Novel LC-MS/MS Method for Simultaneous Determination of Monoamine Neurotransmitters and Metabolites in Human Samples.

For the simultaneous determination of monoamine neurotransmitters (NTs) like dopamine, serotonin, noradrenaline, and epinephrine, and their metabolites (metanephrine, normetanephrine, 3-methoxytyramine, vanillylmandelic acid, 3,4-dihydroxyphenylacetic acid, homovanillic acid, and 5-hydroxyindoleacetic acid), a robust liquid chromatography method coupled with tandem mass spectrometry (LC-MS/MS) was introduced as the analytical method. This analytical method proved to be accurate for the simultaneous measurement of the amounts of 11 NTs and their metabolites in biological samples. The method proved to be more efficient and better than the previously reported method in terms of precision, recovery, sample requirement, and extraction procedure. The reported method requires only 100 µL of blood and 200 µL of urine, and the extraction procedure requires acetonitrile precipitation, filtration, drying, and reconstitution in water. The separation of all analytes was performed on an C18 column (4.6 mm × 150 mm and 1.8 µm). A 10 min gradient elution program with a mobile phase consisting of phase A (0.2% formic acid in water) and phase B (methanol) was used. The positive ionization mode was used for the detection of all analytes in multiple reaction monitoring (MRM). The proposed method was validated with an internal standard and yielded lower limits of detection and quantification ranges of 0.0182-0.0797 ng/mL and 0.0553-0.2415 ng/mL, respectively, with a good linearity (R2) between 0.9959 and 0.9994. The recoveries ranged from 73.37% to 116.63% in blood and from 80.9% to 115.33% in urine. For the NTs and metabolites, the intra- and interday % CV were 0.24-9.36 and 0.85-9.67, respectively. The developed LC-MS/MS method was successfully used for the determination of trace amounts of endogenous compounds in human blood and urine samples.

Microdialysis coupled with droplet microfluidics and mass spectrometry for determination of neurotransmitters in vivo with high temporal resolution.

Monitoring the concentration fluctuations of neurotransmitters in vivo is valuable for elucidating the chemical signals that underlie brain functions. Microdialysis sampling is a widely used tool for monitoring neurochemicals in vivo. The volume requirements of most techniques that have been coupled to microdialysis, such as HPLC, result in fraction collection times of minutes, thus limiting the temporal resolution possible. Further the time of analysis can become long for cases where many fractions are collected. Previously we have used direct analysis of dialysate by low-flow electrospray ionization-tandem mass spectrometry (ESI-MS/MS) on a triple quadrupole mass spectrometer to monitor acetylcholine, glutamate, and γ-amino-butyric acid to achieve multiplexed in vivo monitoring with temporal resolution of seconds. Here, we have expanded this approach to adenosine, dopamine, and serotonin. The method achieved limits of detection down to 2 nM, enabling basal concentrations of all these compounds, except serotonin, to be measured in vivo. Comparative analysis with LC-MS/MS showed accurate results for all compounds except for glutamate, possibly due to interference for this compound in vivo. Pairing this analysis with droplet microfluidics yields 11 s temporal resolution and can generate dialysate fractions down to 3 nL at rates up to 3 fractions per s from a microdialysis probe. The system is applied to multiplexed monitoring of neurotransmitter dynamics in response to stimulation by 100 mM K+ and amphetamine. These applications demonstrate the suitability of the droplet ESI-MS/MS method for monitoring short-term dynamics of up to six neurotransmitters simultaneously.

Waste Coffee Ground-Derived Porous Carbon for Neurochemical Detection.

