1,625 research outputs found

    CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

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    Opioid overdose is a growing public health crisis in the United States. This crisis, recognized as "opioid epidemic," has widespread societal consequences including the degradation of health, and the increase in crime rates and family problems. To improve the overdose surveillance and to identify the areas in need of prevention effort, in this work, we focus on forecasting opioid overdose using real-time crime dynamics. Previous work identified various types of links between opioid use and criminal activities, such as financial motives and common causes. Motivated by these observations, we propose a novel spatio-temporal predictive model for opioid overdose forecasting by leveraging the spatio-temporal patterns of crime incidents. Our proposed model incorporates multi-head attentional networks to learn different representation subspaces of features. Such deep learning architecture, called "community-attentive" networks, allows the prediction of a given location to be optimized by a mixture of groups (i.e., communities) of regions. In addition, our proposed model allows for interpreting what features, from what communities, have more contributions to predicting local incidents as well as how these communities are captured through forecasting. Our results on two real-world overdose datasets indicate that our model achieves superior forecasting performance and provides meaningful interpretations in terms of spatio-temporal relationships between the dynamics of crime and that of opioid overdose.Comment: Accepted as conference paper at ECML-PKDD 201

    Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

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    Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

    Low dose radiation and cancer in A-bomb survivors: latency and non-linear dose-response in the 1950–90 mortality cohort

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    BACKGROUND: Analyses of Japanese A-bomb survivors' cancer mortality risks are used to establish recommended annual dose limits, currently set at 1 mSv (public) and 20 mSv (occupational). Do radiation doses below 20 mSv have significant impact on cancer mortality in Japanese A-bomb survivors, and is the dose-response linear? METHODS: I analyse stomach, liver, lung, colon, uterus, and all-solid cancer mortality in the 0 – 20 mSv colon dose subcohort of the 1950–90 (grouped) mortality cohort, by Poisson regression using a time-lagged colon dose to detect latency, while controlling for gender, attained age, and age-at-exposure. I compare linear and non-linear models, including one adapted from the cellular bystander effect for α particles. RESULTS: With a lagged linear model, Excess Relative Risk (ERR) for the liver and all-solid cancers is significantly positive and several orders of magnitude above extrapolations from the Life Span Study Report 12 analysis of the full cohort. Non-linear models are strongly superior to the linear model for the stomach (latency 11.89 years), liver (36.90), lung (13.60) and all-solid (43.86) in fitting the 0 – 20 mSv data and show significant positive ERR at 0.25 mSv and 10 mSv lagged dose. The slope of the dose-response near zero is several orders of magnitude above the slope at high doses. CONCLUSION: The standard linear model applied to the full 1950–90 cohort greatly underestimates the risks at low doses, which are significant when the 0 – 20 mSv subcohort is modelled with latency. Non-linear models give a much better fit and are compatible with a bystander effect

    ‘Do i care?’ young adults' recalled experiences of early adolescent overweight and obesity: a qualitative study

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    <p>Objective: Individual behaviour change to reduce obesity requires awareness of, and concern about, weight. This paper therefore describes how young adults, known to have been overweight or obese during early adolescence, recalled early adolescent weight-related awareness and concerns. Associations between recalled concerns and weight-, health- and peer-related survey responses collected during adolescence are also examined.</p> <p>Design: Qualitative semi-structured interviews with young adults; data compared with responses to self-report questionnaires obtained in adolescence.</p> <p>Participants: A total of 35 participants, purposively sub-sampled at age 24 from a longitudinal study of a school year cohort, previously surveyed at ages 11, 13 and 15. Physical measures during previous surveys allowed identification of participants with a body mass index (BMI) indicative of overweight or obesity (based on British 1990 growth reference) during early adolescence. Overall, 26 had been obese, of whom 11 had BMI99.6th centile, whereas 9 had been overweight (BMI=95th–97.9th centile).</p> <p>Measures: Qualitative interview responses describing teenage life, with prompts for school-, social- and health-related concerns. Early adolescent self-report questionnaire data on weight-worries, self-esteem, friends and victimisation (closed questions).</p> <p>Results: Most, but not all recalled having been aware of their overweight. None referred to themselves as having been obese. None recalled weight-related health worries. Recollection of early adolescent obesity varied from major concerns impacting on much of an individual's life to almost no concern, with little relation to actual severity of overweight. Recalled concerns were not clearly patterned by gender, but young adult males recalling concerns had previously reported more worries about weight, lower self-esteem, fewer friends and more victimisation in early adolescence; no such pattern was seen among females. Conclusion: The popular image of the unhappy overweight teenager was not borne out. Many obese adolescents, although well aware of their overweight recalled neither major dissatisfaction nor concern. Weight-reduction behaviours are unlikely in such circumstances.</p&gt

