Simultaneous Voltammetric Measurements of Glucose and Dopamine Demonstrate the Coupling of Glucose Availability with Increased Metabolic Demand in the Rat Striatum

Optimized Fabrication of Carbon-Fiber Microbiosensors for Codetection of Glucose and Dopamine in Brain Tissue

Dopamine (DA) signaling is critically important in striatal function, and this metabolically demanding process is fueled largely by glucose. However, DA and glucose are typically studied independently and, as such, the precise relationship between DA release and glucose availability remains unclear. Fast-scan cyclic voltammetry (FSCV) is commonly coupled with carbon-fiber microelectrodes to study DA transients. These microelectrodes can be modified with glucose oxidase (GOx) to generate microbiosensors capable of simultaneously quantifying real-time and physiologically relevant fluctuations of glucose, a nonelectrochemically active substrate, and DA, which is readily oxidized and reduced at the electrode surface. A chitosan hydrogel can be electrodeposited to entrap the oxidase enzyme on the sensor surface for stable, sensitive, and selective codetection of glucose and DA using FSCV. This strategy can also be used to entrap lactate oxidase on the carbon-fiber surface for codetection of lactate and DA. However, these custom probes are individually fabricated by hand, and performance is variable. This study characterizes the physical nature of the hydrogel and its effects on the acquired electrochemical data in the detection of glucose (2.6 mM) and DA (1 μM). The results demonstrate that the electrodeposition of the hydrogel membrane is improved using a linear potential sweep rather than a direct step to the target potential. Electrochemical impedance spectroscopy data relate information on the physical nature of the electrode/solution interface to the electrochemical performance of bare and enzyme-modified carbon-fiber microelectrodes. The electrodeposition waveform and scan rate were characterized for optimal membrane formation and performance. Finally, codetection of both DA/glucose and DA/lactate was demonstrated in intact rat striatum using probes fabricated according to the optimized protocol. Overall, this work improves the reliable fabrication of carbon-fiber microbiosensors for codetection of DA and important energetic substrates that are locally delivered to the recording site to meet metabolic demand.

Editors' Choice-Review-The Future of Carbon-Based Neurochemical Sensing: A Critical Perspective

Carbon-based sensors have remained critical materials for electrochemical detection of neurochemicals, rooted in their inherent biocompatibility and broad potential window. Real-time monitoring using fast-scan cyclic voltammetry has resulted in the rise of minimally invasive carbon fiber microelectrodes as the material of choice for making measurements in tissue, but challenges with carbon fiber's innate properties have limited its applicability to understudied neurochemicals. Here, we provide a critical review of the state of carbon-based real-time neurochemical detection and offer insight into ways we envision addressing these limitations in the future. This piece focuses on three main hinderances of traditional carbon fiber based materials: diminished temporal resolution due to geometric properties and adsorption/desorption properties of the material, poor selectivity/specificity to most neurochemicals, and the inability to tune amorphous carbon surfaces for specific interfacial interactions. Routes to addressing these challenges could lie in methods like computational modeling of single-molecule interfacial interactions, expansion to tunable carbon-based materials, and novel approaches to synthesizing these materials. We hope this critical piece does justice to describing the novel carbon-based materials that have preceded this work, and we hope this review provides useful solutions to innovate carbon-based material development in the future for individualized neurochemical structures.

Simultaneous, Real-Time Detection of Glutamate and Dopamine in Rat Striatum Using Fast-Scan Cyclic Voltammetry

Glutamate and dopamine (DA) represent two key contributors to striatal functioning, a region of the brain that is essential to motor coordination and motivated behavior. While electroanalytical techniques can be utilized for rapid, spatially resolved detection of DA in the interferent-rich brain environment, glutamate, a nonelectroactive analyte, cannot be directly detected using electroanalytical techniques. However, it can be probed using enzyme-based sensors, which generate an electroactive reporter in the presence of glutamate. The vast majority of glutamate biosensors have relied on amperometric sensing, which is an inherently nonselective detection technique. This approach necessitates the use of complex and performance-limiting modifications to ensure the desired single-analyte specificity. Here, we present a novel glutamate microbiosensor fabricated on a carbon-fiber microelectrode substrate and coupled with fast-scan cyclic voltammetry (FSCV) to enable the simultaneous quantification of glutamate and DA at single recording sites in the brain, which is impossible when using typical amperometric approaches. The glutamate microbiosensors were characterized for sensitivity, stability, and selectivity by using a voltammetric waveform optimized for the simultaneous detection of both species. The applicability of these sensors for the investigation of neural circuits was validated in the rat ventral striatum. Electrically evoked glutamate and DA release were recorded at single-micrometer-scale locations before and after pharmacological manipulation of glutamatergic signaling. Our novel glutamate microbiosensor advances the state of the art by providing a powerful tool for probing coordination between these two species in a way that has previously not been possible.

