Anti-manic effect of deep brain stimulation of the ventral tegmental area in an animal model of mania induced by methamphetamine.

BACKGROUND: Treatment of refractory bipolar disorder (BD) is extremely challenging. Deep brain stimulation (DBS) holds promise as an effective treatment intervention. However, we still understand very little about the mechanisms of DBS and its application on BD. AIM: The present study aimed to investigate the behavioural and neurochemical effects of ventral tegmental area (VTA) DBS in an animal model of mania induced by methamphetamine (m-amph). METHODS: Wistar rats were given 14 days of m-amph injections, and on the last day, animals were submitted to 20 min of VTA DBS in two different patterns: intermittent low-frequency stimulation (LFS) or continuous high-frequency stimulation (HFS). Immediately after DBS, manic-like behaviour and nucleus accumbens (NAc) phasic dopamine (DA) release were evaluated in different groups of animals through open-field tests and fast-scan cyclic voltammetry. Levels of NAc dopaminergic markers were evaluated by immunohistochemistry. RESULTS: M-amph induced hyperlocomotion in the animals and both DBS parameters reversed this alteration. M-amph increased DA reuptake time post-sham compared to baseline levels, and both LFS and HFS were able to block this alteration. LFS was also able to reduce phasic DA release when compared to baseline. LFS was able to increase dopamine transporter (DAT) expression in the NAc. CONCLUSION: These results demonstrate that both VTA LFS and HFS DBS exert anti-manic effects and modulation of DA dynamics in the NAc. More specifically the increase in DA reuptake driven by increased DAT expression may serve as a potential mechanism by which VTA DBS exerts its anti-manic effects.

Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.

With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques for measuring tonic extracellular concentrations of neurotransmitters, including voltammetry, enzyme-based sensors, amperometry, and in vivo microdialysis, there is currently no means to resolve concentrations of structurally similar neurotransmitters from mixtures in the in vivo environment with high spatiotemporal resolution and limited tissue damage. Since a variety of research and clinical investigations involve brain regions containing electrochemically similar monoamines, such as dopamine and norepinephrine, developing a model to resolve the respective contributions of these neurotransmitters is of vital importance. Here we have developed a deep learning network, DiscrimNet, a convolutional autoencoder capable of accurately predicting individual tonic concentrations of dopamine, norepinephrine, and serotonin from both in vitro mixtures and the in vivo environment in anesthetized rats, measured using voltammetry. The architecture of DiscrimNet is described, and its ability to accurately predict in vitro and unseen in vivo concentrations is shown to vastly outperform a variety of shallow learning algorithms previously used for neurotransmitter discrimination. DiscrimNet is shown to generalize well to data captured from electrodes unseen during model training, eliminating the need to retrain the model for each new electrode. DiscrimNet is also shown to accurately predict the expected changes in dopamine and serotonin after cocaine and oxycodone administration in anesthetized rats in vivo. DiscrimNet therefore offers an exciting new method for real-time resolution of in vivo voltammetric signals into component neurotransmitters.

An arteriovenous mock circulatory loop and accompanying bond graph model for in vitro study of peripheral intravascular bioartificial organs.

BACKGROUND: Silicon nanopore membrane-based implantable bioartificial organs are dependent on arteriovenous implantation of a mechanically robust and biocompatible hemofilter. The hemofilter acts as a low-resistance, high-flow network, with blood flow physiology similar to arteriovenous shunts commonly created for hemodialysis access. A mock circulatory loop (MCL) that mimics shunt physiology is an essential tool for refinement and durability testing of arteriovenous implantable bioartificial organs and silicon blood-interfacing membranes. We sought to develop a compact and cost-effective MCL to replicate flow conditions through an arteriovenous shunt and used data from the MCL and swine to inform a bond graph mathematical model of the physical setup. METHODS: Flow physiology through bioartificial organ prototypes was obtained in the MCL and during extracorporeal attachment to swine for biologic comparison. The MCL was tested for stability overtime by measuring pressurewave variability over a 48-h period. Data obtained in vitro and extracorporeally informed creation of a bond graph model of the MCL. RESULTS: The arteriovenous MCL was a cost-effective, portable system that reproduced flow rates and pressures consistent with a pulsatile arteriovenous shunt as measured in swine. MCL performance was stable over prolonged use, providing a cost-effective simulator for enhanced testing of peripherally implanted bioartificial organ prototypes. The corresponding bond graph model recapitulates MCL and animal physiology, offering a tool for further refinement of the MCL system.

