prediction.By systematically analyzing the limitations of existing hydrogen storage approaches and the transformative potential of artificial intelligence-driven methods,this review offers insights into the discovery and optimization of high-performance hydrogen storage materials,contributing to sustainable global energy development and technological innovation.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
This study discusses the impact of the increasing use of colonoscopy on the trends of colorectal cancer(CRC)in Korea.Different views are raised on the research methods and conclusions of Kim et al.It emphasizes the ne...This study discusses the impact of the increasing use of colonoscopy on the trends of colorectal cancer(CRC)in Korea.Different views are raised on the research methods and conclusions of Kim et al.It emphasizes the need to carefully consider the balance between the benefits of early detection and the risks of over-screening.This letter also suggests directions for future research and policy considerations in the field of CRC screening and prevention in Korea.展开更多
As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as l...As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.展开更多
基金supported by the National Key R&D Program of China(No.2022YFC2504403)the National Natural Science Foundation of China(No.62172202)+1 种基金the Experiment Project of China Manned Space Program(No.HYZHXM01019)the Fundamental Research Funds for the Central Universities from Southeast University(No.3207032101C3)。
文摘Organoids possess immense potential for unraveling the intricate functions of human tissues and facilitating preclinical disease treatment.Their applications span from high-throughput drug screening to the modeling of complex diseases,with some even achieving clinical translation.Changes in the overall size,shape,boundary,and other morphological features of organoids provide a noninvasive method for assessing organoid drug sensitivity.However,the precise segmentation of organoids in bright-field microscopy images is made difficult by the complexity of the organoid morphology and interference,including overlapping organoids,bubbles,dust particles,and cell fragments.This paper introduces the precision organoid segmentation technique(POST),which is a deep-learning algorithm for segmenting challenging organoids under simple bright-field imaging conditions.Unlike existing methods,POST accurately segments each organoid and eliminates various artifacts encountered during organoid culturing and imaging.Furthermore,it is sensitive to and aligns with measurements of organoid activity in drug sensitivity experiments.POST is expected to be a valuable tool for drug screening using organoids owing to its capability of automatically and rapidly eliminating interfering substances and thereby streamlining the organoid analysis and drug screening process.
基金financially supported by National Natural Science Foundation ofChina(No.12374405)Provincial Science Foundation for Distinguished Young Scholars of Fujian(No.2024J010024)+1 种基金Natural Science Foundation of Fujian Province of China(No.2023J011267)Major Research Projects for Young and Middle-aged Researchers of Fujian Provincial Health Commission(No.2021ZQNZD010).
文摘Nasopharyngeal carcinoma(NPC)is a malignant tumor prevalent in southern China and Southeast Asia,where its early detection is crucial for improving patient prognosis and reducing mortality rates.However,existing screening methods suffer from limitations in accuracy and accessibility,hindering their application in large-scale population screening.In this work,a surface-enhanced Raman spectroscopy(SERS)-based method was established to explore the profiles of different stratified components in saliva from NPC and healthy subjects after fractionation processing.The study findings indicate that all fractionated samples exhibit diseaseassociated molecular signaling differences,where small-molecule(molecular weight cut-offvalue is 10 kDa)demonstrating superior classification capabilities with sensitivity of 90.5%and speci-ficity of 75.6%,area under receiver operating characteristic(ROC)curve of 0:925±0:031.The primary objective of this study was to qualitatively explore patterns in saliva composition across groups.The proposed SERS detection strategy for fractionated saliva offers novel insights for enhancing the sensitivity and reliability of noninvasive NPC screening,laying the foundation for translational application in large-scale clinical settings.
基金supported by the National Natural Science Foundation of China(No.82104353)China Postdoctoral Science Foundation funded project(No.2022M711680).
文摘Insects represent emerging sources of bioactive peptides and functional materials.Mantidis Oötheca(Sang-Piao-Xiao in Chinese,SPX)serves as an insect-derived medicine for treating kidney disease.This study demonstrated that supernatant(SPX)improved kidney function in adriamycin(ADR)-induced nephropathy mice model.Transcriptomic analysis revealed that SPX inhibited complement activation by targeting the MASP1-C3/C3a receptor(C3aR)pathway.Peptidomic analysis identified 304 peptides from SPX,with 49 peptides selected for evaluation using prediction tools and molecular docking with complement core protein C3.Three peptides(PMGFPFDR,FNDPK,AAQFFNR)exhibiting docking scores below-8.0 were synthesized to verify complement inhibition and anti-fibrotic activities.The synthetic peptide AAQFFNR demonstrated complement inhibitory activity,with an inhibitory complement hemolytic 50%(ICH_(50))value of 24.54μmol·L^(-1),and exhibited superior protective effects in ADR-induced HK-2 cells.Surface plasmon resonance(SPR)assay revealed direct interaction between AAQFFNR and complement C3 with K_(d)value of 16.8μmol·L^(-1).The reno-protective effect of AAQFFNR was subsequently verified in ADR-induced mice.This research provides initial evidence that complement C3-inhibiting peptides from insects demonstrate potential in preventing nephropathy through in silico and in vivo validation approaches.