Hydrogel-Coated Microelectrode Resists Protein Passivation of In Vivo Amperometric Sensors

Passivation of electrodes caused by nonspecific adsorption of protein can dramatically reduce sensing sensitivity and accuracy, which is a great challenge for in vivo neurochemical monitoring. However, most antipassivation strategies are not suitable to carbon fiber microelectrodes (CFMEs) for in vivo measurement, and these methods also do not work on electrochemical biosensors that fix biometric elements. In this study, we demonstrate that chitosan hydrogel-coated microelectrodes can avoid the current passivation caused by protein adsorption on the surface of carbon fiber because the chitosan hydrogel prepared by local pH gradient caused by hydrogen evolution reaction has three-dimensional networks containing large amounts of water. The highly hydrophilic three-dimensional structure of hydrogel not only forms a biocompatible interface to confine enzymes but also keeps the fast mass transfer of analytes, such as dopamine, ascorbic acid, and glucose. The consistency of the precalibration and postcalibration of the prepared sensor enables in vivo amperometric detection of both electroactive species based on their redox property and electroinactive species based on the enzyme. This study provides a simple and versatile strategy to constitute an amperometric sensor interface to resist passivation of protein adsorption in a complex biological environment such as the brain.

Investigating lytic polysaccharide monooxygenase-assisted wood cell wall degradation with microsensors

Lytic polysaccharide monooxygenase (LPMO) supports biomass hydrolysis by increasing saccharification efficiency and rate. Recent studies demonstrate that H₂O₂ rather than O₂ is the cosubstrate of the LPMO-catalyzed depolymerization of polysaccharides. Some studies have questioned the physiological relevance of the H₂O₂-based mechanism for plant cell wall degradation. This study reports the localized and time-resolved determination of LPMO activity on poplar wood cell walls by measuring the H₂O₂ concentration in their vicinity with a piezo-controlled H₂O₂ microsensor. The investigated Neurospora crassa LPMO binds to the inner cell wall layer and consumes enzymatically generated H₂O₂. The results point towards a high catalytic efficiency of LPMO at a low H₂O₂ concentration that auxiliary oxidoreductases in fungal secretomes can easily generate. Measurements with a glucose microbiosensor additionally demonstrate that LPMO promotes cellobiohydrolase activity on wood cell walls and plays a synergistic role in the fungal extracellular catabolism and in industrial biomass degradation.

Contrasting dose-dependent effects of acute intravenous methamphetamine on lateral hypothalamic extracellular glucose dynamics in male and female rats

Glucose is the brain's primary energetic resource. The brain's use of glucose is dynamic, balancing delivery from the neurovasculature with local metabolism. Although glucose metabolism is known to differ in humans with and without methamphetamine use disorder (MUD), it is unknown how central glucose regulation changes with acute methamphetamine experience. Here, we determined how intravenous methamphetamine regulates extracellular glucose levels in a brain region implicated in MUD-like behavior, the lateral hypothalamus (LH). We measured extracellular LH glucose in awake adult male and female drug-naive Wistar rats using enzyme-linked amperometric glucose biosensors. Changes in LH glucose were monitored during a single session after: 1) natural nondrug stimuli (novel object presentation and a tail-touch), 2) increasing cumulative doses of intravenous methamphetamine (0.025, 0.05, 0.1, and 0.2 mg/kg), and 3) an injection of 60 mg of glucose. We found second-scale fluctuations in LH glucose in response to natural stimuli that differed by both stimulus type and sex. Although rapid, second-scale changes in LH glucose during methamphetamine injections were variable, slow, minute-scale changes following most injections were robust and resulted in a reduction in LH glucose levels. Dose and sex differences at this timescale indicated that female rats may be more sensitive to the impact of methamphetamine on central glucose regulation. These findings suggest that the effects of MUD on healthy brain function may be linked to how methamphetamine alters extracellular glucose regulation in the LH and point to possible mechanisms by which methamphetamine influences central glucose metabolism more broadly.NEW & NOTEWORTHY Enzyme-linked glucose biosensors were used to monitor lateral hypothalamic (LH) extracellular fluctuations during nondrug stimuli and intravenous methamphetamine injections in drug-naive awake male and female rats. Second-scale glucose changes occurred after nondrug stimuli, differing by modality and sex. Robust minute-scale decreases followed most methamphetamine injections. Sex differences at the minute-scale indicate female central glucose regulation is more sensitive to methamphetamine effects. We discuss likely mechanisms underlying these fluctuations, and their implications in methamphetamine use disorder.

