The misuse of antibiotics has accelerated the rise of antimicrobial resistance (AMR), particularly in resource-limited regions, posing a critical threat to global public health. Current antibiotic susceptibility test (AST) technologies are trapped in a paradox: regions most in need of rapid diagnostics face the greatest implementation barriers due to culture-based delays and infrastructure dependence. No existing platform simultaneously overcomes these spatiotemporal constraints while maintaining phenotypic reliability. Combining the self-healing property of skins with discrete state control of D flip-flop, we present a low-cost (0. 62) centrifugal microfluidic chip with self-healing valves (μCFC-shv) that integrates bacterial enrichment (1000-fold without time-consuming incubation), antibiotic gradient generation, and AST. The shvs autonomously actuate/reseal with centrifugal speed changes, enabling robust, long-term, and repeatable use. The μCFC-shv detects pathogens within 5 min postenrichment, achieving 100% sensitivity and specificity, with a 10 °CFU/mL detection limit. Critically, it performs culture-free AST in 30 min of antibiotic exposure, demonstrating an accuracy of 97. 39% across 306 clinical cases, comparable or superior to current single-bacterium detection methods. To overcome ambient light interference and subjective interpretation, we integrate a machine learning model that automates result analysis with 98. 83% accuracy. This combination of accessibility and culture-free strategy makes μCFC-shv a transformative tool for AST, especially in resource-limited areas, advancing global efforts to combat bacterial infections and AMR.
Wan et al. (Wed,) studied this question.