In vivo Hippocampal Serotonin Dynamics in Male and Female Mice: Determining Effects of Acute Escitalopram Using Fast Scan Cyclic Voltammetry

Modulation of serotonin transporter expression by escitalopram under inflammation

Selective serotonin reuptake inhibitors (SSRIs) are widely used for depression based on the monoamine deficiency hypothesis. However, the clinical use of these agents is controversial, in part because of their variable clinical efficacy and in part because of their delayed onset of action. Because of the complexities involved in replicating human disease and clinical dosing in animal models, the scientific community has not reached a consensus on the reasons for these phenomena. In this work, we create a theoretical hippocampal model incorporating escitalopram's pharmacokinetics, pharmacodynamics (competitive and non-competitive inhibition, and serotonin transporter (SERT) internalization), inflammation, and receptor dynamics. With this model, we simulate chronic oral escitalopram in mice showing that days to weeks are needed for serotonin levels to reach steady-state. We show escitalopram's chemical efficacy is diminished under inflammation. Our model thus offers mechanisms for how chronic escitalopram affects brain serotonin, emphasizing the importance of optimized dose and time for future antidepressant discoveries.

Microdosing ketamine in Drosophila does not block serotonin reuptake, but causes complex behavioral changes mediated by glutamate and serotonin receptors

Microdosing ketamine is a novel antidepressant for treatment-resistant depression. Traditional antidepressants, like selective serotonin reuptake inhibitors (SSRIs), inhibit serotonin reuptake, but it is not clear if ketamine shows a similar mechanism. Here, we tested the effects of feeding ketamine and SSRIs to Drosophila melanogaster larvae, which has a similar serotonin system to mammals and is a good model to track depressive behaviors, such as locomotion and feeding. Fast-scan cyclic voltammetry (FSCV) was used to measure optogenetically stimulated serotonin changes, and locomotion tracking software and blue dye feeding to monitor behavior. We fed larvae various doses (1-100 mM) of antidepressants for 24 h and found that 1 mM ketamine did not affect serotonin, but increased locomotion and feeding. Low doses (≤10 mM) of escitalopram and fluoxetine inhibited dSERT and also increased feeding and locomotion behaviors. At 100 mM, ketamine inhibited dSERT and increased serotonin concentrations, but decreased locomotion and feeding because of its anesthetic properties. Since microdosing ketamine causes behavioral effects, we further investigated behavioral changes with a SERT16 mutant and low doses of other NMDA receptor antagonists and 5-HT1A and 2 agonists. Feeding and locomotion changes were similar to ketamine in the mutant, and we found NMDA receptor antagonism increased feeding, while serotonin receptor agonism increased locomotion, which could explain these effects with ketamine. Ultimately, this work shows that Drosophila is a good model to discern antidepressant mechanisms, and that ketamine does not work on dSERT like SSRIs, but effects behavior with other mechanisms that should be investigated further.

Serotonin as a biomarker of toxin-induced Parkinsonism

BACKGROUND

Loss of dopaminergic neurons underlies the motor symptoms of Parkinson's disease (PD). However stereotypical PD symptoms only manifest after approximately 80% of dopamine neurons have died making dopamine-related motor phenotypes unreliable markers of the earlier stages of the disease. There are other non-motor symptoms, such as depression, that may present decades before motor symptoms.

METHODS

Because serotonin is implicated in depression, here we use niche, fast electrochemistry paired with mathematical modelling and machine learning to, for the first time, robustly evaluate serotonin neurochemistry in vivo in real time in a toxicological model of Parkinsonism, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP).

RESULTS

Mice treated with acute MPTP had lower concentrations of in vivo, evoked and ambient serotonin in the hippocampus, consistent with the clinical comorbidity of depression with PD. These mice did not chemically respond to SSRI, as strongly as control animals did, following the clinical literature showing that antidepressant success during PD is highly variable. Following L-DOPA administration, using a novel machine learning analysis tool, we observed a dynamic shift from evoked serotonin release in the hippocampus to dopamine release. We hypothesize that this finding shows, in real time, that serotonergic neurons uptake L-DOPA and produce dopamine at the expense of serotonin, supporting the significant clinical correlation between L-DOPA and depression. Finally, we found that this post L-DOPA dopamine release was less regulated, staying in the synapse for longer. This finding is perhaps due to lack of autoreceptor control and may provide a ground from which to study L-DOPA induced dyskinesia.

CONCLUSIONS

These results validate key prior hypotheses about the roles of serotonin during PD and open an avenue to study to potentially improve therapeutics for levodopa-induced dyskinesia and depression.

