289 research outputs found

    Author Correction: Ecology, evolution and spillover of coronaviruses from bats.

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    In the past two decades, three coronaviruses with ancestral origins in bats have emerged and caused widespread outbreaks in humans, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the first SARS epidemic in 2002–2003, the appreciation of bats as key hosts of zoonotic coronaviruses has advanced rapidly. More than 4,000 coronavirus sequences from 14 bat families have been identified, yet the true diversity of bat coronaviruses is probably much greater. Given that bats are the likely evolutionary source for several human coronaviruses, including strains that cause mild upper respiratory tract disease, their role in historic and future pandemics requires ongoing investigation. We review and integrate information on bat–coronavirus interactions at the molecular, tissue, host and population levels. We identify critical gaps in knowledge of bat coronaviruses, which relate to spillover and pandemic risk, including the pathways to zoonotic spillover, the infection dynamics within bat reservoir hosts, the role of prior adaptation in intermediate hosts for zoonotic transmission and the viral genotypes or traits that predict zoonotic capacity and pandemic potential. Filling these knowledge gaps may help prevent the next pandemic

    Search for short baseline nu(e) disappearance with the T2K near detector

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    8 pages, 6 figures, submitted to PRD rapid communication8 pages, 6 figures, submitted to PRD rapid communicationWe thank the J-PARC staff for superb accelerator performance and the CERN NA61 collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC and CFI, Canada; Commissariat `a l’Energie Atomique and Centre National de la Recherche Scientifique–Institut National de Physique Nucle´aire et de Physique des Particules, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; Russian Science Foundation, RFBR and Ministry of Education and Science, Russia; MINECO and European Regional Development Fund, Spain; Swiss National Science Foundation and State Secretariat for Education, Research and Innovation, Switzerland; STFC, UK; and DOE, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK. In addition participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; DOE Early Career program, USA

    Measurements of neutrino oscillation in appearance and disappearance channels by the T2K experiment with 6.6 x 10(20) protons on target

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    111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee commentsWe thank the J-PARC staff for superb accelerator performance and the CERN NA61/SHINE Collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC, and CFI, Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; RSF, RFBR and MES, Russia; MINECO and ERDF funds, Spain; SNSF and SER, Switzerland; STFC, UK; and the U. S. Deparment of Energy, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK, and the Emerald High Performance Computing facility in the Centre for Innovation, UK. In addition, participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; and DOE Early Career program, USA

    Measurement of the electron neutrino charged-current interaction rate on water with the T2K ND280 pi(0) detector

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    10 pages, 6 figures, Submitted to PRDhttp://journals.aps.org/prd/abstract/10.1103/PhysRevD.91.112010© 2015 American Physical Society11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PR

    Schizosaccharomyces pombe Ofd2 Is a Nuclear 2-Oxoglutarate and Iron Dependent Dioxygenase Interacting with Histones

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    2-oxoglutarate (2OG) dependent dioxygenases are ubiquitous iron containing enzymes that couple substrate oxidation to the conversion of 2OG to succinate and carbon dioxide. They participate in a wide range of biological processes including collagen biosynthesis, fatty acid metabolism, hypoxic sensing and demethylation of nucleic acids and histones. Although substantial progress has been made in elucidating their function, the role of many 2OG dioxygenases remains enigmatic. Here we have studied the 2OG and iron (Fe(II)) dependent dioxygenase Ofd2 in Schizosaccharomyces pombe, a member of the AlkB subfamily of dioxygenases. We show that decarboxylation of 2OG by recombinant Ofd2 is dependent on Fe(II) and a histidine residue predicted to be involved in Fe(II) coordination. The decarboxylase activity of Ofd2 is stimulated by histones, and H2A has the strongest effect. Ofd2 interacts with all four core histones, however, only very weakly with H4. Our results define a new subclass of AlkB proteins interacting with histones, which also might comprise some of the human AlkB homologs with unknown function

    Effects of isoflavones (soy phyto-estrogens) on serum lipids: a meta-analysis of randomized controlled trials

