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  • Title: Dosage-sensitive and simultaneous detection of multiple small-molecule pollutants in environmental water and agriproducts using portable SERS-based lateral flow immunosensor.
    Author: Wang J, Zheng Y, Wang X, Zhou X, Qiu Y, Qin W, ShenTu X, Wang S, Yu X, Ye Z.
    Journal: Sci Total Environ; 2024 Feb 20; 912():169440. PubMed ID: 38123096.
    Abstract:
    The co-contamination of pesticide residues and mycotoxins in agricultural products is a global concern, with the potential for cumulative and synergistic damaging effects, imposing substantial health and economic burdens to the public. The dosage-sensitive and simultaneous detection of multiple pollutants, with a heightened sensitivity in real samples, poses a significant demand and challenge. Herein, we propose a portable detection method integrating surface-enhanced Raman scattering (SERS)-with lateral flow immunoassay (LFIA), offering high sensitivity and multiplex analysis capabilities. This approach enables the simultaneous detection of imidacloprid (IMI), pyraclostrobin (PYR) and aflatoxin B1 (AFB1) through a single test strip. Utilizing the immune-specific binding between antigen and antibodies, we immobilised antibody- conjugated SERS nanotags on three test lines of the strips to generate Raman signal amplification in the proposed biosensor. Accurate quantitative analysis was performed by measuring the SERS signal intensity on the test lines. The limits of detection were 8.6 pg/mL for IMI, 97.4 pg/mL for PYR and 8.9 pg/mL for AFB1, exhibiting sensitivities 12-fold, 102-fold and11-fold higher than the colorimetric signals, respectively. Importantly, the SERS-LFIA immunosensor demonstrated robust performance when applied to real samples, yielding recoveries ranging from 86.16 % to 115.0 %, with relative standard deviation values below 8.67 %. These results underscore the excellent stability, high selectivity and reliability the proposed SERS-LFIA immunosensor. Consequently, it holds promise for the detection of multiple pesticides and mycotoxins in both environmental and agricultural samples.
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