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

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.

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Publication Details

Journal
Microsystems & Nanoengineering
Published
2025-05-22
DOI
https://doi.org/10.1038/s41378-025-00923-5
Citations
14
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
9.44

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article

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

Fuzhou Niu, Eng Gee Lim, Wenwen Yuan, Quan Zhang et al.
14 citations
Microsystems & Nanoengineering
Biosensors and Analytical Detection
9.44
article

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

Fuzhou Niu, Eng Gee Lim, Wenwen Yuan, Quan Zhang, Pengfei Song, Yongjie Wang, Hang Yuan, Ruiqi Yong
article en
14 citations

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.

Microsystems & NanoengineeringVol. 11(1)
University of Liverpool (GB), Harbin Institute of Technology (CN), Suzhou University of Science and Technology (CN), Xi’an Jiaotong-Liverpool University (CN)
Government of Jiangsu Province, Xi’an Jiaotong-Liverpool University
Openalex Percentile: Top 2%
Biosensors and Analytical Detection
9.44
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