基于荧光的横向流动免疫分析法,使用 AIEgen 封装的纳米颗粒快速灵敏地检测促胃泌素释放肽

IF 5.3 2区 化学 Q1 CHEMISTRY, ANALYTICAL
Xiangyang Shao, Xiaoli Liu, Lianzi Yu, Xiuzhi Yu, Jianhua Hu
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引用次数: 0

摘要

本文介绍了一种荧光横向流动免疫分析法(F-LFIA),该方法采用纳米颗粒作为荧光标记,其分子被包裹在纳米颗粒中,其发射是由聚集引起的,从而定量检测血清中的胃泌素释放肽前体(proGRP)。检测系统经过优化,F-LFIA 的线性检测范围为 10 ~ 5000 pg/mL,检测限为 6 pg/mL。该方法具有良好的灵敏度、特异性和重现性。在对 183 份人体血清样本的分析中,对 F-LFIA 的性能和适用性进行了评估,结果与电化学发光免疫分析的结果密切相关。所提出的F-LFIA可作为一种精确、快速检测proGRP的方法,并有望用于小细胞肺癌(SCLC)的早期诊断。 图文摘要
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fluorescence-based lateral flow immunoassay using AIEgen-encapsulated nanoparticles to rapidly and sensitively detect pro-gastrin-releasing peptide

A fluorescence lateral flow immunoassay (F-LFIA) is presented using nanoparticles with encapsulated molecules whose emission is caused by aggregation as the fluorescent label to quantitatively detect gastrin-releasing peptide precursor (proGRP) in serum. The detection system was optimized to achieve a broad linear detection range of 10 ~ 5000 pg/mL and a detection limit of 6 pg/mL for F-LFIA. The proposed method exhibited good sensitivity, specificity, and reproducibility. The performance and applicability of the F-LFIA were evaluated in the analysis of 183 human serum samples, and the results were strongly correlated with those of the electrochemiluminescence immunoassay. The proposed F-LFIA can serve as a precise and rapid detection method to detect proGRP and has potential for the early diagnosis of small-cell lung cancer (SCLC).

Graphical Abstract

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来源期刊
Microchimica Acta
Microchimica Acta 化学-分析化学
CiteScore
9.80
自引率
5.30%
发文量
410
审稿时长
2.7 months
期刊介绍: As a peer-reviewed journal for analytical sciences and technologies on the micro- and nanoscale, Microchimica Acta has established itself as a premier forum for truly novel approaches in chemical and biochemical analysis. Coverage includes methods and devices that provide expedient solutions to the most contemporary demands in this area. Examples are point-of-care technologies, wearable (bio)sensors, in-vivo-monitoring, micro/nanomotors and materials based on synthetic biology as well as biomedical imaging and targeting.
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