Batch Fabrication of Microelectrode Arrays with Glassy Carbon Microelectrodes and Interconnections for Neurochemical Sensing: Promises and Challenges

Flexible multielectrode arrays with glassy carbon (GC) electrodes and metal interconnection (hybrid MEAs) have shown promising performance in multi-channel neurochemical sensing. A primary challenge faced by hybrid MEAs fabrication is the adhesion of the metal traces with the GC electrodes, as prolonged electrical and mechanical stimulation can lead to adhesion failure. Previous devices with GC electrodes and interconnects made of a homogeneous material (all GC) demonstrated exceptional electrochemical stability but required miniaturization for enhanced tissue integration and chronic electrochemical sensing. In this study, we used two different methods for the fabrication of all GC-MEAs on thin flexible substrates with miniaturized features. The first method, like that previously reported, involves a double pattern-transfer photolithographic process, including transfer-bonding on temporary polymeric support. The second method requires a double-etching process, which uses a 2 µm-thick low stress silicon nitride coating of the Si wafer as the bottom insulator layer for the MEAs, bypassing the pattern-transfer and demonstrating a novel technique with potential advantages. We confirmed the feasibility of the two fabrication processes by verifying the practical conductivity of 3 µm-wide 2 µm-thick GC traces, the GC microelectrode functionality, and their sensing capability for the detection of serotonin using fast scan cyclic voltammetry. Through the exchange and discussion of insights regarding the strengths and limitations of these microfabrication methods, our goal is to propel the advancement of GC-based MEAs for the next generation of neural interface devices.

SmartFSCV: An Artificial Intelligence Enabled Miniaturised FSCV Device Targeting Serotonin

Goal: Dynamically monitoring serotonin in real-time within target brain regions would significantly improve the diagnostic and therapeutic approaches to a variety of neurological and psychiatric disorders. Current systems for measuring serotonin lack immediacy and portability and are bulky and expensive. Methods: We present a new miniaturised device, named SmartFSCV, designed to monitor dynamic changes of serotonin using fast-scan cyclic voltammetry (FSCV). This device outputs a precision voltage potential between -3 to +3 V, and measures current between -1.5 to +1.5 μA with nano-ampere accuracy. The device can output modifiable arbitrary waveforms for various measurements and uses an N-shaped waveform at a scan-rate of 1000 V/s for sensing serotonin. Results: Four experiments were conducted to validate SmartFSCV: static bench test, dynamic serotonin test and two artificial intelligence (AI) algorithm tests. Conclusions: These tests confirmed the ability of SmartFSCV to accurately sense and make informed decisions about the presence of serotonin using AI.

Serotonin is a common thread linking different classes of antidepressants

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of escitalopram, fluoxetine, reboxetine, and ketamine. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking, and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis, and the monoamine hypothesis).

Microdosing ketamine in Drosophila does not inhibit SERT like SSRIs, but causes behavioral changes mediated by glutamate and serotonin receptors

Recently, the FDA approved microdosing ketamine for treatment resistant depression. Traditional antidepressants, like serotonin selective reuptake inhibitors (SSRIs), block serotonin reuptake, but it is not clear if ketamine blocks serotonin reuptake. Here, we tested the effects of feeding ketamine and SSRIs to Drosophila melanogaster larvae, which has a similar serotonin system to mammals, and is a good model to track depression behaviors, such as locomotion and feeding. Fast-scan cyclic voltammetry (FSCV) was used to measure optogenetically-stimulated serotonin changes, and locomotion tracking software and blue dye feeding to monitor behavior. We fed larvae various doses (1-100 mM) of antidepressants for 24 hours and found that 1 mM ketamine did not affect serotonin, but increased locomotion and feeding. Low doses (≤ 10 mM) of escitalopram and fluoxetine inhibited dSERT and also increased feeding and locomotion behaviors. At 100 mM, ketamine inhibited dSERT and increased serotonin concentrations, but decreased locomotion and feeding due to its anesthetic properties. Since microdosing ketamine causes behavioral effects, we also investigated behavior changes with low doses of other NMDA receptor antagonists and 5-HT1A and 2 agonists, which are other possible sites for ketamine action. NMDA receptor antagonism increased feeding, while serotonin receptor agonism increased locomotion, which could explain these effects with ketamine. Ultimately, this work shows that Drosophila is a good model to discern antidepressant mechanisms, and that ketamine does not work on dSERT like SSRIs at microdoses, but affects behavior with other mechanisms.

Serotonin is a Common Thread Linking Different Classes of Antidepressants

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (synaptic plasticity and neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of antidepressants. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis and the monoamine hypothesis).

