2,518 research outputs found

    Herman Melville and the Problem of Evil

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    Part of a series of public lectures delivered at The Rice Institute on Sunday afternoons during autumn 194

    Breaking the prejudice habit: Mechanisms, timecourse, and longevity

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    The prejudice habit-breaking intervention (Devine et al., 2012) and its offshoots (e.g., Carnes et al., 2012) have shown promise in effecting long-term change in key outcomes related to intergroup bias, including increases in awareness, concern about discrimination, and, in one study, long-term decreases in implicit bias. This intervention is based on the premise that unintentional bias is like a habit that can be broken with sufficient motivation, awareness, and effort. We conducted replication of the original habit-breaking intervention experiment in a sample more than three times the size of the original (N = 292). We also measured all outcomes every other day for 14 days and measured potential mechanisms for the intervention’s effects. Consistent with previous results, the habit-breaking intervention produced a change in concern that endured two weeks post-intervention. These effects were associated with increased sensitivity to the biases of others and an increased tendency to label biases as wrong. Contrasting with the original work, both control and intervention participants decreased in implicit bias, and the effects of the habit-breaking intervention on awareness declined in the second week of the study. In a subsample recruited two years later, intervention participants were more likely than control participants to object on a public online forum to an essay endorsing racial stereotyping. Our results suggest that the habit-breaking intervention produces enduring changes in peoples’ knowledge of and beliefs about race-related issues, and we argue that these changes are even more important for promoting long-term behavioral change than are changes in implicit bias

    The potential of cell cultures for the production of salt tolerant cultivars.

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    The progress towards the production of salt tolerant plants through selection in cell cultures is briefly reviewed. The need for a fuller understanding of the mechanisms of salt tolerance in non-halophytes is emphasised and illustrated with reference to recent investigations on the role of proline. A clear protective effect, against salt stress, of exogenously applied proline has been demonstrated suggesting elevated levels of endogenous proline synthesis, for which there is a direct selection procedure, as a basis for improved salt tolerance. Salt tolerance of proline-overproducing plants and cell cultures is currently under investigation in a Nicotiana sylvestris line with almost 100-fold increase in free proline

    Use of systems biology to decipher host–pathogen interaction networks and predict biomarkers

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    AbstractIn systems biology, researchers aim to understand complex biological systems as a whole, which is often achieved by mathematical modelling and the analyses of high-throughput data. In this review, we give an overview of medical applications of systems biology approaches with special focus on host–pathogen interactions. After introducing general ideas of systems biology, we focus on (1) the detection of putative biomarkers for improved diagnosis and support of therapeutic decisions, (2) network modelling for the identification of regulatory interactions between cellular molecules to reveal putative drug targets and (3) module discovery for the detection of phenotype-specific modules in molecular interaction networks. Biomarker detection applies supervised machine learning methods utilizing high-throughput data (e.g. single nucleotide polymorphism (SNP) detection, RNA-seq, proteomics) and clinical data. We demonstrate structural analysis of molecular networks, especially by identification of disease modules as a novel strategy, and discuss possible applications to host–pathogen interactions. Pioneering work was done to predict molecular host–pathogen interactions networks based on dual RNA-seq data. However, currently this network modelling is restricted to a small number of genes. With increasing number and quality of databases and data repositories, the prediction of large-scale networks will also be feasible that can used for multidimensional diagnosis and decision support for prevention and therapy of diseases. Finally, we outline further perspective issues such as support of personalized medicine with high-throughput data and generation of multiscale host–pathogen interaction models

    Effectiveness of the ADEC as a level 2 screening test for young children with suspected autism spectrum disorders in a clinical setting

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    Background The Autism Detection in Early Childhood (ADEC) is a clinician-administered, Level 2 screening tool. A retrospective file audit was used to investigate its clinical effectiveness. Method Toddlers referred to an Australian child development service between 2008 and 2010 (N?=?53, M age?=?32.2 months) were screened with the ADEC. Their medical records were reviewed in 2013 when their mean age was 74.5 months, and the original ADEC screening results were compared with later diagnostic outcomes. Results The ADEC had good sensitivity (87.5%) and moderate specificity (62%). Three behaviours predicted autism spectrum disorders (ASDs): response to name, gaze switching, and gaze monitoring (p???.001). Conclusions The ADEC shows promise as a screening tool that can discriminate between young children with ASDs and those who have specific communication disorders or developmental delays that persist into middle childhood but who do not meet the criteria for ASDs

    IHOC Summary For Members - Helping Your Child’s Doctor Helps Your Child

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    IHOC’s goal is to improve the health of children. For example, many children in Maine do not get their vaccines on time. So IHOC will work with doctor’s offices to help more children get their vaccines on time. This will help protect all children in the state, by reducing certain contagious illnesses

    IHOC Summary For Providers - Improving Health Outcomes for Children in Maine and Vermont

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    In February 2010, Maine and Vermont were awarded a five-year child health quality improvement grant. The project focuses on using quality measures and information technology to improve health outcomes for children. The goal is to improve timely access to quality care for children who are insured by Medicaid
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