Artificial neural network-facilitated V₂C MNs-based colorimetric/fluorescence dual-channel biosensor for highly...

In this work, V₂C Mxene nano-enzyme materials (V₂C MNs) with excellent peroxidase-like activity and fluorescence quenching performance were prepared, and it was modified using 6-carboxyfluorescein-labelled aptamers (ssDNA-FAM) to construct a novel dual-mode sensor V₂C@ssDNA-FAM, with detection limits of 0.0477 ng mL^-1 and 0.2789 ng mL^-1 of fluorescence (linear range of 0.1-550 ng mL^-1) and colorimetric (linear range of 1-1000 ng mL^-1) modes, respectively. Meanwhile, an ANN intelligent detection platform has been constructed, which could automatically track and analyze the fluorescence and colorimetric signal of the detection system through machine learning and immediately obtain the AFB₁ concentration, and the detection limits of the fluorescence (linear range of 0.1-500 ng mL^-1) and colorimetric (linear range of 1-800 ng mL^-1) channels of it were 0.0905 ng mL^-1 and 0.6845 ng mL^-1, respectively. The recovery rates of fluorescence, colorimetric sensing detection and ANN-assisted fluorescence and colorimetric sensing detection of real samples ranged from 95.40% to 101.76%. The method constructed in this work was superior to most existing literature reports and had great potential for application in the field of food quality testing.