150 research outputs found

    International Veterinary Epilepsy Task Force consensus report on epilepsy definition, classification and terminology in companion animals

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    Dogs with epilepsy are among the commonest neurological patients in veterinary practice and therefore have historically attracted much attention with regard to definitions, clinical approach and management. A number of classification proposals for canine epilepsy have been published during the years reflecting always in parts the current proposals coming from the human epilepsy organisation the International League Against Epilepsy (ILAE). It has however not been possible to gain agreed consensus, “a common language”, for the classification and terminology used between veterinary and human neurologists and neuroscientists, practitioners, neuropharmacologists and neuropathologists. This has led to an unfortunate situation where different veterinary publications and textbook chapters on epilepsy merely reflect individual author preferences with respect to terminology, which can be confusing to the readers and influence the definition and diagnosis of epilepsy in first line practice and research studies. In this document the International Veterinary Epilepsy Task Force (IVETF) discusses current understanding of canine epilepsy and presents our 2015 proposal for terminology and classification of epilepsy and epileptic seizures. We propose a classification system which reflects new thoughts from the human ILAE but also roots in former well accepted terminology. We think that this classification system can be used by all stakeholders

    Implementation of Dynamical Nucleation Theory Effective Fragment Potentials Method for Modeling Aerosol Chemistry

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    In this work, the dynamical nucleation theory (DNT) model using the ab initio based effective fragment potential (EFP) is implemented for evaluating the evaporation rate constant and molecular properties of molecular clusters. Predicting the nucleation rates of aerosol particles in different chemical environments is a key step toward understanding the dynamics of complex aerosol chemistry. Therefore, molecular scale models of nanoclusters are required to understand the macroscopic nucleation process. On the basis of variational transition state theory, DNT provides an efficient approach to predict nucleation kinetics. While most DNT Monte Carlo simulations use analytic potentials to model critical sized clusters, or use ab initio potentials to model very small clusters, the DNTEFP Monte Carlo method presented here can treat up to critical sized clusters using the effective fragment potential (EFP), a rigorous nonempirical intermolecular model potential based on ab initio electronic structure theory calculations, improvable in a systematic manner. The DNTEFP method is applied to study the evaporation rates, energetics, and structure factors of multicomponent clusters containing water and isoprene. The most probable topology of the transition state characterizing the evaporation of one water molecule from a water hexamer at 243 K is predicted to be a conformer that contains six hydrogen bonds, with a topology that corresponds to two water molecules stacked on top of a quadrangular (H2O)4 cluster. For the water hexamer in the presence of isoprene, an increase in the cluster size and a 3-fold increase in the evaporation rate are predicted relative to the reaction in which one water molecule evaporates from a water hexamer cluster

    Rh-Based Mixed Alcohol Synthesis Catalysts: Characterization and Computational Report

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    The U.S. Department of Energy is conducting a program focused on developing a process for the conversion of biomass to bio-based fuels and co-products. Biomass-derived syngas is converted thermochemically within a temperature range of 240 to 330°C and at elevated pressure (e.g., 1200 psig) over a catalyst. Ethanol is the desired reaction product, although other side compounds are produced, including C3 to C5 alcohols; higher (i.e., greater than C1) oxygenates such as methyl acetate, ethyl acetate, acetic acid and acetaldehyde; and higher hydrocarbon gases such as methane, ethane/ethene, propane/propene, etc. Saturated hydrocarbon gases (especially methane) are undesirable because they represent a diminished yield of carbon to the desired ethanol product and represent compounds that must be steam reformed at high energy cost to reproduce CO and H2. Ethanol produced by the thermochemical reaction of syngas could be separated and blended directly with gasoline to produce a liquid transportation fuel. Additionally, higher oxygenates and unsaturated hydrocarbon side products such as olefins also could be further processed to liquid fuels. The goal of the current project is the development of a Rh-based catalyst with high activity and selectivity to C2+ oxygenates. This report chronicles an effort to characterize numerous supports and catalysts to identify particular traits that could be correlated with the most active and/or selective catalysts. Carbon and silica supports and catalysts were analyzed. Generally, analyses provided guidance in the selection of acceptable catalyst supports. For example, supports with high surface areas due to a high number of micropores were generally found to be poor at producing oxygenates, possibly because of mass transfer limitations of the products formed out of the micropores. To probe fundamental aspects of the complicated reaction network of CO with H2, a computational/ theoretical investigation using quantum mechanical and ab initio molecular dynamics calculations was initiated in 2009. Computational investigations were performed first to elucidate understanding of the nature of the catalytically active site. Thermodynamic calculations revealed that Mn likely exists as a metallic alloy with Rh in Rh-rich environments under reducing conditions at the temperatures of interest. After determining that reduced Rh-Mn alloy metal clusters were in a reduced state, the activation energy barriers of numerous transition state species on the catalytically active metal particles were calculated to compute the activation barriers of several reaction pathways that are possible on the catalyst surface. Comparison of calculations with a Rh nanoparticle versus a Rh-Mn nanoparticle revealed that the presence of Mn enabled the reaction pathway of CH with CO to form an adsorbed CHCO species, which was a precursor to C2+ oxygenates. The presence of Mn did not have a significant effect on the rate of CH4 production. Ir was observed during empirical catalyst screening experiments to improve the activity and selectivity of Rh-Mn catalysts. Thus, the addition of Ir to the Rh-Mn nanoparticles also was probed computationally. Simulations of Rh-Mn-Ir nanoparticles revealed that, with sufficient Ir concentrations, the Rh, Mn and Ir presumably would be well mixed within a nanoparticle. Activation barriers were calculated for Rh-Mn-Ir nanoparticles for several C-, H-, and O-containing transitional species on the nanoparticle surface. It was found that the presence of Ir opened yet another reactive pathway whereby HCO is formed and may undergo insertion with CHx surface moieties. The reaction pathway opened by the presence of Ir is in addition to the CO + CH pathway opened by the presence of Mn. Similar to Mn, the presence of Ir was not found to not affect the rate of CH4 production