Techniques for Measurement of Serotonin: Implications in Neuropsychiatric Disorders and Advances in Absolute Value Recording Methods.

Serotonin (5-HT) is a monoamine neurotransmitter in the peripheral, enteric, and central nervous systems (CNS). Within the CNS, serotonin is principally involved in mood regulation and reward-seeking behaviors. It is a critical regulator in CNS pathologies such as major depressive disorder, addiction, and schizophrenia. Consequently, in vivo serotonin measurements within the CNS have emerged as one of many promising approaches to investigating the pathogenesis, progression, and treatment of these and other neuropsychiatric conditions. These techniques vary in methods, ranging from analyte sampling with microdialysis to voltammetry. Provided this diversity in approach, inherent differences between techniques are inevitable. These include biosensor size, temporal/spatial resolution, and absolute value measurement capabilities, all of which must be considered to fit the prospective researcher's needs. In this review, we summarize currently available methods for the measurement of serotonin, including novel voltammetric absolute value measurement techniques. We also detail serotonin's role in various neuropsychiatric conditions, highlighting the role of phasic and tonic serotonergic neuronal firing within each where relevant. Lastly, we briefly review the present clinical application of these techniques and discuss the potential of a closed-loop monitoring and neuromodulation system utilizing deep brain stimulation (DBS).

Renal Embolization-Induced Uremic Swine Model for Assessment of Next-Generation Implantable Hemodialyzers.

Reliable models of renal failure in large animals are critical to the successful translation of the next generation of renal replacement therapies (RRT) into humans. While models exist for the induction of renal failure, none are optimized for the implantation of devices to the retroperitoneal vasculature. We successfully piloted an embolization-to-implantation protocol enabling the first implant of a silicon nanopore membrane hemodialyzer (SNMHD) in a swine renal failure model. Renal arterial embolization is a non-invasive approach to near-total nephrectomy that preserves retroperitoneal anatomy for device implants. Silicon nanopore membranes (SNM) are efficient blood-compatible membranes that enable novel approaches to RRT. Yucatan minipigs underwent staged bilateral renal arterial embolization to induce renal failure, managed by intermittent hemodialysis. A small-scale arteriovenous SNMHD prototype was implanted into the retroperitoneum. Dialysate catheters were tunneled externally for connection to a dialysate recirculation pump. SNMHD clearance was determined by intermittent sampling of recirculating dialysate. Creatinine and urea clearance through the SNMHD were 76-105 mL/min/m2 and 140-165 mL/min/m2, respectively, without albumin leakage. Normalized creatinine and urea clearance measured in the SNMHD may translate to a fully implantable clinical-scale device. This pilot study establishes a path toward therapeutic testing of the clinical-scale SNMHD and other implantable RRT devices.

Feasibility of an implantable bioreactor for renal cell therapy using silicon nanopore membranes.

The definitive treatment for end-stage renal disease is kidney transplantation, which remains limited by organ availability and post-transplant complications. Alternatively, an implantable bioartificial kidney could address both problems while enhancing the quality and length of patient life. An implantable bioartificial kidney requires a bioreactor containing renal cells to replicate key native cell functions, such as water and solute reabsorption, and metabolic and endocrinologic functions. Here, we report a proof-of-concept implantable bioreactor containing silicon nanopore membranes to offer a level of immunoprotection to human renal epithelial cells. After implantation into pigs without systemic anticoagulation or immunosuppression therapy for 7 days, we show that cells maintain >90% viability and functionality, with normal or elevated transporter gene expression and vitamin D activation. Despite implantation into a xenograft model, we find that cells exhibit minimal damage, and recipient cytokine levels are not suggestive of hyperacute rejection. These initial data confirm the potential feasibility of an implantable bioreactor for renal cell therapy utilizing silicon nanopore membranes.

