L'onanisme : dissertacion sur les maladies produites par la masturbation

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Exploring the Consistency and Value of Humour Style Profiles

Sian Jones - ORCID 0000-0002-2399-1017 https://orcid.org/0000-0002-2399-1017Establishing generalisable humour style profiles promises to have significant value for educational, clinical, and occupational application. However, previous research investigating such profiles has thus far presented inconsistent results. To determine the generalisability and value of humour style profiles, a large and geographically diverse examination of humour styles was conducted through a cross-sectional questionnaire methodology involving 863 participants from across three world regions. Findings identify inconsistencies in the humour style profiles across countries tested and the extant literature, possibly indicative of cultural differences in the behavioural expression of trait humour. Furthermore, when directly compared, humour types, rather than humour styles, consistently provide the greatest predictive value for friendship and well-being outcomes. As such, with respect to both consistency and value, capturing humour style profiles appears to represent a relatively reductionist approach to appreciating the nuances in the use and consequences of humour.https://doi.org/10.1080/23743603.2020.17562394pubpub

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Identification and Characterization of Antifungal Compounds Using a Saccharomyces cerevisiae Reporter Bioassay

New antifungal drugs are urgently needed due to the currently limited selection, the emergence of drug resistance, and the toxicity of several commonly used drugs. To identify drug leads, we screened small molecules using a Saccharomyces cerevisiae reporter bioassay in which S. cerevisiae heterologously expresses Hik1, a group III hybrid histidine kinase (HHK) from Magnaporthe grisea. Group III HHKs are integral in fungal cell physiology, and highly conserved throughout this kingdom; they are absent in mammals, making them an attractive drug target. Our screen identified compounds 13 and 33, which showed robust activity against numerous fungal genera including Candida spp., Cryptococcus spp. and molds such as Aspergillus fumigatus and Rhizopus oryzae. Drug-resistant Candida albicans from patients were also highly susceptible to compounds 13 and 33. While the compounds do not act directly on HHKs, microarray analysis showed that compound 13 induced transcripts associated with oxidative stress, and compound 33, transcripts linked with heavy metal stress. Both compounds were highly active against C. albicans biofilm, in vitro and in vivo, and exerted synergy with fluconazole, which was inactive alone. Thus, we identified potent, broad-spectrum antifungal drug leads from a small molecule screen using a high-throughput, S. cerevisiae reporter bioassay

Structure of the E6/E6AP/p53 complex required for HPV-mediated degradation of p53

The p53 pro-apoptotic tumor suppressor is mutated or functionally altered in most cancers. In epithelial tumors induced by “high-risk” mucosal Human Papillomaviruses (hrm-HPVs), including human cervical carcinoma and a growing number of head-and-neck cancers (1), p53 is degraded by the viral oncoprotein E6 (2). In this process, E6 binds to a short LxxLL consensus sequence within the cellular ubiquitin ligase E6AP (3). Subsequently, the E6/E6AP heterodimer recruits and degrades p53 (4). Neither E6 nor E6AP are separately able to recruit p53 (3,5), and the precise mode of assembly of E6, E6AP and p53 is unknown. Here, we solved the crystal structure of a ternary complex comprising full-length HPV16 E6, the LxxLL motif of E6AP and the core domain of p53. The LxxLL motif of E6AP renders the conformation of E6 competent for interaction with p53 by structuring a p53-binding cleft on E6. Mutagenesis of critical positions at the E6-p53 interface disrupts p53 degradation. The E6-binding site of p53 is distal from previously described DNA- and protein-binding surfaces of the core domain. This suggests that, in principle, E6 may avoid competition with cellular factors by targeting both free and bound p53 molecules. The E6/E6AP/p53 complex represents a prototype of viral hijacking of both the ubiquitin-mediated protein degradation pathway and the p53 tumor suppressor pathway. The present structure provides a framework for the design of inhibitory therapeutic strategies against HPV-mediated oncogenesis

The UniProt-GO Annotation database in 2011

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data se