644 research outputs found

    Ovarian and cervical cancer awareness: development of two validated measurement tools.

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    The aim of the study was to develop and validate measures of awareness of symptoms and risk factors for ovarian and cervical cancer (Ovarian and Cervical Cancer Awareness Measures)

    Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

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    Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Dynamical Boson Stars

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    The idea of stable, localized bundles of energy has strong appeal as a model for particles. In the 1950s John Wheeler envisioned such bundles as smooth configurations of electromagnetic energy that he called {\em geons}, but none were found. Instead, particle-like solutions were found in the late 1960s with the addition of a scalar field, and these were given the name {\em boson stars}. Since then, boson stars find use in a wide variety of models as sources of dark matter, as black hole mimickers, in simple models of binary systems, and as a tool in finding black holes in higher dimensions with only a single killing vector. We discuss important varieties of boson stars, their dynamic properties, and some of their uses, concentrating on recent efforts.Comment: 79 pages, 25 figures, invited review for Living Reviews in Relativity; major revision in 201

    Moving out of the shadows: accomplishing bisexual motherhood

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    Our qualitative study explored the ways in which bisexual mothers came to identify as such and how they structured their relationships and parenting within hetero-patriarchal society. The experiences of seven self-identified White bisexual women (aged from 28 to 56-years-old) from across England and the Republic of Ireland were investigated through semi-structured interviews. Participants’ children were aged 8 months to 28 years old at the time of their interviews. A thematic narrative analysis highlighted the following issues that participants had encountered in constructing their self-identity: prioritizing children; connecting and disconnecting with others and finessing self-definition; questioning societal relationship expectations. Nevertheless, participants varied considerably in how each of the themes identified were reflected in their lives, in particular depending upon each participant’s interpretation of her local social context. Both motherhood and self-identifying as bisexual gave a sense of meaning and purpose to participants’ life stories, although participants sometimes foregrounded their commitment to their children even at a personal cost to their bisexual identity. Using three different theoretical perspectives from feminist theory, queer theory and life course theory, the narratives analysed revealed ways in which bisexual motherhood not only had been influenced both intentionally and unintentionally by heteronormative expectations but also had directly and indirectly challenged these expectations

    The SAMI Galaxy Survey: Early Data Release

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    We present the Early Data Release of the Sydney–AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey. The SAMI Galaxy Survey is an ongoing integral field spectroscopic survey of _3400 low-redshift (z < 0:12) galaxies, covering galaxies in the field and in groups within the Galaxy And Mass Assembly (GAMA) survey regions, and a sample of galaxies in clusters. In the Early Data Release, we publicly release the fully calibrated datacubes for a representative selection of 107 galaxies drawn from the GAMA regions, along with information about these galaxies from the GAMA catalogues. All datacubes for the Early Data Release galaxies can be downloaded individually or as a set from the SAMI Galaxy Survey website. In this paper we also assess the quality of the pipeline used to reduce the SAMI data, giving metrics that quantify its performance at all stages in processing the raw data into calibrated datacubes. The pipeline gives excellent results throughout, with typical sky subtraction residuals in the continuum of 0.9–1.2 per cent, a relative flux calibration uncertainty of 4.1 per cent (systematic) plus 4.3 per cent (statistical), and atmospheric dispersion removed with an accuracy of 0:0009, less than a fifth of a spaxel

    The SAMI Galaxy Survey: Early Data Release

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    We present the Early Data Release of the Sydney–AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey. The SAMI Galaxy Survey is an ongoing integral field spectroscopic survey of _3400 low-redshift (z < 0:12) galaxies, covering galaxies in the field and in groups within the Galaxy And Mass Assembly (GAMA) survey regions, and a sample of galaxies in clusters. In the Early Data Release, we publicly release the fully calibrated datacubes for a representative selection of 107 galaxies drawn from the GAMA regions, along with information about these galaxies from the GAMA catalogues. All datacubes for the Early Data Release galaxies can be downloaded individually or as a set from the SAMI Galaxy Survey website. In this paper we also assess the quality of the pipeline used to reduce the SAMI data, giving metrics that quantify its performance at all stages in processing the raw data into calibrated datacubes. The pipeline gives excellent results throughout, with typical sky subtraction residuals in the continuum of 0.9–1.2 per cent, a relative flux calibration uncertainty of 4.1 per cent (systematic) plus 4.3 per cent (statistical), and atmospheric dispersion removed with an accuracy of 0:0009, less than a fifth of a spaxel

    Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers.