We present an optimized synthetic method for repurposing coffee waste to create controllable, uniform porous carbon frameworks for biosensor applications to enhance neurotransmitter detection with fast-scan cyclic voltammetry. Harnessing porous carbon structures from biowastes is a common practice for low-cost energy storage applications; however, repurposing biowastes for biosensing applications has not been explored. Waste coffee ground-derived porous carbon was synthesized by chemical activation to form multivoid, hierarchical porous carbon, and this synthesis was specifically optimized for porous uniformity and electrochemical detection. These materials, when modified on carbon-fiber microelectrodes, exhibited high surface roughness and pore distribution, which contributed to significant improvements in electrochemical reversibility and oxidative current for dopamine (3.5 ± 0.4-fold) and other neurochemicals. Capacitive current increases were small, showing evidence of small increases in electroactive surface area. Local trapping of dopamine within the pores led to improved electrochemical reversibility and frequency-independent behavior. Overall, we demonstrate an optimized biowaste-derived porous carbon synthesis for neurotransmitter detection for the first time and show material utility for viable neurotransmitter detection within a tissue matrix. This work supports the notion that controlled surface nanogeometries play a key role in electrochemical detection.

Simultaneous determination of human plasma 5 amino acid neurotransmitters using liquid chromatography-tandem mass spectrometry: Establishment of reference intervals in Chinese adult population and application to patients with schizophrenia.

Schizophrenia is a serious mental disease with unknown etiology that affects approximately 1 % of the population around the world. Altered levels of amino acid neurotransmitters may underlie the physiopathology of schizophrenia (SZ). This study aimed to develop a rapid and robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous determination of glutamate acid (Glu), aspartic acid (Asp), γ-aminobutyric acid (GABA), glycine acid (Gly), and Taurine acid (Tau) in patients with schizophrenia plasma and establish reference intervals for Chinese adult populations, and applied to patients with schizophrenia for a preliminary exploration of changes in their plasma levels of five amino acid neurotransmitters. Sample treatment involved protein precipitation followed by dansyl chloride (DNS-Cl) derivatization and total run time is 5.8 min. The method was validated according to the latest national and international guidelines, which achieved acceptable precision (0.54-14.54 %) and accuracy (97.06-103.82 %). The reference interval for Glu, Asp, Gly, Tau, and GABA were 55.51-189.06, 27.51-92.38, 204.01-574.55, 107.50-227.65, and <1 µmol/L, respectively. Increased Tau levels and decreased Asp and Glu levels were shown in patients with schizophrenia. This method was suitable for clinical routine detection of plasma 5 amino acid neurotransmitters in Chinese adult populations.

Simultaneous Mapping of Amino Neurotransmitters and Nucleoside Neuromodulators on Brain Tissue Sections by On-Tissue Chemoselective Derivatization and MALDI-MSI.

Neurotransmitters (NTs) and neuromodulators (NMs) are two of the most important neurochemicals in the brain, and their imbalances in specific brain regions are thought to underlie certain neurological disorders. We present an on-tissue chemoselective derivatization mass spectrometry imaging (OTCD-MSI) method for the simultaneous mapping of NTs and NMs. Our derivatization system consists of a pyridiniumyl-benzylboronic acid based derivatization reagent and pyrylium salt, which facilitate covalent charge labeling of molecules containing cis-diol and primary amino, respectively. These derivatization systems improved the detection sensitivity of matrix-assisted laser desorption/ionization (MALDI)-MSI and simplified the identification of amino NTs and nucleoside NMs by the innate chemoselectivity of derivatization reagents and the unique isotopic pattern of boron-derivative reagents. We demonstrated the ability of the developed method on brain sections from a hypoxia mouse model and control. The simultaneous imaging of NTs and NMs provided a method for exploring how hypoxic stress and drugs affect specific brain regions through neurotransmitter modulation.

A sensitive liquid chromatography-tandem mass spectrometry method for determination biomarkers of monoamine neurotransmitter disorders in cerebrospinal fluid.

