132 research outputs found

    Publishing and sharing multi-dimensional image data with OMERO

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    Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org

    Evidence to support IL-13 as a risk locus for psoriatic arthritis but not psoriasis vulgaris

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    Objective: There is great interest in the identification of genetic factors that differentiate psoriatic arthritis (PsA) from psoriasis vulgaris (PsV), as such discoveries could lead to the identification of distinct underlying aetiological pathways. Recent studies identified single nucleotide polymorphisms (SNPs) in the interleukin 13 (IL-13) gene region as risk factors for PsV. Further investigations in one of these studies found the effect to be primarily restricted to PsA, thus suggesting the discovery of a specific genetic risk factor for PsA. Given this intriguing evidence, association to this gene was investigated in large collections of PsA and PsV patients and healthy controls. Methods: Two SNPs (rs20541 and rs1800925) mapping to the IL-13 gene were genotyped in 1057 PsA and 778 type I PsV patients using the Sequenom genotyping platform. Genotype frequencies were compared to those of 5575 healthy controls. Additional analyses were performed in phenotypic subgroups of PsA (type I or II PsV and in those seronegative for rheumatoid factor). Results: Both SNPs were found to be highly associated with susceptibility to PsA (rs1800925 ptrend = 6.1×10−5 OR 1.33, rs20541 ptrend = 8.0×10−4 OR 1.27), but neither SNP was significantly associated with susceptibility to PsV. Conclusions: This study confirms that the effect of IL-13 risk locus is specific for PsA, thus highlighting a key biological pathway that differentiates PsA from PsV. The identification of markers that differentiate the two diseases raises the possibility in future of allowing screening of PsV patients to identify those at risk of developing PsA

    Distant field BHB stars and the mass of the Galaxy I: Classification of halo A-type stars

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    This is the first in a series of three papers presenting a new calculation of the mass of the Galaxy based on radial velocities and distances measured for a sample of some 100 faint 16 < B < 20 field blue horizontal-branch (BHB) stars. This study aims to reduce the uncertainty in the measured mass of the Galaxy by increasing the number of halo objects at Galactocentric distances r>30 kpc with measured radial velocities by a factor five. Faint A-type stars in the Galactic halo have been identified from UBR photometry in six UK Schmidt fields. We obtain accurate CCD photometry and spectra to classify these stars. This paper describes our methods for separating out clean samples of BHB stars in a way that is efficient in terms of telescope time required. We use the high signal-to-noise ratio (S/N) spectra of A-type stars of Kinman, Suntzeff & Kraft (published in 1994) to assess the reliability of two methods, and to quantify the S/N requirements. First we revisit, refine and extend the hydrogen line width versus colour relation as a classifier. The second method is new and compares the shapes of the Balmer lines. Using the equivalent width of the Ca II K line as an additional filter we find we can reproduce Kinman, Suntzeff & Kraft's classifications with both methods.Comment: 12 pages, 14 figures. Accepted for publication in MNRAS Balmer-line fitting routine available at http://astro.ic.ac.uk/Research/Extragal/milkyway.htm

    Teaching Implicit Leadership Theories to develop leaders and leadership – How and why it can make a difference

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    Implicit leadership theories (ILTs) are lay images of leadership, which are individually and socially determined. We discuss how teaching ILTs contributes to developing leaders and leaderships by raising self- and social awareness for the contexts in which leadership takes place. We present and discuss a drawing exercise to illustrate different ILTs and discuss the implications for leaders and leadership, with a particular focus on how leaders claim, and are granted, leader identities in groups

    “Medically unexplained” symptoms and symptom disorders in primary care: prognosis-based recognition and classification

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    Background: Many patients consult their GP because they experience bodily symptoms. In a substantial proportion of cases, the clinical picture does not meet the existing diagnostic criteria for diseases or disorders. This may be because symptoms are recent and evolving or because symptoms are persistent but, either by their character or the negative results of clinical investigation cannot be attributed to disease: so-called “medically unexplained symptoms” (MUS). MUS are inconsistently recognised, diagnosed and managed in primary care. The specialist classification systems for MUS pose several problems in a primary care setting. The systems generally require great certainty about presence or absence of physical disease, they tend to be mind-body dualistic, and they view symptoms from a narrow specialty determined perspective. We need a new classification of MUS in primary care; a classification that better supports clinical decision-making, creates clearer communication and provides scientific underpinning of research to ensure effective interventions. Discussion: We propose a classification of symptoms that places greater emphasis on prognostic factors. Prognosis-based classification aims to categorise the patient’s risk of ongoing symptoms, complications, increased healthcare use or disability because of the symptoms. Current evidence suggests several factors which may be used: symptom characteristics such as: number, multi-system pattern, frequency, severity. Other factors are: concurrent mental disorders, psychological features and demographic data. We discuss how these characteristics may be used to classify symptoms into three groups: self-limiting symptoms, recurrent and persistent symptoms, and symptom disorders. The middle group is especially relevant in primary care; as these patients generally have reduced quality of life but often go unrecognised and are at risk of iatrogenic harm. The presented characteristics do not contain immediately obvious cut-points, and the assessment of prognosis depends on a combination of several factors. Conclusion: Three criteria (multiple symptoms, multiple systems, multiple times) may support the classification into good, intermediate and poor prognosis when dealing with symptoms in primary care. The proposed new classification specifically targets the patient population in primary care and may provide a rational framework for decision-making in clinical practice and for epidemiologic and clinical research of symptoms

    Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

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    Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

    SOSORT consensus paper: school screening for scoliosis. Where are we today?

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    This report is the SOSORT Consensus Paper on School Screening for Scoliosis discussed at the 4th International Conference on Conservative Management of Spinal Deformities, presented by SOSORT, on May 2007. The objectives were numerous, 1) the inclusion of the existing information on the issue, 2) the analysis and discussion of the responses by the meeting attendees to the twenty six questions of the questionnaire, 3) the impact of screening on frequency of surgical treatment and of its discontinuation, 4) the reasons why these programs must be continued, 5) the evolving aim of School Screening for Scoliosis and 6) recommendations for improvement of the procedure

    Формирование эмоциональной культуры как компонента инновационной культуры студентов

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    Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been

    The James Webb Space Telescope Mission

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    Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4m4m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5m6.5m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure
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