Chitosan-stabilized Prussian blue nanoparticle-based multi-mode readout colorimetric, fluorometric, and photothermal biosensor for sensitive uric acid detection

Abstract

Abnormal levels of uric acid (UA) indicate warning signals for gout and metabolic cardiovascular diseases, requiring the monitoring of UA levels for early diagnosis and prevention. Nevertheless, most of the detection methods for uric acid (UA) rely on a single-mode readout, which is susceptible to a multitude of variables, resulting in inaccurate outcomes. To overcome the above limitations, in this study, we employed chitosan-stabilized Prussian blue nanoparticles (CS@PBNPs), which provide a strategy for a colorimetric, photothermal, and fluorometric multi-mode detection of UA. The CS@PBNPs exhibited excellent peroxidase-like activity, and chitosan, as a stabilizer, notably enhanced both colloidal dispersion and stability. In the presence of hydrogen peroxide, produced by enzymatic reaction, CS@PBNPs oxidize 3,3′,5,5′-tetramethylbenzidine (TMB) and o-phenylenediamine (OPD). Oxidized TMB showed a blue color with a photothermal effect at near-infrared (NIR) regions and was employed as a probe for colorimetric and photothermal detection. Oxidized OPD, which exhibits yellow color and fluorescence, served as a probe for both colorimetric and fluorescent detection. The multi-mode readout sensor demonstrated a broad linear detection range of 0–1000 μM, with limits of detection (LOD) of 1.93 μM (colorimetric), 5.01 μM (fluorometric), and 8.90 μM (photothermal), enhancing the detection range (10–800 μM) and LOD (10 μM) of conventional single-mode readout. Moreover, each method exhibited excellent reliabilty and reproducibility in detection of UA in human serum samples, indicating the suitability in practical applications. Consequently, CS@PBNP-based multi-mode sensing platform provided detection results in different output modes, significant enhancement of assay accuracy. © 2025 Elsevier B.V.