Implantable flexible multielectrode arrays for multi-site sensing of serotonin tonic levels

Real-time multi-channel measurements of tonic serotonin (5-hydroxytryptamine, 5-HT) concentrations across different brain regions are of utmost importance to the understanding of 5-HT’s role in anxiety, depression, and impulse control disorders, which will improve the diagnosis and treatment of these neuropsychiatric illnesses. Chronic sampling of 5-HT is critical in tracking disease development as well as the time course of pharmacological treatments. Despite their value, in vivo chronic multi-site measurements of 5-HT have not been reported. To fill this technological gap, we batch fabricated implantable glassy carbon (GC) microelectrode arrays (MEAs) on a flexible SU-8 substrate to provide an electrochemically stable and biocompatible device/tissue interface. Then, to achieve multi-site detection of tonic 5-HT concentrations, we incorporated the poly(3,4-ethylenedioxythiophene)/functionalized carbon nanotube (PEDOT/CNT) coating on the GC microelectrodes in combination with a new square wave voltammetry (SWV) approach, optimized for selective 5-HT measurement. In vitro , the PEDOT/CNT coated GC microelectrodes achieved high sensitivity towards 5-HT, good fouling resistance in the presence of 5-HT, and excellent selectivity towards the most common neurochemical interferents. In vivo , our PEDOT/CNT-coated GC MEAs were able to successfully detect basal 5-HT concentrations at different locations of the CA2 hippocampal region of mice in both anesthetized and awake head-fixed conditions. Furthermore, the implanted PEDOT/CNT-coated MEA achieved stable detection of tonic 5-HT concentrations for one week. Finally, histology data in the hippocampus shows reduced tissue damage and inflammatory responses compared to stiff silicon probes. To the best of our knowledge, this PEDOT/CNT-coated GC MEA is the first implantable flexible multisite sensor capable of chronic in vivo multi-site sensing of tonic 5-HT. This implantable MEA can be custom-designed according to specific brain region of interests and research questions, with the potential to combine electrophysiology recording and multiple analyte sensing to maximize our understanding of neurochemistry.

Highlights

PEDOT/CNT-coated GC microelectrodes enabled sensitive and selective tonic detection of serotonin (5-HT) using a new square wave voltammetry (SWV) approach PEDOT/CNT-coated GC MEAs achieved multi-site in vivo 5-HT tonic detection for one week. Flexible MEAs lead to reduced tissue damage and inflammation compared to stiff silicon probes.

Two-Steps Method to Prepare Multilayer Sandwich Structure Carbon Fiber Composite with Thermal and Electrical Anisotropy and Electromagnetic Interference Shielding

Carbon fiber (CF) composites performance enhancement is a research hotspot at present. In this work, first, a sandwich structure composite, CF@(carbon nanotube/Fe₃O₄)/epoxy (CF@(CNT/Fe₃O₄)/EP), is prepared by the free arc dispersion-CFs surface spraying-rolling process method, herein, CFs in the middle layer and (CNT/Fe₃O₄)/EP as top and substrate layer. Then, CF@(CNT/Fe₃O₄)/EP (on both sides) and CFs (in the middle) are overlapped by structure design, forming a multilayer CF@(CNT/Fe₃O₄)/EP-CFs composite with a CFs core sheath. A small amount of CNT/Fe₃O₄ is consumed, (CNT/Fe₃O₄)/EP and CFs core sheath realize thermal and electrical anisotropy and directional enhancement, and multilayer sandwich structure makes the electromagnetic interference (EMI) shielding performance better strengthened by multiple absorption-reflection/penetration-reabsorption. From CF-0 to CF-8, CNT/Fe₃O₄ content only increases by 0.045 wt%, axial thermal conductivity (λ_‖) increases from 0.59 W/(m·K) to 1.1 W/(m·K), growth rate is 86%, radial thermal conductivity (λ_⟂) only increases by 0.05 W/(m·K), the maximum λ_‖/λ_⟂ is 2.9, axial electrical conductivity (σ_‖) increases from 6.2 S/cm to 7.7 S/cm, growth rate is 24%, radial electrical conductivity (σ_⟂) only increases by 0.7 × 10^-4 S/cm, the total EMI shielding effectiveness (EMI SE_T) increases by 196%, from 10.3 dB to 30.5 dB. This provides a new idea for enhancing CFs composite properties.

An In Vivo Definition of Brain Histamine Dynamics Reveals Critical Neuromodulatory Roles for This Elusive Messenger

Histamine is well known for mediating peripheral inflammation; however, this amine is also found in high concentrations in the brain where its roles are much less known. In vivo chemical dynamics are difficult to measure, thus fundamental aspects of histamine's neurochemistry remain undefined. In this work, we undertake the first in-depth characterization of real time in vivo histamine dynamics using fast electrochemical tools. We find that histamine release is sensitive to pharmacological manipulation at the level of synthesis, packaging, autoreceptors and metabolism. We find two breakthrough aspects of histamine modulation. First, differences in H3 receptor regulation between sexes show that histamine release in female mice is much more tightly regulated than in male mice under H3 or inflammatory drug challenge. We hypothesize that this finding may contribute to hormone-mediated neuroprotection mechanisms in female mice. Second, a high dose of a commonly available antihistamine, the H1 receptor inverse agonist diphenhydramine, rapidly decreases serotonin levels. This finding highlights the sheer significance of pharmaceuticals on neuromodulation. Our study opens the path to better understanding and treating histamine related disorders of the brain (such as neuroinflammation), emphasizing that sex and modulation (of serotonin) are critical factors to consider when studying/designing new histamine targeting therapeutics.