BACKGROUND: Cerebrospinal fluid (CSF) monoamine neurotransmitters, their precursors and metabolites are essential biomarkers in the diagnosis and follow-up of monoamine neurotransmitter disorders (MNDs). However, their extra low concentrations and potential instability challenge the detection method. Here, we present a method that enables simultaneous quantification of these biomarkers. METHOD: With propyl chloroformate /n-propanol, 16 biomarkers in 50 µL of CSF were derivatized in situ within seconds under an ambient temperature. The derivatives were extracted by ethyl acetate and separated by a reverse phase column followed by mass spectrometric detection. The method was fully validated. Optimal conditions for standard solution preparation and storage, as well as CSF sample handling, were investigated. CSF samples from 200 controls and 16 patients were analyzed. RESULTS: The derivatization reaction stabilized biomarkers and increased sensitivity. Most biomarkers were quantifiable in concentrations between 0.02 and 0.50 nmol/L that were sufficient to measure their endogenous concentrations. The intra- and inter-day imprecision were < 15% for most analytes, and accuracy ranged from 90.3% to 111.6%. The stability study showed that standard stock solutions were stable at -80 °C for six years when prepared in the protection solutions; Analytes in CSF samples were stable for 24 h on wet ice and at least two years at -80 °C; But repeated freeze-thaw should be avoided. With this method, age-dependent reference intervals for each biomarker in the pediatric population were established. Patients with MNDs were successfully identified. CONCLUSION: The developed method is valuable for MNDs diagnosis and research, benefiting from its advantages of sensitivity, comprehensiveness, and high throughput.

Determination of Multiple Neurotransmitters through LC-MS/MS to Confirm the Therapeutic Effects of Althaea rosea Flower on TTX-Intoxicated Rats.

Tetrodotoxin (TTX) inhibits neurotransmission in animals, and there is no specific antidote. In clinical practice in China, Althaea rosea (A. rosea flower) extract has been used to treat TTX poisoning. In this work, the efficacy of the ethyl acetate fraction extract of A. rosea flower in treating TTX poisoning in rats was investigated. A high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine nine neurotransmitters in rat brain tissue, including γ-aminobutyric acid (GABA), dopamine (DA), 5-hydroxytryptamine (5-HT), noradrenaline (NE), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxyindole-3-acetic acid (5-HIAA), epinephrine (E), and tyramine (Tyn). The detoxifying effect of A. rosea flower was verified by comparing the changes in neurotransmitters' content in brain tissue before and after poisoning in rats. The assay was performed in multiple reaction monitoring mode. The quantification method was performed by plotting an internal-standard working curve with good linearity (R2 > 0.9941) and sensitivity. Analyte recoveries were 94.04-107.53% (RSD < 4.21%). Results indicated that the levels of 5-HT, DA, E, and NE in the brains of TTX-intoxicated rats decreased, whereas the levels of GABA, Tyn, and 5-HIAA showed an opposite trend, and HVA and DOPAC were not detected. The levels of all seven neurotransmitters returned to normal after the gavage administration of ethyl acetate extract of A. rosea flower to prove that the ethyl acetate extract of A. rosea flower had a therapeutic effect on TTX poisoning. The work provided new ideas for studies on TTX detoxification.

Real-Time Monitoring of Neurotransmitters in the Brain of Living Animals.

Neurotransmitters, as important chemical small molecules, perform the function of neural signal transmission from cell to cell. Excess concentrations of neurotransmitters are often closely associated with brain diseases, such as Alzheimer's disease, depression, schizophrenia, and Parkinson's disease. On the other hand, the release of neurotransmitters under the induced stimulation indicates the occurrence of reward-related behaviors, including food and drug addiction. Therefore, to understand the physiological and pathological functions of neurotransmitters, especially in complex environments of the living brain, it is urgent to develop effective tools to monitor their dynamics with high sensitivity and specificity. Over the past 30 years, significant advances in electrochemical sensors and optical probes have brought new possibilities for studying neurons and neural circuits by monitoring the changes in neurotransmitters. This Review focuses on the progress in the construction of sensors for in vivo analysis of neurotransmitters in the brain and summarizes current attempts to address key issues in the development of sensors with high selectivity, sensitivity, and stability. Combined with the latest advances in technologies and methods, several strategies for sensor construction are provided for recording chemical signal changes in the complex environment of the brain.

Rapid and sensitive HPLC-MS/MS method for the quantification of dopamine, GABA, serotonin, glutamine and glutamate in rat brain regions after exposure to tobacco cigarettes.

