Chemiluminescence functionalized magnetic nanoparticles-based biosensor for sensitive detection of glucose, uric acid, and cholesterol.

Authors

Shuangyi Hu, Rui Yuan, Xianlong Lu, Wenxia Chen, Yangyang Xue, Rui Yang

Published in

Analytical and bioanalytical chemistry. Jul 02, 2026. Epub Jul 02, 2026.

Abstract

Chemiluminescence (CL) biosensors have attracted extensive attention in biomarker detection owing to their high sensitivity and simplicity. However, the advancement of high-performance CL-functionalized nanoparticles (NPs) continues to encounter challenges, such as achieving high luminescence efficiency, ensuring good stability, and enhancing functionality. In this work, CL-functionalized magnetic NPs (CoFe₂O₄@TA@luminol-Ag NPs) were successfully synthesized. CoFe₂O₄ NPs were modified with tannic acid (TA) and effectively coated with luminol and silver NPs (Ag NPs) on their surfaces. This configuration efficiently catalyzes the luminol-hydrogen peroxide (H₂O₂) CL system, thereby significantly enhancing the CL signal. A highly sensitive biosensing platform for the detection of glucose, uric acid, and cholesterol in human serum was developed. A mixture of glucose oxidase (GOD)/glucose, uricase/uric acid, or cholesterol oxidase (ChOx)/cholesterol, which are capable of generating H₂O₂, was combined with CoFe₂O₄@TA@luminol-Ag NPs to generate a CL signal. The developed CL sensing platform was applied for the sensitive and quick detection of glucose, uric acid, and cholesterol in human serum samples. The concentrations of glucose, uric acid, and cholesterol present excellent linear correlation with the CL signal, with detection limits below 1.51 × 10^-11 M, 6.93 × 10^-12 M, and 2.44 × 10^-11 M, respectively. This biosensor combines the simplicity of magnetic separation with the specificity of enzymatic reactions and the enhanced signal amplification capabilities of nano-catalysis, demonstrating strong anti-interference properties, ease of operation, and good selectivity.

PMID:
42393242
Bibliographic data and abstract were imported from PubMed on 03 Jul 2026.

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