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Multifunctional CoFcMOF Nanozyme Facilitates a Self-Validating Triple-Modal Immunosensor for CRP in Serum and Synovial Fluid

化学 滑液 滑膜关节 生物物理学 分子生物学 定量分析(化学) 生物化学 色谱法 炎症 生物流体
作者
Jingshu Li,Yuee Zhong,Jing Liu,Xuan Wang,Jianru Tang,Xi Zhu,Shu Huang,Youyu Zhang,M C Liu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:98 (18): 13737-13751
标识
DOI:10.1021/acs.analchem.6c00734
摘要

Accurate quantification of C-reactive protein (CRP) in serum and synovial fluid is critical for diagnosing and monitoring localized inflammatory arthritis, but it remains challenging due to the complexity of the matrix and the lack of robust and sensitive assays. To overcome this critical challenge, a novel self-validating triple-modal immunosensing platform was developed based on a rationally designed multifunctional cobalt-ferrocene metal–organic framework (CoFcMOF) nanozyme, which ensures robust detection reliability through a synergistic signal fusion mechanism. The innovation lies in the “three-in-one” nanolabel of CoFcMOF that concurrently serves as a peroxidase (POD) mimic for colorimetric readout, an efficient quencher for the electrochemiluminescence (ECL) of carboxylated graphitic carbon nitride (C-g-C3N4), and a bioconjugation tag that amplifies the electrochemical impedance spectroscopy (EIS) signal upon immunocomplex formation. Critically, all three mechanistically distinct yet intrinsically linked signaling pathways are intrinsically triggered by a single biorecognition event, enabling real-time and built-in cross-validation. This cooperative design affords exceptional sensitivity, with detection limits of 0.075 pg/mL (ECL), 0.095 pg/mL (EIS), and 0.29 pg/mL (colorimetry) for CRP, while demonstrating outstanding anti-interference performance in serum and synovial fluid samples. Beyond providing a precise and reliable method for CRP analysis, this work establishes a new biosensing paradigm that utilizes rationally engineered multifunctional materials for inherently self-validating, multimechanism detection, paving the way for next-generation diagnostic systems capable of high-accuracy analysis in complex real-world samples.
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