The XMM Cluster Survey: Evidence for energy injection at high redshift from evolution of the X-ray luminosity-temperature relation

We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with spectroscopic redshifts drawn from the XMM Cluster Survey first data release (XCS-DR1). This is the first study spanning this redshift range using a single, large, homogeneous cluster sample. Using an orthogonal regression technique, we find no evidence for evolution in the slope or intrinsic scatter of the relation since z~1.5, finding both to be consistent with previous measurements at z~0.1. However, the normalisation is seen to evolve negatively with respect to the self-similar expectation: we find E(z)^{-1} L_X = 10^{44.67 +/- 0.09} (T/5)^{3.04 +/- 0.16} (1+z)^{-1.5 +/- 0.5}, which is within 2 sigma of the zero evolution case. We see milder, but still negative, evolution with respect to self-similar when using a bisector regression technique. We compare our results to numerical simulations, where we fit simulated cluster samples using the same methods used on the XCS data. Our data favour models in which the majority of the excess entropy required to explain the slope of the L_X-T relation is injected at high redshift. Simulations in which AGN feedback is implemented using prescriptions from current semi-analytic galaxy formation models predict positive evolution of the normalisation, and differ from our data at more than 5 sigma. This suggests that more efficient feedback at high redshift may be needed in these models.Comment: Accepted for publication in MNRAS; 12 pages, 6 figures; added references to match published versio

The XMM Cluster Survey: X-ray analysis methodology

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we describe the data processing methodology applied to the 5,776 XMM observations used to construct the current XCS source catalogue. A total of 3,675 > 4-sigma cluster candidates with > 50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg^2. Of these, 993 candidates are detected with > 300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of < 40 (< 10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMM images. These tests show that the simple isothermal beta-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically-confirmed clusters.Comment: MNRAS accepted, 45 pages, 38 figures. Our companion paper describing our optical analysis methodology and presenting a first set of confirmed clusters has now been submitted to MNRA

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

mTORC1 in the Paneth cell niche couples intestinal stem cell function to calorie intake

How adult tissue stem and niche cells respond to the nutritional state of an organism is not well understood. Here we find that Paneth cells, a key constituent of the mammalian intestinal stem-cell (ISC) niche, augment stem-cell function in response to calorie restriction. Calorie restriction acts by reducing mechanistic target of rapamycin complex 1 (mTORC1) signalling in Paneth cells, and the ISC-enhancing effects of calorie restriction can be mimicked by rapamycin. Calorie intake regulates mTORC1 in Paneth cells, but not ISCs, and forced activation of mTORC1 in Paneth cells during calorie restriction abolishes the ISC-augmenting effects of the niche. Finally, increased expression of bone stromal antigen 1 (Bst1) in Paneth cells—an ectoenzyme that produces the paracrine factor cyclic ADP ribose—mediates the effects of calorie restriction and rapamycin on ISC function. Our findings establish that mTORC1 non-cell-autonomously regulates stem-cell self-renewal, and highlight a significant role of the mammalian intestinal niche in coupling stem-cell function to organismal physiology.National Institutes of Health (U.S.) (CA103866)National Institutes of Health (U.S.) (CA129105)David H. Koch Institute for Integrative Cancer Research at MIT (Initiator Award)Ellison Medical FoundationNational Cancer Institute (U.S.) (NCI (T32CA09216) fellowship support)Academy of FinlandFoundations’ Postdoc PoolNational Institutes of Health (U.S.) (NIH (1F32AG032833-01A1))Jane Coffin Childs Memorial Fund for Medical Researc

Simple and Complex Metafluids and Metastructures with Sharp Spectral Features in a Broad Extinction Spectrum: Particle-Particle Interactions and Testing the Limits of the Beer-Lambert Law

Metallic nanocrystals (NCs) are useful instruments for light manipulation around the visible spectrum. As their plasmonic resonances depend heavily on the NC geometry, modern fabrication techniques afford a great degree of control over their optical responses. We take advantage of this fact to create optical filters in the visible-near IR. Our systems show an extinction spectrum that covers a wide range of wavelengths (UV to mid-IR), while featuring a narrow transparency band around a wavelength of choice. We achieve this by carefully selecting the geometries of a collection of NCs with narrow resonances that cover densely the spectrum from UV to mid-IR except for the frequencies targeted for transmission. This fundamental design can be executed in different kinds of systems, including a solution of colloidal metal NCs (metafluids), a structured planar metasurface or a combination of both. Along with the theory, we report experimental results, showing metasurface realizations of the system, and we discuss the strengths and weaknesses of these different approaches, paying particular attention to particle-particle interaction and to what extent it hinders the intended objective by shifting and modifying the profile of the planned resonances through the hybridization of their plasmonic modes. We have found that the Beer-Lambert law is very robust overall and is violated only upon aggregation or in configurations with nearly-touching NCs. This striking property favors the creation of metafluids with a narrow transparency window, which are investigated here.Comment: Includes Supplementary Information, totaling 32 pages and 8 figure

Preliminary Multiphysics Analyses of HFIR LEU Fuel Conversion using COMSOL

The research documented herein was performed by several individuals across multiple organizations. We have previously acknowledged our funding for the project, but another common thread among the authors of this document, and hence the research performed, is the analysis tool COMSOL. The research has been divided into categories to allow the COMSOL analysis to be performed independently to the extent possible. As will be seen herein, the research has progressed to the point where it is expected that next year (2011) a large fraction of the research will require collaboration of our efforts as we progress almost exclusively into three-dimensional (3D) analysis. To the extent possible, we have tried to segregate the development effort into two-dimensional (2D) analysis in order to arrive at techniques and methodology that can be extended to 3D models in a timely manner. The Research Reactors Division (RRD) of ORNL has contracted with the University of Tennessee, Knoxville (UTK) Mechanical, Aerospace and Biomedical Engineering Department (MABE) to perform a significant fraction of this research. This group has been chosen due to their expertise and long-term commitment in using COMSOL and also because the participating students are able to work onsite on a part-time basis due to the close proximity of UTK with the ORNL campus. The UTK research has been governed by a statement of work (SOW) which clearly defines the specific tasks reported herein on the perspective areas of research. Ph.D. student Isaac T. Bodey has focused on heat transfer, fluid flow, modeling, and meshing issues and has been aided by his major professor Dr. Rao V. Arimilli and is the primary contributor to Section 2 of this report. Ph.D student Franklin G. Curtis has been focusing exclusively on fluid-structure interaction (FSI) due to the mechanical forces acting on the plate caused by the flow and has also been aided by his major professor Dr. Kivanc Ekici and is the primary contributor to Section 4 of this report. The HFIR LEU conversion project has also obtained the services of Dr. Prashant K. Jain of the Reactor & Nuclear Systems Division (RNSD) of ORNL. Prashant has quickly adapted to the COMSOL tools and has been focusing on thermal-structure interaction (TSI) issues and development of alternative 3D model approaches that could yield faster-running solutions. Prashant is the primary contributor to Section 5 of the report. And finally, while incorporating findings from all members of the COMSOL team (i.e., the team) and contributing as the senior COMSOL leader and advocate, Dr. James D. Freels has focused on the 3D model development, cluster deployment, and has contributed primarily to Section 3 and overall integration of this report. The team has migrated to the current release of COMSOL at version 4.1 for all the work described in this report, except where stated otherwise. Just as in the performance of the research, each of the respective sections has been originally authored by the respective authors. Therefore, the reader will observe a contrast in writing style throughout this document