Suppr超能文献

基于计算机辅助抗体的用于油田化学品中二苯并[a,h]蒽现场检测的定量免疫传感器。

Quantitative immunosensor for dibenz[a,h]anthracene on-site detection in oilfield chemicals based on computer-aided antibody.

作者信息

Li Jiaxun, Chen Haifeng, Shu Yong, Jiang Luming, Gao Wei, Kuang Hua, Xu Chuanlai, Guo Lingling

机构信息

Jiangsu Provincial Quality Supervision and Inspection Institute, Nanjing, 210000, Jiangsu, China.

State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, People's Republic of China.

出版信息

Mikrochim Acta. 2025 Mar 20;192(4):245. doi: 10.1007/s00604-025-07035-x.

Abstract

A paper sensor, a gold nanoparticles-based lateral flow immunochromatographic assay (GNPs-LFIA), was successfully established for the rapid quantitative detection of dibenz[a,h]anthracene (DBA) in drilling fluids (DFs). Computational analysis was employed to rationally design a novel hapten to effectively expose the active site of DBA, resulting in the successful development of a monoclonal antibody with high sensitivity and specificity. The half-maximum inhibitory concentration was 5.814 ng/mL. Then, the GNPs-LFIA was established following the optimization of the extraction agent and method. The limit of detection for DF samples was 0.273 mg/kg. Recovery experiments showed a high level of consistency with the results obtained by high-performance liquid chromatography-fluorescence detection, which indicated that the established GNPs-LFIA offered exceptional accuracy and reliability. Consequently, this method is well-suited for the rapid screening and determination of DBA in oilfield chemicals and presents a technical solution to identify polycyclic aromatic hydrocarbons.

摘要

一种纸质传感器,即基于金纳米颗粒的侧向流动免疫色谱分析法(GNPs-LFIA),已成功建立,用于快速定量检测钻井液(DFs)中的二苯并[a,h]蒽(DBA)。采用计算分析合理设计了一种新型半抗原,以有效暴露DBA的活性位点,从而成功开发出一种具有高灵敏度和特异性的单克隆抗体。半数抑制浓度为5.814 ng/mL。然后,在优化萃取剂和方法后建立了GNPs-LFIA。DF样品的检测限为0.273 mg/kg。回收率实验结果与高效液相色谱-荧光检测法的结果高度一致,这表明所建立的GNPs-LFIA具有极高的准确性和可靠性。因此,该方法非常适合于油田化学品中DBA的快速筛选和测定,并为识别多环芳烃提供了一种技术解决方案。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验