Nano- and Microsensors for In Vivo Real-Time Electrochemical Analysis: Present and Future Perspectives

Electrochemical nano- and microsensors have been a useful tool for measuring different analytes because of their small size, sensitivity, and favorable electrochemical properties. Using such sensors, it is possible to study physiological mechanisms at the cellular, tissue, and organ levels and determine the state of health and diseases. In this review, we highlight recent advances in the application of electrochemical sensors for measuring neurotransmitters, oxygen, ascorbate, drugs, pH values, and other analytes in vivo. The evolution of electrochemical sensors is discussed, with a particular focus on the development of significant fabrication schemes. Finally, we highlight the extensive applications of electrochemical sensors in medicine and biological science.

Flexible Glassy Carbon Multielectrode Array for In Vivo Multisite Detection of Tonic and Phasic Dopamine Concentrations

Dopamine (DA) plays a central role in the modulation of various physiological brain functions, including learning, motivation, reward, and movement control. The DA dynamic occurs over multiple timescales, including fast phasic release, as a result of neuronal firing and slow tonic release, which regulates the phasic firing. Real-time measurements of tonic and phasic DA concentrations in the living brain can shed light on the mechanism of DA dynamics underlying behavioral and psychiatric disorders and on the action of pharmacological treatments targeting DA. Current state-of-the-art in vivo DA detection technologies are limited in either spatial or temporal resolution, channel count, longitudinal stability, and ability to measure both phasic and tonic dynamics. We present here an implantable glassy carbon (GC) multielectrode array on a SU-8 flexible substrate for integrated multichannel phasic and tonic measurements of DA concentrations. The GC MEA demonstrated in vivo multichannel fast-scan cyclic voltammetry (FSCV) detection of electrically stimulated phasic DA release simultaneously at different locations of the mouse dorsal striatum. Tonic DA measurement was enabled by coating GC electrodes with poly(3,4-ethylenedioxythiophene)/carbon nanotube (PEDOT/CNT) and using optimized square-wave voltammetry (SWV). Implanted PEDOT/CNT-coated MEAs achieved stable detection of tonic DA concentrations for up to 3 weeks in the mouse dorsal striatum. This is the first demonstration of implantable flexible MEA capable of multisite electrochemical sensing of both tonic and phasic DA dynamics in vivo with chronic stability.

Voltammetric Approach for Characterizing the Biophysical and Chemical Functionality of Human Induced Pluripotent Stem Cell-Derived Serotonin Neurons

Depression is quickly becoming one of the world's most pressing public health crises, and there is an urgent need for better diagnostics and therapeutics. Behavioral models in animals and humans have not adequately addressed the diagnosis and treatment of depression, and biomarkers of mental illnesses remain ill-defined. It has been very difficult to identify biomarkers of depression because of in vivo measurement challenges. While our group has made important strides in developing in vivo tools to measure such biomarkers (e.g., serotonin) in mice using voltammetry, these tools cannot be easily applied for depression diagnosis and drug screening in humans due to the inaccessibility of the human brain. In this work, we take a chemical approach, ex vivo, to introduce a human-derived system to investigate brain serotonin. We utilize human induced pluripotent stem cells differentiated into serotonin neurons and establish a new ex vivo model of real-time serotonin neurotransmission measurements. We show that evoked serotonin release responds to stimulation intensity and tryptophan preloading, and that serotonin release and reuptake kinetics resemble those found in vivo in rodents. Finally, after selective serotonin reuptake inhibitor (SSRI) exposure, we find dose-dependent internalization of the serotonin reuptake transporters (a signature of the in vivo response to SSRI). Our new human-derived chemical model has great potential to provide an ex vivo chemical platform as a translational tool for in vivo neuropsychopharmacology.

A tale of two transmitters: serotonin and histamine as in vivo biomarkers of chronic stress in mice

Background

Stress-induced mental illnesses (mediated by neuroinflammation) pose one of the world’s most urgent public health challenges. A reliable in vivo chemical biomarker of stress would significantly improve the clinical communities’ diagnostic and therapeutic approaches to illnesses, such as depression.

Methods

Male and female C57BL/6J mice underwent a chronic stress paradigm. We paired innovative in vivo serotonin and histamine voltammetric measurement technologies, behavioral testing, and cutting-edge mathematical methods to correlate chemistry to stress and behavior.

Results

Inflammation-induced increases in hypothalamic histamine were co-measured with decreased in vivo extracellular hippocampal serotonin in mice that underwent a chronic stress paradigm, regardless of behavioral phenotype. In animals with depression phenotypes, correlations were found between serotonin and the extent of behavioral indices of depression. We created a high accuracy algorithm that could predict whether animals had been exposed to stress or not based solely on the serotonin measurement. We next developed a model of serotonin and histamine modulation, which predicted that stress-induced neuroinflammation increases histaminergic activity, serving to inhibit serotonin. Finally, we created a mathematical index of stress, S_i and predicted that during chronic stress, where S_i is high, simultaneously increasing serotonin and decreasing histamine is the most effective chemical strategy to restoring serotonin to pre-stress levels. When we pursued this idea pharmacologically, our experiments were nearly identical to the model’s predictions.

