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Issue 44, 2018
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Sensitive detection of bisphenol A in drinking water and river water using an upconversion nanoparticles-based fluorescence immunoassay in combination with magnetic separation

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Abstract

We have proposed a sensitive fluorescence immunoassay for detecting bisphenol A (BPA) in barreled drinking water, bottled mineral water, and river water using the anti-BPA antibody conjugated carboxyl-functionalized NaYF4:Yb/Tm upconversion nanoparticles (UCNPs) (emission maximum at 454 nm with excitation at 980 nm) as the signal probe and the coating antigen conjugated carboxyl-functionalized magnetic polystyrene microspheres (MPMs) as the capture probe. The proposed assay has a linear detection range of 0.1 to 500 μg L−1 (R2 = 0.9954). The water samples without any pretreatment can be directly analyzed. The limit of detection (LOD) of BPA in the water samples is 0.02 μg L−1. The recoveries of BPA from spiked water samples for the proposed assay range from 85.35% to 108.35%. Low concentrations of BPA have been detected in the real barreled drinking water and river water samples, and the results are validated by high-performance liquid chromatography (HPLC) to be reliable, reflecting the good practicability of the proposed assay. The proposed fluorescence immunoassay can serve as a useful detection approach for the simple, rapid, sensitive, and accurate determination of BPA in drinking and environmental water.

Graphical abstract: Sensitive detection of bisphenol A in drinking water and river water using an upconversion nanoparticles-based fluorescence immunoassay in combination with magnetic separation

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Publication details

The article was received on 03 Jun 2018, accepted on 17 Oct 2018 and first published on 17 Oct 2018


Article type: Paper
DOI: 10.1039/C8AY01260A
Citation: Anal. Methods, 2018,10, 5313-5320
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    Sensitive detection of bisphenol A in drinking water and river water using an upconversion nanoparticles-based fluorescence immunoassay in combination with magnetic separation

    W. Sheng, W. Duan, Y. Shi, Q. Chang, Y. Zhang, Y. Lu and S. Wang, Anal. Methods, 2018, 10, 5313
    DOI: 10.1039/C8AY01260A

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