Training, Match and Non-Rugby Activities in Elite Male Youth Rugby Union Players in England

Rugby union is a late specialisation sport. As a consequence, youth players may still be engaged in other activities and sports throughout the year as they transition to rugby specialisation. Limited research exists quantifying rugby union training and matches as well as engagement in other activities and sports. Therefore, the aim of this study was to quantify and compare rugby union training, matches and other activities of elite youth U15 and U16 rugby union players at different stages of the season

The search for transient astrophysical neutrino emission with IceCube-DeepCore

We present the results of a search for astrophysical sources of brief transient neutrino emission using IceCube and DeepCore data acquired between 2012 May 15 and 2013 April 30. While the search methods employed in this analysis are similar to those used in previous IceCube point source searches, the data set being examined consists of a sample of predominantly sub-TeV muon-neutrinos from the Northern Sky (-5 degrees < delta < 90 degrees) obtained through a novel event selection method. This search represents a first attempt by IceCube to identify astrophysical neutrino sources in this relatively unexplored energy range. The reconstructed direction and time of arrival of neutrino events are used to search for any significant self-correlation in the data set. The data revealed no significant source of transient neutrino emission. This result has been used to construct limits at timescales ranging from roughly 1 s to 10 days for generic soft-spectra transients. We also present limits on a specific model of neutrino emission from soft jets in core-collapse supernovae

Pim1 promotes human prostate cancer cell tumorigenicity and c-MYC transcriptional activity

<p>Abstract</p> <p>Background</p> <p>The serine/threonine kinase PIM1 has been implicated as an oncogene in various human cancers including lymphomas, gastric, colorectal and prostate carcinomas. In mouse models, Pim1 is known to cooperate with c-Myc to promote tumorigenicity. However, there has been limited analysis of the tumorigenic potential of Pim1 overexpression in benign and malignant human prostate cancer cells <it>in vivo</it>.</p> <p>Methods</p> <p>We overexpressed Pim1 in three human prostate cell lines representing different disease stages including benign (RWPE1), androgen-dependent cancer (LNCaP) and androgen-independent cancer (DU145). We then analyzed <it>in vitro </it>and <it>in vivo </it>tumorigenicity as well as the effect of Pim1 overexpression on c-MYC transcriptional activity by reporter assays and gene expression profiling using an inducible MYC-ER system. To validate that Pim1 induces tumorigenicity and target gene expression by modulating c-MYC transcriptional activity, we inhibited c-MYC using a small molecule inhibitor (10058-F4) or RNA interference.</p> <p>Results</p> <p>Overexpression of Pim1 alone was not sufficient to convert the benign RWPE1 cell to malignancy although it enhanced their proliferation rates when grown as xenografts <it>in vivo</it>. However, Pim1 expression enhanced the <it>in vitro </it>and <it>in vivo </it>tumorigenic potentials of the human prostate cancer cell lines LNCaP and DU145. Reporter assays revealed increased c-MYC transcriptional activity in Pim1-expressing cells and mRNA expression profiling demonstrated that a large fraction of c-MYC target genes were also regulated by Pim1 expression. The c-MYC inhibitor 10058-F4 suppressed the tumorigenicity of Pim1-expressing prostate cancer cells. Interestingly, 10058-F4 treatment also led to a reduction of Pim1 protein but not mRNA. Knocking-down c-MYC using short hairpin RNA reversed the effects of Pim1 on Pim1/MYC target genes.</p> <p>Conclusion</p> <p>Our results suggest an <it>in vivo </it>role of Pim1 in promoting prostate tumorigenesis although it displayed distinct oncogenic activities depending on the disease stage of the cell line. Pim1 promotes tumorigenicity at least in part by enhancing c-MYC transcriptional activity. We also made the novel discovery that treatment of cells with the c-MYC inhibitor 10058-F4 leads to a reduction in Pim1 protein levels.</p

IceCube-Gen2: A Vision for the Future of Neutrino Astronomy in Antarctica

20 pages, 12 figures. Address correspondence to: E. Blaufuss, F. Halzen, C. Kopper (Changed to add one missing author, no other changes from initial version.)20 pages, 12 figures. Address correspondence to: E. Blaufuss, F. Halzen, C. Kopper (Changed to add one missing author, no other changes from initial version.)20 pages, 12 figures. Address correspondence to: E. Blaufuss, F. Halzen, C. Kopper (Changed to add one missing author, no other changes from initial version.)The recent observation by the IceCube neutrino observatory of an astrophysical flux of neutrinos represents the "first light" in the nascent field of neutrino astronomy. The observed diffuse neutrino flux seems to suggest a much larger level of hadronic activity in the non-thermal universe than previously thought and suggests a rich discovery potential for a larger neutrino observatory. This document presents a vision for an substantial expansion of the current IceCube detector, IceCube-Gen2, including the aim of instrumenting a $10\,\mathrm{km}^3$ volume of clear glacial ice at the South Pole to deliver substantial increases in the astrophysical neutrino sample for all flavors. A detector of this size would have a rich physics program with the goal to resolve the sources of these astrophysical neutrinos, discover GZK neutrinos, and be a leading observatory in future multi-messenger astronomy programs

The IceCube Neutrino Observatory - Contributions to ICRC 2017 Part VI: IceCube-Gen2, the Next Generation Neutrino Observatory

Papers on research & development towards IceCube-Gen2, the next generation neutrino observatory at South Pole, submitted to the 35th International Cosmic Ray Conference (ICRC 2017, Busan, South Korea) by the IceCube-Gen2 Collaboration

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL