High resolution optical spectroscopy of an LBV-candidate inside the CygOB2 association

For the first time, we obtained the high-resolution (R=15000 and 60000) optical spectra for the extremely luminous star No.12, associated with the IR-source IRAS20308+4104, a member of the CygOB2 association. We have found about 200 spectral features in range 4552-7939AA, including the interstellar NaI, KI lines and numerous DIBs, which are the strongest absorption lines in the spectrum, along with the HeI, CII, and SiII lines. A two-dimensional spectral classification indicates that the spectral type is B5+/-0.5 Ia+. Our analysis of the Vr data shows the presence of a Vr gradient in the stellar atmosphere, caused by the infall of matter onto the star. The strong Halpha emission displays broad Thompson wings and time-variable core absorption, providing evidence that the stellar wind is inhomogeneous, and a slightly blue-shifted PCyg type absorption profile. We concluded that the wind is variable in time.Comment: 20 pages, 5 figures, 2 table

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Rethinking use-wear analysis and experimentation as applied to the study of past hominin tool use

In prehistoric human populations, technologies played a fundamental role in the acquisition of different resources and are represented in the main daily living activities, such as with bone, wooden, and stone-tipped spears for hunting, and chipped-stone tools for butchering. Considering that paleoanthropologists and archeologists are focused on the study of different processes involved in the evolution of human behavior, investigating how hominins acted in the past through the study of evidence on archeological artifacts is crucial. Thus, investigat ing tool use is of major importance for a comprehensive understanding of all processes that characterize human choices of raw materials, techniques, and tool types. Many functional assumptions of tool use have been based on tool design and morphology according to archeologists’ interpretations and ethnographic observations. Such assumptions are used as baselines when inferring human behavior and have driven an improvement in the methods and techniques employed in functional studies over the past few decades. Here, while arguing that use-wear analysis is a key discipline to assess past hominin tool use and to interpret the organization and variability of artifact types in the archeological record, we aim to review and discuss the current state-of-the-art methods, protocols, and their limitations. In doing so, our discussion focuses on three main topics: (1) the need for fundamental improvements by adopting established methods and techniques from similar research fields, (2) the need to implement and combine different levels of experimentation, and (3) the crucial need to establish standards and protocols in order to improve data quality, standard ization, repeatability, and reproducibility. By adopting this perspective, we believe that studies will increase the reliability and applicability of use-wear methods on tool function. The need for a holistic approach that combines not only use-wear traces but also tool technology, design, curation, durability, and efficiency is also debated and revised. Such a revision is a crucial step if archeologists want to build major inferences on human decision making behavior and biocultural evolution processes.info:eu-repo/semantics/publishedVersio

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