Conclusions

This work shines the light on two biomarkers of chronic stress, histamine and serotonin, and implies that both may be important in our future investigations of the pathology and treatment of inflammation-induced depression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02508-9.

Novel, User-Friendly Experimental and Analysis Strategies for Fast Voltammetry: Next Generation FSCAV with Artificial Neural Networks

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.

Low-Frequency Oscillations of In Vivo Ambient Extracellular Brain Serotonin

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 min 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.

Dopamine and serotonin interplay for valence-based spatial learning

Dopamine (DA) and serotonin (5-HT) are important neuromodulators of synaptic plasticity that have been linked to learning from positive or negative outcomes or valence-based learning. In the hippocampus, both affect long-term plasticity but play different roles in encoding uncertainty or predicted reward. DA has been related to positive valence, from reward consumption or avoidance behavior, and 5-HT to aversive encoding. We propose DA produces overall LTP while 5-HT elicits LTD. Here, we compare two reward-modulated spike timing-dependent plasticity (R-STDP) rules to describe the action of these neuromodulators. We examined their role in cognitive performance and flexibility for computational models of the Morris water maze task and reversal learning. Our results show that the interplay of DA and 5-HT improves learning performance and can explain experimental evidence. This study reinforces the importance of neuromodulation in determining the direction of plasticity.

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

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.

ROS-Scavenging Selenofluoxetine Derivatives Inhibit In Vivo Serotonin Reuptake

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.

Cocaine increases stimulation-evoked serotonin efflux in the nucleus accumbens

Although dopamine is the most implicated neurotransmitter in the mediation of the pathophysiology of addiction, animal studies show serotonin also plays a vital role. Cocaine is one of the most common illicit drugs globally, but the role of serotonin in its mechanism of action is insufficiently characterized. Consequently, we investigated the acute effects of the psychomotor stimulant cocaine on electrical stimulation-evoked serotonin (phasic) release in the nucleus accumbens core (NAcc) of urethane-anesthetized (1.5 g/kg ip) male Sprague-Dawley rats using N-shaped fast-scan cyclic voltammetry (N-FSCV). A single carbon fiber microelectrode was first implanted in the NAcc. Stimulation was applied to the medial forebrain bundle using 60 Hz, 2 ms, 0.2 mA, 2-s biphasic pulses before and after cocaine (2 mg/kg iv) was administered. Stimulation-evoked serotonin release significantly increased 5 min after cocaine injection compared with baseline (153 ± 21 nM vs. 257 ± 12 nM; P = 0.0042; n = 5) but was unaffected by saline injection (1 mL/kg iv; n = 5). N-FSCV's selective measurement of serotonin release in vivo was confirmed pharmacologically via administration of the selective serotonin reuptake inhibitor escitalopram (10 mg/kg ip) that effectively increased the signal in a separate group of rats (n = 5). Selectivity to serotonin was further confirmed in vitro in which dopamine was minimally detected by N-FSCV with a serotonin to dopamine response ratio of 1:0.04 (200 nM of serotonin:1 µM dopamine ratio; P = 0.0048; n = 5 electrodes). This study demonstrates a noteworthy influence of cocaine on serotonin dynamics, and confirms that N-FSCV can effectively and selectively measure phasic serotonin release in the NAcc.NEW & NOTEWORTHY Serotonin plays a vital role in drug addiction. Here, using N-shaped fast-scan cyclic voltammetry, we demonstrated the effect of cocaine on the phasic release of serotonin at the nucleus accumbens core. To the best of our knowledge, this has not previously been elucidated. Our results not only reinforce the role of serotonin in the mechanism of action of cocaine but also help to fill a gap in our knowledge and provide a baseline for future studies in cocaine addiction.

Determination of Drugs in Clinical Trials: Current Status and Outlook

All pharmaceutical drugs, vaccines, cosmetic products, and many medical breakthroughs must first be approved through clinical research and trials before advancing to standard practice or entering the marketplace. Clinical trials are sets of tests that are required to determine the safety and efficacy of pharmaceutical compounds, drugs, and treatments. There is one pre-phase and four main clinical phase requirements that every drug must pass to obtain final approval. Analytical techniques play a unique role in clinical trials for measuring the concentrations of pharmaceutical compounds in biological matrices and monitoring the conditions of patients (or volunteers) during various clinical phases. This review focuses on recent analytical methods that are employed to determine the concentrations of drugs and medications in biological matrices, including whole blood, plasma, urine, and breast milk. Four primary analytical techniques (extraction, spectroscopy, chromatography, and electrochemical) are discussed, and their advantages and limitations are assessed. Subsequent to a survey of evidence and results, it is clear that microelectromechanical system (MEMS) based electrochemical sensor and biosensor technologies exhibit several notable advantages over other analytical methods, and their future prospects are discussed.