Letting the little light of mind shine: Advances and future directions in neurochemical detection

Synaptic transmission via neurochemical release is the fundamental process that integrates and relays encoded information in the brain to regulate physiological function, cognition, and emotion. To unravel the biochemical, biophysical, and computational mechanisms of signal processing, one needs to precisely measure the neurochemical release dynamics with molecular and cell-type specificity and high resolution. Here we reviewed the development of analytical, electrochemical, and fluorescence imaging approaches to detect neurotransmitter and neuromodulator release. We discussed the advantages and practicality in implementation of each technology for ease-of-use, flexibility for multimodal studies, and challenges for future optimization. We hope this review will provide a versatile guide for tool engineering and applications for recording neurochemical release.

Organic Bioelectronic Devices for Metabolite Sensing

Electrochemical detection of metabolites is essential for early diagnosis and continuous monitoring of a variety of health conditions. This review focuses on organic electronic material-based metabolite sensors and highlights their potential to tackle critical challenges associated with metabolite detection. We provide an overview of the distinct classes of organic electronic materials and biorecognition units used in metabolite sensors, explain the different detection strategies developed to date, and identify the advantages and drawbacks of each technology. We then benchmark state-of-the-art organic electronic metabolite sensors by categorizing them based on their application area (in vitro, body-interfaced, in vivo, and cell-interfaced). Finally, we share our perspective on using organic bioelectronic materials for metabolite sensing and address the current challenges for the devices and progress to come.

In Parkinson's patient-derived dopamine neurons, the triplication of α-synuclein locus induces distinctive firing pattern by impeding D2 receptor autoinhibition

Pathophysiological changes in dopamine neurons precede their demise and contribute to the early phases of Parkinson's disease (PD). Intracellular pathological inclusions of the protein α-synuclein within dopaminergic neurons are a cardinal feature of PD, but the mechanisms by which α-synuclein contributes to dopaminergic neuron vulnerability remain unknown. The inaccessibility to diseased tissue has been a limitation in studying progression of pathophysiology prior to degeneration of dopamine neurons. To address these issues, we differentiated induced pluripotent stem cells (iPSCs) from a PD patient carrying the α-synuclein triplication mutation (AST) and an unaffected first-degree relative (NAS) into dopaminergic neurons. In human-like dopamine neurons α-synuclein overexpression reduced the functional availability of D2 receptors, resulting in a stark dysregulation in firing activity, dopamine release, and neuronal morphology. We back-translated these findings into primary mouse neurons overexpressing α-synuclein and found a similar phenotype, supporting the causal role for α-synuclein. Importantly, application of D2 receptor agonist, quinpirole, restored the altered firing activity of AST-derived dopaminergic neurons to normal levels. These results provide novel insights into the pre-degenerative pathophysiological neuro-phenotype induced by α-synuclein overexpression and introduce a potential mechanism for the long-established clinical efficacy of D2 receptor agonists in the treatment of PD.

Brain neurochemical monitoring

Brain neurochemical monitoring aims to provide continuous and accurate measurements of brain biomarkers. It has enabled significant advances in neuroscience for application in clinical diagnostics, treatment, and prevention of brain diseases. Microfabricated electrochemical and optical spectroscopy sensing technologies have been developed for precise monitoring of brain neurochemicals. Here, a comprehensive review on the progress of sensing technologies developed for brain neurochemical monitoring is presented. The review provides a summary of the widely measured clinically relevant neurochemicals and commonly adopted recognition technologies. Recent advances in sampling, electrochemistry, and optical spectroscopy for brain neurochemical monitoring are highlighted and their application are discussed. Existing gaps in current technologies and future directions to design industry standard brain neurochemical sensing devices for clinical applications are addressed.

