Abstract

At present, the majority of methods used for uric acid (UA) detection are not able to meet the detection requirements with speed, accuracy, high sensitivity, high specificity, a wide linear range or a low cost. Compared with other methods, the electrochemical method has a high sensitivity and fast detection. The present study aimed to identify an electrochemical sensor with high sensitivity, fast detection and a wide linear range for the detection of UA. A glassy carbon electrode modified with graphene-molybdenum disulfide-Nafion (G-MoS2-Nafion) composites was prepared for use as the working electrode. The morphologies and elemental compositions of the G-MoS2 composites were characterized by field emission scanning electron microscopy, elemental distribution spectrometry and X-ray diffraction, respectively. The electrochemical behaviors were investigated by cyclic voltammetry, linear sweep voltammetry and the amperometric i-t curve (i-t). The interference of glucose, ascorbic acid and dopamine, and the accuracy and precision of the electrochemical method were subsequently evaluated. The present study identified the following: (1) Only the reduction peak of UA was detected in human serum, indicating that the method established in the present study has a high specificity for the determination of UA in human serum; (2) UA concentration has a linear correlation with current intensity (y=0.012×+0.998; R2=0.998), wide linear range and high sensitivity (minimum detectability=13.91 µM; signal-to-noise ratio=3); (3) the values of UA content in human serum were positively proportional to the clinical results (y=0.9802×+11.494; R2=0.978); (4) the average recovery rate of UA (95.28%) and the replicability assay of the i-t electrochemical method (coefficient of variation=2.04%), suggest that the method had a high accuracy and good precision for UA detection. Due to its characteristics of good accuracy, high sensitivity, wide linear range, good anti-interference ability and replicability, G-MoS2-Nafion has good prospects for UA detection in the clinical setting.

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