Antidepressants determination using an electroanalytical approach: A review of methods

Antidepressants are the pharmaceutical compounds used in the treatment of depression, anxiety disorders and all related disturbances promoted by genetic factors, environmental problems or modern lifestyles. Nonetheless, the inadequate ingestion of antidepressants provokes adverse effects in the human body and can contaminate the environment. For this reason, it is necessary to identify and quantify these compounds in biological fluids, natural water, wastewater, and pharmaceutical formulations. Consequently, this review presents the main electroanalytical techniques used in the analysis of antidepressants, indicating the advantages, which include low cost, suitable analytical parameters, simplified sample preparation steps, easy operation and reduced time for completion of the analysis. Reports in specialized literature, published from 2000 to 2020, are presented and some are discussed, demonstrating that the electroanalytical techniques can be employed, with success, in the determination of antidepressants, indicating alternative methodologies to improve analytical parameters and minimize the use and generation of toxic residues.

Novel, User-Friendly Experimental and Analysis Strategies for Fast Voltammetry: 1. The Analysis Kid for FSCV

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 http://analysis-kid.hashemilab.com/. The web application code is found, under an MIT license, at https://github.com/sermeor/The-Analysis-Kid.

High-fat diet induces neuroinflammation and reduces the serotonergic response to escitalopram in the hippocampus of obese rats

Clinical studies indicate that obese individuals have an increased risk of developing co-morbid depressive illness and that these patients have reduced responses to antidepressant therapy, including selective serotonin reuptake inhibitors (SSRIs). Obesity, a condition of chronic mild inflammation including obesity-induced neuroinflammation, is proposed to contribute to decreases in synaptic concentrations of neurotransmitters like serotonin (5HT) by decreasing 5HT synthesis in the dorsal raphe nucleus (DRN) and/or affecting 5HT reuptake in DRN target regions like the hippocampus. In view of these observations, the goal of the current study was to examine inflammatory markers and serotonergic dynamics in co-morbid obesity and depression. Biochemical and behavioral assays revealed that high-fat diet produced an obesity and depressive-like phenotype in one cohort of rats and that these changes were marked by increases in key pro-inflammatory cytokines in the hippocampus. In real time using fast scan cyclic voltammetry (FSCV), we observed no changes in basal levels of hippocampal 5HT; however responses to escitalopram were significantly impaired in the hippocampus of obese rats compared to diet resistant rats and control rats. Further studies revealed that these neurochemical observations could be explained by increases in serotonin transporter (SERT) expression in the hippocampus driven by elevated neuroinflammation. Collectively, these results demonstrate that obesity-induced increases in neuroinflammation adversely affect SERT expression in the hippocampus of obese rats, thereby providing a potential synaptic mechanism for reduced SSRI responsiveness in obese subjects with co-morbid depressive illness.

Glutamate Electropolymerization on Carbon Increases Analytical Sensitivity to Dopamine and Serotonin: An Auspicious In Vivo Phenomenon in Mice?

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.

Inflammation-Induced Histamine Impairs the Capacity of Escitalopram to Increase Hippocampal Extracellular Serotonin

Commonly prescribed selective serotonin reuptake inhibitors (SSRIs) inhibit the serotonin transporter to correct a presumed deficit in extracellular serotonin signaling during depression. These agents bring clinical relief to many who take them; however, a significant and growing number of individuals are resistant to SSRIs. There is emerging evidence that inflammation plays a significant role in the clinical variability of SSRIs, though how SSRIs and inflammation intersect with synaptic serotonin modulation remains unknown. In this work, we use fast in vivo serotonin measurement tools to investigate the nexus between serotonin, inflammation, and SSRIs. Upon acute systemic lipopolysaccharide (LPS) administration in male and female mice, we find robust decreases in extracellular serotonin in the mouse hippocampus. We show that these decreased serotonin levels are supported by increased histamine activity (because of inflammation), acting on inhibitory histamine H3 heteroreceptors on serotonin terminals. Importantly, under LPS-induced histamine increase, the ability of escitalopram to augment extracellular serotonin is impaired because of an off-target action of escitalopram to inhibit histamine reuptake. Finally, we show that a functional decrease in histamine synthesis boosts the ability of escitalopram to increase extracellular serotonin levels following LPS. This work reveals a profound effect of inflammation on brain chemistry, specifically the rapidity of inflammation-induced decreased extracellular serotonin, and points the spotlight at a potentially critical player in the pathology of depression, histamine. The serotonin/histamine homeostasis thus, may be a crucial new avenue in improving serotonin-based treatments for depression.SIGNIFICANCE STATEMENT Acute LPS-induced inflammation (1) increases CNS histamine, (2) decreases CNS serotonin (via inhibitory histamine receptors), and (3) prevents a selective serotonin reuptake inhibitor (SSRI) from effectively increasing extracellular serotonin. A targeted depletion of histamine recovers SSRI-induced increases in extracellular hippocampal serotonin.

