Browse
Submit Data
Databases
API
Help

Dataset Information

48 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Integral methods for automatic quantification of fast-scan-cyclic-voltammetry detected neurotransmitters.

ABSTRACT: Modern techniques for estimating basal levels of electroactive neurotransmitters rely on the measurement of oxidative charges. This requires time integration of oxidation currents at certain intervals. Unfortunately, the selection of integration intervals relies on ad-hoc visual identification of peaks on the oxidation currents, which introduces sources of error and precludes the development of automated procedures necessary for analysis and quantification of neurotransmitter levels in large data sets. In an effort to improve charge quantification techniques, here we present novel methods for automatic selection of integration boundaries. Our results show that these methods allow quantification of oxidation reactions both in vitro and in vivo and of multiple analytes in vitro.

SUBMITTER: Espin LX

PROVIDER: S-EPMC8312965 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Integral methods for automatic quantification of fast-scan-cyclic-voltammetry detected neurotransmitters.

Espín Leonardo X LX Asp Anders J AJ Trevathan James K JK Ludwig Kip A KA Lujan J Luis JL

PloS one 20210726 7

Modern techniques for estimating basal levels of electroactive neurotransmitters rely on the measurement of oxidative charges. This requires time integration of oxidation currents at certain intervals. Unfortunately, the selection of integration intervals relies on ad-hoc visual identification of peaks on the oxidation currents, which introduces sources of error and precludes the development of automated procedures necessary for analysis and quantification of neurotransmitter levels in large dat ...[more]

PMID: 34310610

Similar Datasets

Assessing principal component regression prediction of neurochemicals detected with fast-scan cyclic voltammetry.

Project description:Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook's distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards.

| S-EPMC3182154 | biostudies-other

Fundamentals of fast-scan cyclic voltammetry for dopamine detection.

Project description:Fast-scan cyclic voltammetry (FSCV) is used with carbon-fiber microelectrodes for the real-time detection of neurotransmitters on the subsecond time scale. With FSCV, the potential is ramped up from a holding potential to a switching potential and back, usually at a 400 V s-1 scan rate and a frequency of 10 Hz. The plot of current vs. applied potential, the cyclic voltammogram (CV), has a very different shape for FSCV than for traditional cyclic voltammetry collected at scan rates which are 1000-fold slower. Here, we explore the theory of FSCV, with a focus on dopamine detection. First, we examine the shape of the CVs. Background currents, which are 100-fold higher than faradaic currents, are subtracted out. Peak separation is primarily due to slow electron transfer kinetics, while the symmetrical peak shape is due to exhaustive electrolysis of all the adsorbed neurotransmitters. Second, we explain the origins of the dopamine waveform, and the factors that limit the holding potential (oxygen reduction), switching potential (water oxidation), scan rate (electrode instability), and repetition rate (adsorption). Third, we discuss data analysis, from data visualization with color plots, to the automated algorithms like principal components regression that distinguish dopamine from pH changes. Finally, newer applications are discussed, including optimization of waveforms for analyte selectivity, carbon nanomaterial electrodes that trap dopamine, and basal level measurements that facilitate neurotransmitter measurements on a longer time scale. FSCV theory is complex, but understanding it enables better development of new techniques to monitor neurotransmitters in vivo.

| S-EPMC7028514 | biostudies-literature

Real-Time Fast Scan Cyclic Voltammetry Detection and Quantification of Exogenously Administered Melatonin in Mice Brain.

Project description:Melatonin (MT) has been recently considered an excellent candidate for the treatment of sleep disorders, neural injuries, and neurological diseases. To better investigate the actions of MT in various brain functions, real-time detection of MT concentrations in specific brain regions is much desired. Previously, we have demonstrated detection of exogenously administered MT in anesthetized mouse brain using square wave voltammetry (SWV). Here, for the first time, we show successful detection of exogenous MT in the brain using fast scan cyclic voltammetry (FSCV) on electrochemically pre-activated carbon fiber microelectrodes (CFEs). In vitro evaluation showed the highest sensitivity (28.1 nA/μM) and lowest detection limit (20.2 ± 4.8 nM) ever reported for MT detection at carbon surface. Additionally, an extensive CFE stability and fouling assessment demonstrated that a prolonged CFE pre-conditioning stabilizes the background, in vitro and in vivo, and provides consistent CFE sensitivity over time even in the presence of a high MT concentration. Finally, the stable in vivo background, with minimized CFE fouling, allows us to achieve a drift-free FSCV detection of exogenous administered MT in mouse brain over a period of 3 min, which is significantly longer than the duration limit (usually < 90 s) for traditional in vivo FSCV acquisition. The MT concentration and dynamics measured by FSCV are in good agreement with SWV, while microdialysis further validated the concentration range. These results demonstrated reliable MT detection using FSCV that has the potential to monitor MT in the brain over long periods of time.

| S-EPMC7732424 | biostudies-literature

Removal of Differential Capacitive Interferences in Fast-Scan Cyclic Voltammetry.

