Aggregation-induced emissive copper nanoclusters with peroxidase-like activity for colorimetric detection of cholesterol

胆固醇氧化酶 检出限 纳米团簇 过氧化物酶 比色法 吸光度 谷胱甘肽过氧化物酶 材料科学 胆固醇 组合化学 化学 谷胱甘肽 核化学 纳米技术 生物化学 色谱法
作者
Yang Wang,Sheng Wang,Yuan Fang,Dengwu Tao,Kaiyan Tang,Jinshan Nie,Baisong Chang
出处
期刊:Nanotechnology [IOP Publishing]
标识
DOI:10.1088/1361-6528/ad8582
摘要

Accurate and point-of-care cholesterol detection is of paramount significance for the prevention of cardiovascular diseases. The colorimetric assay based on peroxidase is a commonly used approach for cholesterol detection, without requiring any complicated biomolecular labeling or sophisticated instrumentation. Copper nanoclusters (CuNCs), exhibiting luminescent properties and peroxidase activity, have garnered significant attention in biomedical application recently. Herein, the glutathione-stabilized copper nanoclusters (GSH-CuNCs) were prepared with an easy one-pot method, employing glutathione as both a reducing agent and stabilizer. An optimization of the GSH-CuNCs preparation was carried out to obtain the highest peroxidase-like activity. UV-Vis absorption was measured to explore the steady-state kinetics of the GSH-CuNCs-catalyzed oxidation of 3,3',5,5' - tetramethylbenzidine (TMB) by H2O2. A colorimetric method for cholesterol detection was developed by combining the catalytic reaction of CuNCs and the enzymatic oxidation of cholesterol with cholesterol oxidase (ChOx). Under the optimized conditions, the UV-Vis absorbance of oxidized TMB (oxTMB) is proportional to the concentration of cholesterol within the range of 6.2-187.5 μM, and the limit of detection (LOD) is determined to be 3.0 μM. More importantly, cholesterol levels can be directly distinguished with the naked eye. Furthermore, the practicality of the method for detecting cholesterol in human serum has been verified with promising results. As expected, this simple, cost-effective, and easy-to-operate colorimetric method for cholesterol detection has potential applications in clinical diagnosis and provides valuable insights into the colorimetric sensing based on CuNCs.
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