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V2C Mxene纳米酶
TALANTA · 2023 · IF 6.1

Artificial neural network-facilitated V2C MNs-based colorimetric/fluorescence dual-channel biosensor for highly sensitive detection of AFB1 in peanut

Yiqian Kong,Zongyi Li,Qi Liu,Juncheng Song,Yinghua Zhu,Jinping Lin,Lili Song,Xiangyang Li

In this work, V 2 C Mxene nano-enzyme materials (V 2 C 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 V 2 C@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 AFB 1 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.

CAS / MDL: 75-59-2
研究领域: 食品安全检测 · 生物传感 · 人工智能辅助分析
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