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基于卷积的非 Faradaic 电流消除法测量基础神经递质水平。

Measurement of Basal Neurotransmitter Levels Using Convolution-Based Nonfaradaic Current Removal.

出版信息

Anal Chem. 2018 Jun 19;90(12):7181-7189. doi: 10.1021/acs.analchem.7b04682. Epub 2018 Jun 7.

Abstract

Fast-scan cyclic voltammetry permits robust subsecond measurements of in vivo neurotransmitter dynamics, resulting in its established use in elucidating these species' roles in the actions of behaving animals. However, the technique's limitations, namely the need for digital background subtraction for analytical signal resolution, have restricted the information obtainable largely to that about phasic neurotransmitter release on the second-to-minute time scale. The study of basal levels of neurotransmitters and their dynamics requires a means of isolating the portion of the background current arising from neurotransmitter redox reactions. Previously, we reported on the use of a convolution-based method for prediction of the resistive-capacitive portion of the carbon-fiber microelectrode background signal, to improve the information content of background-subtracted data. Here we evaluated this approach for direct analytical signal isolation. First, protocol modifications (i.e., applied waveform and carbon-fiber type) were optimized to permit simplification of the interfering background current to components that are convolution-predictable. It was found that the use of holding potentials of at least 0.0 V, as well as the use of pitch-based carbon fibers, improved the agreement between convolution predictions and the observed background. Subsequently, it was shown that measurements of basal dopamine concentrations are possible with careful control of the electrode state. Successful use of this approach for measurement of in vivo basal dopamine levels is demonstrated, suggesting the approach may serve as a useful tool in expanding the capabilities of fast-scan cyclic voltammetry.

摘要

快速扫描循环伏安法允许对体内神经递质动力学进行稳健的亚秒级测量,从而使其在阐明这些物质在行为动物作用中的作用方面得到了广泛应用。然而,该技术的局限性,即需要数字背景扣除来解析分析信号,在很大程度上限制了可获得的信息仅限于关于在秒到分钟时间范围内的相位神经递质释放。研究神经递质的基础水平及其动力学需要一种能够分离来自神经递质氧化还原反应的背景电流部分的方法。以前,我们报告了使用基于卷积的方法来预测碳纤维微电极背景信号的电阻-电容部分,以提高背景扣除数据的信息量。在这里,我们评估了这种方法用于直接分析信号隔离。首先,对协议进行了修改(即施加的波形和碳纤维类型),以简化干扰背景电流,使其成为卷积可预测的部分。结果发现,使用至少 0.0 V 的保持电位以及使用基于节距的碳纤维可以改善卷积预测和观察到的背景之间的一致性。随后表明,通过仔细控制电极状态,可以进行基础多巴胺浓度的测量。成功地将这种方法用于测量体内基础多巴胺水平,表明该方法可能成为扩展快速扫描循环伏安法功能的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fdf/6011837/8ab60d8c6182/ac-2017-04682j_0008.jpg

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