4.8 Article

Regenerative Flexible Upconversion-Luminescence Biosensor for Visual Detection of Diethylstilbestrol Based on Smartphone Imaging

期刊

ANALYTICAL CHEMISTRY
卷 93, 期 47, 页码 15667-15676

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.1c03325

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资金

  1. Natural Science Foundation of Jiangsu Province [BK20190100]
  2. Selfinnovation Fund Project of Agricultural Science and Technology in Jiangsu Province [CX(20)2005]
  3. Key R&D Program of Jiangsu Province [BE2020379]
  4. Project of Faculty of Agricultural Equipment of Jiangsu University

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A regenerative flexible upconversion-fluorescence biosensor was designed for detecting DES in food and environmental samples through a FRET system, showing good linear relationships. It demonstrated a spiked recovery rate of 77.91-97.95% in real environments and maintained an accuracy threshold of 80% after being regenerated seven times, indicating practicality and reusability.
Diethylstilbestrol (DES), an endocrine disrupting chemical, has been linked to serious health problems in humans. In this work, a regenerative flexible upconversion-fluorescence biosensor was designed for the detection of DES in foodstuffs and environmental samples. Herein, amino-functionalized upconversion nanoparticles (UCNPs) were synthesized and immobilized on the surface of a flexible polydimethylsiloxane substrate, which was further modified with complementary DNA and dabcyl-labeled DES aptamer. The fluorescence resonance energy transfer (FRET) system was established for DES detection between dabcyl and UCNPs as the acceptor and donor pairs, respectively, which resulted in the quenching of the upconversion luminescence intensity. In the presence of a target, the FRET system was destroyed and upconversion fluorescence was restored due to the stronger affinity of the aptamer toward DES. The designed biosensor was also implemented in a dual-mode signal readout based on images from a smartphone and spectra from a spectrometer. Under the optimized experimental conditions, good linear relationships were achieved based on imaging (y = 53.055x + 36.175, R-2 = 0.9851) and spectral data (y = 1.1582x + 1.9561, R-2 = 0.9897). The designed biosensor revealed great practicability with a spiked recovery rate of 77.91-97.95% for DES detection in real environment and foodstuff samples. Furthermore, the proposed biosensor was regenerated seven times with an accuracy threshold of 80% demonstrating its durability and reusability. Thus, this biosensor is expected to be applied to point-of-care and on-site detection based on the developed portable smartphone device and android application.

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