Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

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

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

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

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

Anti-Apoptotic Machinery Protects the Necrotrophic Fungus Botrytis cinerea from Host-Induced Apoptotic-Like Cell Death during Plant Infection

Necrotrophic fungi are unable to occupy living plant cells. How such pathogens survive first contact with living host tissue and initiate infection is therefore unclear. Here, we show that the necrotrophic grey mold fungus Botrytis cinerea undergoes massive apoptotic-like programmed cell death (PCD) following germination on the host plant. Manipulation of an anti-apoptotic gene BcBIR1 modified fungal response to PCD-inducing conditions. As a consequence, strains with reduced sensitivity to PCD were hyper virulent, while strains in which PCD was over-stimulated showed reduced pathogenicity. Similarly, reduced levels of PCD in the fungus were recorded following infection of Arabidopsis mutants that show enhanced susceptibility to B. cinerea. When considered together, these results suggest that Botrytis PCD machinery is targeted by plant defense molecules, and that the fungal anti-apoptotic machinery is essential for overcoming this host-induced PCD and hence, for establishment of infection. As such, fungal PCD machinery represents a novel target for fungicides and antifungal drugs

Isoform-Specific Biased Agonism of Histamine H 3 Receptor Agonists s

ABSTRACT The human histamine H 3 receptor (hH 3 R) is subject to extensive gene splicing that gives rise to a large number of functional and nonfunctional isoforms. Despite the general acceptance that G protein-coupled receptors can adopt different ligand-induced conformations that give rise to biased signaling, this has not been studied for the H 3 R; further, it is unknown whether splice variants of the same receptor engender the same or differential biased signaling. Herein, we profiled the pharmacology of histamine receptor agonists at the two most abundant hH 3 R splice variants (hH 3 R 445 and hH 3 R 365 ) across seven signaling endpoints. Both isoforms engender biased signaling, notably for 4-[3-(benzyloxy)propyl]-1H-imidazole (proxyfan) [e.g., strong bias toward phosphorylation of glycogen synthase kinase 3b (GSK3b) via the full-length receptor] and its congener 3-(1H-imidazol-4-yl)propyl-(4-iodophenyl)-methyl ether (iodoproxyfan), which are strongly consistent with the former's designation as a "protean" agonist. The 80 amino acid IL3 deleted isoform hH 3 R 365 is more permissive in its signaling than hH 3 R 445 : 2-(1H-imidazol-5-yl)ethyl imidothiocarbamate (imetit), proxyfan, and iodoproxyfan were all markedly biased away from calcium signaling, and principal component analysis of the full data set revealed divergent profiles for all five agonists. However, most interesting was the identification of differential biased signaling between the two isoforms. Strikingly, hH 3 R 365 was completely unable to stimulate GSK3b phosphorylation, an endpoint robustly activated by the full-length receptor. To the best of our knowledge, this is the first quantitative example of differential biased signaling via isoforms of the same G proteincoupled receptor that are simultaneously expressed in vivo and gives rise to the possibility of selective pharmacological targeting of individual receptor splice variants

The Lick AGN Monitoring Project 2016 : velocity-resolved Hβ lags in luminous Seyfert galaxies

Funding: K.H. acknowledges support from STFC grant ST/R000824/1.We carried out spectroscopic monitoring of 21 low-redshift Seyfert 1 galaxies using the Kast double spectrograph on the 3 m Shane telescope at Lick Observatory from April 2016 to May 2017. Targetingactive galactic nuclei (AGN) with luminosities of λLλ(5100 Å) ≈ 1044 erg s−1 and predicted Hβ lags of∼ 20–30 days or black hole masses of 107–108.5 M⊙, our campaign probes luminosity-dependent trends in broad-line region (BLR) structure and dynamics as well as to improve calibrations for single-epoch estimates of quasar black hole masses. Here we present the first results from the campaign, including Hβ emission-line light curves, integrated Hβ lag times (8–30 days) measured against V -band continuum light curves, velocity-resolved reverberation lags, line widths of the broad Hβ components, and virial black hole mass estimates (107.1–108.1 M⊙). Our results add significantly to the number of existing velocity-resolved lag measurements and reveal a diversity of BLR gas kinematics at moderately high AGN luminosities. AGN continuum luminosity appears not to be correlated with the type of kinematics that its BLR gas may exhibit. Follow-up direct modeling of this dataset will elucidate the detailed kinematics and provide robust dynamical black hole masses for several objects in this sample.Publisher PDFPeer reviewe