707 research outputs found

    Level of confidence evaluation and its usage for Roll-back Recovery with Checkpointing optimization

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    Increasing soft error rates for semiconductor devices manu- factured in later technologies enforces the use of fault tolerant techniques such as Roll-back Recovery with Checkpointing (RRC). However, RRC introduces time overhead that increases the completion (execution) time. For non-real-time systems, research have focused on optimizing RRC and shown that it is possible to find the optimal number of checkpoints such that the average execution time is minimal. While minimal average execution time is important, it is for real-time systems important to provide a high probability that deadlines are met. Hence, there is a need of probabilistic guarantees that jobs employing RRC complete before a given deadline. First, we present a mathematical framework for the evaluation of level of confidence, the probability that a given deadline is met, when RRC is employed. Second, we present an optimization method for RRC that finds the number of checkpoints that results in the minimal completion time while the minimal com- pletion time satisfies a given level of confidence requirement. Third, we use the proposed framework to evaluate probabilistic guarantees for RRC optimization in non-real-time systems

    Birthweight, Type 2 Diabetes Mellitus, and Cardiovascular Disease: Addressing the Barker Hypothesis With Mendelian Randomization.

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    BACKGROUND: Low birthweight has been associated with a higher risk of hypertension, type 2 diabetes mellitus (T2D), and cardiovascular disease. The Barker hypothesis posits that intrauterine growth restriction resulting in lower birthweight is causal for these diseases, but causality is difficult to infer from observational studies. METHODS: We performed regression analyses to assess associations of birthweight with cardiovascular disease and T2D in 237 631 individuals from the UK Biobank. Further, we assessed the causal relationship of such associations using Mendelian randomization. RESULTS: In the observational analyses, birthweight showed inverse associations with systolic and diastolic blood pressure (β, -0.83 and -0.26; per raw unit in outcomes and SD change in birthweight; 95% confidence interval [CI], -0.90 to -0.75 and -0.31 to -0.22, respectively), T2D (odds ratio, 0.83; 95% CI, 0.79-0.87), lipid-lowering treatment (odds ratio, 0.84; 95% CI, 0.81-0.86), and coronary artery disease (hazard ratio, 0.85; 95% CI, 0.78-0.94), whereas the associations with adult body mass index and body fat (β, 0.04 and 0.02; per SD change in outcomes and birthweight; 95% CI, 0.03-0.04 and 0.01-0.02, respectively) were positive. The Mendelian randomization analyses indicated inverse causal associations of birthweight with low-density lipoprotein cholesterol, 2-hour glucose, coronary artery disease, and T2D and positive causal association with body mass index but no associations with blood pressure. CONCLUSIONS: Our study indicates that lower birthweight, used as a proxy for intrauterine growth retardation, is causally related with increased susceptibility to coronary artery disease and T2D. This causal relationship is not mediated by adult obesity or hypertension

    Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome

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    Background: Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual's genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. Methods: We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen. Results: We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction P=2.87x10(-8)) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082-1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497-1.565]). These findings were replicated in FinnGen (interaction P=1.38x10(-6)). Conclusions: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.Peer reviewe

    Early exposure to dogs and farm animals and the risk of childhood asthma

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    IMPORTANCE: The association between early exposure to animals and childhood asthma is not clear, and previous studies have yielded contradictory results. OBJECTIVE: To determine whether exposure to dogs and farm animals confers a risk of asthma. DESIGN, SETTING AND PARTICIPANTS: In a nationwide cohort study, the association between early exposure to dogs and farm animals and the risk of asthma was evaluated and included all children born in Sweden from January 1, 2001, to December 31, 2010 (N = 1,011,051), using registry data on dog and farm registration, asthma medication, diagnosis, and confounders for parents and their children. The association was assessed as the odds ratio (OR) for a current diagnosis of asthma at age 6 years for school-aged children and as the hazard ratio (HR) for incident asthma at ages 1 to 5 years for preschool-aged children. Data were analyzed from January 1, 2007, to September 30, 2012. EXPOSURES: Living with a dog or farm animal. MAIN OUTCOMES AND MEASURES: Childhood asthma diagnosis and medication used. RESULTS: Of the 1,011,051 children born during the study period, 376,638 preschool-aged (53,460 [14.2%] exposed to dogs and 1729 [0.5%] exposed to farm animals) and 276,298 school-aged children (22,629 [8.2%] exposed to dogs and 958 [0.3%] exposed to farm animals) were included in the analyses. Of these, 18,799 children (5.0%) in the preschool-aged children's cohort experienced an asthmatic event before baseline, and 28,511 cases of asthma and 906,071 years at risk were recorded during follow-up (incidence rate, 3.1 cases per 1000 years at risk). In the school-aged children's cohort, 11,585 children (4.2%) experienced an asthmatic event during the seventh year of life. Dog exposure during the first year of life was associated with a decreased risk of asthma in school-aged children (OR, 0.87; 95% CI, 0.81-0.93) and in preschool-aged children 3 years or older (HR, 0.90; 95% CI, 0.83-0.99) but not in children younger than 3 years (HR, 1.03; 95% CI, 1.00-1.07). Results were comparable when analyzing only first-born children. Farm animal exposure was associated with a reduced risk of asthma in both school-aged children and preschool-aged children (OR, 0.48; 95% CI, 0.31-0.76, and HR, 0.69; 95% CI, 0.56-0.84), respectively. CONCLUSIONS AND RELEVANCE: In this study, the data support the hypothesis that exposure to dogs and farm animals during the first year of life reduces the risk of asthma in children at age 6 years. This information might be helpful in decision making for families and physicians on the appropriateness and timing of early animal exposure.NonePublishe

    Access Time Analysis for IEEE P1687

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    Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes

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    Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate.Peer reviewe
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