Abstract
Accurate quantification of enzyme activity is essential for early metabolic disease diagnosis and point-of-care bioanalysis. Abnormal α-glucosidase (α-GAA) activity is closely related to metabolic disorders, making its sensitive detection increasingly important. However, most current assays rely on one-to-one signal transduction, where each enzymatic event produces only a single detectable signal, inherently limiting sensitivity and compromising reliable detection under complex physiological conditions. Here, we establish a hierarchical catalytic amplification strategy for ultrasensitive α-GAA detection by integrating enzymatic hydrolysis, glucose oxidase-mediated H2O2 generation, and Ce3+-protected copper nanozyme catalysis. Crucially, a matrix-matched blank subtraction strategy is introduced to effectively eliminate interference from endogenous glucose and other non-specific reductants, ensuring that the final amplified signal exclusively originates from α-GAA activity. Benefiting from this three-stage amplification architecture and the blank correction, the platform enabled highly sensitive α-GAA quantification. Benefiting from this three-stage amplification architecture, the platform enabled highly sensitive α-GAA quantification over a linear range of 0.1-40 U/L with a detection limit of 0.026 U/L. The biosensor further exhibited excellent selectivity, reliable analytical performance in human serum, and portable quantitative analysis through smartphone-assisted colorimetric detection. This work advances nanozyme-based biosensing from conventional signal reporting toward amplification-guided analytical design, providing a generalizable strategy for developing next-generation decentralized diagnostic platforms.