Project description:Due to its high spatiotemporal resolution, fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes enables the localized in vivo monitoring of subsecond fluctuations in electroactive neurotransmitter concentrations. In practice, resolution of the analytical signal relies on digital background subtraction for removal of the large current due to charging of the electrical double layer as well as surface faradaic reactions. However, fluctuations in this background current often occur with changes in the electrode state or ionic environment, leading to nonspecific contributions to the FSCV data that confound data analysis. Here, we both explore the origin of such shifts seen with local changes in cations and develop a model to account for their shape. Further, we describe a convolution-based method for removal of the differential capacitive contributions to the FSCV current. The method relies on the use of a small-amplitude pulse made prior to the FSCV sweep that probes the impedance of the system. To predict the nonfaradaic current response to the voltammetric sweep, the step current response is differentiated to provide an estimate of the system's impulse response function and is used to convolute the applied waveform. The generated prediction is then subtracted from the observed current to the voltammetric sweep, removing artifacts associated with electrode impedance changes. The technique is demonstrated to remove select contributions from capacitive characteristics changes of the electrode both in vitro (i.e., in flow-injection analysis) and in vivo (i.e., during a spreading depression event in an anesthetized rat).

| S-EPMC5685151 | biostudies-literature

Simultaneous detection of neurotransmitters and Cu<sup>2+</sup> using double-bore carbon fiber microelectrodes <i>via</i> fast-scan cyclic voltammetry.

Project description:There is a great demand to broaden our understanding of the multifactorial complex etiology of neurodegenerative diseases to aid the development of more efficient therapeutics and slow down the progression of neuronal cell death. The role of co-transmission and the effect of environmental factors on such diseases have yet to be explored adequately, mainly due to the lack of a proper analytical tool that can perform simultaneous multi-analyte detection in real time with excellent analytical parameters. In this study, we report a simple fabrication protocol of a double-bore carbon-fiber microelectrode (CFM) capable of performing rapid simultaneous detection of neurotransmitters and Cu2+via fast-scan cyclic voltammetry (FSCV) in Tris buffer. After imaging our CFMs via optical microscopy and scanning electron microscopy to ensure the intact nature of the two electrodes in our electrode composite, we performed a detailed analysis of the performance characteristics of our double-bore CFM in five different analyte mixtures, Cu2+-5HT, Cu2+-DA, Cu2+-AA, 5-HT-DA, and 5-HT-AA in Tris buffer, by applying different analyte-specific FSCV waveforms simultaneously. Calibration curves for each analyte in each mixture were plotted while extracting the analytical parameters such as the limit of detection (LOD), linear range, and sensitivity. We also carried out a control experiment series for the same mixtures with single-bore CFMs by applying one waveform at a time to compare the capabilities of our double-bore CFMs. Interestingly, except for the Cu2+-DA solution, all other combinations showed improved LOD, linear ranges, and sensitivity when detecting simultaneously with double-bore CFMs compared to single-bore CFMs, an excellent finding for developing this sensor for future in vivo applications.

| S-EPMC10658548 | biostudies-literature

Optimizing the Temporal Resolution of Fast-Scan Cyclic Voltammetry.

Project description:Electrochemical detection with carbon-fiber microelectrodes has become an established method to monitor directly the release of dopamine from neurons and its uptake by the dopamine transporter. With constant potential amperometry (CPA) the measured current provides a real time view of the rapid concentration changes, but the method lacks chemical identification of the monitored species and markedly increases the difficulty of signal calibration. Monitoring with fast-scan cyclic voltammetry (FSCV) allows species identification and concentration measurements, but often exhibits a delayed response time due to the time-dependent adsorption/desorption of electroactive species at the electrode. We sought to improve the temporal resolution of FSCV to make it more comparable to CPA by increasing the waveform repetition rate from 10 to 60 Hz with uncoated carbon-fiber electrodes. The faster acquisition led to diminished time delays of the recordings that tracked more closely with CPA measurements. The measurements reveal that FSCV at 10 Hz underestimates the normal rate of dopamine uptake by about 18%. However, FSCV collection at 10 Hz and 60 Hz provide identical results when a dopamine transporter (DAT) blocker such as cocaine is bath applied. To verify further the utility of this method, we used transgenic mice that over-express DAT. After accounting for the slight adsorption delay time, FSCV at 60 Hz adequately monitored the increased uptake rate that arose from overexpression of DAT and, again, was similar to CPA results. Furthermore, the utility of collecting data at 60 Hz was verified in an anesthetized rat by using a higher scan rate (2400 V/s) to increase sensitivity and the overall signal.

| S-EPMC3375060 | biostudies-other

Electrode calibration with a microfluidic flow cell for fast-scan cyclic voltammetry.