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financially supported by the National Natural Science Foundation of China(Nos.22341304,22303100 and 12205270)the National Key R&D Program of China(Nos.2023YFA1008800 and 2020YFA0713601)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDC0180303)。
文摘The equilibrium dynamics and nonlinear rheology of unentangled polymer blends remain inadequately understood,especially regarding the influence of short-chain matrix length N_(S) on the structure and rheological behavior of dispersed long chains.Using molecular dynamics simulations based on the Kremer-Grest model,we systematically explore the N_(S)-dependence of static conformations,equilibrium dynamics,and nonlinear shear responses in unentangled long-chain/short-chain polymer blends.Our results demonstrate a decoupling between the static and dynamic sensitivity to N_(S):while the static chain size,R_g,follows Flory theory with slight swelling at small N_(S) due to incomplete excluded volume screening,the diffusion coefficient,D,and the relaxation time,τ_(0),exhibit a strong,non-monotonic N_(S)-dependence,transitioning from monomeric friction dominance at small N_(S) to collective segmental rearrangement at large N_(S).Additionally,we observe partial decoupling between the viscous and normal stress responses:while the zero-shear viscosity,η,is strongly N_(S)-dependent,the first and second normal stress coefficients,Ψ_(1) and Ψ_(2),collapse onto universal curves when scaled by the dimensionless shear rate,γτ_(0),suggesting a common mechanism of orientation and stretching.Under shear,long chains compress in the vorticity direction λ_(z)~Wi^(-0.2),which reduces collision frequency and contributes to shear thinning,while the scaling of weaker orientation resistance m_(G)~Wi^(0.35)reflects hydrodynamic screening by the short-chain matrix.These findings highlight the limitations of single-chain models and emphasize the necessity of considering N_(S)-dependent matrix dynamics and flow-induced structural changes in understanding the rheology of unentangled polymer blends.
文摘Background Frailty is common and significantly impacts prognosis in heart failure(HF). The Vulnerable Elders Survey-13(VES-13), widely used in oncogeriatrics and public health, remains unexplored as a frailty screening tool in HF outpatients. In this study, we prospectively evaluated VES-13 against a multimodal screening assessment in detecting frailty and predicting individual risk of adverse prognosis.Methods Frailty was assessed at the initial visit using both a multimodal approach, incorporating Barthel Index, Older American Resources and Services scale, Pfeiffer Test, abbreviated Geriatric Depression Scale, age > 85 years, lacking support systems,and VES-13. Patients scoring ≥ 3 on VES-13 or meeting at least one multimodal criterion were classified as frail. Endpoints included all-cause mortality, a composite of death or HF hospitalization, and recurrent HF hospitalizations.Results A total of 301 patients were evaluated. VES-13 identified 40.2% as frail and the multimodal assessment 33.2%. In Cox regression analyses, frailty identified by VES-13 showed greater prognostic significance than the multimodal assessment for allcause mortality(HR = 3.70 [2.15–6.33], P < 0.001 vs. 2.40 [1.46–4.0], P = 0.001) and the composite endpoint(HR = 3.13 [2.02–4.84], P< 0.001 vs. 1.96 [1.28–2.99], P = 0.002). Recurrent HF hospitalizations were four times more frequent in VES-13 frail patients while two times in those identified as frail by the multimodal assessment. Additionally, stratifying patients by VES-13 tertiles provided robust risk differentiation.Conclusions VES-13, a simple frailty tool, outperformed a comprehensive multimodal assessment and could be easily integrated into routine HF care, highlighting its clinical utility in identifying patients at risk for poor outcomes.
基金supported by the Natural Science Foundation of Guangdong Province(No.2021B1515120053)Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515140166).
文摘Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.
基金supported by the Grant PID2021-126715OB-IOO financed by MCIN/AEI/10.13039/501100011033 and"ERDFA way of making Europe"by the Grant PI22CⅢ/00055 funded by Instituto de Salud CarlosⅢ(ISCⅢ)+6 种基金the UFIECPY 398/19(PEJ2018-004965) grant to RGS funded by AEI(Spain)the UFIECPY-396/19(PEJ2018-004961)grant financed by MCIN (Spain)FI23CⅢ/00003 grant funded by ISCⅢ-PFIS Spain) to PMMthe UFIECPY 328/22 (PEJ-2021-TL/BMD-21001) grant to LM financed by CAM (Spain)the grant by CAPES (Coordination for the Improvement of Higher Education Personnel)through the PDSE program (Programa de Doutorado Sanduiche no Exterior)to VSCG financed by MEC (Brazil)
文摘The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.
基金supported by the Jilin Science and Technology Development Program,China (20240602032RC)the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZD001)+1 种基金the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZY012)the Jilin Province Development and Reform Commission-Project for Improving the Independent Innovation Capacity of Major Grain Crops,China (2024C002)。
文摘Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).
基金supported by the Ministry of Science and Technology of China,No.2020AAA0109605(to XL)Meizhou Major Scientific and Technological Innovation PlatformsProjects of Guangdong Provincial Science & Technology Plan Projects,No.2019A0102005(to HW).
