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首页> 外文期刊>Analytical and bioanalytical chemistry >Chemiluminescence microarray immunoassay for multiple aminoglycoside antibiotics based on carbon nanotube-assisted signal amplification
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Chemiluminescence microarray immunoassay for multiple aminoglycoside antibiotics based on carbon nanotube-assisted signal amplification

机译:Chemiluminescence microarray immunoassay for multiple aminoglycoside antibiotics based on carbon nanotube-assisted signal amplification

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摘要

The simultaneous determination of multiple analytes has been an urgent demand in screening of antibiotic residues in food products of animal origin due to its higher analysis efficiency. Five aminoglycoside antibiotics (AGAs) have been monitored in milk, including gentamicin (GEN), kanamycin (KAN), neomycin (NEO), and streptomycin/dihydrostreptomycin (STR/diSTR). A chemiluminescence microarray immunoassay (CLMIA) based on nitrocellulose membrane had been developed for the detection of multiple AGAs, which the LODs for STR, KAN, NEO, and GEN were 4.74 ng/mL, 4.97 ng/mL, 2.99 ng/mL, and 4.42 ng/mL respectively. To improve the sensitivity of immunoassay, single-well carbon tubes (SWCNTs) were utilized as solid support for loading horseradish peroxidase-labelled goat anti-mouse antibody to obtain the multi-enzyme particles. After the optimization of usage of multi-enzyme particles and antibodies, the enhanced CLMIA was established and evaluated. The LODs were 1.25 ng/mL for STR, 0.64 ng/mL for KAN, 0.38 ng/mL for GEN, and 0.39 ng/mL for NEO, which was improved by threefold, sevenfold, 11-fold, and sevenfold compared with the conventional CLMIA developed. These methods presented higher specificity and repeatability. Finally, the enhanced CLMIA based on CNT-assisted multi-enzyme particles was utilized to analyze twenty-five milk samples from local market and dairy farm, which all the results were below the LOD. The enhanced CLMIA showed the great application potential for the detection of multiple targets simultaneously and provided efficient tool for the screening of pollutants in food.

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