165 research outputs found

    Medical graduates’ early career choices of specialty and their eventual specialty destinations: UK prospective cohort studies

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    Objective To report on doctors’ early choices of specialty at selected intervals after qualification, and eventual career destinations

    Early career choices and successful career progression in surgery in the UK: prospective cohort studies

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    <p>Abstract</p> <p>Background</p> <p>Changes to the structure of medical training worldwide require doctors to decide on their career specialty at an increasingly early stage after graduation. We studied trends in career choices for surgery, and the eventual career destinations, of UK graduates who declared an early preference for surgery.</p> <p>Methods</p> <p>Postal questionnaires were sent, at regular time intervals after qualification, to all medical qualifiers from all UK medical schools in selected qualification years between 1974 and 2005. They were sent in the first year after qualification, at year three and five years after qualification, and at longer time intervals thereafter.</p> <p>Results</p> <p>Responses were received from 27 749 of 38 280 doctors (73%) at year one, 23 468 of 33151 (71%) at year three, and 17 689 of 24 870 (71%) at year five. Early career preferences showed that surgery has become more popular over the past two decades. Looking forward from early career choice, 60% of respondents (64% of men, 48% of women) with a first preference for a surgical specialty at year one eventually worked in surgery (p < 0.001 for the male-female comparison). Looking backward from eventual career destinations, 90% of responders working in surgery had originally specified a first choice for a surgical specialty at year one. 'Match' rates between eventual destinations and early choices were much higher for surgery than for other specialties. Considering factors that influenced early specialty choice 'a great deal', comparing aspiring surgeons and aspiring general practitioners (GPs), a significantly higher percentage who chose surgery than general practice specified enthusiasm for the specialty (73% vs. 53%), a particular teacher or department (34% vs. 12%), inclinations before medical school (20% vs. 11%), and future financial prospects (24% vs. 13%); and a lower percentage specified that hours and working conditions had influenced their choice (21% vs. 71%). Women choosing surgery were influenced less than men by their inclinations before medical school or by their future financial prospects.</p> <p>Conclusions</p> <p>Surgery is a popular specialty choice in the UK. The great majority of doctors who progressed in a surgical career made an early and definitive decision to do so.</p

    Mobilising Knowledge through Global Partnerships to Support Research-informed Teaching: Five Models for Translational Research

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    Education Futures Collaboration Charity The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Improving the quality of teaching is of global concern: UNESCO’s Sustainable Development Goal (SDG) 4c in the Education 2030: Framework for Action calls for high quality teaching for all. The OECD challenges the education system to improve Knowledge Management. JET’s (2015) special issue: Translational Research (TR) and Knowledge Mobilisation in Teacher Education introduced the concept of ‘translational’ or ‘theory to practice’ research - well-established in medicine but not in education. Five TR models were subsequently developed by the MESH charity’s international network with organisations in South Africa, Bangladesh, Australia, Pakistan, UK. These distinct models engage 1) university staff and teachers 2) subject associations, 3) research units, 4) an international NGO working in crisis settings, 5) PhD tutors and students. Each model shares common features forming the MESH Translational Research methodology introduced in this article. A TR repository is part of the MESH knowledge mobilisation strategy giving teachers access to research summaries which, overtime, accumulate knowledge. TR publications called MESHGuides (www.meshguides.org) complement existing forms of publication. This article proposes the MESH TR methodology as one affordable and scalable solution to OECD and UNESCO’s challenges of keeping teachers up-to-date and making new knowledge accessible to teachers regardless of location

    Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design

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    We present a retrospective investigation of the role of genomics in the prediction of central versus marginal disease progression patterns for glioblastoma (GBM). Between August 2000 and May 2010, 41 patients with GBM and gene expression and methylation data available were treated with radiotherapy with or without concurrent temozolomide. Location of disease progression was categorized as within the high dose (60 Gy) or low dose (46 Gy) volume. Samples were grouped into previously described TCGA genomic groupings: Mesenchymal (m), classical (c), proneural (pn), and neural (n); and were also classified by MGMT-Methylation status and G-Cimp methylation phenotype. Genomic groupings and methylation status were investigated as a possible predictor of disease progression in the high dose region, progression in the low dose region, and time to progression. Based on TCGA category there was no difference in OS (p = 0.26), 60 Gy progression (PN: 71 %, N: 60 %, M: 89 %, C: 83 %, p = 0.19), 46 Gy progression (PN: 57 %, N: 40 %, M: 61 %, C: 50 %, p = 0.8) or time to progression (PN: 9 months, N:15 months, M: 9 months, C: 7 months, p = 0.58). MGMT methylation predicted for improved OS (median 25 vs. 13 months, p = 0.01), improved DFS (median 13 vs. 8 months, p = 0.007) and decreased 60 Gy (p = 0.003) and 46 Gy (p = 0.006) progression. There was a cohort of MGMT methylated patients with late marginal disease progression (4/22 patients, 18 %). TCGA groups demonstrated no difference in survival or progression patterns. MGMT methylation predicted for a statistically significant decrease in in-field and marginal disease progression. There was a cohort of MGMT methylated patients with late marginal progression. Validations of these findings would have implications that could affect radiation field size

    Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration

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    To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events

    Host Genetics and Chlamydia Disease: Prediction and Validation of Disease Severity Mechanisms

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    Genetic mapping studies may provide association between sequence variants and disease susceptibility that can, with further experimental and computational analysis, lead to discovery of causal mechanisms and effective intervention. We have previously demonstrated that polymorphisms in immunity-related GTPases (IRG) confer a significant difference in susceptibility to Chlamydia psittaci infection in BXD recombinant mice. Here we combine genetic mapping and network modeling to identify causal pathways underlying this association. We infected a large panel of BXD strains with C. psittaci and assessed host genotype, IRG protein polymorphisms, pathogen load, expression of 32 cytokines, inflammatory cell populations, and weight change. Proinflammatory cytokines correlated with each other and were controlled by a novel genetic locus on chromosome 1, but did not affect disease status, as quantified by weight change 6 days after infection In contrast, weight change correlated strongly with levels of inflammatory cell populations and pathogen load that were controlled by an IRG encoding genetic locus (Ctrq3) on chromosome 11. These data provided content to generate a predictive model of infection using a Bayesian framework incorporating genotypes, immune system parameters, and weight change as a measure of disease severity. Two predictions derived from the model were tested and confirmed in a second round of experiments. First, strains with the susceptible IRG haplotype lost weight as a function of pathogen load whereas strains with the resistant haplotype were almost completely unaffected over a very wide range of pathogen load. Second, we predicted that macrophage activation by Ctrq3 would be central in conferring pathogen tolerance. We demonstrated that macrophage depletion in strains with the resistant haplotype led to neutrophil influx and greater weight loss despite a lower pathogen burden. Our results show that genetic mapping and network modeling can be combined to identify causal pathways underlying chlamydial disease susceptibility

    The Protective Action Encoding of Serotonin Transients in the Human Brain

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    The role of serotonin in human brain function remains elusive due, at least in part, to our inability to measure rapidly the local concentration of this neurotransmitter. We used fast-scan cyclic voltammetry to infer serotonergic signaling from the striatum of fourteen brains of human patients with Parkinson's disease. Here we report these novel measurements and show that they correlate with outcomes and decisions in a sequential investment game. We find that serotonergic concentrations transiently increase as a whole following negative reward prediction errors, while reversing when counterfactual losses predominate. This provides initial evidence that the serotonergic system acts as an opponent to dopamine signaling, as anticipated by theoretical models. Serotonin transients on one trial were also associated with actions on the next trial in a manner that correlated with decreased exposure to poor outcomes. Thus, the fluctuations observed for serotonin appear to correlate with the inhibition of over-reactions and promote persistence of ongoing strategies in the face of short-term environmental changes. Together these findings elucidate a role for serotonin in the striatum, suggesting it encodes a protective action strategy that mitigates risk and modulates choice selection particularly following negative environmental events
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