Isolation of δ-missulenatoxin-Mb1a, the major vertebrate-active spider δ-toxin from the venom of Missulena bradleyi (Actinopodidae)

The present study describes the isolation and pharmacological characterisation of the neurotoxin δ-missulenatoxin-Mb1a (δ-MSTX-Mb1a) from the venom of the male Australian eastern mouse spider, Missulena bradleyi. This toxin was isolated using reverse-phase high-performance liquid chromatography and was subsequently shown to cause an increase in resting tension, muscle fasciculation and a decrease in indirect twitch tension in a chick biventer cervicis nerve-muscle bioassay. Interestingly, these effects were neutralised by antivenom raised against the venom of the Sydney funnel-web spider Atrax robustus. Subsequent whole-cell patch-clamp electrophysiology on rat dorsal root ganglion neurones revealed that δ-MSTX-Mb1a caused a reduction in peak tetrodotoxin (TTX)-sensitive sodium current, a slowing of sodium current inactivation and a hyperpolarising shift in the voltage at half-maximal activation. In addition, δ-MSTX-Mb1a failed to affect TTX-resistant sodium currents. Subsequent Edman degradation revealed a 42-residue peptide with unusual N- and C-terminal cysteines and a cysteine triplet (Cys14-16). This toxin was highly homologous to a family of δ-atracotoxins (δ-ACTX) from Australian funnel-web spiders including conservation of all eight cysteine residues. In addition to actions on sodium channel gating and kinetics to δ-ACTX, δ-MSTX-Mb1a caused significant insect toxicity at doses up to 2000 pmol/g. δ-MSTX-Mb1a therefore provides evidence of a highly conserved spider δ-toxin from a phylogenetically distinct spider family that has not undergone significant modification. © 2003 Published by Elsevier B.V. on behalf of the Federation of European Biochemical Societies

Selective Modulation of α5 GABAA Receptors Exacerbates Aberrant Inhibition at Key Hippocampal Neuronal Circuits in APP Mouse Model of Alzheimer’s Disease

Selective negative allosteric modulators (NAMs), targeting α5 subunit-containing GABAA receptors (GABAARs) as potential therapeutic targets for disorders associated with cognitive deficits, including Alzheimer’s disease (AD), continually fail clinical trials. We investigated whether this was due to the change in the expression of α5 GABAARs, consequently altering synaptic function during AD pathogenesis. Using medicinal chemistry and computational modeling, we developed aqueous soluble hybrids of 6,6-dimethyl-3-(2-hydroxyethyl) thio-1-(thiazol-2-yl)-6,7-dihydro-2-benzothiophene-4(5H)-one, that demonstrated selective binding and high negative allosteric modulation, specifically for the α5 GABAAR subtypes in constructed HEK293 stable cell-lines. Using a knock-in mouse model of AD (APPNL−F/NL−F), which expresses a mutant form of human amyloid-β (Aβ), we performed immunofluorescence studies combined with electrophysiological whole-cell recordings to investigate the effects of our key molecule, α5-SOP002 in the hippocampal CA1 region. In aged APPNL−F/NL−F mice, selective preservation of α5 GABAARs was observed in, calretinin- (CR), cholecystokinin- (CCK), somatostatin- (SST) expressing interneurons, and pyramidal cells. Previously, we reported that CR dis-inhibitory interneurons, specialized in regulating other interneurons displayed abnormally high levels of synaptic inhibition in the APPNL−F/NL−F mouse model, here we show that this excessive inhibition was “normalized” to control values with bath-applied α5-SOP002 (1 μM). However, α5-SOP002, further impaired inhibition onto CCK and pyramidal cells that were already largely compromised by exhibiting a deficit of inhibition in the AD model. In summary, using a multi-disciplinary approach, we show that exposure to α5 GABAAR NAMs may further compromise aberrant synapses in AD. We, therefore, suggest that the α5 GABAAR is not a suitable therapeutic target for the treatment of AD or other cognitive deficits due to the widespread neuronal-networks that use α5 GABAARs

Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training

Stellar Coronal and Wind Models: Impact on Exoplanets

Surface magnetism is believed to be the main driver of coronal heating and stellar wind acceleration. Coronae are believed to be formed by plasma confined in closed magnetic coronal loops of the stars, with winds mainly originating in open magnetic field line regions. In this Chapter, we review some basic properties of stellar coronae and winds and present some existing models. In the last part of this Chapter, we discuss the effects of coronal winds on exoplanets.Comment: Chapter published in the "Handbook of Exoplanets", Editors in Chief: Juan Antonio Belmonte and Hans Deeg, Section Editor: Nuccio Lanza. Springer Reference Work

Outcome measurement in functional neurological disorder: a systematic review and recommendations.

OBJECTIVES: We aimed to identify existing outcome measures for functional neurological disorder (FND), to inform the development of recommendations and to guide future research on FND outcomes. METHODS: A systematic review was conducted to identify existing FND-specific outcome measures and the most common measurement domains and measures in previous treatment studies. Searches of Embase, MEDLINE and PsycINFO were conducted between January 1965 and June 2019. The findings were discussed during two international meetings of the FND-Core Outcome Measures group. RESULTS: Five FND-specific measures were identified-three clinician-rated and two patient-rated-but their measurement properties have not been rigorously evaluated. No single measure was identified for use across the range of FND symptoms in adults. Across randomised controlled trials (k=40) and observational treatment studies (k=40), outcome measures most often assessed core FND symptom change. Other domains measured commonly were additional physical and psychological symptoms, life impact (ie, quality of life, disability and general functioning) and health economics/cost-utility (eg, healthcare resource use and quality-adjusted life years). CONCLUSIONS: There are few well-validated FND-specific outcome measures. Thus, at present, we recommend that existing outcome measures, known to be reliable, valid and responsive in FND or closely related populations, are used to capture key outcome domains. Increased consistency in outcome measurement will facilitate comparison of treatment effects across FND symptom types and treatment modalities. Future work needs to more rigorously validate outcome measures used in this population

