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用于实时跟踪强直神经递质水平的伏安法软件。

Software for near-real-time voltammetric tracking of tonic neurotransmitter levels .

作者信息

Goyal Abhinav, Hwang Sangmun, Rusheen Aaron E, Blaha Charles D, Bennet Kevin E, Lee Kendall H, Jang Dong Pyo, Oh Yoonbae, Shin Hojin

机构信息

Mayo Clinic Medical Scientist Training Program, Mayo Clinic, Rochester, MN, United States.

Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States.

出版信息

Front Neurosci. 2022 Sep 23;16:899436. doi: 10.3389/fnins.2022.899436. eCollection 2022.

Abstract

Tonic extracellular neurotransmitter concentrations are important modulators of central network homeostasis. Disruptions in these tonic levels are thought to play a role in neurologic and psychiatric disease. Therefore, ways to improve their quantification are actively being investigated. Previously published voltammetric software packages have implemented FSCV, which is not capable of measuring tonic concentrations of neurotransmitters . In this paper, custom software was developed for near-real-time tracking (scans every 10 s) of neurotransmitters' tonic concentrations with high sensitivity and spatiotemporal resolution both and using cyclic voltammetry combined with dynamic background subtraction (M-CSWV and FSCAV). This software was designed with flexibility, speed, and user-friendliness in mind. This software enables near-real-time measurement by reducing data analysis time through an optimized modeling algorithm, and efficient memory handling makes long-term measurement possible. The software permits customization of the cyclic voltammetric waveform shape, enabling experiments to detect a specific analyte of interest. Finally, flexibility considerations allow the user to alter the fitting parameters, filtering characteristics, and size and shape of the analyte kernel, based on data obtained live during the experiment to obtain accurate measurements as experimental conditions change. Herein, the design and advantages of this near-real-time voltammetric software are described, and its use is demonstrated in experiments.

摘要

细胞外神经递质的稳态浓度是中枢网络稳态的重要调节因子。这些稳态水平的破坏被认为在神经和精神疾病中起作用。因此,人们正在积极研究提高其定量的方法。先前发表的伏安软件包采用了快速扫描循环伏安法(FSCV),该方法无法测量神经递质的稳态浓度。在本文中,开发了定制软件,用于通过循环伏安法结合动态背景扣除(M-CSWV和FSCAV)以高灵敏度和时空分辨率对神经递质的稳态浓度进行近实时跟踪(每10秒扫描一次)。该软件在设计时考虑了灵活性、速度和用户友好性。该软件通过优化的建模算法减少数据分析时间,实现近实时测量,高效的内存处理使长期测量成为可能。该软件允许定制循环伏安波形形状,使实验能够检测特定的目标分析物。最后,出于灵活性考虑,用户可以根据实验过程中实时获得的数据改变拟合参数、滤波特性以及分析物内核的大小和形状,以便在实验条件变化时获得准确测量结果。本文描述了这种近实时伏安软件的设计和优点,并在实验中展示了其应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f5ab/9537688/45dd9c5dde7b/fnins-16-899436-g001.jpg

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