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Abstract
Point-of-care testing (POCT) is widely used for early diagnosis and monitoring of diseases. Lateral flow assay (LFA) is a successfully commercial tool for POCT. However, LFA often suffers from a lack of quantification and analytical sensitivity. To solve these drawbacks, we have previously developed a thermal LFA using plasmonic gold nanoparticles for thermal contrast into a portable device. Although this methodology significantly improves the analytical sensitivity compared with conventional visual detection, quantification problems are still remaining. In this study, we optimized the operating conditions for the device using conduction and radiation thermal sensing modes allowing the quantification of LFA. The limit of detection of the strips merely containing nanoparticles was decreased by 5-fold (conduction mode) and 12-fold (radiation mode) compared to traditional visual detection. The effect of the ambient temperature was studied for both methods of detection showing that the radiation mode was more affected by the ambient temperature than the conduction mode. To validate the thermal sensing method, human chorionic gonadotropin (HCG) biomarker was quantified using our LFA strips, obtaining a detection limit of 2.8 mIU/mL when using the radiation method of detection.
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1 Shanghai Jiao Tong University, Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293)
2 Shanghai Jiao Tong University, Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293); Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales Nanomedicina (CIBER-BBN), Madrid, Spain (GRID:grid.413448.e) (ISNI:0000 0000 9314 1427)
3 Shanghai Jiao Tong University, Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent diagnosis and treatment instrument, Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293); Instituto de Ciencia de Materiales de Aragón (ICMA), CSIC/Universidad de Zaragoza, Zaragoza, Spain (GRID:grid.466773.7) (ISNI:0000 0001 0576 2336); Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales Nanomedicina (CIBER-BBN), Madrid, Spain (GRID:grid.413448.e) (ISNI:0000 0000 9314 1427)