Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbi...Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbidity and mortality.This review synthesizes recent advances in diagnostic methodologies,including serological assays,point-of-care diagnostics,polymerase chain reaction(PCR)-based and sequencing technologies,as well as artificial intelligence(AI)-and machine learning(ML)-powered tools.Emerging diagnostic approaches have demonstrated notable improvements in detection accuracy,turnaround time,and antifungal resistance profiling capabilities,especially for drug-resistant strains.Nevertheless,substantial challenges persist in terms of standardization,scalability,cost-effectiveness,and implementation,particularly in resource-constrained settings.Future efforts should be directed toward the continuous innovation of rapid,sensitive,and multiplex diagnostic platforms for the simultaneous detection of fungi,bacteria,and viruses.Such advances may accelerate result acquisition,enhance diagnostic accuracy,support the development of more targeted therapeutic strategies,and ultimately improve clinical outcomes for patients.展开更多
基金supported by the MOST Key R&D Program of China(grant number 2022YFC2303500 to X.H.)the National Natural Science Foundation of China(grant numbers 32570236,32170195,and 32311530119 to C.C.and 32470200 to X.H.)+1 种基金Shanghai Science and Technology Innovation Action Plan 2023“Basic Research Project”(grant number 23JC1404200 to C.C.)the Foundation of State Key Laboratory of Pathogen and Biosecurity(grant number SKLPBS2236 to C.C.).
文摘Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbidity and mortality.This review synthesizes recent advances in diagnostic methodologies,including serological assays,point-of-care diagnostics,polymerase chain reaction(PCR)-based and sequencing technologies,as well as artificial intelligence(AI)-and machine learning(ML)-powered tools.Emerging diagnostic approaches have demonstrated notable improvements in detection accuracy,turnaround time,and antifungal resistance profiling capabilities,especially for drug-resistant strains.Nevertheless,substantial challenges persist in terms of standardization,scalability,cost-effectiveness,and implementation,particularly in resource-constrained settings.Future efforts should be directed toward the continuous innovation of rapid,sensitive,and multiplex diagnostic platforms for the simultaneous detection of fungi,bacteria,and viruses.Such advances may accelerate result acquisition,enhance diagnostic accuracy,support the development of more targeted therapeutic strategies,and ultimately improve clinical outcomes for patients.
