Colorimetric/Fluorescent/SERS Triple-Mode Synergistic Sensing for Highly Sensitive and Accurate Cardiac Troponin I Detection.

Cardiac troponin I (cTnI) is a cardiomyocyte-specific protein, and its serum level positively correlates with the degree of myocardial damage, making it a gold-standard biomarker for the clinical diagnosis of acute myocardial infarction (AMI). Nevertheless, conventional strategies for cTnI detection generally suffer from insufficient sensitivity and frequent false detection results, which greatly restrict their practical clinical utility. To overcome these limitations, this work constructs a triple-mode aptasensor for the sensitive and precise quantitative detection of cTnI. The sensor relies on flower-like covalent organic framework@gold nanoparticle (flower-like COF@Au) composites as the core functional material, which integrates oxidase-like catalytic activity, intrinsic fluorescence property and surface-enhanced Raman spectroscopy (SERS) enhancement effect in a single nanostructure. This material can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) without the assistance of exogenous hydrogen peroxide, producing obvious color variations that support colorimetric sensing. The TMB oxidation product also acts as an effective SERS signal reporter to achieve highly sensitive detection. In addition, the flower-like COF@Au composite possesses inherent fluorescence characteristics, endowing the sensing platform with fluorescent detection capability. Moreover, the material exhibits excellent adsorption performance and flexible surface modification characteristics, enabling the facile fabrication of a high-performance aptasensor. The integration of three independent sensing modes realizes mutual verification of detection results, effectively improving sensing sensitivity and eliminating the false positive and negative errors that commonly exist in single-mode detection platforms. Therefore, the developed triple-mode aptasensor presents excellent application potential for clinical AMI diagnosis.