Chronic SSRI treatment reverses HIV-1 protein-mediated synaptodendritic damage

HIV-1 infection affects approximately 37 million individuals, and approximately 50% of seropositive individuals will develop symptoms of clinical depression and/or apathy. Dysfunctions of both serotonergic and dopaminergic neurotransmission have been implicated in the pathogenesis of motivational alterations. The present study evaluated the efficacy of a SSRI (escitalopram) in the HIV-1 transgenic (Tg) rat. Behavioral, neurochemical, and neuroanatomical outcomes with respect to HIV-1 and sex were evaluated to determine the efficacy of chronic escitalopram treatment. Escitalopram treatment restored function in each of the behavioral tasks that were sensitive to HIV-1-induced impairments. Further, escitalopram treatment restored HIV-1-mediated synaptodendritic damage in the nucleus accumbens; treatment with escitalopram significantly increased dendritic proliferation in HIV-1 Tg rats. However, restoration did not consistently occur with the neurochemical analysis in the HIV-1 rat. Taken together, these results suggest a role for SSRI therapies in repairing long-term HIV-1 protein-mediated neuronal damage and restoring function.

Improving serotonin fast-scan cyclic voltammetry detection: new waveforms to reduce electrode fouling

Serotonin is a neuromodulator implicated in depression that is often measured in real-time by fast-scan cyclic voltammetry (FSCV). A specialized "Jackson" waveform (JW, 0.2, 1.0 V, -0.1 V, 0.2 V, 1000 V s-1) was developed to reduce serotonin fouling, but the 1.0 V switching potential limits sensitivity and electrodes still foul. The goal of this study was to test the effects of extending the FSCV switching potential to increase serotonin sensitivity and decrease fouling. We compared the Jackson waveform, the dopamine waveform (DA, -0.4 V, 1.3 V, 400 V s-1), and two new waveforms: the extended serotonin waveform (ESW, 0.2, 1.3, -0.1, 0.2, 1000 V s-1) and extended hold serotonin waveform (EHSW, 0.2, 1.3 (hold 1 ms), -0.1, 0.2, 400 V s-1). The EHSW was the most sensitive (LOD = 0.6 nM), and the JW the least sensitive (LOD = 2.4 nM). With the Jackson waveform, electrode fouling was significant with repeated injections of serotonin or exposure to its metabolite, 5-hydroxyindoleacetic acid (5-HIAA). Using the extended waveforms, electrodes fouled 50% less than with the Jackson waveform for both analytes. No electrode fouling was observed with the dopamine waveform because of the negative holding potential. The Jackson waveform was the most selective for serotonin over dopamine (800×), and the ESW was also highly selective. All waveforms were useful for measuring serotonin with optogenetic stimulation in Drosophila larvae. These results provide new FSCV waveforms to measure dynamic serotonin changes with different experimental requirements, like high sensitivity (EHSW), high selectivity (ESW, JW), or eliminating electrode fouling (DA).

Direct Detection of DNA and RNA on Carbon Fiber Microelectrodes Using Fast-Scan Cyclic Voltammetry

DNA and RNA have been measured with many techniques but often with relatively long analysis times. In this study, we utilize fast-scan cyclic voltammetry (FSCV) for the subsecond codetection of adenine, guanine, and cytosine, first as free nucleosides, and then within custom synthesized oligos, plasmid DNA, and RNA from the nematode Caenorhabditis elegans. Previous studies have shown the detection of adenosine and guanosine with FSCV with high spatiotemporal resolution, while we have extended the assay to include cytidine and adenine, guanine, and cytosine in RNA and single- and double-stranded DNA (ssDNA and dSDNA). We find that FSCV testing has a higher sensitivity and yields higher peak oxidative currents when detecting shorter oligonucleotides and ssDNA samples at equivalent nucleobase concentrations. This is consistent with an electrostatic repulsion from negatively charged oxide groups on the surface of the carbon fiber microelectrode (CFME), the negative holding potential, and the negatively charged phosphate backbone. Moreover, as opposed to dsDNA, ssDNA nucleobases are not hydrogen-bonded to one another and thus are free to adsorb onto the surface of the carbon electrode. We also demonstrate that the simultaneous determination of nucleobases is not masked even in biologically complex serum samples. This is the first report demonstrating that FSCV, when used with CFMEs, is able to codetect nucleobases when polymerized into DNA or RNA and could potentially pave the way for future uses in clinical, diagnostic, or research applications.

Detection of neuropeptides in vivo and open questions for current and upcoming fluorescent sensors for neuropeptides

During a stress response, various neuropeptides are secreted in a spatiotemporally coordinated way in the brain. For a precise understanding of peptide functions in a stress response, it is important to investigate when and where they are released, how they diffuse, and how they are broken down in the brain. In the past two decades, genetically encoded fluorescent calcium indicators have greatly advanced our knowledge of the functions of specific neuronal activity in regulation of behavioral changes and physiological responses during stress. In addition, various kinds of structural information on G-protein-coupled receptors (GPCRs) for neuropeptides have been revealed. Recently, genetically encoded fluorescent sensors have been developed for detection of neurotransmitters by making use of conformational changes induced by ligand binding. In this review, we summarize the recent and upcoming advances of techniques for detection of neuropeptides and then present several open questions that will be solved by application of recent or upcoming technical advances in detection of neuropeptides in vivo.