Energy sensors in drug addiction: A potential therapeutic target

Addiction is defined as the repeated exposure and compulsive seek of psychotropic drugs that, despite the harmful effects, generate relapse after the abstinence period. The psychophysiological processes associated with drug addiction (acquisition/expression, withdrawal, and relapse) imply important alterations in neurotransmission and changes in presynaptic and postsynaptic plasticity and cellular structure (neuroadaptations) in neurons of the reward circuits (dopaminergic neuronal activity) and other corticolimbic regions. These neuroadaptation mechanisms imply important changes in neuronal energy balance and protein synthesis machinery. Scientific literature links drug-induced stimulation of dopaminergic and glutamatergic pathways along with presence of neurotrophic factors with alterations in synaptic plasticity and membrane excitability driven by metabolic sensors. Here, we provide current knowledge of the role of molecular targets that constitute true metabolic/energy sensors such as AMPK, mTOR, ERK, or K_ATP in the development of the different phases of addiction standing out the main brain regions (ventral tegmental area, nucleus accumbens, hippocampus, and amygdala) constituting the hubs in the development of addiction. Because the available treatments show very limited effectiveness, evaluating the drug efficacy of AMPK and mTOR specific modulators opens up the possibility of testing novel pharmacotherapies for an individualized approach in drug abuse.

Simultaneous voltammetric detection of glucose and lactate fluctuations in rat striatum evoked by electrical stimulation of the midbrain

Glucose and lactate provide energy for cellular function in the brain and serve as an important carbon source in the synthesis of a variety of biomolecules. Thus, there is a critical need to quantitatively monitor these molecules in situ on a time scale commensurate with neuronal function. In this work, carbon-fiber microbiosensors were coupled with fast-scan cyclic voltammetry to monitor glucose and lactate fluctuations at a discrete site within rat striatum upon electrical stimulation of the midbrain projection to the region. Systematic variation of stimulation parameters revealed the distinct dynamics by which glucose and lactate responded to the metabolic demand of synaptic function. Immediately upon stimulation, extracellular glucose and lactate availability rapidly increased. If stimulation was sufficiently intense, concentrations then immediately fell below baseline in response to incurred metabolic demand. The dynamics were dependent on stimulation frequency, such that more robust fluctuations were observed when the same number of pulses was delivered at a higher frequency. The rates at which glucose was supplied to, and depleted from, the local recording region were dependent on stimulation intensity, and glucose dynamics led those of lactate in response to the most substantial stimulations. Glucose fluctuated over a larger concentration range than lactate as stimulation duration increased, and glucose fell further from baseline concentrations. These real-time measurements provide an unprecedented direct comparison of glucose and lactate dynamics in response to metabolic demand elicited by neuronal activation. Graphical abstract.

Positive association between cerebral grey matter metabolism and dopamine D2/D3 receptor availability in healthy and schizophrenia subjects: An 18F-fluorodeoxyglucose and 18F-fallypride positron emission tomography study

Objectives: Overlapping decreases in extrastriatal dopamine D₂/D₃-receptor availability and glucose metabolism have been reported in subjects with schizophrenia. It remains unknown whether these findings are physiologically related or coincidental.Methods: To ascertain this, we used two consecutive ¹⁸F-fluorodeoxyglucose and ¹⁸F-fallypride positron emission tomography scans in 19 healthy and 25 unmedicated schizophrenia subjects. Matrices of correlations between ¹⁸F-fluorodeoxyglucose uptake and ¹⁸F-fallypride binding in voxels at the same xyz location and AFNI-generated regions of interest were evaluated in both diagnostic groups.Results:¹⁸F-fluorodeoxyglucose uptake and ¹⁸F-fallypride binding potential were predominantly positively correlated across the striatal and extrastriatal grey matter in both healthy and schizophrenia subjects. In comparison to healthy subjects, significantly weaker correlations in subjects with schizophrenia were confirmed in the right cingulate gyrus and thalamus, including the mediodorsal, lateral dorsal, anterior, and midline nuclei. Schizophrenia subjects showed decreased D₂/D₃-receptor availability in the hypothalamus, mamillary bodies, thalamus and several thalamic nuclei, and increased glucose uptake in three lobules of the cerebellar vermis.Conclusions: Dopaminergic system may be involved in modulation of grey matter metabolism and neurometabolic coupling in both healthy human brain and psychopathology. Hyperdopaminergic state in untreated schizophrenia may at least partly account for the corresponding decreases in grey matter metabolism.

