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基于纸的竞争性侧向流动免疫分析,使用单克隆抗体标记红色荧光纳米颗粒检测多种β-激动剂残留。

A paper-based competitive lateral flow immunoassay for multi β-agonist residues by using a single monoclonal antibody labelled with red fluorescent nanoparticles.

机构信息

1Key Laboratory of Agro-product Safety and Quality, Ministry of Agriculture, Beijing, 100081 People's Republic of China.

2Institute of Quality Standards & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing, 100081 People's Republic of China.

出版信息

Mikrochim Acta. 2018;185(3):191. doi: 10.1007/s00604-018-2730-9. Epub 2018 Feb 22.

Abstract

An ultrasensitive paper based lateral flow assay is described for rapid and simultaneous fluorometric detection of several β-agonists including clenbuterol and its chemical analogues (mabuterol, brombuterol, cimaterol, cimbuterol, bromchlorbuterol and banbuterol). A nonspecific monoclonal antibody (mAb) against clenbuterol and its analogues was prepared and employed in a competitive immunoassay where mAb conjugated to fluorescent nanoparticles and free β-agonists compete for the binding sites. This enables rapid screening for the 7 β-agonists in a single run that takes about 8 min. Detection limits for the seven β-agonists are <50 pg g of pork. Recoveries ranged from 69.5% to 102.4%, and relative standard deviations were ±15%. The assay was applied to the analysis of both using spiked and unspiked pork for β-agonists, and the results compare well to those obtained by HPLC-MS. Graphical abstractSchematic presentation of an ultra sensitive fluorescent nanoparticle based paper based assay for rapid detection of multi β-agonists in pork tissue.

摘要

一种超灵敏的基于纸的横向流动分析方法被描述用于快速和同时荧光检测几种β-激动剂,包括克仑特罗及其化学类似物(马布特罗、溴布特罗、西马特罗、西布特罗、溴氯丁特罗和班布特罗)。制备了一种针对克仑特罗及其类似物的非特异性单克隆抗体(mAb),并将其用于竞争性免疫测定中,其中 mAb 与荧光纳米颗粒偶联,并与游离的β-激动剂竞争结合位点。这使得能够在大约 8 分钟的单个运行中快速筛选 7 种β-激动剂。七种β-激动剂的检测限<50pg g 的猪肉。回收率在 69.5%到 102.4%之间,相对标准偏差为±15%。该测定法应用于使用添加和未添加β-激动剂的猪肉进行的分析,结果与 HPLC-MS 获得的结果相当。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eecd/5823949/829c5c15842d/604_2018_2730_Figa_HTML.jpg

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