    Hydrophobically Modified Sulfobetaine Copolymers with Tunable Aqueous UCST through Postpolymerization Modification of Poly(pentafluorophenyl acrylate)

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    Polysulfobetaines, polymers carrying highly polar zwitterionic side chains, present a promising research field by virtue of their antifouling properties, hemocompatibility, and stimulus-responsive behavior. However, limited synthetic approaches exist to produce sulfobetaine copolymers comprising hydrophobic components. Postpolymerization modification of an activated ester precursor, poly(pentafluorophenyl acrylate), employing a zwitterionic amine, 3-((3-aminopropyl)dimethylammonio)propane-1-sulfonate, ADPS, is presented as a novel, one-step synthetic concept toward sulfobetaine (co)polymers. Modifications were performed in homogeneous solution using propylene carbonate as solvent with mixtures of ADPS and pentylamine, benzylamine, and dodecylamine producing a series of well-defined statistical acrylamido sulfobetaine copolymers containing hydrophobic pentyl, benzyl, or dodecylacrylamide comonomers with well-controllable molar composition as evidenced by NMR and FT-IR spectroscopy and size exclusion chromatography.This synthetic strategy was exploited to investigate, for the first time, the influence of hydrophobic modification on the upper critical solution temperature (UCST) of sulfobetaine copolymers in aqueous solution. Surprisingly, incorporation of pentyl groups was found to increase solubility over a wide composition range, whereas benzyl groups decreased solubility—an effect attributed to different entropic and enthalpic contributions of both functional groups. While UCST transitions of polysulfobetaines are typically limited to higher molar mass samples, incorporation of 0–65 mol % of benzyl groups into copolymers with molar masses of 25.5–34.5 kg/mol enabled sharp, reversible transitions from 6 to 82 °C in solutions containing up to 76 mM NaCl, as observed by optical transmittance and dynamic light scattering. Both synthesis and systematic UCST increase of sulfobetaine copolymers presented here are expected to expand the scope and applicability of these smart materials

    The effects of Δ9-tetrahydrocannabinol on the dopamine system

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    Δ(9)-tetrahydrocannabinol (THC), the main psychoactive ingredient in cannabis, is a pressing concern to global mental health. Patterns of use are changing drastically due to legalisation, availability of synthetic analogues (‘spice’), cannavaping and aggrandizements in the purported therapeutic effects of cannabis. Many of THC’s reinforcing effects are mediated by the dopamine system. Due to complex cannabinoid-dopamine interactions there is conflicting evidence from human and animal research fields. Acute THC causes increased dopamine release and neuron activity, whilst long-term use is associated with blunting of the dopamine system. Future research must examine the long-term and developmental dopaminergic effects of the drug

    Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters

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    No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker

    The thalamus and its subnuclei—a gateway to obsessive-compulsive disorder

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    Larger thalamic volume has been found in children with obsessive-compulsive disorder (OCD) and children with clinical-level symptoms within the general population. Particular thalamic subregions may drive these differences. The ENIGMA-OCD working group conducted mega- and meta-analyses to study thalamic subregional volume in OCD across the lifespan. Structural T-1-weighted brain magnetic resonance imaging (MRI) scans from 2649 OCD patients and 2774 healthy controls across 29 sites (50 datasets) were processed using the FreeSurfer built-in ThalamicNuclei pipeline to extract five thalamic subregions. Volume measures were harmonized for site effects using ComBat before running separate multiple linear regression models for children, adolescents, and adults to estimate volumetric group differences. All analyses were pre-registered (https://osf.io/73dvy) and adjusted for age, sex and intracranial volume. Unmedicated pediatric OCD patients (<12 years) had larger lateral (d = 0.46), pulvinar (d = 0.33), ventral (d = 0.35) and whole thalamus (d = 0.40) volumes at unadjusted p-values <0.05. Adolescent patients showed no volumetric differences. Adult OCD patients compared with controls had smaller volumes across all subregions (anterior, lateral, pulvinar, medial, and ventral) and smaller whole thalamic volume (d = -0.15 to -0.07) after multiple comparisons correction, mostly driven by medicated patients and associated with symptom severity. The anterior thalamus was also significantly smaller in patients after adjusting for thalamus size. Our results suggest that OCD-related thalamic volume differences are global and not driven by particular subregions and that the direction of effects are driven by both age and medication status

    The neurobiological link between OCD and ADHD

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