Impaired brain glucose metabolism and presynaptic dopaminergic functioning in a mouse model of schizophrenia

Background

Schizophrenia is a disease diagnosed by visible signs and symptoms from late adolescence to early adulthood. The etiology of this disease remains unknown. An objective diagnostic approach is required. Here, we used a mouse model that shows schizophrenia-like phenotypes to study brain glucose metabolism and presynaptic dopaminergic functioning by positron emission tomography (PET) and immunohistochemistry. PET scannings were performed on mice after the administration of [¹⁸F]-FDG or [¹⁸F]-F-DOPA. Glucose metabolism was evaluated in basal conditions and after the induction of a hyperdopaminergic state.

Results

Mutant animals show reduced glucose metabolism in prefrontal cortex, amygdala, and nucleus reuniens under the hyperdopaminergic state. They also show reduced [¹⁸F]-F-DOPA uptake in prefrontal cortex, substantia nigra reticulata, raphe nucleus, and ventral striatum but increased [¹⁸F]-F-DOPA uptake in dorsal striatum. Mutant animals also show reduced tyrosine hydroxylase expression on midbrain neurons.

Conclusions

Dopamine D2 mutant animals show reduced glucose metabolism and impaired presynaptic dopaminergic functioning, in line with reports from human studies. This mouse line may be a valuable model of schizophrenia, useful to test novel tracers for PET scanning diagnostic.

In Vivo Electrochemical Sensors for Neurochemicals: Recent Update

In vivo electrochemical sensing based on implantable microelectrodes is a strong driving force of analytical neurochemistry in brain. The complex and dynamic neurochemical network sets stringent standards of in vivo electrochemical sensors including high spatiotemporal resolution, selectivity, sensitivity, and minimized disturbance on brain function. Although advanced materials and novel technologies have promoted the development of in vivo electrochemical sensors drastically, gaps with the goals still exist. This Review mainly focuses on recent attempts on the key issues of in vivo electrochemical sensors including selectivity, tissue response and sensing reliability, and compatibility with electrophysiological techniques. In vivo electrochemical methods with bare carbon fiber electrodes, of which the selectivity is achieved either with electrochemical techniques such as fast-scan cyclic voltammetry and differential pulse voltammetry or based on the physiological nature will not be reviewed. Following the elaboration of each issue involved in in vivo electrochemical sensors, possible solutions supported by the latest methodological progress will be discussed, aiming to provide inspiring and practical instructions for future research.

Next-generation interfaces for studying neural function

Monitoring and modulating the diversity of signals used by neurons and glia in a closed-loop fashion is necessary to establish causative links between biochemical processes within the nervous system and observed behaviors. As developments in neural-interface hardware strive to keep pace with rapid progress in genetically encoded and synthetic reporters and modulators of neural activity, the integration of multiple functional features becomes a key requirement and a pressing challenge in the field of neural engineering. Electrical, optical and chemical approaches have been used to manipulate and record neuronal activity in vivo, with a recent focus on technologies that both integrate multiple modes of interaction with neurons into a single device and enable bidirectional communication with neural circuits with enhanced spatiotemporal precision. These technologies not only are facilitating a greater understanding of the brain, spinal cord and peripheral circuits in the context of health and disease, but also are informing the development of future closed-loop therapies for neurological, neuro-immune and neuroendocrine conditions.

A single nanowire sensor for intracellular glucose detection

Glucose metabolism plays an important role in cell energy supply, and quantitative detection of the intracellular glucose level is particularly important for understanding many physiological processes. Glucose electrochemical sensors are widely used for blood and extracellular glucose detection. However, intracellular glucose detection cannot be achieved by these sensors owing to their large size and consequent low spatial resolution. Herein, we developed a single nanowire glucose sensor for electrochemical detection of intracellular glucose by depositing Pt nanoparticles (Pt NPs) on a SiC@C nanowire and further immobilizing glucose oxidase (GOD) thereon. Glucose was converted by GOD to an electroactive product H2O2 which was further electro-catalyzed by Pt NPs. The glucose nanowire sensor is endowed with a high sensitivity, high spatial-temporal resolution and enzyme specificity due to its nanoscale size and enzymatic reaction. This allows the real-time monitoring of the intracellular glucose level, and the increase of the intracellular glucose level induced by a novel potential hypoglycemic agent, reinforcing its potential application in lowering the blood glucose level. This work provides a versatile method for the construction of enzyme-modified nanosensors to electrochemically detect intracellular non-electroactive molecules, which is of great benefit for physiological and pathological studies.