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    Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.This research uses resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Allergy and Infectious Diseases (NIAID), the National Human Genome Research Institute (NHGRI), the National Institute of Child Health and Human Development (NICHD) and JDRF and supported by grant U01 DK062418 from the US National Institutes of Health. Further support was provided by grants from the NIDDK (DK046635 and DK085678) to P.C. and by a joint JDRF and Wellcome Trust grant (WT061858/09115) to the Diabetes and Inflammation Laboratory at Cambridge University, which also received support from the NIHR Cambridge Biomedical Research Centre. ImmunoBase receives support from Eli Lilly and Company. C.W. and H.G. are funded by the Wellcome Trust (089989). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). We gratefully acknowledge the following groups and individuals who provided biological samples or data for this study. We obtained DNA samples from the British 1958 Birth Cohort collection, funded by the UK Medical Research Council and the Wellcome Trust. We acknowledge use of DNA samples from the NIHR Cambridge BioResource. We thank volunteers for their support and participation in the Cambridge BioResource and members of the Cambridge BioResource Scientific Advisory Board (SAB) and Management Committee for their support of our study. We acknowledge the NIHR Cambridge Biomedical Research Centre for funding. Access to Cambridge BioResource volunteers and to their data and samples are governed by the Cambridge BioResource SAB. Documents describing access arrangements and contact details are available at http://www.cambridgebioresource.org.uk/. We thank the Avon Longitudinal Study of Parents and Children laboratory in Bristol, UK, and the British 1958 Birth Cohort team, including S. Ring, R. Jones, M. Pembrey, W. McArdle, D. Strachan and P. Burton, for preparing and providing the control DNA samples. This study makes use of data generated by the Wellcome Trust Case Control Consortium, funded by Wellcome Trust award 076113; a full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk/.This is the author accepted manuscript. The final version is available via NPG at http://www.nature.com/ng/journal/v47/n4/full/ng.3245.html

    Enteric Pathogens in Stored Drinking Water and on Caregiver's Hands in Tanzanian Households with and without Reported Cases of Child Diarrhea.

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    Diarrhea is one of the leading causes of mortality in young children. Diarrheal pathogens are transmitted via the fecal-oral route, and for children the majority of this transmission is thought to occur within the home. However, very few studies have documented enteric pathogens within households of low-income countries. The presence of molecular markers for three enteric viruses (enterovirus, adenovirus, and rotavirus), seven Escherichia coli virulence genes (ECVG), and human-specific Bacteroidales was assessed in hand rinses and household stored drinking water in Bagamoyo, Tanzania. Using a matched case-control study design, we examined the relationship between contamination of hands and water with these markers and child diarrhea. We found that the presence of ECVG in household stored water was associated with a significant decrease in the odds of a child within the home having diarrhea (OR = 0.51; 95% confidence interval 0.27-0.93). We also evaluated water management and hygiene behaviors. Recent hand contact with water or food was positively associated with detection of enteric pathogen markers on hands, as was relatively lower volumes of water reportedly used for daily hand washing. Enteropathogen markers in stored drinking water were more likely found among households in which the markers were also detected on hands, as well as in households with unimproved water supply and sanitation infrastructure. The prevalence of enteric pathogen genes and the human-specific Bacteroidales fecal marker in stored water and on hands suggests extensive environmental contamination within homes both with and without reported child diarrhea. Better stored water quality among households with diarrhea indicates caregivers with sick children may be more likely to ensure safe drinking water in the home. Interventions to increase the quantity of water available for hand washing, and to improve food hygiene, may reduce exposure to enteric pathogens in the domestic environment
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