12 research outputs found

    Explanation Trees for Causal Bayesian Networks

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    Bayesian networks can be used to extract explanations about the observed state of a subset of variables. In this paper, we ex- plicate the desiderata of an explanation and confront them with the concept of expla- nation proposed by existing methods. The necessity of taking into account causal ap- proaches when a causal graph is available is discussed. We then introduce causal expla- nation trees, based on the construction of ex- planation trees using the measure of causal information flow (Ay and Polani, 2006). This approach is compared to several other meth- ods on known networks

    Measurement of jet fragmentation in Pb+Pb and pppp collisions at sNN=2.76\sqrt{{s_\mathrm{NN}}} = 2.76 TeV with the ATLAS detector at the LHC

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    An online atlas of human plasma metabolite signatures of gut microbiome composition

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    Human gut microbiota produce a variety of molecules, some of which enter the bloodstream and impact health. Conversely, dietary or pharmacological compounds may affect the microbiota before entering the circulation. Characterization of these interactions is an important step towards understanding the effects of the gut microbiota on health. In this cross-sectional study, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for a detailed characterization of the gut microbiota and plasma metabolome, respectively, of 8583 participants invited at age 50 to 64 from the population-based Swedish CArdioPulmonary bioImage Study. Here, we find that the gut microbiota explain up to 58% of the variance of individual plasma metabolites and we present 997 associations between alpha diversity and plasma metabolites and 546,819 associations between specific gut metagenomic species and plasma metabolites in an online atlas (https://gutsyatlas.serve.scilifelab.se/). We exemplify the potential of this resource by presenting novel associations between dietary factors and oral medication with the gut microbiome, and microbial species strongly associated with the uremic toxin p-cresol sulfate. This resource can be used as the basis for targeted studies of perturbation of specific metabolites and for identification of candidate plasma biomarkers of gut microbiota composition

    Streptococcus Species Abundance in the Gut Is Linked to Subclinical Coronary Atherosclerosis in 8973 Participants From the SCAPIS Cohort

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    Background: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography-based measures of coronary atherosclerosis and to explore relevant clinical correlates. Methods: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of stool, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva. Results: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10-5). Associations were largely similar across coronary computed tomography angiography-based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. Five species, including 3 streptococci, correlated with the same species in saliva and were associated with worse dental health in the Malmö Offspring Dental Study. Microbial functional potential of dissimilatory nitrate reduction, anaerobic fatty acid β-oxidation, and amino acid degradation were associated with coronary artery calcium score. Conclusions: This study provides evidence of an association of a gut microbiota composition characterized by increased abundance of Streptococcus spp and other species commonly found in the oral cavity with coronary atherosclerosis and systemic inflammation markers. Further longitudinal and experimental studies are warranted to explore the potential implications of a bacterial component in atherogenesis
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