期刊
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
卷 494, 期 1-2, 页码 181-187出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2017.10.059
关键词
Ex vivo sensor; Dopamine; Mouse Parkinson's disease model; Molybdenum disulfide; One-step electrochemical deposition
资金
- Pioneer Research Center Program through the National Research Foundation (NRF) - Ministry of Science, ICT & Future Planning (MSIP) of Korea [2013M3C1A3065522, 2009-0083538]
- Cooperative Research Program for Agriculture Science & Technology Development Rural Development Administration, Republic of Korea [PJ011757032017]
- National Research Foundation of Korea [2013M3C1A3065522, 22A20130012283] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- Rural Development Administration (RDA), Republic of Korea [PJ011757032017] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
We developed a new strategy for construction of a biosensor for the neurotransmitter dopamine. The biosensor was constructed by one-step electrochemical deposition of a nanocomposite in aqueous solution at pH 7.0, consisting of molybdenum disulfide, multi-walled carbon nanotubes, and polypyrrole. A series of analytical methods was performed to investigate the surface characteristics and the improved electrocatalytic effect of the nanocomposite, including cyclic voltammetry, electrochemical impedance spectroscopy, field-emission scanning electron microscopy, atomic force microscopy, and Raman spectroscopy. The constructed biosensor showed high sensitivity (1.130 mu A mu M(-1)cm(-2)) with a dynamic linearity range of 25-1000 nM and a detection limit of 10 nM. Additionally, the designed sensor exhibited strong anti-interference ability and satisfactory reproducibility. The practical application of the sensor was manifested for the ex vivo determination of dopamine neurotransmitters using brain tissue samples of a mouse Parkinson's disease model. (C) 2017 Elsevier Inc. All rights reserved.
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