Issue 44, 2018

A MnO2 nanosheets–o-phenylenediamine oxidative system for the sensitive fluorescence determination of alkaline phosphatase activity

Abstract

Alkaline phosphatase (ALP) plays a crucial role in the regulation of intracellular processes and acts as an important biomarker for diagnosis of diverse diseases. Herein, we report a selective, sensitive and convenient sensing assay for detecting ALP based on a MnO2 nanosheets–o-phenylenediamine (OPDA) oxidative system. In this system, the MnO2 nanosheets could effectively oxidize OPDA to produce fluorescent OPDAox for fluorescence detection, while the incubation of MnO2 nanosheets with ascorbic acid (AA) would first lead to the reduction of the MnO2 nanosheets and then inhibit the formation of fluorescent OPDAox. Based on this principle, a sensitive and rapid method for fluorescence sensing of AA with a good linear relationship from 0.1 to 50 μM (R2 = 0.9962) was achieved. ALP can enzymatically hydrolyze 2-phospho-L-ascorbic acid (AAP) to produce AA, which could reduce the MnO2 nanosheets and inhibit the oxidation of OPDA to fluorescent OPDAox. Then, the MnO2 nanosheets–OPDA sensing system was applied to detect ALP. This fluorescence sensing system could detect ALP activity selectively, sensitively and conveniently with a good linear relationship from 0.1 to 200 U L−1 (R2 = 0.9946); meanwhile, this system was also applied to detect ALP in human serum samples. Taken together, the proposed MnO2–OPDA oxidative system shows promising potential in biomedical applications.

Graphical abstract: A MnO2 nanosheets–o-phenylenediamine oxidative system for the sensitive fluorescence determination of alkaline phosphatase activity

Supplementary files

Article information

Article type
Paper
Submitted
19 Sep 2018
Accepted
25 Oct 2018
First published
29 Oct 2018

Anal. Methods, 2018,10, 5341-5346

A MnO2 nanosheets–o-phenylenediamine oxidative system for the sensitive fluorescence determination of alkaline phosphatase activity

X. Tan, Z. Li, Y. Du, A. Zheng, Y. Zeng, X. Zhang, X. Liu and N. Peng, Anal. Methods, 2018, 10, 5341 DOI: 10.1039/C8AY02061B

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