Oxycodone-induced dopaminergic and respiratory effects are modulated by deep brain stimulation.

Introduction: Opioids are the leading cause of overdose death in the United States, accounting for almost 70,000 deaths in 2020. Deep brain stimulation (DBS) is a promising new treatment for substance use disorders. Here, we hypothesized that VTA DBS would modulate both the dopaminergic and respiratory effect of oxycodone. Methods: Multiple-cyclic square wave voltammetry (M-CSWV) was used to investigate how deep brain stimulation (130 Hz, 0.2 ms, and 0.2 mA) of the rodent ventral segmental area (VTA), which contains abundant dopaminergic neurons, modulates the acute effects of oxycodone administration (2.5 mg/kg, i.v.) on nucleus accumbens core (NAcc) tonic extracellular dopamine levels and respiratory rate in urethane-anesthetized rats (1.5 g/kg, i.p.). Results: I.V. administration of oxycodone resulted in an increase in NAcc tonic dopamine levels (296.9 ± 37.0 nM) compared to baseline (150.7 ± 15.5 nM) and saline administration (152.0 ± 16.1 nM) (296.9 ± 37.0 vs. 150.7 ± 15.5 vs. 152.0 ± 16.1, respectively, p = 0.022, n = 5). This robust oxycodone-induced increase in NAcc dopamine concentration was associated with a sharp reduction in respiratory rate (111.7 ± 2.6 min-1 vs. 67.9 ± 8.3 min-1; pre- vs. post-oxycodone; p < 0.001). Continuous DBS targeted at the VTA (n = 5) reduced baseline dopamine levels, attenuated the oxycodone-induced increase in dopamine levels to (+39.0% vs. +95%), and respiratory depression (121.5 ± 6.7 min-1 vs. 105.2 ± 4.1 min-1; pre- vs. post-oxycodone; p = 0.072). Discussion: Here we demonstrated VTA DBS alleviates oxycodone-induced increases in NAcc dopamine levels and reverses respiratory suppression. These results support the possibility of using neuromodulation technology for treatment of drug addiction.

Deep brain stimulation alleviates tics in Tourette syndrome via striatal dopamine transmission.

Tourette syndrome is a childhood-onset neuropsychiatric disorder characterized by intrusive motor and vocal tics that can lead to self-injury and deleterious mental health complications. While dysfunction in striatal dopamine neurotransmission has been proposed to underlie tic behaviour, evidence is scarce and inconclusive. Deep brain stimulation (DBS) of the thalamic centromedian parafascicular complex (CMPf), an approved surgical interventive treatment for medical refractory Tourette syndrome, may reduce tics by affecting striatal dopamine release. Here, we use electrophysiology, electrochemistry, optogenetics, pharmacological treatments and behavioural measurements to mechanistically examine how thalamic DBS modulates synaptic and tonic dopamine activity in the dorsomedial striatum. Previous studies demonstrated focal disruption of GABAergic transmission in the dorsolateral striatum of rats led to repetitive motor tics recapitulating the major symptom of Tourette syndrome. We employed this model under light anaesthesia and found CMPf DBS evoked synaptic dopamine release and elevated tonic dopamine levels via striatal cholinergic interneurons while concomitantly reducing motor tic behaviour. The improvement in tic behaviour was found to be mediated by D2 receptor activation as blocking this receptor prevented the therapeutic response. Our results demonstrate that release of striatal dopamine mediates the therapeutic effects of CMPf DBS and points to striatal dopamine dysfunction as a driver for motor tics in the pathoneurophysiology of Tourette syndrome.

Characterization of human islet function in a convection-driven intravascular bioartificial pancreas.