文摘Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.
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.
文摘The exact worldwide prevalence of gastroesophageal reflux disease(GERD)re-mains uncertain,despite its recognition as a common condition.This conundrum arises primarily from the lack of a standardized definition for GERD.The gold standard diagnostic tests for GERD,such as pH impedance testing and endo-scopy,are cumbersome and impractical for assessing community prevalence.Consequently,most epidemiological studies rely on symptom-based screening tools.GERD symptoms can be both esophageal and extraesophageal,varying widely among individuals.This variability has led to multiple symptom-based definitions of GERD,with no consensus,resulting in prevalence estimates ranging from 5%to 25%worldwide.Most systematic reviews define GERD as experi-encing heartburn and/or regurgitation at least once weekly,yielding a calculated prevalence of 13.98%.In 2017,the global age-standardized prevalence of GERD was estimated at 8819 per 100000 people(95%confidence interval:7781-9863),a figure that has remained stable from 1990 to 2017.Prevalence increases with age,leading to more years lived with disability.GERD significantly impairs quality of life and can lead to multiple complications.Additionally,it imposes a severe economic burden,with the United States alone estimated to spend around 10 billion dollars annually on diagnosis and treatment.In summary,GERD preva-lence varies greatly by region and even within different areas of the same province.Determining the exact prevalence is challenging due to inconsistent diagnostic criteria.However,it is well-documented that GERD poses a significant global burden,affecting the quality of life of individuals and creating a substantial healthcare cost.
文摘The problem of gastric cancer(GC)prevention remains relevant for a long time.Various methods of population serological screening of atrophic gastritis and precancerous changes in the gastric mucosa have been created at present.Modern endoscopic and morphological methods of verification of the diagnosis of precancerous diseases and changes in the gastric mucosa have been introduced into the practice of gastroenterologists and oncologists.GC risk stratification systems allow the formation of risk groups that require population screening.Practical hints for population serological screening of atrophic gastritis,endoscopic and morphological verification of precancerous changes and diseases of the stomach recommend using it:When developing state programs for the prevention of stomach cancer;when implementing preventive measures for stomach cancer by doctors of all specialties;the authors also offer the possibility of use by anyone over the age of 40,provided that they seek methodological help from their doctor;in the work of health schools in any medical and preventive institutions.The use of an assessment system of certain risk factor signatures with prognostic value would add significant assistance to preventive measures against GC.
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the National Natural Science Foundation of China(No.22273096)the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.22409139).
文摘In the global transition towards sustainable energy sources,hydrogen energy has emerged as an indispensable pillar in reshaping the energy landscape,owing to its environmental sustainability,zero emissions,and high efficiency.Nevertheless,the large-scale deployment of hydrogen energy is confronted with substantial technical barriers in storage and transportation.Although contemporary research has shifted focus to the development of highly efficient hydrogen storage materials,conventional material design concepts remain predominantly empirical,typically relying on trial-and-error methodologies.Importantly,the widespread application of artificial intelligence technologies in accelerating materials discovery and optimization has attracted considerable attention.This review provides a comprehensive overview of the latest advancements in hydrogen storage technologies,with an emphasis on the synergistic application of high-throughput screening and machine learning in solid-state hydrogen storage materials.These approaches demonstrate exceptional potential in accurately predicting hydrogen storage properties,optimizing material performance,and accelerating the development of innovative hydrogen storage materials.Specifically,we discuss in detail the essential role of artificial intelligence in developing hydrogen storage materials such as metal hydrides,alloys,carbon materials,metal–organic frameworks,and zeolites.Moreover,underground hydrogen storage is further explored as a scalable renewable energy storage solution,particularly in terms of optimizing storage parameters and performance prediction.By systematically analyzing the limitations of existing hydrogen storage approaches and the transformative potential of artificial intelligence-driven methods,this review offers insights into the discovery and optimization of high-performance hydrogen storage materials,contributing to sustainable global energy development and technological innovation.
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.
文摘This study discusses the impact of the increasing use of colonoscopy on the trends of colorectal cancer(CRC)in Korea.Different views are raised on the research methods and conclusions of Kim et al.It emphasizes the need to carefully consider the balance between the benefits of early detection and the risks of over-screening.This letter also suggests directions for future research and policy considerations in the field of CRC screening and prevention in Korea.
基金supported by the National Natural Science Foundation of China(Grant Nos.22225801,W2441009,22408228)。
文摘As energy demands continue to rise in modern society,the development of high-performance lithium-ion batteries(LIBs)has become crucial.However,traditional research methods of material science face challenges such as lengthy timelines and complex processes.In recent years,the integration of machine learning(ML)in LIB materials,including electrolytes,solid-state electrolytes,and electrodes,has yielded remarkable achievements.This comprehensive review explores the latest applications of ML in predicting LIB material performance,covering the core principles and recent advancements in three key inverse material design strategies:high-throughput virtual screening,global optimization,and generative models.These strategies have played a pivotal role in fostering LIB material innovations.Meanwhile,the paper briefly discusses the challenges associated with applying ML to materials research and offers insights and directions for future research.
