Chenggraham9370

COAS, CORS, MIXED and TFs all displayed significant down-regulated expression (q.value  1.5), but only modestly impacted PPARγ responses. GSEA analyses of the PGC1α transcriptome revealed that it significantly altered the AR-dependent transcriptome, and was enriched for epigenetic modifiers. PGC1α-dependent genes were overlapped with PGC1α-ChIP-Seq genes and significantly associated in TCGA with higher grade tumors and worse disease-free survival. These methods and data demonstrate an approach to identify cancer-driver coregulators in cancer, and that PGC1α expression is clinically significant yet underexplored coregulator in aggressive early stage PCa.We have derived an expression of the Dzyaloshinskii-Moriya interaction (DMI), where all the three components of the DMI vector can be calculated independently, for a general, non-collinear magnetic configuration. The formalism is implemented in a real space-linear muffin-tin orbital-atomic sphere approximation (RS-LMTO-ASA) method. We have chosen the Cr triangular trimer on Au(111) and Mn triangular trimers on Ag(111) and Au(111) surfaces as numerical examples. The results show that the DMI (module and direction) is drastically different between collinear and non-collinear states. Based on the relation between the spin and charge currents flowing in the system and their coupling to the non-collinear magnetic configuration of the triangular trimer, we demonstrate that the DMI interaction can be significant, even in the absence of spin-orbit coupling. This is shown to emanate from the non-collinear magnetic structure, that can induce significant spin and charge currents even with spin-orbit coupling is ignored.The Cannabis sativa plant contains more than 120 cannabinoids. With the exceptions of ∆9-tetrahydrocannabinol (∆9-THC) and cannabidiol (CBD), comparatively little is known about the pharmacology of the less-abundant plant-derived (phyto) cannabinoids. The best-studied transducers of cannabinoid-dependent effects are type 1 and type 2 cannabinoid receptors (CB1R, CB2R). Partial agonism of CB1R by ∆9-THC is known to bring about the 'high' associated with Cannabis use, as well as the pain-, appetite-, and anxiety-modulating effects that are potentially therapeutic. CB2R activation by certain cannabinoids has been associated with anti-inflammatory activities. We assessed the activity of 8 phytocannabinoids at human CB1R, and CB2R in Chinese hamster ovary (CHO) cells stably expressing these receptors and in C57BL/6 mice in an attempt to better understand their pharmacodynamics. Specifically, ∆9-THC, ∆9-tetrahydrocannabinolic acid (∆9-THCa), ∆9-tetrahydrocannabivarin (THCV), CBD, cannabidiolic acid (CBDa), cannabidivarin (CBDV), cannabigerol (CBG), and cannabichromene (CBC) were evaluated. Compounds were assessed for their affinity to receptors, ability to inhibit cAMP accumulation, βarrestin2 recruitment, receptor selectivity, and ligand bias in cell culture; and cataleptic, hypothermic, anti-nociceptive, hypolocomotive, and anxiolytic effects in mice. learn more Our data reveal partial agonist activity for many phytocannabinoids tested at CB1R and/or CB2R, as well as in vivo responses often associated with activation of CB1R. These data build on the growing body of literature showing cannabinoid receptor-dependent pharmacology for these less-abundant phytocannabinoids and are critical in understanding the complex and interactive pharmacology of Cannabis-derived molecules.The use of microorganisms that allows the recovery of critical high-tech elements such as gallium (Ga) and indium (In) has been considered an excellent eco-strategy. In this perspective, it is relevant to understand the strategies of Ga and In resistant strains to cope with these critical metals. This study aimed to explore the effect of these metals on two Ga/In resistant strains and to scrutinize the biological processes behind the oxidative stress in response to exposure to these critical metals. Two strains of Serratia fonticola, A3242 and B2A1Ga1, with high resistance to Ga and In, were submitted to metal stress and their protein profiles showed an overexpressed Superoxide Dismutase (SOD) in presence of In. Results of inhibitor-protein native gel incubations identified the overexpressed enzyme as a Fe-SOD. Both strains exhibited a huge increase of oxidative stress when exposed to indium, visible by an extreme high amount of reactive oxygen species (ROS) production. The toxicity induced by indium triggered biological mechanisms of stress control namely, the decrease in reduced glutathione/total glutathione levels and an increase in the SOD activity. The effect of gallium in cells was not so boisterous, visible only by the decrease of reduced glutathione levels. Analysis of the cellular metabolic viability revealed that each strain was affected differently by the critical metals, which could be related to the distinct metal uptakes. Strain A3242 accumulated more Ga and In in comparison to strain B2A1Ga1, and showed lower metabolic activity. Understanding the biological response of the two metal resistant strains of S. fonticola to stress induced by Ga and In will tackle the current gap of information related with bacteria-critical metals interactions.We propose a random forest classifier for identifying adequacy of liver MR images using handcrafted (HC) features and deep convolutional neural networks (CNNs), and analyze the relative role of these two components in relation to the training sample size. The HC features, specifically developed for this application, include Gaussian mixture models, Euler characteristic curves and texture analysis. Using HC features outperforms the CNN for smaller