This critical review highlights significant technical advances and in vivo studies from the last five years that facilitate the development of diagnostic tools for brain disorders.

While the neurochemistry that underpins the behavioral phenotypes of depression is the subject of many studies, oxidative stress caused by the inflammation comorbid with depression has not adequately been addressed. In this study, we described novel antidepressant−antioxidant agents consisting of selenium-modified fluoxetine derivatives to simultaneously target serotonin reuptake (antidepressant action) and oxidative stress. Excitingly, we show that one of these agents (1-F) carries the ability to inhibit serotonin reuptake in vivo in mice. We therefore present a frontier dual strategy that paves the way for the future of antidepressant therapies.

Carbon is the material of choice for electroanalysis of biological systems, being particularly applicable to neurotransmitter analysis as carbon fiber microelectrodes (CFMs). CFMs are most often applied to dopamine detection; however, the scope of CFM analysis has rapidly expanded over the last decade with our laboratory’s focus being on improving serotonin detection at CFMs, which we achieved in the past via Nafion modification. We began this present work by seeking to optimize this modification to gain increased analytical sensitivity toward serotonin under the assumption that exposure of bare carbon to the in vivo environment rapidly deteriorates analytical performance. However, we were unable to experimentally verify this assumption and found that electrodes that had been exposed to the in vivo environment were more sensitive to evoked and ambient dopamine. We hypothesized that high in vivo concentrations of ambient extracellular glutamate could polymerize with a negative charge onto CFMs and facilitate response to dopamine. We verified this polymerization electrochemically and characterized the mechanisms of deposition with micro- and nano-imaging. Importantly, we identified that the application of 1.3 V as a positive upper waveform limit is a crucial factor for facilitating glutamate polymerization, thus improving analytical performance. Critically, information gained from these dopamine studies were extended to an in vivo environment where a 2-fold increase in sensitivity to evoked serotonin was achieved. Thus, we present here the novel finding that innate aspects of the in vivo environment are auspicious for detection of dopamine and serotonin at carbon fibers, offering a solution to our goal of an improved fast-scan cyclic voltammetry serotonin detection paradigm.

Fast-scan cyclic voltammetry (FSCV) at carbon fiber microelectrodes measures low concentrations of analytes in biological systems. There are ongoing efforts to simplify FSCV analysis, and several custom platforms are available for filtering and multimodal analysis of FSCV signals, but there is no single, easily accessible platform that has the capacity for all of these features. Here we present The Analysis Kid: currently, the only free, open-source cloud application that does not require a specialized runtime environment and is easily accessible via common browsers. We show that a user-friendly interface can analyze multiplatform file formats to provide multimodal visualization of FSCV color plots with digital background subtraction. We highlight key features that allow interactive calibration and semiautomatic parametric analysis via peak finding algorithms to automatically detect the maximum amplitude, area under the curve, and clearance rate of the signal. Finally, The Analysis Kid enables semiautomatic fitting of data with Michaelis–Menten kinetics with single or dual reuptake models. The Analysis Kid can be freely accessed at . The web application code is found, under an MIT license, at .

Fast-scan adsorption-controlled voltammetry (FSCAV) was recently derived from fast-scan cyclic voltammetry to estimate the absolute concentrations of neurotransmitters by using the innate adsorption properties of carbon fiber microelectrodes. This technique has improved our knowledge of serotonin dynamics in vivo. However, the analysis of FSCAV data is laborious and technically challenging. First, each electrode requires post-experimental in vitro calibration. Second, current analysis methods are semi-manual and time-consuming and require a steep learning curve. Finally, the calibration methods used do not adapt to nonlinear electrode responses. In this work, we provide freely accessible computational solutions to these issues. First, we design an artificial neural network (ANN) and train it with a large data set (calibrations from 140 electrodes by six different researchers) to achieve calibration-free estimations and improve predictive error. We discuss the power of the ANN to obtain a low predictive error without electrode-specific calibrations as a function of being able to predict the sensitivity of the electrode. We use the ANN to successfully predict the absolute serotonin concentrations of real in vivo data. Finally, we create a fast and user-friendly, fully automated analysis web platform to simplify and reduce the expertise required for the postanalysis of FSCAV signals.

Fast-scan cyclic voltammetry at carbon fiber microelectrodes measures low concentrations of analytes in biological systems. There are ongoing efforts to simplify FSCV analysis and several custom platforms are available for filtering and multi-modal analysis of FSCV signals but there is no single, easily accessible platform that has capacity for all these features. Here we present The Analysis Kid: a free, open-source cloud application that does not require a specialized runtime environment and is easily accessible via common browsers. We show that a user-friendly interface can analyze multi-platform file formats to provide multimodal visualization of FSCV color plots with digital background subtraction. We highlight key features that allow interactive calibration and parametric analysis via peak finding algorithms to automatically detect the maximum amplitude, area under the curve and clearance rate of the signal. Finally, The Analysis Kid enables semi-automatic fitting of data with Michaelis Menten kinetics with single or dual reuptake models. The Analysis Kid can be freely accessed at https://analysis-kid.herokuapp.com/. The web application code is found, under an MIT license, at https://github.com/sermeor/The-Analysis-Kid.

Serotonin is an important neurotransmitter that plays a major role in many aspects of neuroscience. Fast-scan cyclic voltammetry measures fast in vivo serotonin dynamics using carbon fiber microelectrodes. More recently, fast-scan controlled-adsorption voltammetry (FSCAV) has been developed to measure slower, minute-to-minute changes in ambient extracellular serotonin. We have previously demonstrated that FSCAV measurements of basal serotonin levels give critical information regarding brain physiology and disease. In this work, we revealed the presence of low-periodicity fluctuations in serotonin levels in mouse hippocampi, measured in vivo with FSCAV. Using correlation analyses, we found robust evidence of oscillations in the basal serotonin levels, which had a period of 10 minutes and were not present in vitro. Under control conditions, the oscillations did not differ between male and female mice, nor do they differ between mice that underwent a chronic stress paradigm and those in the control group. After the acute administration of a selective serotonin reuptake inhibitor, we observed a shift in the frequency of the oscillations, leading us to hypothesize that the newly observed fluctuations were transporter regulated. Finally, we optimized the experimental parameters of the FSCAV to measure at a higher temporal resolution and found more pronounced shifts in the oscillation frequency, along with a decreased oscillation amplitude. We postulate that this work may serve as a potential bridge for studying serotonin/endocrine interactions that occur on the same time scale.

Guanosine acts in both neuroprotective and neurosignaling pathways in the central nervous system; in this paper, we present the first fast voltammetric measurements of endogenous guanosine release during pre-and post-ischemic conditions. We discuss the metric of our measurements via analysis of event concentration, duration, and interevent time of rapid guanosine release. We observe changes across all three metrics from our normoxic to ischemic conditions. Pharmacological studies were performed to confirm that guanosine release is a calcium-dependent process and that the signaling observed is purinergic. Finally, we show the validity of our ischemic model via staining and fluorescent imaging. Overall, this paper sets the tone for rapid monitoring of guanosine and provides a platform to investigate the extent to which guanosine accumulates at the site of brain injury, i.e., ischemia.