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对硫磷的半抗原预测、单克隆抗体制备及免疫层析检测方法的开发

Hapten prediction, monoclonal antibody preparation, and development of an immunochromatographic assay for the detection of fenamiphos.

作者信息

Lu Qianqian, Guo Lingling, Xu Xinxin, Kuang Hua, Liu Liqiang, Xu Chuanlai, Sun Maozhong

机构信息

International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, PR China.

International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, PR China.

出版信息

J Hazard Mater. 2025 Apr 5;487:137168. doi: 10.1016/j.jhazmat.2025.137168. Epub 2025 Jan 8.

Abstract

Fenamiphos (FENA) is an organophosphorus insecticide, and its residues in fruits, vegetables, and the environment have raised concerns. Therefore, it is very important to develop a simple, rapid, and accurate method for FENA detection. In this study, a novel FENA hapten was designed and predicted based on computer-aided simulation technology, and high-performance anti-FENA monoclonal antibodies were screened using a matrix effect-enhanced screening method, with a half-maximal inhibitory concentration of 1.269 ng/mL. Furthermore, a colloidal gold immunochromatographic assay (ICA) was established for the detection of FENA, with calculated limits of detection of 1.030 μg/kg, 0.515 μg/kg, 0.250 ng/mL, and 0.405 μg/kg in oranges, cowpeas, river water, and soil. Spiked recovery experiments and real sample validation showed that the detection results from the ICA and LC-MS/MS were consistent, with a CV < 10 %, indicating that the ICA had good accuracy and stability and shows promise as a rapid screening method for FENA in fruits, vegetables, and the environment.

摘要

苯线磷(FENA)是一种有机磷杀虫剂,其在水果、蔬菜和环境中的残留引发了人们的关注。因此,开发一种简单、快速且准确的FENA检测方法非常重要。在本研究中,基于计算机辅助模拟技术设计并预测了一种新型FENA半抗原,并采用基质效应增强筛选方法筛选出了高效抗FENA单克隆抗体,其半数抑制浓度为1.269 ng/mL。此外,建立了一种胶体金免疫层析法(ICA)用于检测FENA,在橙子、豇豆、河水和土壤中的计算检测限分别为1.030 μg/kg、0.515 μg/kg、0.250 ng/mL和0.405 μg/kg。加标回收实验和实际样品验证表明,ICA和LC-MS/MS的检测结果一致,变异系数<10%,表明ICA具有良好的准确性和稳定性,有望作为水果、蔬菜和环境中FENA的快速筛选方法。

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