Clinical islet transplantation for treatment of type 1 diabetes (T1D) is limited by the shortage of pancreas donors and need for lifelong immunosuppressive therapy. A convection-driven intravascular bioartificial pancreas (iBAP) based on highly permeable, yet immunologically protective, silicon nanopore membranes (SNM) holds promise to sustain islet function without the need for immunosuppressants. Here, we investigate short-term functionality of encapsulated human islets in an iBAP prototype. Using the finite element method (FEM), we calculated predicted oxygen profiles within islet scaffolds at normalized perifusion rates of 14-200 nl/min/IEQ. The modeling showed the need for minimum in vitro and in vivo islet perifusion rates of 28 and 100 nl/min/IEQ, respectively to support metabolic insulin production requirements in the iBAP. In vitro glucose-stimulated insulin secretion (GSIS) profiles revealed a first-phase response time of <15 min and comparable insulin production rates to standard perifusion systems (~10 pg/min/IEQ) for perifusion rates of 100-200 nl/min/IEQ. An intravenous glucose tolerance test (IVGTT), performed at a perifusion rate of 100-170 nl/min/IEQ in a non-diabetic pig, demonstrated a clinically relevant C-peptide production rate (1.0-2.8 pg/min/IEQ) with a response time of <5 min.

High frequency deep brain stimulation can mitigate the acute effects of cocaine administration on tonic dopamine levels in the rat nucleus accumbens.

Cocaine's addictive properties stem from its capacity to increase tonic extracellular dopamine levels in the nucleus accumbens (NAc). The ventral tegmental area (VTA) is a principal source of NAc dopamine. To investigate how high frequency stimulation (HFS) of the rodent VTA or nucleus accumbens core (NAcc) modulates the acute effects of cocaine administration on NAcc tonic dopamine levels multiple-cyclic square wave voltammetry (M-CSWV) was used. VTA HFS alone decreased NAcc tonic dopamine levels by 42%. NAcc HFS alone resulted in an initial decrease in tonic dopamine levels followed by a return to baseline. VTA or NAcc HFS following cocaine administration prevented the cocaine-induced increase in NAcc tonic dopamine. The present results suggest a possible underlying mechanism of NAc deep brain stimulation (DBS) in the treatment of substance use disorders (SUDs) and the possibility of treating SUD by abolishing dopamine release elicited by cocaine and other drugs of abuse by DBS in VTA, although further studies with chronic addiction models are required to confirm that. Furthermore, we demonstrated the use of M-CSWV can reliably measure tonic dopamine levels in vivo with both drug administration and DBS with minimal artifacts.

Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo.

Tonic extracellular neurotransmitter concentrations are important modulators of central network homeostasis. Disruptions in these tonic levels are thought to play a role in neurologic and psychiatric disease. Therefore, ways to improve their quantification are actively being investigated. Previously published voltammetric software packages have implemented FSCV, which is not capable of measuring tonic concentrations of neurotransmitters in vivo. In this paper, custom software was developed for near-real-time tracking (scans every 10 s) of neurotransmitters' tonic concentrations with high sensitivity and spatiotemporal resolution both in vitro and in vivo using cyclic voltammetry combined with dynamic background subtraction (M-CSWV and FSCAV). This software was designed with flexibility, speed, and user-friendliness in mind. This software enables near-real-time measurement by reducing data analysis time through an optimized modeling algorithm, and efficient memory handling makes long-term measurement possible. The software permits customization of the cyclic voltammetric waveform shape, enabling experiments to detect a specific analyte of interest. Finally, flexibility considerations allow the user to alter the fitting parameters, filtering characteristics, and size and shape of the analyte kernel, based on data obtained live during the experiment to obtain accurate measurements as experimental conditions change. Herein, the design and advantages of this near-real-time voltammetric software are described, and its use is demonstrated in in vivo experiments.

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.

Deep Brain Stimulation for Addictive Disorders-Where Are We Now?