Tobacco smoking is a preventable main cause of fatal diseases. Accurate measurements of the effects it has on neurotransmitters are essential in developing new strategies for smoking cessation. Moreover, measurements of neurotransmitter levels can aid in developing drugs that counteract the effects of smoking. The aim of this study is to develop and validate a fast, simultaneous and sensitive method for measuring the levels of neurotransmitters in rat brain after the exposure of tobacco cigarettes. The selected neurotransmitters include dopamine, GABA, serotonin, glutamine and glutamate. The method is based on high-performance liquid chromatography-tandem mass spectrometry. Chromatographic separation was achieved within 3 min using a Zorbax SB C18 column (3.0 × 100 mm, 1.8 µm particle size). The mobile phase consisted of HPLC-grade water and acetonitrile each containing 0.3% heptafluorobutyric acid and 0.5% formic acid at gradient conditions. The linear range was 0.015-0.07, 825-7,218, 140-520, 63.42-160.75 and 38.25 × 103 to 110.35 × 103  ng/ml for dopamine, GABA, serotonin, glutamine and glutamate, respectively. Inter- and intra-run accuracy were in the range 97.82-103.37% with a precision (CV%) of ≤0.90%. The results revealed that 4 weeks of cigarette exposure significantly increased neurotransmitter levels after exposure to tobacco cigarettes in various brain regions, including the hippocampus and the amygdala. This increase in neurotransmitters levels may in turn activate the nicotine dependence pathway.

Conformationally Flexible Dimeric-Serotonin-Based Sensitive and Selective Electrochemical Biosensing Strategy for Serotonin Recognition.

A novel electrochemical sensor was constructed based on an enzyme-mediated physiological reaction between neurotransmitter serotonin per-oxidation to reconstruct dual-molecule 4,4'-dimeric-serotonin self-assembled derivative, and the potential biomedical application of the multi-functional nano-platform was explored. Serotonin accelerated the catalytic activity to form a dual molecule at the C4 position and created phenolic radical-radical coupling intermediates in a peroxidase reaction system. Here, 4,4' dimeric-serotonin possessed the capability to recognize intermolecular interactions between amine groups. The excellent quenching effects on top of the gold surface electrode system archive logically inexpensive and straightforward analytical demands. In biochemical sensing analysis, the serotonin dimerization concept demonstrated a robust, low-cost, and highly sensitive immunosensor, presenting the potential of quantifying serotonin at point-of-care (POC) testing. The high-specificity serotonin electrochemical sensor had a limit of detection (LOD) of 0.9 nM in phosphate buffer and 1.4 nM in human serum samples and a linear range of 10 to 400 with a sensitivity of 2.0 × 10-2 nM. The bivalent 4,4'-dimer-serotonin interaction strategy provides a promising platform for serotonin biosensing with high specificity, sensitivity, selectivity, stability, and reproducibility. The self-assembling gold surface electrochemical system presents a new analytical method for explicitly detecting tiny neurotransmitter-responsive serotonin neuromolecules.

Synaptic Secretion and Beyond: Targeting Synapse and Neurotransmitters to Treat Neurodegenerative Diseases.

The nervous system is important, because it regulates the physiological function of the body. Neurons are the most basic structural and functional unit of the nervous system. The synapse is an asymmetric structure that is important for neuronal function. The chemical transmission mode of the synapse is realized through neurotransmitters and electrical processes. Based on vesicle transport, the abnormal information transmission process in the synapse can lead to a series of neurorelated diseases. Numerous proteins and complexes that regulate the process of vesicle transport, such as SNARE proteins, Munc18-1, and Synaptotagmin-1, have been identified. Their regulation of synaptic vesicle secretion is complicated and delicate, and their defects can lead to a series of neurodegenerative diseases. This review will discuss the structure and functions of vesicle-based synapses and their roles in neurons. Furthermore, we will analyze neurotransmitter and synaptic functions in neurodegenerative diseases and discuss the potential of using related drugs in their treatment.

Liquid chromatography-tandem mass spectrometry method for simultaneous quantification of neurotransmitters in rat brain tissue exposed to 4'-fluoro-α-PHP.

