Reinforcing and neurochemical effects of the "bath salts" constituents 3,4-methylenedioxypyrovalerone (MDPV) and 3,4-methylenedioxy-N-methylcathinone (methylone) in male rats.

RATIONALE: 3,4-Methylenedioxypyrovalerone (MDPV) and 3,4-methylenedioxy-N-methylcathinone (methylone) are synthetic drugs found in so-called "bath salts" products. Both drugs exert their effects by interacting with monoamine transporter proteins. MDPV is a potent uptake blocker at transporters for dopamine and norepinephrine while methylone is a non-selective releaser at transporters for dopamine, norepinephrine, and serotonin (5-HT). OBJECTIVES: We hypothesized that prominent 5-HT-releasing actions of methylone would render this drug less reinforcing than MDPV. METHODS: To test this hypothesis, we compared behavioral effects of MDPV and methylone using intravenous (i.v.) self-administration on a fixed-ratio 1 schedule in male rats. Additionally, neurochemical effects of the drugs were examined using in vivo microdialysis in nucleus accumbens, in a separate cohort of rats. RESULTS: MDPV self-administration (0.03 mg/kg/inj) was acquired rapidly and reached 40 infusions per session, similar to the effects of cocaine (0.5 mg/kg/inj), by the end of training. In contrast, methylone self-administration (0.3 and 0.5 mg/kg/inj) was acquired slowly, and response rates only reached 20 infusions per session by the end of training. In dose substitution studies, MDPV and cocaine displayed typical inverted U-shaped dose-effect functions, but methylone did not. In vivo microdialysis revealed that i.v. MDPV (0.1 and 0.3 mg/kg) increased extracellular dopamine while i.v. methylone (1 and 3 mg/kg) increased extracellular dopamine and 5-HT. CONCLUSIONS: Our findings support the hypothesis that elevations in extracellular 5-HT in the brain can dampen positive reinforcing effects of cathinone-type drugs. Nevertheless, MDPV and methylone are both self-administered by rats, suggesting these drugs possess significant abuse liability in humans

Pollutant dispersion in a developing valley cold-air pool

Pollutants are trapped and accumulate within cold-air pools, thereby affecting air quality. A numerical model is used to quantify the role of cold-air-pooling processes in the dispersion of air pollution in a developing cold-air pool within an alpine valley under decoupled stable conditions. Results indicate that the negatively buoyant downslope flows transport and mix pollutants into the valley to depths that depend on the temperature deficit of the flow and the ambient temperature structure inside the valley. Along the slopes, pollutants are generally entrained above the cold-air pool and detrained within the cold-air pool, largely above the ground-based inversion layer. The ability of the cold-air pool to dilute pollutants is quantified. The analysis shows that the downslope flows fill the valley with air from above, which is then largely trapped within the cold-air pool, and that dilution depends on where the pollutants are emitted with respect to the positions of the top of the ground-based inversion layer and cold-air pool, and on the slope wind speeds. Over the lower part of the slopes, the cold-air-pool-averaged concentrations are proportional to the slope wind speeds where the pollutants are emitted, and diminish as the cold-air pool deepens. Pollutants emitted within the ground-based inversion layer are largely trapped there. Pollutants emitted farther up the slopes detrain within the cold-air pool above the ground-based inversion layer, although some fraction, increasing with distance from the top of the slopes, penetrates into the ground-based inversion layer.Peer reviewe

Sebomic identification of sex- and ethnicity-specific variations in residual skin surface components (RSSC) for bio-monitoring or forensic applications

Background: “Residual skin surface components” (RSSC) is the collective term used for the superficial layer of sebum, residue of sweat, small quantities of intercellular lipids and components of natural moisturising factor present on the skin surface. Potential applications of RSSC include use as a sampling matrix for identifying biomarkers of disease, environmental exposure monitoring, and forensics (retrospective identification of exposure to toxic chemicals). However, it is essential to first define the composition of “normal” RSSC. Therefore, the aim of the current study was to characterise RSSC to determine commonalities and differences in RSSC composition in relation to sex and ethnicity. Methods: Samples of RSSC were acquired from volunteers using a previously validated method and analysed by high-pressure liquid chromatography–atmospheric pressure chemical ionisation–mass spectrometry (HPLC-APCI-MS). The resulting data underwent sebomic analysis. Results: The composition and abundance of RSSC components varied according to sex and ethnicity. The normalised abundance of free fatty acids, wax esters, diglycerides and triglycerides was significantly higher in males than females. Ethnicity-specific differences were observed in free fatty acids and a diglyceride. Conclusions: The HPLC-APCI-MS method developed in this study was successfully used to analyse the normal composition of RSSC. Compositional differences in the RSSC can be attributed to sex and ethnicity and may reflect underlying factors such as diet, hormonal levels and enzyme expression.Peer reviewedFinal Published versio

HIPPIE: Integrating Protein Interaction Networks with Experiment Based Quality Scores

Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level

Vegetation forcing modulates global land monsoon and water resources in a CO2-enriched climate

The global monsoon is characterised by transitions between pronounced dry and wet seasons, affecting food security for two-thirds of the world’s population. Rising atmospheric CO2 influences the terrestrial hydrological cycle through climate-radiative and vegetation-physiological forcings. How these two forcings affect the seasonal intensity and characteristics of monsoonal precipitation and runoff is poorly understood. Here we use four Earth System Models to show that in a CO2-enriched climate, radiative forcing changes drive annual precipitation increases for most monsoon regions. Further, vegetation feedbacks substantially affect annual precipitation in North and South America and Australia monsoon regions. In the dry season, runoff increases over most monsoon regions, due to stomatal closure-driven evapotranspiration reductions and associated atmospheric circulation change. Our results imply that flood risks may amplify in the wet season. However, the lengthening of the monsoon rainfall season and reduced evapotranspiration will shorten the water resources scarcity period for most monsoon regions