Frontiers in Electrochemical Sensors for Neurotransmitter Detection: Towards Measuring Neurotransmitters as Chemical Diagnostics for Brain Disorders

It is extremely challenging to chemically diagnose disorders of the brain. There is hence great interest in designing and optimizing tools for direct detection of chemical biomarkers implicated in neurological disorders to improve diagnosis and treatment. Tools that are capable of monitoring brain chemicals, neurotransmitters in particular, need to be biocompatible, perform with high spatiotemporal resolution, and ensure high selectivity and sensitivity. Recent advances in electrochemical methods are addressing these criteria; the resulting devices demonstrate great promise for in vivo neurotransmitter detection. None of these devices are currently used for diagnostic purposes, however these cutting-edge technologies are promising more sensitive, selective, faster, and less invasive measurements. Via this review we highlight significant technical advances and in vivo studies, performed in the last 5 years, that we believe will facilitate the development of diagnostic tools for brain disorders.

Drift Subtraction for Fast-Scan Cyclic Voltammetry Using Double-Waveform Partial-Least-Squares Regression

Background-subtracted fast-scan cyclic voltammetry (FSCV) provides a method for detecting molecular fluctuations with high spatiotemporal resolution in the brain of awake and behaving animals. The rapid scan rates generate large background currents that are subtracted to reveal changes in analyte concentration. Although these background currents are relatively stable, small changes do occur over time. These changes, referred to as electrochemical drift, result in background-subtraction artifacts that constrain the utility of FSCV, particularly when quantifying chemical changes that gradually occur over long measurement times (minutes). The voltammetric features of electrochemical drift are varied and can span the entire potential window, potentially obscuring the signal from any targeted analyte. We present a straightforward method for extending the duration of a single FSCV recording window. First, we have implemented voltammetric waveforms in pairs that consist of a smaller triangular sweep followed by a conventional voltammetric scan. The initial, abbreviated waveform is used to capture drift information that can serve as a predictor for the contribution of electrochemical drift to the subsequent full voltammetric scan using partial-least-squares regression (PLSR). This double-waveform partial-least-squares regression (DW-PLSR) paradigm permits reliable subtraction of the drift component to the voltammetric data. Here, DW-PLSR is used to improve quantification of adenosine, dopamine, and hydrogen peroxide fluctuations occurring >10 min from the initial background position, both in vitro and in vivo. The results demonstrate that DW-PLSR is a powerful tool for evaluating and interpreting both rapid (seconds) and gradual (minutes) chemical changes captured in FSCV recordings over extended durations.

Carbon Nanoelectrodes for the Electrochemical Detection of Neurotransmitters

Carbon-based electrodes have been developed for the detection of neurotransmitters over the past 30 years using voltammetry and amperometry. The traditional electrode for neurotransmitter detection is the carbon fiber microelectrode (CFME). The carbon-based electrode is suitable for in vivo neurotransmitter detection due to the fact that it is biocompatible and relatively small in surface area. The advent of nanoscale electrodes is in high demand due to smaller surface areas required to target specific brain regions that are also minimally invasive and cause relatively low tissue damage when implanted into living organisms. Carbon nanotubes (CNTs), carbon nanofibers, carbon nanospikes, and carbon nanopetals among others have all been utilized for this purpose. Novel electrode materials have also required novel insulations such as glass, epoxy, and polyimide coated fused silica capillaries for their construction and usage. Recent research developments have yielded a wide array of carbon nanoelectrodes with superior properties and performances in comparison to traditional electrode materials. These electrodes have thoroughly enhanced neurotransmitter detection allowing for the sensing of biological compounds at lower limits of detection, fast temporal resolution, and without surface fouling. This will allow for greater understanding of several neurological disease states based on the detection of neurotransmitters.