The combination of different advanced analytical techniques makes it possible to determine the concentrations of neurotransmitters in various biological matrices, providing a complex and comprehensive study of the effects of psychoactive substances. The present study aimed to develop and validate a fast and simple analytical method for the determination of acetylcholine, serotonin, γ-aminobutyric acid, glutamate, dopamine and metabolites in rats brain tissue by liquid chromatography coupled to tandem mass spectrometry. The brain was homogenized and aliquots of the sample, dopamine-d4 , and acetone were added to a tube and then vortexed and centrifuged. The supernatant was collected and dried. The residue was reconstituted and injected. The LLOQ ranged from 0.001 to 1 µg/g; the intra-run precision ranged from 0.47 to 11.52%; the inter-run precision ranged from 0.68 to 17.54%; and the bias ranged from 89.10 to 109.60%. As proof of concept, the method was applied to animals exposed to the synthetic cathinone 4'-fuoro-α-pyrrolidinohexanophenone (300 mg/kg). In addition, the workflow proved to be simple, rapid and useful to estimate the concentration of neurotransmitters. This analytical tool can be used to support the investigation of the changes in the neurochemical profile for the characterization of the mechanism of action of psychoactive substances, as well as both neurological and psychiatric diseases.

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synaptic efflux of neurochemicals in vivo, principal component regression (PCR), has been commonly used to predict the identity and concentrations of neurotransmitters. However, the sensitivity and discrimination performance of PCR have room for improvement, especially for analyzing mixtures of similar oxidizable neurochemicals. Deep learning may be able to address these challenges. To date, there have been a few studies to apply machine learning to FSCV, but no attempt to apply deep learning to neurotransmitter mixture discrimination and no comparative study have been performed between PCR and deep learning methods to demonstrate which is more accurate for FSCV analysis so far. In this study, we compared the neurochemical identification and concentration estimation performance of PCR and deep learning in an analysis of FSCV recordings of catecholamine and indolamine neurotransmitters. Both analysis methods were tested on in vitro FSCV data with a single or mixture of neurotransmitters at the desired concentration. In addition, the estimation performance of PCR and deep learning was compared in incorporation with in vivo experiments to evaluate the practical usage. Pharmacological tests were also conducted to see whether deep learning would track the increased amount of catecholamine levels in the brain. Using conventional FSCV, we used five electrodes and recorded in vitro background-subtracted cyclic voltammograms from four neurotransmitters, dopamine, epinephrine, norepinephrine, and serotonin, with five concentrations of each substance, as well as various mixtures of the four analytes. The results showed that the identification accuracy errors were reduced 5-20% by using deep learning compared to using PCR for mixture analysis, and the two methods were comparable for single analyte analysis. The applied deep-learning-based method demonstrated not only higher identification accuracy but also better discrimination performance than PCR for mixtures of neurochemicals and even for in vivo testing. Therefore, we suggest that deep learning should be chosen as a more reliable tool to analyze FSCV data compared to conventional PCR methods although further work is still needed on developing complete validation procedures prior to widespread use.

Associations Between Disordered Microbial Metabolites and Changes of Neurotransmitters in Depressed Mice.

Backgrounds: Many pieces of evidence demonstrated that there were close relationships between gut microbiota and depression. However, the specific molecular mechanisms were still unknown. Here, using targeted metabolomics, this study was conducted to explore the relationships between microbial metabolites in feces and neurotransmitters in prefrontal cortex of depressed mice. Methods: Chronic unpredictable mild stress (CUMS) model of depression was built in this study. Targeted liquid chromatography-mass spectrometry analysis was used to detect the microbial metabolites in feces and neurotransmitters in prefrontal cortex of mice. Both univariate and multivariate statistical analyses were applied to identify the differential microbial metabolites and neurotransmitters and explore relationships between them. Results: Ninety-eight differential microbial metabolites (mainly belonged to amino acids, fatty acids, and bile acids) and 11 differential neurotransmitters (belonged to tryptophan pathway, GABAergic pathway, and catecholaminergic pathway) were identified. Five affected amino acid-related metabolic pathways were found in depressed mice. The 19 differential microbial metabolites and 10 differential neurotransmitters were found to be significantly correlated with depressive-like behaviors. The two differential neurotransmitters (tyrosine and glutamate) and differential microbial metabolites belonged to amino acids had greater contributions to the overall correlations between microbial metabolites and neurotransmitters. In addition, the significantly decreased L-tyrosine as microbial metabolites and tyrosine as neurotransmitter had the significantly positive correlation (r = 0.681, p = 0.0009). Conclusions: These results indicated that CUMS-induced disturbances of microbial metabolites (especially amino acids) might affect the levels of neurotransmitters in prefrontal cortex and then caused the onset of depression. Our findings could broaden the understanding of how gut microbiota was involved in the onset of depression.