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    OBJECTIVES: To determine the effects of isoflavones (soy phyto-estrogens) on serum total cholesterol (TC), low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL) and triglyceride (TG). METHODS: We searched electronic databases and included randomized trials with isoflavones interventions in the forms of tablets, isolated soy protein or soy diets. Review Manager 4.2 was used to calculate the pooled risk differences with fixed effects model. RESULTS: Seventeen studies (21 comparisons) with 853 subjects were included in this meta-analysis. Isoflavones tablets had insignificant effects on serum TC, 0.01 mmol/L (95% CI: -0.17 to 0.18, heterogeneity p = 1.0); LDL, 0.00 mmol/L (95% CI: -0.14 to 0.15, heterogeneity p = 0.9); HDL, 0.01 mmol/L (95% CI: -0.05 to 0.06, heterogeneity p = 1.0); and triglyceride, 0.03 mmol/L (95% CI: -0.06 to 0.12, heterogeneity p = 0.9). Isoflavones interventions in the forms of isolated soy protein (ISP), soy diets or soy protein capsule were heterogeneous to combine. CONCLUSIONS: Isoflavones tablets, isolated or mixtures with up to 150 mg per day, seemed to have no overall statistical and clinical benefits on serum lipids. Isoflavones interventions in the forms of soy proteins may need further investigations to resolve whether synergistic effects are necessary with other soy components

    Evaluating the Sensitivity of Mycobacterium tuberculosis to Biotin Deprivation Using Regulated Gene Expression

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    In the search for new drug targets, we evaluated the biotin synthetic pathway of Mycobacterium tuberculosis (Mtb) and constructed an Mtb mutant lacking the biotin biosynthetic enzyme 7,8-diaminopelargonic acid synthase, BioA. In biotin-free synthetic media, ΔbioA did not produce wild-type levels of biotinylated proteins, and therefore did not grow and lost viability. ΔbioA was also unable to establish infection in mice. Conditionally-regulated knockdown strains of Mtb similarly exhibited impaired bacterial growth and viability in vitro and in mice, irrespective of the timing of transcriptional silencing. Biochemical studies further showed that BioA activity has to be reduced by approximately 99% to prevent growth. These studies thus establish that de novo biotin synthesis is essential for Mtb to establish and maintain a chronic infection in a murine model of TB. Moreover, these studies provide an experimental strategy to systematically rank the in vivo value of potential drug targets in Mtb and other pathogens

    Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

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    Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. As of yet, radiomics remains intriguing, but not clinically validated. We aimed to test the feasibility of a non-custom-constructed platform for disseminating existing large, standardized databases across institutions for promoting radiomics studies. Hence, University of Texas MD Anderson Cancer Center organized two public radiomics challenges in head and neck radiation oncology domain. This was done in conjunction with MICCAI 2016 satellite symposium using Kaggle-in-Class, a machine-learning and predictive analytics platform. We drew on clinical data matched to radiomics data derived from diagnostic contrast-enhanced computed tomography (CECT) images in a dataset of 315 patients with oropharyngeal cancer. Contestants were tasked to develop models for (i) classifying patients according to their human papillomavirus status, or (ii) predicting local tumor recurrence, following radiotherapy. Data were split into training, and test sets. Seventeen teams from various professional domains participated in one or both of the challenges. This review paper was based on the contestants' feedback; provided by 8 contestants only (47%). Six contestants (75%) incorporated extracted radiomics features into their predictive model building, either alone (n = 5; 62.5%), as was the case with the winner of the “HPV” challenge, or in conjunction with matched clinical attributes (n = 2; 25%). Only 23% of contestants, notably, including the winner of the “local recurrence” challenge, built their model relying solely on clinical data. In addition to the value of the integration of machine learning into clinical decision-making, our experience sheds light on challenges in sharing and directing existing datasets toward clinical applications of radiomics, including hyper-dimensionality of the clinical/imaging data attributes. Our experience may help guide researchers to create a framework for sharing and reuse of already published data that we believe will ultimately accelerate the pace of clinical applications of radiomics; both in challenge or clinical settings
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