195 research outputs found

    A novel score for predicting alzheimer’s disease risk from late life psychopathological and health risk factors

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    With the increasing size of the aging population, dementia risk reduction has become a main public health concern. Dementia risk models or indices may help to identify individuals in the community at high risk to develop dementia. We have aimed to develop a novel dementia risk index focused on the late-life (65 years or more) population, that addresses risk factors for Alz-heimer’s disease (AD) easily identifiable at primary care settings. These risk factors include some shown to be associated with the risk of AD but not featured in existing indices, such as hearing loss and anxiety. Our index is also the first to account for the competing risk of death. The Zaragoza Dementia and Depression Project (ZARADEMP) Alzheimer Dementia Risk Score predicts an indi-vidual´s risk of developing AD within 5 years. The probability of late onset AD significantly in-creases in those with risk scores between 21 and 28 and, furthermore, is almost 4-fold higher for those with risk scores of 29 or higher. Our index may provide a practical instrument to identify subjects at high risk of AD and to design preventive strategies targeting the contributing risk factors

    Prevalence of anxiety in medical students during the covid-19 pandemic: A rapid systematic review with meta-analysis

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    The novel coronavirus disease (COVID-19) pandemic has brought a great deal of pressure for medical students, who typically show elevated anxiety rates. Our aim is to investigate the prevalence of anxiety in medical students during this pandemic. This systematic review and mini meta-analysis has been conducted following the PRISMA guidelines. Two researchers independently searched PubMed on 26 August 2020 for cross-sectional studies on medical students during the COVID-19 outbreak, with no language restrictions applied. We then performed a manual search to detect other potentially eligible investigations. To the 1361 records retrieved in the initial search, 4 more were added by manual search on medRxiv. Finally, eight studies were finally included for qualitative and quantitative analysis, which yielded an estimated prevalence of anxiety of 28% (95% CI: 22–34%), with significant heterogeneity between studies. The prevalence of anxiety in medical students is similar to that prior to the pandemic but correlates with several specific COVID-related stressors. While some preventive and risk factors have been previously identified in a non-pandemic context, knowledge and cognitions on COVID-19 transmission, treatment, prognosis and prevention negatively correlate with anxiety, emerging as a key preventive factor that may provide a rationale for why the levels of anxiety have remained stable in medical students during the pandemic while increasing in their non-medical peers and the general population. Other reasons for the invariability of anxiety rates in this population are discussed. A major limitation of our review is that Chinese students comprised 89% the total sample, which could compromise the external validity of our work

    Prevalence of anxiety in the COVID-19 pandemic: An updated meta-analysis of community-based studies

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    Background: The unprecedented worldwide crisis caused by the rapid spread of COVID-19 and the restrictive public health measures enforced by some countries to slow down its transmission have severely threatened the physical and mental wellbeing of communities globally. Methods: We conducted a systematic review and meta-analysis to determine the prevalence of anxiety in the general population during the COVID-19 pandemic. Two researchers independently searched for cross-sectional community-based studies published between December 1, 2019 and August 23, 2020, using PubMed, WoS, Embase, and other sources (e.g., grey literature, manual search). Results: Of 3049 records retrieved, 43 studies were included. These studies yielded an estimated overall prevalence of anxiety of 25%, which varied significantly across the different tools used to measure anxiety. Consistently reported risk factors for the development of anxiety included initial or peak phase of the outbreak, female sex, younger age, marriage, social isolation, unemployment and student status, financial hardship, low educational level, insufficient knowledge of COVID-19, epidemiological or clinical risk of disease and some lifestyle and personality variables. Conclusions: As the overall global prevalence of anxiety disorders is estimated to be 7.3% normally, our results suggest that rates of anxiety in the general population could be more than 3 times higher during the COVID-19 pandemic. These findings suggest a substantial impact on mental health that should be targeted by individual and population-level strategies

    Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review

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    In professional soccer, increasing amounts of data are collected that harness great potential when it comes to analysing tactical behaviour. Unlocking this potential is difficult as big data challenges the data management and analytics methods commonly employed in sports. By joining forces with computer science, solutions to these challenges could be achieved, helping sports science to find new insights, as is happening in other scientific domains. We aim to bring multiple domains together in the context of analysing tactical behaviour in soccer using position tracking data. A systematic literature search for studies employing position tracking data to study tactical behaviour in soccer was conducted in seven electronic databases, resulting in 2338 identified studies and finally the inclusion of 73 papers. Each domain clearly contributes to the analysis of tactical behaviour, albeit in - sometimes radically - different ways. Accordingly, we present a multidisciplinary framework where each domain's contributions to feature construction, modelling and interpretation can be situated. We discuss a set of key challenges concerning the data analytics process, specifically feature construction, spatial and temporal aggregation. Moreover, we discuss how these challenges could be resolved through multidisciplinary collaboration, which is pivotal in unlocking the potential of position tracking data in sports analytics.Algorithms and the Foundations of Software technolog

    Physics of Solar Prominences: II - Magnetic Structure and Dynamics

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    Observations and models of solar prominences are reviewed. We focus on non-eruptive prominences, and describe recent progress in four areas of prominence research: (1) magnetic structure deduced from observations and models, (2) the dynamics of prominence plasmas (formation and flows), (3) Magneto-hydrodynamic (MHD) waves in prominences and (4) the formation and large-scale patterns of the filament channels in which prominences are located. Finally, several outstanding issues in prominence research are discussed, along with observations and models required to resolve them.Comment: 75 pages, 31 pictures, review pape

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Produção e valor nutritivo da forragem de capim-elefante em dois sistemas de produção.

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    Esta pesquisa foi realizada com o objetivo de avaliar a produção e o valor nutritivo da forragem de capimelefante cultivado em sistemas convencional e agroecológico. No sistema convencional, o capim-elefante foi estabelecido em cultivo exclusivo, em linhas com espaçamento de 1,4 m e, no sistema agroecológico, em linhas afastadas 3 m. Nas entrelinhas, estabeleceu-se azevém no período hibernal para desenvolvimento de espécies de crescimento espontâneo no período estival. Avaliaram-se a massa, a produção e a composição botânica e estrutural da forragem e a carga animal. Amostras de simulação de pastejo foram coletadas para determinação dos teores de proteína bruta e fibra em detergente neutro e da digestibilidade in vitro da matéria seca e matéria orgânica. O delineamento experimental foi o inteiramente casualizado com dois tratamentos (sistemas convencional e agroecológico) e duas repetições (piquetes). Valores mais elevados para massa de forragem, produção de forragem, taxa de acúmulo diário e carga animal foram observados no sistema convencional. A relação folha:colmo foi similar entre os sistemas. Valor mais elevado de proteína bruta foi observado no sistema agroecológico. O capim-elefante sob manejo convencional apresenta maior produção de forragem, com menores teores de proteína bruta. O sistema agroecológico apresenta melhor distribuição da produção de forragem no decorrer do ano
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