sample sizes and with increased interpretability. On the other hand, with enough training data, the combined classifier outperforms the models trained with HC features or CNN features alone. These results illustrate the added value of HC features with respect to CNNs, especially when insufficient data is available, as is often found in clinical studies.Carboranes are a class of carbon-boron molecular clusters with three-dimensional aromaticity, and inherent robustness. These endowments enable carboranes as valuable building blocks for applications ranging from functional materials to pharmaceuticals. Thus, the chemistry of carboranes has received tremendous research interest, and significant progress has been made in the past decades. However, many attempts to the synthesis of carboranes with more than 14 vertices had been unsuccessful since the report of a 14-vertex carborane in 2005. The question arises as to whether these long sought-after molecules exist. We describe in this article the synthesis and structural characterization of 15- and 16-vertex closo-carboranes as well as 16-vertex ruthenacarborane. Such a success relies on the introduction of silyl groups to both cage carbons, stabilizing the corresponding nido-carborane dianions and promoting the capitation reaction with HBBr2·SMe2. This work would shed some light on the preparation of carboranes with 17 vertices or more, and open the door for studying supercarborane chemistry.To function, biomolecules require sufficient specificity of interaction as well as stability to live in the cell while still being able to move. Thermodynamic stability of only a limited number of specific structures is important so as to prevent promiscuous interactions. link2 The individual interactions in proteins, therefore, have evolved collectively to give funneled minimally frustrated landscapes but some strategic parts of biomolecular sequences located at specific sites in the structure have been selected to be frustrated in order to allow both motion and interaction with partners. We describe a framework efficiently to quantify and localize biomolecular frustration at atomic resolution by examining the statistics of the energy changes that occur when the local environment of a site is changed. The location of patches of highly frustrated interactions correlates with key biological locations needed for physiological function. At atomic resolution, it becomes possible to extend frustration analysis to protein-ligand complexes. At this resolution one sees that drug specificity is correlated with there being a minimally frustrated binding pocket leading to a funneled binding landscape. Atomistic frustration analysis provides a route for screening for more specific compounds for drug discovery.Continuous cropping lowers the production and quality of ramie (Boehmeria nivea L. Gaud). This study aimed to reveal the metagenomic and metabolomic changes between the healthy- and obstacle-plant after a long period of continuous cropping. After 10 years of continuous cropping, ramie planted in some portions of the land exhibited weak growth and low yield (Obstacle-group), whereas, ramie planted in the other portion of the land grew healthy (Health-group). We collected rhizosphere soil and root samples from which measurements of soil chemical and plant physiochemical properties were taken. All samples were subjected to non-targeted gas chromatograph-mass spectrometer (GS/MS) metabolome analysis. Further, metagenomics was performed to analyze the functional genes in rhizospheric soil organisms. Based on the findings, ramie in Obstacle-group were characterized by shorter plant height, smaller stem diameter, and lower fiber production than that in Health-group. Besides, the Obstacle-group showed a lower relative abundance of Rhizobiaceae, Lysobacter antibioticus, and Bradyrhizobium japonicum, but a higher relative abundance of Azospirillum lipoferum and A. brasilense compared to the Health-group. Metabolomic analysis results implicated cysteinylglycine (Cys-Gly), uracil, malonate, and glycerol as the key differential metabolites between the Health- and Obstacle-group. Notably, this work revealed that bacteria such as Rhizobia potentially synthesize IAA and are likely to reduce the biotic stress of ramie. L. antibioticus also exerts a positive effect on plants in the fight against biotic stress and is mediated by metabolites including orthophosphate, uracil, and Cys-Gly, which may serve as markers for disease risk. These bacterial effects can play a key role in plant resistance to biotic stress via metabolic and methionine metabolism pathways.Copy-number variants (CNVs) are an important part of human genetic variation. They can be benign or can play a role in human disease by creating dosage imbalances and disrupting genes and regulatory elements. Accurate identification and clinical annotation of CNVs is essential, however, manual evaluation of individual CNVs by clinicians is challenging on a large scale. Here, we present ClassifyCNV, an easy-to-use tool that implements the 2019 ACMG classification guidelines to assess CNV pathogenicity. ClassifyCNV uses genomic coordinates and CNV type as input and reports a clinical classification for each variant, a classification score breakdown, and a list of genes of potential importance for variant interpretation. link3 We validate ClassifyCNV's performance using a set of known clinical CNVs and a set of manually evaluated variants. ClassifyCNV matches the pathogenicity category for 81% of manually evaluated variants with the significance of the remaining pathogenic and benign variants automatically determined as uncertain, requiring a further evaluation by a clinician.