Paper-based triple-readout nanosensor for point-of-care detection of glucose in urine.

Glucose detection is critical for diabetes diagnosis and management. This study aimed to develop an enzyme-free, cascade-based, triple-readout paper sensor utilizing bismuth (Bi)-based metal-organic frameworks/gold nanoparticles (Bi-BDC-NH2@Au) for detecting urine glucose. Herein, Bi-BDC-NH2@Au exhibited glucose oxidase-like activity and oxidized glucose to generate H2O2, which then quenched the blue fluorescence of FP@Bi-BDC-NH2@Au through an inner filter effect. Additionally, owing to its pronounced peroxidase-like activity, Bi-BDC-NH2@Au catalyzed H2O2 to produce ·OH, which oxidized colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue oxidized TMB (oxTMB), thereby increasing the system temperature owing to the excellent photothermal conversion properties of oxTMB. These mechanisms enabled the triple-readout of glucose levels. Quantification in the fluorescence and colorimetric modes was achieved through a Python-based image recognition algorithm that accurately read B/(R + G + B) values, and the photothermal mode relied on a portable infrared thermal imager to monitor temperature changes. The detection limits for the fluorescence, colorimetric, and photothermal modes were 4.2, 3.3, and 5.7 μM, respectively. The self-calibration ability of the sensor across different modes markedly enhanced its detection accuracy and robustness. The developed sensor successfully has detected and quantified urine glucose, effectively distinguishing between healthy individuals and patients with diabetes, providing a convenient and efficient tool for diabetes management.