In the face of a global epidemic of drug addiction, neglecting to develop new effective therapies will perpetuate the staggering human and economic costs of substance use. This review aims to summarize and evaluate the preclinical and clinical studies of deep brain stimulation (DBS) as a novel therapy for refractory addiction, in hopes to engage and inform future research in this promising novel treatment avenue. An electronic database search (MEDLINE, EMBASE, Cochrane library) was performed using keywords and predefined inclusion criteria between 1974 and 6/18/2021 (registered on Open Science Registry). Selected articles were reviewed in full text and key details were summarized and analyzed to understand DBS' therapeutic potential and possible mechanisms of action. The search yielded 25 animal and 22 human studies. Animal studies showed that DBS of targets such as nucleus accumbens (NAc), insula, and subthalamic nucleus reduces drug use and seeking. All human studies were case series/reports (level 4/5 evidence), mostly targeting the NAc with generally positive outcomes. From the limited evidence in the literature, DBS, particularly of the NAc, appears to be a reasonable last resort option for refractory addictive disorders. We propose that future research in objective electrophysiological (e.g., local field potentials) and neurochemical (e.g., extracellular dopamine levels) biomarkers would assist monitoring the progress of treatment and developing a closed-loop DBS system. Preclinical literature also highlighted the prefrontal cortex as a promising DBS target, which should be explored in human research.

The development of ultra-high field MRI guidance technology for neuronavigation.

OBJECTIVE: Magnetic resonance imaging at 7T offers improved image spatial and contrast resolution for visualization of small brain nuclei targeted in neuromodulation. However, greater image geometric distortion and a lack of compatible instrumentation preclude implementation. In this report, the authors detail the development of a stereotactic image localizer and accompanying imaging sequences designed to mitigate geometric distortion, enabling accurate image registration and surgical planning of basal ganglia nuclei. METHODS: Magnetization-prepared rapid acquisition with gradient echo (MPRAGE), fast gray matter acquisition T1 inversion recovery (FGATIR), T2-weighted, and T2*-weighted sequences were optimized for 7T in 9 human subjects to visualize basal ganglia nuclei, minimize image distortion, and maximize target contrast-to-noise and signal-to-noise ratios. Extracranial spatial distortions were mapped to develop a skull-contoured image localizer embedded with spherical silicone fiducials for improved MR image registration and target guidance. Surgical plan accuracy testing was initially performed in a custom-developed MRI phantom (n = 5 phantom studies) and finally in a human trial. RESULTS: MPRAGE and T2*-weighted sequences had the best measures among global measures of image quality (3.8/4, p < 0.0001; and 3.7/4, p = 0.0002, respectively). Among basal ganglia nuclei, FGATIR outperformed MPRAGE for globus pallidus externus (GPe) visualization (2.67/4 vs 1.78/4, p = 0.008), and FGATIR, T2-weighted imaging, and T2*-weighted imaging outperformed MPRAGE for substantia nigra visualization (1.44/4 vs 2.56/4, p = 0.04; vs 2.56/4, p = 0.04; vs 2.67/4, p = 0.003). Extracranial distortion was lower in the head's midregion compared with the base and apex ( 1.17-1.33 mm; MPRAGE and FGATIR, p < 0.0001; T2-weighted imaging, p > 0.05; and T2*-weighted imaging, p = 0.013). Fiducial placement on the localizer in low distortion areas improved image registration (fiducial registration error, 0.79-1.19 mm; p < 0.0001) and targeting accuracy (target registration error, 0.60-1.09 mm; p = 0.04). Custom surgical software and the refined image localizer enabled successful surgical planning in a human trial (fiducial registration error = 1.0 mm). CONCLUSIONS: A skull-contoured image localizer that accounts for image distortion is necessary to enable high-accuracy 7T imaging-guided targeting for surgical neuromodulation. These results may enable improved clinical efficacy for the treatment of neurological disease.

Biomarkers for Deep Brain Stimulation in Animal Models of Depression.

