Non-competitive immunoassay for low-molecular-weight contaminant detection in food, feed and agricultural products: A mini-review

免疫分析 半抗原 分析物 污染 生化工程 竞争性约束 化学 色谱法 环境科学 抗体 生物 工程类 生态学 生物化学 受体 免疫学
作者
Aiping Liu,Laura Anfossi,Lihua Shen,Cheng Li,Xiaohong Wang
出处
期刊:Trends in Food Science and Technology [Elsevier BV]
卷期号:71: 181-187 被引量:37
标识
DOI:10.1016/j.tifs.2017.11.014
摘要

Immunoassays have gained considerable attention in safety assurance for food, feed and agricultural products. Generally, immunoassays are presented either in a competitive or non-competitive, sandwich-type format, and the former is extensively employed for low-molecular-weight contaminants, which usually bear one accessible epitope. Theoretically, non-competitive, sandwich-type immunoassays have higher sensitivity, precision and linearity. However, the analyte to be measured in such a format must be large enough to have at least two epitopes to be captured. It is not feasible to detect low-molecular-weight contaminants through conventional non-competitive sandwich-type immunoassay. Consequently, there is a trend to develop new types of sensitive non-competitive immunoassays for low-molecular-weight contaminants. This article reviews the progress in non-competitive immunoassays for low molecular weight contaminants in food, feed and agricultural products, including the principles, applications and suggested perspectives for this field. Anti-metatype antibody-based immunoassays are the most promising method, but dissociation of the antibody-hapten complex might be a challenge, and therefore more in-depth research should be focused on preparation of new formats of the antibody-hapten complex. Meanwhile, strategies for direct non-competitive detection or aimed at the simultaneous detection of different targets would be especially desirable besides focusing on improving the sensitivity and specificity of the detection.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ldroc完成签到,获得积分10
刚刚
1秒前
111发布了新的文献求助10
1秒前
CipherSage应助欣慰的乐荷采纳,获得10
1秒前
1秒前
1秒前
小文关注了科研通微信公众号
2秒前
慕青应助starying采纳,获得10
2秒前
2秒前
小马完成签到 ,获得积分10
3秒前
3秒前
Lily完成签到,获得积分10
3秒前
123完成签到,获得积分20
3秒前
4秒前
余呀余完成签到 ,获得积分10
4秒前
爆米花应助淡然的小霸王采纳,获得10
4秒前
粗心小熊猫完成签到,获得积分10
4秒前
天真的冥王星完成签到,获得积分10
5秒前
Leucalypt完成签到,获得积分10
5秒前
storm完成签到 ,获得积分10
5秒前
cwm完成签到,获得积分10
5秒前
5秒前
5秒前
Pyrene完成签到,获得积分10
6秒前
W23完成签到,获得积分20
6秒前
柯同发布了新的文献求助10
7秒前
8秒前
8秒前
NexusExplorer应助sghpv采纳,获得10
8秒前
粗心的飞槐完成签到 ,获得积分10
8秒前
SAODEN完成签到,获得积分10
9秒前
一秒的剧情完成签到,获得积分10
9秒前
9秒前
zee发布了新的文献求助10
9秒前
ALU完成签到 ,获得积分10
9秒前
沉默思山完成签到,获得积分10
10秒前
taowang完成签到,获得积分10
10秒前
10秒前
10秒前
倩倩发布了新的文献求助10
10秒前
高分求助中
Applied Survey Data Analysis (第三版, 2025) 800
Assessing and Diagnosing Young Children with Neurodevelopmental Disorders (2nd Edition) 700
Images that translate 500
引进保护装置的分析评价八七年国外进口线路等保护运行情况介绍 500
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3841198
求助须知:如何正确求助?哪些是违规求助? 3383176
关于积分的说明 10528587
捐赠科研通 3103166
什么是DOI,文献DOI怎么找? 1709180
邀请新用户注册赠送积分活动 822971
科研通“疑难数据库(出版商)”最低求助积分说明 773733