4.8 Article

Towards timely Alzheimer diagnosis: A self-powered amperometric biosensor for the neurotransmitter acetylcholine

期刊

BIOSENSORS & BIOELECTRONICS
卷 87, 期 -, 页码 607-614

出版社

ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2016.08.104

关键词

Enzymatic fuel cell; Acetylcholinesterase; Acetylcholine; Highly porous gold; Alzheimer

资金

  1. Fundacao para a Ciencia e Tecnologia [SFRH/BPD/97891/2013]
  2. Fundação para a Ciência e a Tecnologia [SFRH/BPD/97891/2013] Funding Source: FCT

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Serious brain disorders, such as the Alzheimer's Disease (AD), are associated with a marked drop in the levels of important neurotransmitters, such as acetylcholine (ACh). Real time monitoring of such biomarkers can therefore play a critical role in enhancing AD therapies by allowing timely diagnosis, verifications of treatment effectiveness, and developments of new medicines. In this study, we present the first acetylcholine/oxygen hybrid enzymatic fuel cell for the self-powered on site detection of ACh in plasma, which is based on the combination of an enzymatic anode with a Pt cathode. Firstly, an effective acetylcholinesterase immobilized electrode was developed and its electrochemical performance evaluated. Highly porous gold was used as the electrode material, and the enzyme was immobilized via a one step rapid and simple procedure that does not require the use of harsh chemicals or any electrode/enzyme pre-treatments. The resulting enzymatic electrode was subsequently used as the anode of a miniature flow-through membrane-less fuel cell and showed excellent response to varying concentrations of ACh. The peak power generated by the fuel cell was 4 nW at a voltage of 260 mV and with a current density of 9 mu A cm(-2). The limit of detection of the fuel cell sensor was 10 mu M, with an average response time as short as 3 min. These exciting results open new horizons for point-of-care Alzheimer diagnosis and provide an attractive potential alternative to established methods that require laborious and time-consuming sample treatments and expensive instruments. (C) 2016 Elsevier B.V. All rights reserved.

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