Autoreceptor control of serotonin dynamics

BACKGROUND

Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding involves genomics, neurochemistry, electrophysiology, and behavior. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders. This paper presents a new deterministic model of serotonin metabolism and a new systems population model that takes into account the large variation in enzyme and transporter expression levels, tryptophan input, and autoreceptor function.

RESULTS

We discuss the steady state of the model and the steady state distribution of extracellular serotonin under different hypotheses on the autoreceptors and we show the effect of tryptophan input on the steady state and the effect of meals. We use the deterministic model to interpret experimental data on the responses in the hippocampus of male and female mice, and to illustrate the short-time dynamics of the autoreceptors. We show there are likely two reuptake mechanisms for serotonin and that the autoreceptors have long-lasting influence and compare our results to measurements of serotonin dynamics in the substantia nigra pars reticulata. We also show how histamine affects serotonin dynamics. We examine experimental data that show very variable response curves in populations of mice and ask how much variation in parameters in the model is necessary to produce the observed variation in the data. Finally, we show how the systems population model can potentially be used to investigate specific biological and clinical questions.

CONCLUSIONS

We have shown that our new models can be used to investigate the effects of tryptophan input and meals and the behavior of experimental response curves in different brain nuclei. The systems population model incorporates individual variation and can be used to investigate clinical questions and the variation in drug efficacy. The codes for both the deterministic model and the systems population model are available from the authors and can be used by other researchers to investigate the serotonergic system.

Toxicity of ayahuasca after 28 days daily exposure and effects on monoamines and brain-derived neurotrophic factor (BDNF) in brain of Wistar rats

Ayahuasca is a hallucinogenic beverage that affects the serotonergic system and have therapeutic potential for many diseases and disorders, including depression and drug addiction. The objectives of this study were to evaluate the potential toxic effects of ayahuasca on rats after chronic exposure, and the levels of monoamines, their metabolites and the brain-derived neurotrophic factor (BDNF) in the brain. Female and male rats were treated orally for 28 days with H₂O (control), fluoxetine (FLX), a selective serotonin reuptake inhibitor antidepressant, or ayahuasca (Aya) at doses of 0.5X, 1X and 2X the ritualistic dose (7 to 10 animals/group). Clinical, hematological and macroscopic results showed that ayahuasca was safe to the rats. Behavior tests conducted one hour after the last treatment showed that male rats from the Aya1 group explored the open field central area less than the control group, and the number of entries in the central area compared to total locomotion was also significantly lower in this group and in the FLX group. The hippocampus was removed for BDNF analysis and the remaining brain was used for monoamine analysis by HPLC-FL. Serotonin levels were significantly higher than control only in the Aya2 female group, while a significant reduction of its metabolite 5-HIAA was observed in the FLX group. Dopamine levels were similar among the experimental groups, but the levels of its metabolite DOPAC increased significantly in the Aya1 and Aya2 groups compared to controls, especially in females, and the DOPAC/dopamine turnover was significantly higher in Aya2 group. The levels of HVA, another dopamine metabolite, did not change with the treatments compared to controls, but HVA/DOPAC ratio was significantly lower in all ayahuasca male groups. Norepinephrine was not detected in any brain sample, and the levels of its metabolite MHPG did not change significantly among the groups. BDNF levels in the hippocampus were significantly higher in the FLX and Aya2 female groups compared to controls when expressed in relation to the total brain weight. The mechanisms involved in the increase in serotonin, dopamine turnover and BDNF levels observed in ayahuasca treated animals should be further investigated in specific brain areas.

High Young's modulus carbon fibers are fouling resistant with fast-scan cyclic voltammetry

High modulus carbon-fibers exhibit similar resistance to chemical fouling as carbon nanotube based materials with fast-scan cyclic voltammetry.

Phasic dopamine release identification using convolutional neural network

Dopamine has a major behavioral impact related to drug dependence, learning and memory functions, as well as pathologies such as schizophrenia and Parkinson's disease. Phasic release of dopamine can be measured in vivo with fast-scan cyclic voltammetry. However, even for a specialist, manual analysis of experiment results is a repetitive and time consuming task. This work aims to improve the automatic dopamine identification from fast-scan cyclic voltammetry data using convolutional neural networks (CNN). The best performance obtained in the experiments achieved an accuracy of 98.31% using a combined CNN approach. The end-to-end object detection system using YOLOv3 achieved an accuracy of 97.66%. Also, a new public dopamine release dataset was presented, and it is available at https://web.inf.ufpr.br/vri/databases/phasicdopaminerelease/.