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Dual signal amplification strategy for electrochemical detection of platelet-derived growth factor BB

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Abstract

The authors report a dual signal amplification strategy for improving the sensitivity of an electrochemical immunosensor. Single-walled carbon nanotubes (SCNTs) served as supports for aptamers and alkaline phosphatase (ALP), and then the modified SCNTs were utilized as electrochemical probes. The aptamer contains phosphate groups, while ALP can hydrolyse one molecular pyrophosphate into two molecular phosphate ions. The phosphate can react with molybdate to form a redox-active molybdophosphate precipitate on the surface of the glassy carbon electrode (GCE). With applying a relatively low voltage of 0.21 V (vs. Ag/AgCl), the generated electrochemical current intensity is proportional to the concentration of the analyte. The cancer biomarker platelet-derived growth factor BB (PDGF-BB) was chosen as a model antigen (analyte). The immunosensor was prepared by sequential capturing of the antibodies against PDGF-BB, analyte (PDGF-BB) and modified SCNTs on the GCE to form a sandwich structure. The current signal is linear in the concentration range of 0.1 pg mL−1 to 50 ng mL−1 PDGF-BB, with a detection limit as low as 50 fg mL−1. The immunosensor was finally applied in the determination of PDGF-BB concentration in serum samples. Our perception is that this signal amplification strategy can be adapted to the preparation of other immunosensors and will find wide applications in the detection of different biomarkers and related species.

Graphical abstract: Dual signal amplification strategy for electrochemical detection of platelet-derived growth factor BB

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Publication details

The article was received on 26 Oct 2017, accepted on 06 Nov 2017 and first published on 07 Nov 2017


Article type: Paper
DOI: 10.1039/C7AY02513K
Citation: Anal. Methods, 2017, Advance Article
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    Dual signal amplification strategy for electrochemical detection of platelet-derived growth factor BB

    B. Xie, N. Zhou, R. Ding, Y. Zhao, B. Zhang, T. Li and M. Yang, Anal. Methods, 2017, Advance Article , DOI: 10.1039/C7AY02513K

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