Peroxidase nanozyme-incorporated sponge: A smartphone-enabled dual-mode visual sensing platform for trace uric acid detection via a shape-memory effect-driven signal amplification strategy

Abstract

Uric acid (UA) is an important biomolecule in human body fluids and serves as a diagnostic indicator for diseases. However, accurately quantifying UA samples with concentrations below the minimum linear range has been a persistent challenge in previous studies. In this study, a hydrophilic shape-memory sponge integrated with peroxidase (POD)-nanozyme was prepared to overcome this limitation. Following UA catalysis by uricase, the nanozyme-incorporated sponge decomposes hydrogen peroxide (H₂O₂) through its POD-like activity, oxidizing colorless o-phenylenediamine (OPD) to yellow 2,3-diaminophenazine (DAP) and simultaneously generating blue fluorescence. Due to electrostatic interaction, the formed DAP is strongly adsorbed onto the sponge, which allows the colorimetric and fluorescence signal of DAP from the catalysis are enriched on the sponge by repeatedly adding low-concentration UA samples. When combined with smartphone-based image processing, this assay functions as a practical dual-mode sensor for real-time monitoring. Notably, based on its shape-memory effect and the adsorption of DAP, the proposed nanozyme-incorporated sponge can reduce the minimum linear range (LRmin) for UA by up to 10 times, improving the sensitivity of dual-mode sensing platform, which is beneficial to the detection of trace UA. This work provides a reliable and efficient approach for on-site UA detection and offers new insights into trace analyte detection.