568 research outputs found

    Tracking disease outbreaks from sparse data with Bayesian inference

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    The COVID-19 pandemic provides new motivation for a classic problem in epidemiology: estimating the empirical rate of transmission during an outbreak (formally, the time-varying reproduction number) from case counts. While standard methods exist, they work best at coarse-grained national or state scales with abundant data, and struggle to accommodate the partial observability and sparse data common at finer scales (e.g., individual schools or towns). For example, case counts may be sparse when only a small fraction of infections are caught by a testing program. Or, whether an infected individual tests positive may depend on the kind of test and the point in time when they are tested. We propose a Bayesian framework which accommodates partial observability in a principled manner. Our model places a Gaussian process prior over the unknown reproduction number at each time step and models observations sampled from the distribution of a specific testing program. For example, our framework can accommodate a variety of kinds of tests (viral RNA, antibody, antigen, etc.) and sampling schemes (e.g., longitudinal or cross-sectional screening). Inference in this framework is complicated by the presence of tens or hundreds of thousands of discrete latent variables. To address this challenge, we propose an efficient stochastic variational inference method which relies on a novel gradient estimator for the variational objective. Experimental results for an example motivated by COVID-19 show that our method produces an accurate and well-calibrated posterior, while standard methods for estimating the reproduction number can fail badly

    Children's biobehavioral reactivity to challenge predicts DNA methylation in adolescence and emerging adulthood.

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    A growing body of research has documented associations between adverse childhood environments and DNA methylation, highlighting epigenetic processes as potential mechanisms through which early external contexts influence health across the life course. The present study tested a complementary hypothesis: indicators of children's early internal, biological, and behavioral responses to stressful challenges may also be linked to stable patterns of DNA methylation later in life. Children's autonomic nervous system reactivity, temperament, and mental health symptoms were prospectively assessed from infancy through early childhood, and principal components analysis (PCA) was applied to derive composites of biological and behavioral reactivity. Buccal epithelial cells were collected from participants at 15 and 18 years of age. Findings revealed an association between early life biobehavioral inhibition/disinhibition and DNA methylation across many genes. Notably, reactive, inhibited children were found to have decreased DNA methylation of the DLX5 and IGF2 genes at both time points, as compared to non-reactive, disinhibited children. Results of the present study are provisional but suggest that the gene's profile of DNA methylation may constitute a biomarker of normative or potentially pathological differences in reactivity. Overall, findings provide a foundation for future research to explore relations among epigenetic processes and differences in both individual-level biobehavioral risk and qualities of the early, external childhood environment

    A Preliminary Survey of Interprofessional Education

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153603/1/jddj002203372006704tb04096x.pd

    Maternal fucosyltransferase 2 status affects the gut bifidobacterial communities of breastfed infants.

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    BackgroundIndividuals with inactive alleles of the fucosyltransferase 2 gene (FUT2; termed the 'secretor' gene) are common in many populations. Some members of the genus Bifidobacterium, common infant gut commensals, are known to consume 2'-fucosylated glycans found in the breast milk of secretor mothers. We investigated the effects of maternal secretor status on the developing infant microbiota with a special emphasis on bifidobacterial species abundance.ResultsOn average, bifidobacteria were established earlier and more often in infants fed by secretor mothers than in infants fed by non-secretor mothers. In secretor-fed infants, the relative abundance of the Bifidobacterium longum group was most strongly correlated with high percentages of the order Bifidobacteriales. Conversely, in non-secretor-fed infants, Bifidobacterium breve was positively correlated with Bifidobacteriales, while the B. longum group was negatively correlated. A higher percentage of bifidobacteria isolated from secretor-fed infants consumed 2'-fucosyllactose. Infant feces with high levels of bifidobacteria had lower milk oligosaccharide levels in the feces and higher amounts of lactate. Furthermore, feces containing different bifidobacterial species possessed differing amounts of oligosaccharides, suggesting differential consumption in situ.ConclusionsInfants fed by non-secretor mothers are delayed in the establishment of a bifidobacteria-laden microbiota. This delay may be due to difficulties in the infant acquiring a species of bifidobacteria able to consume the specific milk oligosaccharides delivered by the mother. This work provides mechanistic insight into how milk glycans enrich specific beneficial bacterial populations in infants and reveals clues for enhancing enrichment of bifidobacterial populations in at risk populations - such as premature infants

    Hyperlipidaemia in HIV-infected patients on lopinavir/ritonavir monotherapy in resource-limited settings

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    Cardiovascular disease (CVD) is an emerging concern for HIV-infected patients. Hyperlipidemia is a risk factor for CVD and a complication of protease-inhibitor-based antiretroviral therapy, but little is known about its incidence and risk factors in treated patients in resource-limited settings (RLS)

    FCIC memo of staff interview with Merrill Lynch

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