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines

Background: The outstanding performance of an elite athlete might be associated with changes in their blood metabolic profile. The aims of this study were to compare the blood metabolic profiles between moderate- and high-power and endurance elite athletes and to identify the potential metabolic pathways underlying these differences. Methods: Metabolic profiling of serum samples from 191 elite athletes from different sports disciplines (121 high- and 70 moderate-endurance athletes, including 44 high- and 144 moderate-power athletes), who participated in national or international sports events and tested negative for doping abuse at anti-doping laboratories, was performed using non-targeted metabolomics-based mass spectroscopy combined with ultrahigh-performance liquid chromatography. Multivariate analysis was conducted using orthogonal partial least squares discriminant analysis. Differences in metabolic levels between high- and moderate-power and endurance sports were assessed by univariate linear models. Results: Out of 743 analyzed metabolites, gamma-glutamyl amino acids were significantly reduced in both high-power and high-endurance athletes compared to moderate counterparts, indicating active glutathione cycle. High-endurance athletes exhibited significant increases in the levels of several sex hormone steroids involved in testosterone and progesterone synthesis, but decreases in diacylglycerols and ecosanoids. High-power athletes had increased levels of phospholipids and xanthine metabolites compared to moderate-power counterparts. Conclusions: This pilot data provides evidence that high-power and high-endurance athletes exhibit a distinct metabolic profile that reflects steroid biosynthesis, fatty acid metabolism, oxidative stress, and energy-related metabolites. Replication studies are warranted to confirm differences in the metabolic profiles associated with athletes’ elite performance in independent data sets, aiming ultimately for deeper understanding of the underlying biochemical processes that could be utilized as biomarkers with potential therapeutic implications

Skeletal muscle metabolomics and blood biochemistry analysis reveal metabolic changes associated with dietary amino acid supplementation in dairy calves

The effects of different amino acid (AA) supplementations of milk protein-based milk replacers in pre-ruminant calves from 3 days to 7 weeks of age were studied. Animals were divided into 4 groups: Ctrl) Control group fed with milk protein-based milk replacer without supplementation; GP) supplementation with 0.1% glycine and 0.3% proline; FY) supplementation with 0.2% phenylalanine and 0.2% tyrosine; MKT) supplementation with 0.62% lysine, 0.22% methionine and 0.61% threonine. For statistical analysis, t-test was used to compare AA-supplemented animals to the Ctrl group. At week 7, body weight and average daily gain (ADG) were measured and blood samples and skeletal muscle biopsies were taken. Blood biochemistry analytes related to energy metabolism were determined and it was shown that MKT group had higher serum creatinine and higher plasma concentration of three supplemented AAs as well as arginine compared with the Ctrl group. GP group had similar glycine/proline plasma concentration compared with the other groups while in FY group only plasma phenylalanine concentration was higher compared with Control. Although the AA supplementations in the GP and FY groups did not affect average daily gain and metabolic health profile from serum, the metabolome analysis from skeletal muscle biopsy revealed several differences between the GP-FY groups and the Ctrl-MKT groups, suggesting a metabolic adaptation especially in GP and FY groupsinfo:eu-repo/semantics/publishedVersio

NMR-based metabolic characterization of chicken tissues and biofluids: a model for avian research

Introduction Poultry is one of the most consumed meat in the world and its related industry is always looking for ways to improve animal welfare and productivity. It is therefore essential to understand the metabolic response of the chicken to new feed formulas, various supplements, infections and treatments. Objectives As a basis for future research investigating the impact of diet and infections on chicken’s metabolism, we established a high-resolution proton nuclear magnetic resonance (NMR)-based metabolic atlas of the healthy chicken (Gallus gallus). Methods Metabolic extractions were performed prior to 1H-NMR and 2D NMR spectra acquisition on twelve biological matrices: liver, kidney, spleen, plasma, egg yolk and white, colon, caecum, faecal water, ileum, pectoral muscle and brain of 6 chickens. Metabolic profiles were then exhaustively characterized. Results Nearly 80 metabolites were identified. A cross-comparison of these matrices was performed to determine metabolic variations between and within each section and highlighted that only eight core metabolites were systematically found in every matrice. Conclusion This work constitutes a database for future NMR-based metabolomic investigations in relation to avian production and health

A comparison of laboratory and in situ methods to determine soil thermal conductivity for energy foundations and other ground heat exchanger applications

Soil thermal conductivity is an important factor in the design of energy foundations and other ground heat exchanger systems. It can be determined by a field thermal response test, which is both costly and time consuming, but tests a large volume of soil. Alternatively, cheaper and quicker laboratory test methods may be applied to smaller soil samples. This paper investigates two different laboratory methods: the steady-state thermal cell and the transient needle probe. U100 soil samples were taken during the site investigation for a small diameter test pile, for which a thermal response test was later conducted. The thermal conductivities of the samples were measured using the two laboratory methods. The results from the thermal cell and needle probe were significantly different, with the thermal cell consistently giving higher values for thermal conductivity. The main difficulty with the thermal cell was determining the rate of heat flow, as the apparatus experiences significant heat losses. The needle probe was found to have fewer significant sources of error, but tests a smaller soil sample than the thermal cell. However, both laboratory methods gave much lower values of thermal conductivity compared to the in situ thermal response test. Possible reasons for these discrepancies are discussed, including sample size, orientation and disturbance