Project description:Fast-scan cyclic voltammetry (FSCV) is a common analytical electrochemistry tool used to measure chemical species. It has recently been adapted for measurement of neurotransmitters such as dopamine in awake and behaving animals (in vivo). Electrode calibration is an essential step in FSCV to relate observed current to concentration of a chemical species. However, existing methods require multiple components, which reduce the ease of calibrations. To this end, a microfluidic flow cell (μFC) was developed as a simple device to switch between buffer and buffer with a known concentration of the analyte of interest--in this case dopamine--in a microfluidic Y-channel. The ability to quickly switch solutions yielded electrode calibrations with faster rise times and that were more stable at peak current values. The μFC reduced the number of external electrical components and produced linear calibrations over a range of concentrations. To demonstrate this, an electrode calibrated with the μFC was used in FSCV recordings from a rat during the delivery of food reward--a stimulus that reliably evokes a brief increase in current due to the oxidation of dopamine. Using the linear calibration, dopamine concentrations were determined from the current responses evoked during the behavioral task. The μFC is able to easily and quickly calibrate FSCV electrode responses to chemical species for both in vitro and in vivo experiments.

| S-EPMC3371170 | biostudies-literature

Flexible software platform for fast-scan cyclic voltammetry data acquisition and analysis.

Project description:Over the last several decades, fast-scan cyclic voltammetry (FSCV) has proved to be a valuable analytical tool for the real-time measurement of neurotransmitter dynamics in vitro and in vivo. Indeed, FSCV has found application in a wide variety of disciplines including electrochemistry, neurobiology, and behavioral psychology. The maturation of FSCV as an in vivo technique led users to pose increasingly complex questions that require a more sophisticated experimental design. To accommodate recent and future advances in FSCV application, our lab has developed High Definition Cyclic Voltammetry (HDCV). HDCV is an electrochemical software suite that includes data acquisition and analysis programs. The data collection program delivers greater experimental flexibility and better user feedback through live displays. It supports experiments involving multiple electrodes with customized waveforms. It is compatible with transistor-transistor logic-based systems that are used for monitoring animal behavior, and it enables simultaneous recording of electrochemical and electrophysiological data. HDCV analysis streamlines data processing with superior filtering options, seamlessly manages behavioral events, and integrates chemometric processing. Furthermore, analysis is capable of handling single files collected over extended periods of time, allowing the user to consider biological events on both subsecond and multiminute time scales. Here we describe and demonstrate the utility of HDCV for in vivo experiments.

| S-EPMC3838858 | biostudies-literature

Improved Serotonin Measurement with Fast-Scan Cyclic Voltammetry: Mitigating Fouling by SSRIs.

Project description:Selective serotonin reuptake inhibitors (SSRIs) have been used for decades to treat disorders linked to serotonin dysregulation in the brain. Moreover, SSRIs are often used in studies aimed at measuring serotonin with fast-scan cyclic voltammetry (FSCV) in living tissues. Here, we show that three different SSRIs - fluoxetine, escitalopram, and sertraline - significantly diminish the faradaic oxidation current of serotonin when employing the commonly used Jackson waveform. Coating carbon-fiber microelectrodes (CFMs) with Nafion resulted in further degradation of peak current, increased response times, and decreased background charging currents compared to bare CFMs. To decrease fouling, we employed a recently published extended serotonin waveform, which scans to a maximum positive potential of +1.3 V, rather than +1.0 V used in the Jackson waveform. Use of this waveform with bare CFMs alleviated the decrease in faradaic current, indicating decreased electrode fouling. Collectively, our results suggest that fouling considerations are important when designing FSCV experiments that employ SSRIs and that they can be overcome by using the appropriate waveform.

| S-EPMC9491377 | biostudies-literature

Enzyme-modified carbon-fiber microelectrode for the quantification of dynamic fluctuations of nonelectroactive analytes using fast-scan cyclic voltammetry.

Project description:Neurotransmission occurs on a millisecond time scale, but conventional methods for monitoring nonelectroactive neurochemicals are limited by slow sampling rates. Despite a significant global market, a sensor capable of measuring the dynamics of rapidly fluctuating, nonelectroactive molecules at a single recording site with high sensitivity, electrochemical selectivity, and a subsecond response time is still lacking. To address this need, we have enabled the real-time detection of dynamic glucose fluctuations in live brain tissue using background-subtracted, fast-scan cyclic voltammetry. The novel microbiosensor consists of a simple carbon fiber surface modified with an electrodeposited chitosan hydrogel encapsulating glucose oxidase. The selectivity afforded by voltammetry enables quantitative and qualitative measurements of enzymatically generated H2O2 without the need for additional strategies to eliminate interfering agents. The microbiosensors possess a sensitivity and limit of detection for glucose of 19.4 ± 0.2 nA mM(-1) and 13.1 ± 0.7 μM, respectively. They are stable, even under deviations from physiological normoxic conditions, and show minimal interference from endogenous electroactive substances. Using this approach, we have quantitatively and selectively monitored pharmacologically evoked glucose fluctuations with unprecedented chemical and spatial resolution. Furthermore, this novel biosensing strategy is widely applicable to the immobilization of any H2O2 producing enzyme, enabling rapid monitoring of many nonelectroactive enzyme substrates.

| S-EPMC3795517 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data