Issue 11, 2015

Stabilization of Prussian blue with polyaniline and carbon nanotubes in neutral media for in vivo determination of glucose in rat brains

Abstract

This study demonstrates a new electrochemical microbiosensor for selective in vivo monitoring of glucose in rat brains. The microbiosensor is prepared by using Prussian blue (PB)/polyaniline (PANI)/multi-walled carbon nanotubes (MWNTs) as the electrocatalyst for the reduction and determination of H2O2 generated from the glucose oxidase (GOx)-based enzymatic catalytic reaction. PANI and MWNTs are used to stabilize PB nanoparticles in physiological solutions. As a result, the as-formed three-dimensional (3D) PB/PANI/MWNT nanostructure exhibits a stable and large electrochemical response compared to the PB-modified electrode. The use of PB/PANI/MWNTs in this work to replace “natural peroxidase” (i.e., horseradish peroxidase) used in the existing microbiosensors enables the method developed here to be facile but selective for in vivo measurements of glucose virtually interference-free from ascorbic acid and other electroactive species coexisting in the brain. This property, along with the good linearity and stability toward glucose, makes this microbiosensor competent for continuous in vivo monitoring of the changes of glucose in rat brains during intraperitoneal injection of insulin. The method demonstrated here can be applied to develop other oxidase-based microbiosensors for other neurochemicals, which would be helpful for understanding the chemical process involved in some physiological and pathological events.

Graphical abstract: Stabilization of Prussian blue with polyaniline and carbon nanotubes in neutral media for in vivo determination of glucose in rat brains

Article information

Article type
Paper
Submitted
21 Dec. 2014
Accepted
16 Janv. 2015
First published
19 Janv. 2015

Analyst, 2015,140, 3746-3752

Stabilization of Prussian blue with polyaniline and carbon nanotubes in neutral media for in vivo determination of glucose in rat brains

R. Li, D. Guo, J. Ye and M. Zhang, Analyst, 2015, 140, 3746 DOI: 10.1039/C4AN02352H

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