    The transcriptional repressor protein NsrR senses nitric oxide directly via a [2Fe-2S] cluster

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    The regulatory protein NsrR, a member of the Rrf2 family of transcription repressors, is specifically dedicated to sensing nitric oxide (NO) in a variety of pathogenic and non-pathogenic bacteria. It has been proposed that NO directly modulates NsrR activity by interacting with a predicted [Fe-S] cluster in the NsrR protein, but no experimental evidence has been published to support this hypothesis. Here we report the purification of NsrR from the obligate aerobe Streptomyces coelicolor. We demonstrate using UV-visible, near UV CD and EPR spectroscopy that the protein contains an NO-sensitive [2Fe-2S] cluster when purified from E. coli. Upon exposure of NsrR to NO, the cluster is nitrosylated, which results in the loss of DNA binding activity as detected by bandshift assays. Removal of the [2Fe-2S] cluster to generate apo-NsrR also resulted in loss of DNA binding activity. This is the first demonstration that NsrR contains an NO-sensitive [2Fe-2S] cluster that is required for DNA binding activity

    Identification of the occurrence and pattern of masseter muscle activities during sleep using EMG and accelerometer systems

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    <p>Abstract</p> <p>Background</p> <p>Sleep bruxism has been described as a combination of different orofacial motor activities that include grinding, clenching and tapping, although accurate distribution of the activities still remains to be clarified.</p> <p>Methods</p> <p>We developed a new system for analyzing sleep bruxism to examine the muscle activities and mandibular movement patterns during sleep bruxism. The system consisted of a 2-axis accelerometer, electroencephalography and electromyography. Nineteen healthy volunteers were recruited and screened to evaluate sleep bruxism in the sleep laboratory.</p> <p>Results</p> <p>The new system could easily distinguish the different patterns of bruxism movement of the mandible and the body movement. Results showed that grinding (59.5%) was most common, followed by clenching (35.6%) based on relative activity to maximum voluntary contraction (%MVC), whereas tapping was only (4.9%).</p> <p>Conclusion</p> <p>It was concluded that the tapping, clenching, and grinding movement of the mandible could be effectively differentiated by the new system and sleep bruxism was predominantly perceived as clenching and grinding, which varied between individuals.</p

    Arduous implementation: Does the Normalisation Process Model explain why it's so difficult to embed decision support technologies for patients in routine clinical practice

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    Background: decision support technologies (DSTs, also known as decision aids) help patients and professionals take part in collaborative decision-making processes. Trials have shown favorable impacts on patient knowledge, satisfaction, decisional conflict and confidence. However, they have not become routinely embedded in health care settings. Few studies have approached this issue using a theoretical framework. We explained problems of implementing DSTs using the Normalization Process Model, a conceptual model that focuses attention on how complex interventions become routinely embedded in practice.Methods: the Normalization Process Model was used as the basis of conceptual analysis of the outcomes of previous primary research and reviews. Using a virtual working environment we applied the model and its main concepts to examine: the 'workability' of DSTs in professional-patient interactions; how DSTs affect knowledge relations between their users; how DSTs impact on users' skills and performance; and the impact of DSTs on the allocation of organizational resources.Results: conceptual analysis using the Normalization Process Model provided insight on implementation problems for DSTs in routine settings. Current research focuses mainly on the interactional workability of these technologies, but factors related to divisions of labor and health care, and the organizational contexts in which DSTs are used, are poorly described and understood.Conclusion: the model successfully provided a framework for helping to identify factors that promote and inhibit the implementation of DSTs in healthcare and gave us insights into factors influencing the introduction of new technologies into contexts where negotiations are characterized by asymmetries of power and knowledge. Future research and development on the deployment of DSTs needs to take a more holistic approach and give emphasis to the structural conditions and social norms in which these technologies are enacte

    Screening of DUB activity and specificity by MALDI-TOF mass spectrometry

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    Deubiquitylases (DUBs) are key regulators of the ubiquitin system which cleave ubiquitin moieties from proteins and polyubiquitin chains. Several DUBs have been implicated in various diseases and are attractive drug targets. We have developed a sensitive and fast assay to quantify in vitro DUB enzyme activity using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Unlike other current assays, this method uses unmodified substrates, such as diubiquitin topoisomers. By analyzing 42 human DUBs against all diubiquitin topoisomers we provide an extensive characterization of DUB activity and specificity. Our results confirm the high specificity of many members of the OTU and JAMM DUB families and highlight that all USPs tested display low linkage selectivity. We also demonstrate that this assay can be deployed to assess the potency and specificity of DUB inhibitors by profiling 11 compounds against a panel of 32 DUBs
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