OBJECTIVES: Despite recent advances in depression treatment, many patients still do not respond to serial conventional therapies and are considered "treatment resistant." Deep brain stimulation (DBS) has therapeutic potential in this context. This comprehensive review of recent studies of DBS for depression in animal models identifies potential biomarkers for improving therapeutic efficacy and predictability of conventional DBS to aid future development of closed-loop control of DBS systems. MATERIALS AND METHODS: A systematic search was performed in Pubmed, EMBASE, and Cochrane Review using relevant keywords. Overall, 56 animal studies satisfied the inclusion criteria. RESULTS: Outcomes were divided into biochemical/physiological, electrophysiological, and behavioral categories. Promising biomarkers include biochemical assays (in particular, microdialysis and electrochemical measurements), which provide real-time results in awake animals. Electrophysiological tests, showing changes at both the target site and downstream structures, also revealed characteristic changes at several anatomic targets (such as the medial prefrontal cortex and locus coeruleus). However, the substantial range of models and DBS targets limits the ability to draw generalizable conclusions in animal behavioral models. CONCLUSIONS: Overall, DBS is a promising therapeutic modality for treatment-resistant depression. Different outcomes have been used to assess its efficacy in animal studies. From the review, electrophysiological and biochemical markers appear to offer the greatest potential as biomarkers for depression. However, to develop closed-loop DBS for depression, additional preclinical and clinical studies with a focus on identifying reliable, safe, and effective biomarkers are warranted.

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.

Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry.

Here, we present the development of a novel voltammetric technique, N-shaped multiple cyclic square wave voltammetry (N-MCSWV) and its application in vivo. It allows quantitative measurements of tonic extracellular levels of serotonin in vivo with mitigated fouling effects. N-MCSWV enriches the electrochemical information by generating high dimensional voltammograms, which enables high sensitivity and selectivity against 5-hydroindoleacetic acid (5-HIAA), dopamine, 3,4-dihydroxyphenylacetic acid (DOPAC), histamine, ascorbic acid, norepinephrine, adenosine, and pH. Using N-MCSWV, in combination with PEDOT:Nafion-coated carbon fiber microelectrodes, a tonic serotonin concentration of 52 ± 5.8 nM (n = 20 rats, ±SEM) was determined in the substantia nigra pars reticulata of urethane-anesthetized rats. Pharmacological challenges with dopaminergic, noradrenergic, and serotonergic synaptic reuptake inhibitors supported the ability of N-MCSWV to selectively detect tonic serotonin levels in vivo. Overall, N-MCSWV is a novel voltammetric technique for analytical quantification of serotonin. It offers continuous monitoring of changes in tonic serotonin concentrations in the brain to further our understanding of the role of serotonin in normal behaviors and psychiatric disorders.

Synthesis and Preliminary Biological Assessment of Carborane-Loaded Theranostic Nanoparticles to Target Prostate-Specific Membrane Antigen.

Boron neutron capture therapy (BNCT) is an encouraging therapeutic modality for cancer treatment. Prostate-specific membrane antigen (PSMA) is a cell membrane protein that is abundantly overexpressed in prostate cancer and can be targeted with radioligand therapies to stimulate clinical responses in patients. In principle, a spatially targeted neutron beam together with specifically targeted PSMA ligands could enable prostate cancer-targeted BNCT. Thus, we developed and tested PSMA-targeted poly(lactide-co-glycolide)-block-poly(ethylene glycol) (PLGA-b-PEG) nanoparticles (NPs) loaded with carborane and tethered to the radiometal chelator deferoxamine B (DFB) for simultaneous positron emission tomography (PET) imaging and selective delivery of boron to prostate cancer. Monomeric PLGA-b-PEGs were covalently functionalized with either DFB or the PSMA ligand ACUPA. Different nanoparticle formulations were generated by nanoemulsification of the corresponding unmodified and DFB- or ACUPA-modified monomers in varying percent fractions. The nanoparticles were efficiently labeled with 89Zr and were subjected to in vitro and in vivo evaluation. The optimized DFB(25)ACUPA(75) NPs exhibited strong in vitro binding to PSMA in direct binding and competition radioligand binding assays in PSMA(+) PC3-Pip cells. [89Zr]DFB(25) NPs and [89Zr]DFB(25)ACUPA(75) NPs were injected to mice with bilateral PSMA(-) PC3-Flu and PSMA(+) PC3-Pip dual xenografts. The NPs demonstrated twofold superior accumulation in PC3-Pip tumors to that of PC3-Flu tumors with a tumor/blood ratio of 25; however, no substantial effect of the ACUPA ligands was detected. Moreover, fast release of carborane from the NPs was observed, resulting in a low boron delivery to tumors in vivo. In summary, these data demonstrate the synthesis, characterization, and initial biological assessment of PSMA-targeted, carborane-loaded PLGA-b-PEG nanoparticles and establish the foundation for future efforts to enable their best use in vivo.

