1,098 research outputs found

    Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK

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    Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations

    Progranulin Gene Variability and Plasma Levels in Bipolar Disorder and Schizophrenia

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    Basing on the assumption that frontotemporal lobar degeneration (FTLD), schizophrenia and bipolar disorder (BPD) might share common aetiological mechanisms, we analyzed genetic variation in the FTLD risk gene progranulin (GRN) in a German population of patients with schizophrenia (n = 271) or BPD (n = 237) as compared with 574 age-, gender- and ethnicity-matched controls. Furthermore, we measured plasma progranulin levels in 26 German BPD patients as well as in 61 Italian BPD patients and 29 matched controls

    PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity

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    <p>Abstract</p> <p>Background</p> <p>Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. Due to the difficulty in performing high-throughput mass spectrometry-based experiment, there is a desire to predict phosphorylation sites using computational methods. However, previous studies regarding <it>in silico </it>prediction of plant phosphorylation sites lack the consideration of kinase-specific phosphorylation data. Thus, we are motivated to propose a new method that investigates different substrate specificities in plant phosphorylation sites.</p> <p>Results</p> <p>Experimentally verified phosphorylation data were extracted from TAIR9-a protein database containing 3006 phosphorylation data from the plant species <it>Arabidopsis thaliana</it>. In an attempt to investigate the various substrate motifs in plant phosphorylation, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. Profile hidden Markov model (HMM) is then applied to learn a predictive model for each subgroup. Cross-validation evaluation on the MDD-clustered HMMs yields an average accuracy of 82.4% for serine, 78.6% for threonine, and 89.0% for tyrosine models. Moreover, independent test results using <it>Arabidopsis thaliana </it>phosphorylation data from UniProtKB/Swiss-Prot show that the proposed models are able to correctly predict 81.4% phosphoserine, 77.1% phosphothreonine, and 83.7% phosphotyrosine sites. Interestingly, several MDD-clustered subgroups are observed to have similar amino acid conservation with the substrate motifs of well-known kinases from Phospho.ELM-a database containing kinase-specific phosphorylation data from multiple organisms.</p> <p>Conclusions</p> <p>This work presents a novel method for identifying plant phosphorylation sites with various substrate motifs. Based on cross-validation and independent testing, results show that the MDD-clustered models outperform models trained without using MDD. The proposed method has been implemented as a web-based plant phosphorylation prediction tool, PlantPhos <url>http://csb.cse.yzu.edu.tw/PlantPhos/</url>. Additionally, two case studies have been demonstrated to further evaluate the effectiveness of PlantPhos.</p

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

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    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

    Dropout from exercise trials among cancer survivors—An individual patient data meta-analysis from the POLARIS study

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    Introduction: The number of randomized controlled trials (RCTs) investigating the effects of exercise among cancer survivors has increased in recent years; however, participants dropping out of the trials are rarely described. The objective of the present study was to assess which combinations of participant and exercise program characteristics were associated with dropout from the exercise arms of RCTs among cancer survivors. Methods: This study used data collected in the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) study, an international database of RCTs investigating the effects of exercise among cancer survivors. Thirty-four exercise trials, with a total of 2467 patients without metastatic disease randomized to an exercise arm were included. Harmonized studies included a pre and a posttest, and participants were classified as dropouts when missing all assessments at the post-intervention test. Subgroups were identified with a conditional inference tree. Results: Overall, 9.6% of the participants dropped out. Five subgroups were identified in the conditional inference tree based on four significant associations with dropout. Most dropout was observed for participants with BMI &gt;28.4 kg/m2, performing supervised resistance or unsupervised mixed exercise (19.8% dropout) or had low-medium education and performed aerobic or supervised mixed exercise (13.5%). The lowest dropout was found for participants with BMI &gt;28.4 kg/m2 and high education performing aerobic or supervised mixed exercise (5.1%), and participants with BMI ≤28.4 kg/m2 exercising during (5.2%) or post (9.5%) treatment. Conclusions: There are several systematic differences between cancer survivors completing and dropping out from exercise trials, possibly affecting the external validity of exercise effects.</p

    Moderators of Exercise Effects on Cancer-related Fatigue:A Meta-analysis of Individual Patient Data

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    PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCT) to investigate moderators of exercise intervention effects on cancer-related fatigue. METHODS: We used individual patient data from 31 exercise RCT worldwide, representing 4366 patients, of whom 3846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test. RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (β = -0.17; 95% confidence interval [CI], -0.22 to -0.12). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (βdifference = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration ≤12 wk showed larger effects on fatigue (β = -0.29; 95% CI, -0.39 to -0.20) than supervised interventions with a longer duration. CONCLUSIONS: In this individual patient data meta-analysis, we found statistically significant beneficial effects of exercise interventions on fatigue, irrespective of demographic and clinical characteristics. These findings support a role for exercise, preferably supervised exercise interventions, in clinical practice. Reasons for differential effects in duration require further exploration

    Cultural distance, mindfulness and passive xenophobia: Using Integrated Threat Theory to explore home higher education students' perspectives on 'internationalisation at home'

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    This paper addresses the question of interaction between home and international students using qualitative data from 100 home students at two 'teaching intensive' universities in the southwest of England. Stephan and Stephan's Integrated Threat Theory is used to analyse the data, finding evidence for all four types of threat that they predict when outgroups interact. It is found that home students perceive threats to their academic success and group identity from the presence of international students on the campus and in the classroom. These are linked to anxieties around 'mindful' forms of interaction and a taboo around the discussion of difference, leading to a 'passive xenophobia' for the majority. The paper concludes that Integrated Threat Theory is a useful tool in critiquing the 'internationalisation at home' agenda, making suggestions for policies and practices that may alleviate perceived threats, thereby improving the quality and outcomes of intercultural interaction. © 2010 British Educational Research Association

    Targeting exercise interventions to patients with cancer in need:An individual patient data meta-analysis

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    Background: Exercise effects in cancer patients often appear modest, possibly because interventions rarely target patients most in need. This study investigated the moderator effects of baseline values on the exercise outcomes of fatigue, aerobic fitness, muscle strength, quality of life (QoL), and self-reported physical function (PF) in cancer patients during and post-treatment. Methods: Individual patient data from 34 randomized exercise trials (n = 4519) were pooled. Linear mixed-effect models were used to study moderator effects of baseline values on exercise intervention outcomes and to determine whether these moderator effects differed by intervention timing (during vs post-treatment). All statistical tests were two-sided. Results: Moderator effects of baseline fatigue and PF were consistent across intervention timing, with greater effects in patients with worse fatigue (Pinteraction = .05) and worse PF (Pinteraction = .003). Moderator effects of baseline aerobic fitness, muscle strength, and QoL differed by intervention timing. During treatment, effects on aerobic fitness were greater for patients with better baseline aerobic fitness (Pinteraction = .002). Post-treatment, effects on upper (Pinteraction &lt; .001) and lower (Pinteraction = .01) body muscle strength and QoL (Pinteraction &lt; .001) were greater in patients with worse baseline values. Conclusion: Although exercise should be encouraged for most cancer patients during and post-treatments, targeting specific subgroups may be especially beneficial and cost effective. For fatigue and PF, interventions during and post-treatment should target patients with high fatigue and low PF. During treatment, patients experience benefit for muscle strength and QoL regardless of baseline values; however, only patients with low baseline values benefit post-treatment. For aerobic fitness, patients with low baseline values do not appear to benefit from exercise during treatment
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