亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Aptamer-based lateral flow assay on-site biosensors

适体 分析物 生物传感器 免疫分析 检出限 化学 纳米技术 色谱法 材料科学 分子生物学 抗体 生物 免疫学
作者
Lei Huang,Shulin Tian,Wenhao Zhao,Ke Liu,Xing Ma,Jinhong Guo
出处
期刊:Biosensors and Bioelectronics [Elsevier BV]
卷期号:186: 113279-113279 被引量:88
标识
DOI:10.1016/j.bios.2021.113279
摘要

The lateral flow assay (LFA) is a widely used paper-based on-site biosensor that can detect target analytes and obtain test results in several minutes. Generally, antibodies are utilized as the biorecognition molecules in the LFA. However, antibodies selected using an in vivo process not only may risk killing the animal hosts and causing errors between different batches but also their range is restricted by the refrigerated conditions used to store them. To avoid these limitations, aptamers screened by an in vitro process have been studied as biorecognition molecules in LFAs. Based on the sandwich or competitive format, the aptamer-based LFA can accomplish on-site detection of target analytes. Since aptamers have a distinctive ability to undergo conformational changes, the adsorption–desorption format has also been exploited to detect target analytes in aptamer-based LFAs. This paper reviews developments in aptamer-based LFAs in the last three years for the detection of target analytes. Three formats of aptamer-based LFAs, i.e., sandwich, competitive, and adsorption–desorption, are described in detail. Based on these formats, signal amplification strategies and multiplexed detection are discussed in order to provide an overview of aptamer-based LFAs for on-site detection of target analytes. In addition, the potential commercialization and future perspectives of aptamer-based LFAs for rapid detection of SARS-CoV-2 are given to support the COVID-19 pandemic.

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
yat发布了新的文献求助10
1秒前
1a发布了新的文献求助10
2秒前
9秒前
18秒前
18秒前
21秒前
粉鸡家族完成签到,获得积分10
21秒前
xl发布了新的文献求助10
22秒前
23秒前
CipherSage应助dhx7530采纳,获得10
26秒前
牛八先生发布了新的文献求助20
27秒前
OsamaKareem应助科研通管家采纳,获得10
33秒前
科研通AI2S应助科研通管家采纳,获得10
33秒前
36秒前
44秒前
JamesPei应助aaa采纳,获得10
57秒前
xiao_123123发布了新的文献求助20
59秒前
Tania完成签到,获得积分10
1分钟前
1分钟前
1分钟前
科研通AI6.3应助xiao_123123采纳,获得30
1分钟前
汉堡包应助水若琳采纳,获得10
1分钟前
dhx7530发布了新的文献求助10
1分钟前
梦明完成签到 ,获得积分10
1分钟前
万能图书馆应助Sara采纳,获得20
1分钟前
1分钟前
鳗鱼不尤完成签到,获得积分10
1分钟前
水若琳发布了新的文献求助10
1分钟前
在水一方应助坦率的邑采纳,获得10
1分钟前
文艺冰露发布了新的文献求助30
1分钟前
1分钟前
坦率的邑发布了新的文献求助10
1分钟前
1分钟前
科研通AI6.4应助文艺冰露采纳,获得10
1分钟前
科研通AI2S应助坦率的邑采纳,获得10
1分钟前
总是很简单完成签到 ,获得积分10
1分钟前
1分钟前
搜集达人应助ywl采纳,获得10
2分钟前
水若琳发布了新的文献求助10
2分钟前
好友新娘完成签到,获得积分10
2分钟前
高分求助中
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6495759
求助须知:如何正确求助?哪些是违规求助? 8292535
关于积分的说明 17694822
捐赠科研通 5589863
什么是DOI,文献DOI怎么找? 2916654
邀请新用户注册赠送积分活动 1893537
关于科研通互助平台的介绍 1753057