Feasibility of Applying Fourier Transform Electrochemical Impedance Spectroscopy in Fast Cyclic Square Wave Voltammetry for the In Vivo Measurement of Neurotransmitters.

We previously reported on the use of fast cyclic square wave voltammetry (FCSWV) as a new voltammetric technique. Fourier transform electrochemical impedance spectroscopy (FTEIS) has recently been utilized to provide information that enables a detailed analytical description of an electrified interface. In this study, we report on attempts to combine FTEIS with FCSWV (FTEIS-FCSWV) and demonstrate the feasibility of FTEIS-FCSWV in the in vivo detection of neurotransmitters, thus giving a new type of electrochemical impedance information such as biofouling on the electrode surface. From FTEIS-FCSWV, three new equivalent circuit element voltammograms, consisting of charge-transfer resistance (Rct), solution-resistance (Rs), and double-layer capacitance (Cdl) voltammograms were constructed and investigated in the phasic changes in dopamine (DA) concentrations. As a result, all Rct, Rs, and Cdl voltammograms showed different DA redox patterns and linear trends for the DA concentration (R2 > 0.99). Furthermore, the Rct voltammogram in FTEIS-FCSWV showed lower limit of detection (21.6 ± 15.8 nM) than FSCV (35.8 ± 17.4 nM). FTEIS-FCSWV also showed significantly lower prediction errors than FSCV in selectivity evaluations of unknown mixtures of catecholamines. Finally, Cdl from FTEIS-FCSWV showed a significant relationship with fouling effect on the electrode surface by showing decreased DA sensitivity in both flow injection analysis experiment (r = 0.986) and in vivo experiments. Overall, this study demonstrates the feasibility of FTEIS-FCSWV, which could offer a new type of neurochemical spectroscopic information concerning electrochemical monitoring of neurotransmitters in the brain, and the ability to estimate the degree of sensitivity loss caused by biofouling on the electrode surface.

Development and validation of a rapidly deployable CT-guided stereotactic system for external ventricular drainage: preclinical study.

External ventricular drainage (EVD) is an emergency neurosurgical procedure to decrease intracranial pressure through a catheter mediated drainage of cerebrospinal fluid. Most EVD catheters are placed using free hands without direct visualization of the target and catheter trajectory, leading to a high rate of complications- hemorrhage, brain injury and suboptimal catheter placement. Use of stereotactic systems can prevent these complications. However, they have found limited application for this procedure due to their long set-up time and expensive hardware. Therefore, we have developed and pre-clinically validated a novel 3D printed stereotactic system for rapid and accurate implantation of EVD catheters. Its mechanical and imaging accuracies were found to be at par with clinical stereotactic systems. Preclinical trial in human cadaver specimens revealed improved targeting accuracy achieved within an acceptable time frame compared to the free hand technique. CT angiography emulated using cadaver specimen with radio-opaque vascular contrast showed vessel free catheter trajectory. This could potentially translate to reduced hemorrhage rate. Thus, our 3D printed stereotactic system offers the potential to improve the accuracy and safety of EVD catheter placement for patients without significantly increasing the procedure time.