Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression.
Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression.
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DOI:
10.1007/s00216-021-03665-1
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发表时间:
2021-11
影响因子:
4.3
通讯作者:
Andrews AM
中科院分区:
文献类型:
--
作者:
Movassaghi CS;Perrotta KA;Yang H;Iyer R;Cheng X;Dagher M;Fillol MA;Andrews AM
Many voltammetry methods have been developed to monitor brain extracellular dopamine levels. Fewer approaches have been successful in detecting serotonin in vivo. No voltammetric techniques are currently available to monitor both neurotransmitters simultaneously across timescales, even though they play integrated roles in modulating behavior. We provide proof-of-concept for rapid pulse voltammetry coupled with partial least squares regression (RPV-PLSR), an approach adapted from multi-electrode systems (i.e., electronic tongues) used to identify multiple components in complex environments. We exploited small differences in analyte redox profiles to select pulse steps for RPV waveforms. Using an intentionally designed pulse strategy combined with custom instrumentation and analysis software, we monitored basal and stimulated levels of dopamine and serotonin. In addition to faradaic currents, capacitive currents were important factors in analyte identification arguing against background subtraction. Compared to fast-scan cyclic voltammetry-principal components regression (FSCV-PCR), RPV-PLSR better differentiated and quantified basal and stimulated dopamine and serotonin associated with striatal recording electrode position, optical stimulation frequency, and serotonin reuptake inhibition. The RPV-PLSR approach can be generalized to other electrochemically active neurotransmitters and provides a feedback pipeline for future optimization of multi-analyte, fit-for-purpose waveforms and machine learning approaches to data analysis. The online version contains supplementary material available at 10.1007/s00216-021-03665-1.
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DOI:
10.1039/c4cc06165a
发表时间:
2015-02-11
期刊:
Chemical communications (Cambridge, England)
影响因子:
--
作者:
Atcherley CW;Wood KM;Parent KL;Hashemi P;Heien ML
通讯作者:
Heien ML
DOI:
10.1016/j.chemolab.2004.12.011
发表时间:
2005-07-28
影响因子:
3.9
作者:
Chong, IG;Jun, CH
通讯作者:
Jun, CH
影响因子:
8.4
作者:
Campos, Inmaculada;Alcaniz, Miguel;Gil, Luis
通讯作者:
Gil, Luis
影响因子:
3.5
作者:
Avery MC;Krichmar JL
通讯作者:
Krichmar JL
影响因子:
16.2
作者:
Bang D;Kishida KT;Lohrenz T;White JP;Laxton AW;Tatter SB;Fleming SM;Montague PR
通讯作者:
Montague PR