A tissue-like neurotransmitter sensor for the brain and gut.

Neurotransmitters play essential roles in regulating neural circuit dynamics both in the central nervous system as well as at the peripheral, including the gastrointestinal tract1-3. Their real-time monitoring will offer critical information for understanding neural function and diagnosing disease1-3. However, bioelectronic tools to monitor the dynamics of neurotransmitters in vivo, especially in the enteric nervous systems, are underdeveloped. This is mainly owing to the limited availability of biosensing tools that are capable of examining soft, complex and actively moving organs. Here we introduce a tissue-mimicking, stretchable, neurochemical biological interface termed NeuroString, which is prepared by laser patterning of a metal-complexed polyimide into an interconnected graphene/nanoparticle network embedded in an elastomer. NeuroString sensors allow chronic in vivo real-time, multichannel and multiplexed monoamine sensing in the brain of behaving mouse, as well as measuring serotonin dynamics in the gut without undesired stimulations and perturbing peristaltic movements. The described elastic and conformable biosensing interface has broad potential for studying the impact of neurotransmitters on gut microbes, brain-gut communication and may ultimately be extended to biomolecular sensing in other soft organs across the body.

Characterization of monoaminergic neurochemicals in cortex and striatum of mouse brain.

Monoamine neurochemicals regulate most of the physiological and behavioural processes in the vertebrate brain. Mice and rats are the preferred species in scientific research, specifically in biomedical research, due to their anatomical, genetic and physiological similarity to human. Moreover, the interest in monitoring the changes in the central nervous system (CNS) produced by neuroactive compounds is constantly growing. In this study, we have evaluated the performance of liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) for the multiresidue determination of multi-class monoamine neurotransmitters in the main areas of mouse brain (prefrontal cortex and striatum). The best performance was obtained with a BEH amide column, which permitted the separation of 9 compounds in only 10 min. Moreover, the performance of LC-MS/MS was evaluated in terms of linearity, sensitivity, intraday precision and overall robustness. Finally, catecholamine neurochemicals reported significant differences in the concentration levels between prefrontal cortex and striatum, while serotonergic neurochemicals didn't report any significant differences.

A fluorescent nanosensor paint detects dopamine release at axonal varicosities with high spatiotemporal resolution.

The neurotransmitter dopamine (DA) controls multiple behaviors and is perturbed in several major brain diseases. DA is released from large populations of specialized structures called axon varicosities. Determining the DA release mechanisms at such varicosities is essential for a detailed understanding of DA biology and pathobiology but has been limited by the low spatial resolution of DA detection methods. We used a near-infrared fluorescent DA nanosensor paint, adsorbed nanosensors detecting release of dopamine (AndromeDA), to detect DA secretion from cultured murine dopaminergic neurons with high spatial and temporal resolution. We found that AndromeDA detects discrete DA release events and extracellular DA diffusion and observed that DA release varies across varicosities. To systematically detect DA release hotspots, we developed a machine learning­based analysis tool. AndromeDA permitted the simultaneous visualization of DA release for up to 100 dopaminergic varicosities, showing that DA release hotspots are heterogeneous and occur at only ∼17% of all varicosities, indicating that many varicosities are functionally silent. Using AndromeDA, we determined that DA release requires Munc13-type vesicle priming proteins, validating the utility of AndromeDA as a tool to study the molecular and cellular mechanism of DA secretion.

