Centrifugation-assisted lateral flow assay platform: enhancing bioassay sensitivity with active flow control.

IF 7.3 1区 工程技术 Q1 INSTRUMENTS & INSTRUMENTATION
Hang Yuan, Ruiqi Yong, Wenwen Yuan, Quan Zhang, Eng Gee Lim, Yongjie Wang, Fuzhou Niu, Pengfei Song
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引用次数: 0

Abstract

Lateral flow assays (LFAs) are widely used in point-of-care testing (POCT) due to their simplicity and rapid operation. However, their reliance on passive capillary flow limits sensitivity, making it challenging to detect low-abundance biomarkers accurately. Approaches such as computer signal processing, chemical modification, and physical regulation have been explored to improve LFA sensitivity, but they remain limited by passive capillary-driven flow and uncontrollable flow rate. An alternative approach is to actively regulate fluid dynamics to optimize analyte binding and signal generation. The key challenge is to enhance LFA sensitivity while preserving compatibility with existing lateral flow strips (LFSs). Here, this study introduces a centrifugation-assisted LFA (CLFA) platform with smartphone-based result processing. This platform applies centrifugal force opposite to capillary flow, actively regulating fluid movement to optimize incubation time at the reaction zone and enhance detection performance. This approach increases signal intensity while maintaining a rapid detection process (5 min) and ensuring integration with traditional LFSs. As a proof-of-concept, the CLFA platform successfully detected human chorionic gonadotropin (hCG) and hemoglobin (Hb) in artificial urine without requiring custom-designed centrifugal discs or modified chromatography membranes. Its adaptability to diverse biomarkers and smartphone-based quantification make it a promising POCT tool, particularly in resource-limited settings.

离心辅助横向流动分析平台:通过主动流动控制提高生物测定灵敏度。
横向流动分析(LFAs)由于其简单和快速的操作被广泛应用于即时检测(POCT)。然而,它们对被动毛细管流动的依赖限制了灵敏度,使得准确检测低丰度生物标志物具有挑战性。人们探索了计算机信号处理、化学改性和物理调节等方法来提高LFA的灵敏度,但它们仍然受到被动毛细管驱动流动和不可控流量的限制。另一种方法是积极调节流体动力学,以优化分析物结合和信号产生。关键的挑战是提高LFA的灵敏度,同时保持与现有横向流动条带(lfs)的相容性。在这里,本研究介绍了一种基于智能手机的离心辅助LFA (CLFA)平台。该平台利用与毛细管流动相反的离心力,主动调节流体运动,优化反应区孵育时间,提高检测性能。这种方法增加了信号强度,同时保持了快速检测过程(5分钟),并确保了与传统lfs的集成。作为概念验证,CLFA平台成功检测了人造尿液中的人绒毛膜促性腺激素(hCG)和血红蛋白(Hb),而无需定制设计的离心圆盘或改进的色谱膜。它对各种生物标志物的适应性和基于智能手机的量化使其成为一种有前途的POCT工具,特别是在资源有限的环境中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Microsystems & Nanoengineering
Microsystems & Nanoengineering Materials Science-Materials Science (miscellaneous)
CiteScore
12.00
自引率
3.80%
发文量
123
审稿时长
20 weeks
期刊介绍: Microsystems & Nanoengineering is a comprehensive online journal that focuses on the field of Micro and Nano Electro Mechanical Systems (MEMS and NEMS). It provides a platform for researchers to share their original research findings and review articles in this area. The journal covers a wide range of topics, from fundamental research to practical applications. Published by Springer Nature, in collaboration with the Aerospace Information Research Institute, Chinese Academy of Sciences, and with the support of the State Key Laboratory of Transducer Technology, it is an esteemed publication in the field. As an open access journal, it offers free access to its content, allowing readers from around the world to benefit from the latest developments in MEMS and NEMS.
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