Electrochemical Selectivity Achieved Using a Double Voltammetric Waveform and Partial Least Squares Regression: Differentiating Endogenous Hydrogen Peroxide Fluctuations from Shifts in pH

Hydrogen peroxide (H₂O₂) is a reactive oxygen species that serves as an important signaling molecule in normal brain function. At the same time, excessive H₂O₂ concentrations contribute to myriad pathological consequences resulting from oxidative stress. Studies to elucidate the diverse roles that H₂O₂ plays in complex biological environments have been hindered by the lack of robust methods for probing dynamic H₂O₂ fluctuations in living systems with molecular specificity. Background-subtracted fast-scan cyclic voltammetry at carbon-fiber microelectrodes provides a method of detecting rapid H₂O₂ fluctuations with high temporal and spatial resolution in brain tissue. However, H₂O₂ fluctuations can be masked by local changes in pH (ΔpH), because the voltammograms for these species can have significant peak overlap, hindering quantification. We present a method for removing ΔpH-related contributions from complex voltammetric data. By employing two distinct potential waveforms per scan, one in which H₂O₂ is electrochemically silent and a second in which both ΔpH and H₂O₂ are redox active, a clear distinction between H₂O₂ and ΔpH signals is established. A partial least-squares regression (PLSR) model is used to predict the ΔpH signal and subtract it from the voltammetric data. The model has been validated both in vitro and in vivo using k-fold cross-validation. The data demonstrate that the double waveform PLSR model is a powerful tool that can be used to disambiguate and evaluate naturally occurring H₂O₂ fluctuations in vivo.

Selective and Mechanically Robust Sensors for Electrochemical Measurements of Real-Time Hydrogen Peroxide Dynamics in Vivo

Hydrogen peroxide (H2O2) is an endogenous molecule that plays several important roles in brain function: it is generated in cellular respiration, serves as a modulator of dopaminergic signaling, and its presence can indicate the upstream production of more aggressive reactive oxygen species (ROS). H2O2 has been implicated in several neurodegenerative diseases, including Parkinson's disease (PD), creating a critical need to identify mechanisms by which H2O2 modulates cellular processes in general and how it affects the dopaminergic nigrostriatal pathway, in particular. Furthermore, there is broad interest in selective electrochemical quantification of H2O2, because it is often enzymatically generated at biosensors as a reporter for the presence of nonelectroactive target molecules. H2O2 fluctuations can be monitored in real time using fast-scan cyclic voltammetry (FSCV) coupled with carbon-fiber microelectrodes. However, selective identification is a critical issue when working in the presence of other molecules that generate similar voltammograms, such as adenosine and histamine. We have addressed this problem by fabricating a robust, H2O2-selective electrode. 1,3-Phenylenediamine (mPD) was electrodeposited on a carbon-fiber microelectrode to create a size-exclusion membrane, rendering the electrode sensitive to H2O2 fluctuations and pH shifts but not to other commonly studied neurochemicals. The electrodes are described and characterized herein. The data demonstrate that this technology can be used to ensure the selective detection of H2O2, enabling confident characterization of the role this molecule plays in normal physiological function as well as in the progression of PD and other neuropathies involving oxidative stress.

A bio-image sensor for simultaneous detection of multi-neurotransmitters

We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H⁺) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H⁺ sensor to minimize the undesired signal overlap by H⁺ diffusion. Using this bio-image sensor, we can obtain H⁺ diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes.

Spectroelectrochemical Characterization of the Dynamic Carbon-Fiber Surface in Response to Electrochemical Conditioning

The effects of electrochemical preconditioning of P-55 pitch-based carbon-fiber microelectrodes were quantitatively examined in this study. Microstructural characterization of the electrode surface was done using Raman spectroscopy and scanning electron microscopy. Electrochemical performance was evaluated using cyclic voltammetry. The data show that application of positive potentials provides beneficial structural modifications to the electrode surface. Electrodes that were preconditioned using a static potential of +1.0 V exhibited enhanced sensitivity and electron transfer properties when compared to electrodes conditioned for the same amount of time with dynamic (triangular) waveforms reaching +1.0 V. Conditioning elicited microstructural changes to the electrode surface that were dependent on the amount of time spent at potentials greater than ∼1.0 V. Importantly, the data demonstrate that the carbon-fiber microstructure is dynamic. It is able to quickly and continuously undergo rapid structural reorganization as potential is applied, repeatedly alternating between a relatively ordered state and one that exhibits greater disorder in response to applied electrochemical potentials that span the range commonly used in voltammetric experiments.