Composite microsphere-based optical signature-enhanced detection for smart multiparametric diagnosis of urinary tract infections in pregnancy

Developed a portable smart POCT device for home testing of three major UTI pathogens. • Synergistic lensing-nanojet optical enhancement enables highly sensitive detection. • Composite microspheres enable highly specific wash-free multiparameter immunoassay. • Complete testing requires only 30 min at $1.5 per test with accuracy above 90%. Urinary tract infection (UTI) is one of the most common diseases during pregnancy, caused by multiple microbial pathogens and posing significant risks to both maternal and fetal outcomes. Current diagnostic methods are limited by prolonged detection times or require a certain degree of sample preprocessing, making it difficult to meet the needs of personalized at-home testing for pregnant patients. To more effectively address this requirement, we developed an intelligent point-of-care (POC) testing platform based on the composite microsphere-based optical signature-enhanced detection (CMOSED), enabling highly sensitive and real-time personalized diagnosis of three major bacterial pathogens. The platform employs four carboxyl-functionalized polystyrene (PS) microsphere size classes, including three small antigen-coded microspheres and one large antibody-carrying microsphere. Through the synergistic interaction between the microsphere lensing effect and the photonic nanojet (SIMLN), the system achieves high-precision target recognition even within complex urinary matrices; through the dynamic response of microsphere assemblies to varying target concentrations, it enables accurate detection of analyte levels; through the AI-assisted diagnostic system for Urinary Tract Infections in Pregnancy (AID-UTIP), it achieves rapid, personalized home-based testing. The system achieves high sensitivity and specificity detection for the three major UTI pathogens within 30 min at a cost below $1.5 per test. A prospective clinical evaluation ( n  = 25) demonstrated detection accuracies of 96% for UPEC , 92% for Klebsiella pneumoniae , and 92% for Enterococcus faecalis . By integrating diverse antigen-antibody combinations, this method offers a rapid, cost-effective, and extensible strategy for multi-pathogen detection, representing a promising paradigm for intelligent, decentralized infectious disease diagnostics in home-based pregnancy care.