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Register a new userGlassy Carbon Microelectrode Arrays Enable Voltage-Peak Separated Simultaneous Detection of Dopamine and Serotonin Using Fast Scan Cyclic Voltammetry
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Elisa Castagnola Dr.
Publication date
2020
fields
Biology
and research's language is
English
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Progress in real-time, simultaneous in vivo detection of multiple neurotransmitters will help accelerate advances in neuroscience research. The need for development of probes capable of stable electrochemical detection of rapid neurotransmitter fluctuations with high sensitivity and selectivity and sub-second temporal resolution has, therefore, become compelling. Additionally, a higher spatial resolution multi-channel capability is required to capture the complex neurotransmission dynamics across different brain regions. These research needs have inspired the introduction of glassy carbon (GC) microelectrode arrays on flexible polymer substrates through carbon MEMS (C-MEMS) microfabrication process followed by a novel pattern transfer technique. These implantable GC microelectrodes offer unique advantages in electrochemical detection of electroactive neurotransmitters through the presence of active carboxyl, carbonyl, and hydroxyl functional groups. In addition, they offer fast electron transfer kinetics, capacitive electrochemical behavior, and wide electrochemical window. Here, we combine the use of these GC microelectrodes with the fast scan cyclic voltammetry (FSCV) technique to optimize the co-detection of dopamine and serotonin in vitro and in vivo. We demonstrate that using optimized FSCV triangular waveform at scan rates lower than 700 V/s and holding and switching at potentials of 0.4 and 1V respectively, it is possible to discriminate voltage reduction and oxidation peaks of serotonin and dopamine, with serotonin contributing distinct multiple oxidation peaks. Taken together, our results present a compelling case for a carbon-based MEA platform rich with active functional groups that allows for repeatable and stable detection of electroactive multiple neurotransmitters at concentrations as low as 10 nM
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In this paper we present a new localization method SMS-LORETA (Simultaneous Multiple Sources- Low Resolution Brain Electromagnetic Tomography), capable to locate efficiently multiple simultaneous sources. The new method overcomes some of the drawbacks of sLORETA (standardized Low Resolution Brain Electromagnetic Tomography). The key idea of the new method is the iterative search for current dipoles, harnessing the low error single source localization performance of sLORETA. An evaluation of the new method by simulation has been enclosed.
We present a palette of brightly fluorescent genetically encoded voltage indicators (GEVIs) with excitation and emission peaks spanning the visible spectrum, sensitivities from 6 - 10% Delta F/F per 100 mV, and half-maximal response times from 1 - 7 ms. A fluorescent protein is fused to an Archaerhodopsin-derived voltage sensor. Voltage-induced shifts in the absorption spectrum of the rhodopsin lead to voltage-dependent nonradiative quenching of the appended fluorescent protein. Through a library screen, we identified linkers and fluorescent protein combinations which reported neuronal action potentials in cultured rat hippocampal neurons with a single-trial signal-to-noise ratio from 6.6 to 11.6 in a 1 kHz imaging bandwidth at modest illumination intensity. The freedom to choose a voltage indicator from an array of colors facilitates multicolor voltage imaging, as well as combination with other optical reporters and optogenetic actuators.
Detecting dopamine is of great biological importance because the molecule plays many roles in the human body. For instance, the lack of dopamine release is the cause of Parkinsons disease. Although many researchers have carried out experiments on dopamine detection using carbon nanotubes (CNTs), there are only a few theoretical studies on this topic. We study the adsorption properties of dopamine and its derivatives, L-DOPA and dopamine o-quinone, adsorbed on a semiconducting (10, 0) CNT, using density functional theory calculations. Our computational simulations reveal that localized states originating from dopamine o-quinone appear in the bandgap of the (10, 0) CNT, but those originating from dopamine and L-DOPA do not appear in the gap. Therefore, dopamine o-quinone is expected to be detectable using an external electric field but dopamine and L-DOPA should be difficult to detect.
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Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimers disease. While there are extensive studies on cerebrospinal fluids biomarkers (amyloid, tau), the spatial propagation pattern across brain is missing and their interactive mechanisms with neurodegeneration are still unclear. To this end, we aim to analyze the spatiotemporal associations between ATN biomarkers using large-scale neuroimaging data. We first investigate the temporal appearances of amyloid plaques, tau tangles, and neuronal loss by modeling the longitudinal transition trajectories. Second, we propose linear mixed-effects models to quantify the pathological interactions and propagation of ATN biomarkers at each brain region. Our analysis of the current data shows that there exists a temporal latency in the build-up of amyloid to the onset of tau pathology and neurodegeneration. The propagation pattern of amyloid can be characterized by its diffusion along the topological brain network. Our models provide sufficient evidence that the progression of pathological tau and neurodegeneration share a strong regional association, which is different from amyloid.
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