Quantitative detection of captopril in urine by smartphone-assisted ratiometric fluorescence sensing platform.

Captopril (CP) is a widely used antihypertensive drug. In this study, a smartphone-assisted sensing platform on the basis of ratiometric fluorescent test strips was developed, which can accomplish visualization for the quantitative detection of captopril. Ratiometric fluorescent probe was constructed from carbon dots (CDs) and gold nanoclusters (Au NCs). After adding Cu2+ to fluorescent probe, Cu2+ can complex the amino and carboxyl groups on the surface of Au NCs and aggregate Au NCs, which will quench the fluorescence of Au NCs. Compared with amino and carboxyl groups, -SH in CP has a higher affinity for Cu2+ and can capture Cu2+ to restore Au NCs fluorescence. In this process, CDs remained essentially unchanged as background fluorescence. As CP concentration increased, the fluorescence color showed a distinct change from blue to purple to orange. Based on this principle, a sensing platform combining smartphone and fluorescent test strips was constructed to visualize the quantitative detection of CP by RGB values. Under optimal conditions, the wide linear range of CP detection for both fluorescence spectrometer and smartphone paper-based sensing platform was 0.25-50 μM. The limits of detection were as low as 76 nM and 101.3 nM, respectively. Furthermore, it was implemented successfully for the detection of CP in urine. The satisfactory recoveries were 96.0-103.3% and 92.0-108.0% for fluorescence spectrometer and smartphone platform, respectively. This smartphone-assisted platform provided a new approach for visual detection of CP, which showed its great potential in bioanalytical assays. Copyright © 2022. Published by Elsevier B.V.

Citation

Lixia Han, Ting Liu, Di Cui, Jiaqi Yi, Wei Jiang, Xiaoshuang Li, Na Niu, Ligang Chen. Quantitative detection of captopril in urine by smartphone-assisted ratiometric fluorescence sensing platform. Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy. 2022 Nov 05;280:121562

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PMID: 35780761

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