Attribution of the Australian bushfire risk to anthropogenic climate change

Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires

CCL28 Induces Mucosal Homing of HIV-1-Specific IgA-Secreting Plasma Cells in Mice Immunized with HIV-1 Virus-Like Particles

Mucosae-associated epithelial chemokine (MEC or CCL28) binds to CCR3 and CCR10 and recruits IgA-secreting plasma cells (IgA-ASCs) in the mucosal lamina propria. The ability of this chemokine to enhance migration of IgA-ASCs to mucosal sites was assessed in a mouse immunization model using HIV-1IIIB Virus-like particles (VLPs). Mice receiving either HIV-1IIIB VLPs alone, CCL28 alone, or the irrelevant CCL19 chemokine were used as controls. Results showed a significantly increased CCR3 and CCR10 expression on CD19+ splenocytes of HIV-1IIIB VPL-CCL28-treated mice. HIV-1 Env-specific IFN-γ, IL-4 and IL-5 production, total IgA, anti-Env IgA as well as gastro-intestinal mucosal IgA-secreting plasma cells were also significantly augmented in these mice. Notably, sera and vaginal secretions from HIV-1IIIB VLP-CCL28-treated mice exhibited an enhanced neutralizing activity against both a HIV-1/B-subtype laboratory strain and a heterologous HIV-1/C-subtype primary isolate. These data suggest that CCL28 could be useful in enhancing the IgA immune response that will likely play a pivotal role in prophylactic HIV vaccines

Microstructural evolution and trace element mobility in Witwatersrand pyrite

Microstructural analysis of pyrite from a single sample of Witwatersrand conglomerate indicates a complex deformation history involving components of both plastic and brittle deformation. Internal deformation associated with dislocation creep is heterogeneously developed within grains, shows no systematic relationship to bulk rock strain or the location of grain boundaries and is interpreted to represent an episode of pyrite deformation that predates the incorporation of detrital pyrite grains into the Central Rand conglomerates. In contrast, brittle deformation, manifest by grain fragmentation that transects dislocation-related microstructures, is spatially related to grain contacts and is interpreted to represent post-depositional deformation of the Central Rand conglomerates. Analysis of the low-angle boundaries associated with the early dislocation creep phase of deformation indicates the operation of {100} slip systems. However, some orientation boundaries have geometrical characteristics that are not consistent with simple {100} deformation.These boundaries may represent the combination of multiple slip systems or the operation of the previously unrecognized {120} slip system. These boundaries are associated with order of magnitude enrichments in As, Ni and Co that indicate a deformation control on the remobilization of trace elements within pyrite and a potential slip system control on the effectiveness of fast-diffusion pathways. The results confirm the importance of grain-scale elemental remobilization within pyrite prior to their incorporation into the Witwatersrand gold-bearing conglomerates. Since the relationship between gold and pyrite is intimately related to the trace element geochemistry of pyrite, the results have implications for the application of minor element geochemistry to ore deposit formation, suggest a reason for heterogeneous conductivity and localized gold precipitation in natural pyrite and provide a framework for improving mineral processing

Bio::Homology::InterologWalk - A Perl module to build putative protein-protein interaction networks through interolog mapping

<p>Abstract</p> <p>Background</p> <p>Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction.</p> <p>Results</p> <p>We introduce <monospace>Bio::Homology::InterologWalk</monospace>, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, <it>Drosophila melanogaster</it>. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation.</p> <p>Conclusions</p> <p>Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the putative PPI datasets to be easily integrated into existing analysis workflows. The <monospace>Bio::Homology::InterologWalk</monospace> module, sample scripts and full documentation are freely available from the Comprehensive Perl Archive Network (CPAN) under the GNU Public license.</p

A Genomewide Functional Network for the Laboratory Mouse

Establishing a functional network is invaluable to our understanding of gene function, pathways, and systems-level properties of an organism and can be a powerful resource in directing targeted experiments. In this study, we present a functional network for the laboratory mouse based on a Bayesian integration of diverse genetic and functional genomic data. The resulting network includes probabilistic functional linkages among 20,581 protein-coding genes. We show that this network can accurately predict novel functional assignments and network components and present experimental evidence for predictions related to Nanog homeobox (Nanog), a critical gene in mouse embryonic stem cell pluripotency. An analysis of the global topology of the mouse functional network reveals multiple biologically relevant systems-level features of the mouse proteome. Specifically, we identify the clustering coefficient as a critical characteristic of central modulators that affect diverse pathways as well as genes associated with different phenotype traits and diseases. In addition, a cross-species comparison of functional interactomes on a genomic scale revealed distinct functional characteristics of conserved neighborhoods as compared to subnetworks specific to higher organisms. Thus, our global functional network for the laboratory mouse provides the community with a key resource for discovering protein functions and novel pathway components as well as a tool for exploring systems-level topological and evolutionary features of cellular interactomes. To facilitate exploration of this network by the biomedical research community, we illustrate its application in function and disease gene discovery through an interactive, Web-based, publicly available interface at http://mouseNET.princeton.edu