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

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...

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Autores principales: Goyal, Abhinav, Hwang, Sangmun, Rusheen, Aaron E., Blaha, Charles D., Bennet, Kevin E., Lee, Kendall H., Jang, Dong Pyo, Oh, Yoonbae, Shin, Hojin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537688/
https://www.ncbi.nlm.nih.gov/pubmed/36213749
http://dx.doi.org/10.3389/fnins.2022.899436
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author Goyal, Abhinav
Hwang, Sangmun
Rusheen, Aaron E.
Blaha, Charles D.
Bennet, Kevin E.
Lee, Kendall H.
Jang, Dong Pyo
Oh, Yoonbae
Shin, Hojin
author_facet Goyal, Abhinav
Hwang, Sangmun
Rusheen, Aaron E.
Blaha, Charles D.
Bennet, Kevin E.
Lee, Kendall H.
Jang, Dong Pyo
Oh, Yoonbae
Shin, Hojin
author_sort Goyal, Abhinav
collection PubMed
description 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 vivo. 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 in vitro and in vivo 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 in vivo experiments.
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spelling pubmed-95376882022-10-08 Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo Goyal, Abhinav Hwang, Sangmun Rusheen, Aaron E. Blaha, Charles D. Bennet, Kevin E. Lee, Kendall H. Jang, Dong Pyo Oh, Yoonbae Shin, Hojin Front Neurosci Neuroscience 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 vivo. 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 in vitro and in vivo 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 in vivo experiments. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9537688/ /pubmed/36213749 http://dx.doi.org/10.3389/fnins.2022.899436 Text en Copyright © 2022 Goyal, Hwang, Rusheen, Blaha, Bennet, Lee, Jang, Oh and Shin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Goyal, Abhinav
Hwang, Sangmun
Rusheen, Aaron E.
Blaha, Charles D.
Bennet, Kevin E.
Lee, Kendall H.
Jang, Dong Pyo
Oh, Yoonbae
Shin, Hojin
Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title_full Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title_fullStr Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title_full_unstemmed Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title_short Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
title_sort software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537688/
https://www.ncbi.nlm.nih.gov/pubmed/36213749
http://dx.doi.org/10.3389/fnins.2022.899436
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