Extracellular Fluid Collection and Analysis of Drosophila melanogaster Brain Tissue with µ-Low-Flow Push-Pull Perfusion (µLFPP).

The development of methods to generate quantitative chemical content information from precise tissue locations is needed to understand fundamental cellular and tissue physiology. This work describes a method to perfuse the extracellular fluid of fly brains in vivo using µ-low-flow push-pull perfusion (µLFPP) for quantitative chemical content determinations. Miniaturization of push-pull perfusion probe designs allowed the development of methods for probe tip placement into and sampling from the fruit fly's brain. Perfusate analysis identified and quantified arginine, octopamine, histidine, taurine, glycine, glutamate, and aspartate. The perfusate data did not exhibit any statistical differences based on sex. The perfusate analysis was compared to hemolymph samples to confirm probe placement in fly brain tissues. The appearance of probe placement into the brain space was confirmed with the following observations. Hemolymph and perfusate samples were found to contain analytes unique to each sample type. Quantitated levels of perfusate were not a simple dilution of hemolymph content. Further, the discovery of perfusates with composition similar to both hemolymph and brain perfusate when damage was intentionally inflicted supports the observation that perfusates are distinct from hemolymph. The analysis of perfusate collected for greater than an hour of sampling exhibits the possibility of monitoring applications. Altogether, this work demonstrates the viability of performing µ-low-flow push-pull perfusion for in vivo studies of fly brain tissues to identify and quantitate neurotransmitter content.

Molecular Engineered Carbon-Based Sensor for Ultrafast and Specific Detection of Neurotransmitters.

In the quest for designing affordable diagnostic devices with high performance, precisely functionalized carbon-based materials with high accuracy and selectivity are required. Every material has its own unique ability to interact with the analyte, and its performance can be enhanced by probing the interaction mechanism. Herein, p-aminophenol (PAP)-functionalized reduced graphene oxide (rGO) nanoscale material is developed by a one-step synthetic route as an all-organic-based sensor. As the PAP molecules are precisely covalently interacted with the rGO at the basal plane and form a wrinkled-paper-like structure, the functionalized material exhibits an outstanding sensing ability (7.5 nM neurotransmitter dopamine (DA) at a wide linear range, 0.01-100 µM) with fast electrical transduction (<3 s) and good recyclability (∼10 cycles) in a real sample. Combining various analytical and density functional theory (DFT) calculation methods, physicochemical properties and the interaction mechanism of analyte-materials transduction are discussed exclusively. Besides, the potential application of the well-dispersed rGO-PAP gravure ink in flexible-printed electronics fields is explored. This study not only provides new insights into the surface/interface chemistry and working principle of this unique anchoring of PAP on rGO but also offers a new pathway for developing other forms of metal-free/organic functionalized biosensors with high efficiency.

Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression.

Many voltammetry methods have been developed to monitor brain extracellular dopamine levels. Fewer approaches have been successful in detecting serotonin in vivo. No voltammetric techniques are currently available to monitor both neurotransmitters simultaneously across timescales, even though they play integrated roles in modulating behavior. We provide proof-of-concept for rapid pulse voltammetry coupled with partial least squares regression (RPV-PLSR), an approach adapted from multi-electrode systems (i.e., electronic tongues) used to identify multiple components in complex environments. We exploited small differences in analyte redox profiles to select pulse steps for RPV waveforms. Using an intentionally designed pulse strategy combined with custom instrumentation and analysis software, we monitored basal and stimulated levels of dopamine and serotonin. In addition to faradaic currents, capacitive currents were important factors in analyte identification arguing against background subtraction. Compared to fast-scan cyclic voltammetry-principal components regression (FSCV-PCR), RPV-PLSR better differentiated and quantified basal and stimulated dopamine and serotonin associated with striatal recording electrode position, optical stimulation frequency, and serotonin reuptake inhibition. The RPV-PLSR approach can be generalized to other electrochemically active neurotransmitters and provides a feedback pipeline for future optimization of multi-analyte, fit-for-purpose waveforms and machine learning approaches to data analysis.