Bidirectionally Favorable Platform: A Dual-Targeting Probe-Encoded Maple Leaf-Type Fluorescent Lateral Flow Immunoassay for Multiple Biomarker Detection

检出限 化学 纳米团簇 色谱法 荧光 纳米技术 材料科学 物理 量子力学 有机化学
作者
Shen Zeng,Wanchao Zuo,Huilin Zhang,Jiaren Song,Qing Yang,Qian‐Nan Hu,X.L. Meng,Wenxuan Chen,Yazhou Wang,Jianjun Dai,Yanmin Ju
出处
期刊:Analytical Chemistry [American Chemical Society]
标识
DOI:10.1021/acs.analchem.4c06414
摘要

In the traditional multiplexed lateral flow immunoassay (LFIA), different detection probes against different targets are necessary. However, the relative complexity and high cost of probe preparation, as well as the insufficient user-friendliness, limit the application of the multiplexed LFIA in disease diagnosis. Here, we reported a bidirectionally favorable LFIA (BDF-LFIA) platform to maximize convenience for both manufacturers and users. Red-emitting time-resolved fluorescent nanoparticles were coated with different antibodies to recognize multiple targets simultaneously, which greatly simplified probe preparation by the manufacturers. Ultrabright green-emitting gold nanoclusters were pre-embedded on the test line as a reference signal to achieve a target concentration-dependent maple leaf-type hue readout from green to yellow to red, which was quite user-friendly. Taking cancer biomarkers alpha-fetoprotein and carcinoembryonic antigen as examples, this assay achieved a visual detection limit of 2 ng/mL. Compared with the conventional fluorescent LFIA, the BDF-LFIA could generate a more discernible signal around the threshold concentration of the targets. Moreover, the assay successfully diagnosed 54 clinical samples. Overall, the BDF-LFIA showed bidirectional benefits for both manufacturers and users and provided a new concept for the LFIA in multiplexed 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
zhang001完成签到,获得积分10
刚刚
沉默发布了新的文献求助10
1秒前
外向灰狼完成签到 ,获得积分10
2秒前
从容的无极应助xhptzw采纳,获得10
4秒前
蛋妞发布了新的文献求助10
4秒前
爆米花应助傲娇小废柴采纳,获得10
5秒前
5秒前
自觉芝麻完成签到,获得积分20
6秒前
6秒前
7秒前
8秒前
liars发布了新的文献求助10
9秒前
VV2001完成签到,获得积分10
11秒前
super chan发布了新的文献求助10
12秒前
12秒前
桂花酒酿发布了新的文献求助10
12秒前
小谷发布了新的文献求助10
13秒前
ren应助心心采纳,获得10
16秒前
16秒前
16秒前
17秒前
思源应助lyyyy采纳,获得10
17秒前
关中人完成签到,获得积分10
18秒前
20秒前
Reader01完成签到 ,获得积分10
21秒前
坚强的寒风完成签到 ,获得积分10
21秒前
田様应助当当采纳,获得10
23秒前
rous发布了新的文献求助10
23秒前
一米阳光发布了新的文献求助10
24秒前
我唉科研完成签到,获得积分10
24秒前
Edward发布了新的文献求助10
25秒前
傲娇小废柴完成签到,获得积分10
26秒前
CodeCraft应助super chan采纳,获得10
27秒前
小药丸完成签到,获得积分10
28秒前
31秒前
31秒前
31秒前
31秒前
Christine完成签到 ,获得积分10
32秒前
32秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2500
Востребованный временем 2500
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
지식생태학: 생태학, 죽은 지식을 깨우다 600
海南省蛇咬伤流行病学特征与预后影响因素分析 500
Neuromuscular and Electrodiagnostic Medicine Board Review 500
ランス多機能化技術による溶鋼脱ガス処理の高効率化の研究 500
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3461273
求助须知:如何正确求助?哪些是违规求助? 3054977
关于积分的说明 9045885
捐赠科研通 2744911
什么是DOI,文献DOI怎么找? 1505727
科研通“疑难数据库(出版商)”最低求助积分说明 695812
邀请新用户注册赠送积分活动 695233