Meunier Carl J, Roberts James G, McCarty Gregory S, Sombers Leslie A
Department of Chemistry, North Carolina State University , Raleigh, North Carolina 27695-8204, United States.
ACS Chem Neurosci. 2017 Feb 15;8(2):411-419. doi: 10.1021/acschemneuro.6b00325. Epub 2017 Jan 24.
Background-subtracted fast-scan cyclic voltammetry (FSCV) has emerged as a powerful analytical technique for monitoring subsecond molecular fluctuations in live brain tissue. Despite increasing utilization of FSCV, efforts to improve the accuracy of quantification have been limited due to the complexity of the technique and the dynamic recording environment. It is clear that variable electrode performance renders calibration necessary for accurate quantification; however, the nature of in vivo measurements can make conventional postcalibration difficult, or even impossible. Analyte-specific voltammograms and scaling factors that are critical for quantification can shift or fluctuate in vivo. This is largely due to impedance changes, and the effects of impedance on these measurements have not been characterized. We have previously reported that the background current can be used to predict electrode-specific scaling factors in situ. In this work, we employ model circuits to investigate the impact of impedance on FSCV measurements. Additionally, we take another step toward in situ electrode calibration by using the oxidation potential of quinones on the electrode surface to accurately predict the oxidation potential for dopamine at any point in an electrochemical experiment, as both are dependent on impedance. The model, validated both in adrenal slice and live brain tissue, enables information encoded in the shape of the background voltammogram to determine electrochemical parameters that are critical for accurate quantification. This improves data interpretation and provides a significant next step toward more automated methods for in vivo data analysis.
背景扣除快速扫描循环伏安法（FSCV）已成为监测活脑组织中亚秒级分子波动的强大分析技术。尽管FSCV的应用越来越广泛，但由于该技术的复杂性和动态记录环境，提高定量准确性的努力仍然有限。显然，可变的电极性能使得校准对于准确定量是必要的；然而，体内测量的性质可能使传统的校准后处理变得困难，甚至不可能。对于定量至关重要的分析物特异性伏安图和比例因子在体内可能会发生偏移或波动。这主要是由于阻抗变化，而阻抗对这些测量的影响尚未得到表征。我们之前曾报道，背景电流可用于原位预测电极特异性比例因子。在这项工作中，我们使用模型电路来研究阻抗对FSCV测量的影响。此外，我们朝着原位电极校准又迈进了一步，通过利用电极表面醌的氧化电位来准确预测电化学实验中任何时间点多巴胺的氧化电位，因为两者都取决于阻抗。该模型在肾上腺切片和活脑组织中均得到验证，能够利用背景伏安图形状中编码的信息来确定对准确定量至关重要的电化学参数。这改善了数据解释，并朝着更自动化的体内数据分析方法迈出了重要的下一步。
