15 research outputs found

    Remediation in Canadian medical residency programs: Established and emerging best practices

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    <p><b>Background:</b> Policies to guide remediation in postgraduate medical education exist in all Canadian medical schools. This study examines concordance between these policies and processes, and published “best practices” in remediation.</p> <p><b>Method:</b> We conducted a literature review to identify best practices in the area of remediation. We then reviewed remediation policies from all 13 English medical schools in Canada other than our own and conducted interviews with key informants from each institution. Each policy and interview transcript pair was then reviewed for evidence of pre-defined “best practices.” Team members also noted additional potential policy or process enablers of successful remediation.</p> <p><b>Results:</b> Most policies and processes aligned with <i>some</i> but not <i>all</i> published best practices. For instance, all participating schools tailored remediation strategies to individual resident needs, and a majority encouraged faculty-student relationships during remediation. Conversely, few required the teaching of goal-setting, strategic planning, self-monitoring, and self-awareness. In addition, we identified avoidance of automatic training extension and the use of an educational review board to support the remediation process as enablers for success.</p> <p><b>Discussion:</b> Remediation policies and practices in Canada align well with published best practices in this area. Based on key informant opinions, flexibility to avoid training extension and use of an educational review board may also support optimal remediation outcomes.</p

    Population structure inferred in STRUCTURE based on microsatellite data.

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    <p>Each genetic cluster is represented by a colour. Every individual is represented by a single vertical line with coloured segments depicting the estimated proportion of ancestry from a given cluster. a) Results from the analysis where individuals were grouped into populations <i>a priori</i>; K = 5. b) Results from the analysis where individuals were grouped into subspecies <i>a priori</i>; K = 6.</p

    Number of mitochondrial haplotypes and haplotype diversity values of each population.

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    <p>Idaho, Quebec and Georgia were excluded from the analysis since they were represented by less than five individuals.</p

    Pairwise Ѐ<sub>ST</sub> values between populations calculated from mitochondrial haplotype frequencies in Arlequin.

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    <p>Values significantly different in the exact tests of differentiation are in bold. Population abbreviations are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041058#pone-0041058-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041058#pone-0041058-g002" target="_blank">Figure 2</a>.</p

    Investigating Concordance among Genetic Data, Subspecies Circumscriptions and Hostplant Use in the Nymphalid Butterfly <em>Polygonia faunus</em>

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    <div><p>Subspecies are commonly used taxonomic units to formally describe intraspecific geographic variation in morphological traits. However, the concept of subspecies is not clearly defined, and there is little agreement about what they represent in terms of evolutionary units, and whether they can be used as reliably useful units in conservation, evolutionary theory and taxonomy. We here investigate whether the morphologically well-characterized subspecies in the North American butterfly <em>Polygonia faunus</em> are supported by genetic data from mitochondrial sequences and eight microsatellite loci. We also investigate the phylogeographic structure of <em>P. faunus</em> and test whether similarities in host-plant use among populations are related to genetic similarity. Neither the nuclear nor the mitochondrial data corroborated subspecies groupings. We found three well defined genetic clusters corresponding to California, Arizona and (New Mexico+Colorado). There was little structuring among the remaining populations, probably due to gene flow across populations. We found no support for the hypothesis that similarities in host use are related to genetic proximity. The results indicate that the species underwent a recent rapid expansion, probably from two glacial refugia in western North America. The mitochondrial haplotype network indicates at least two independent expansion phases into eastern North America. Our results clearly demonstrate that subspecies in <em>P. faunus</em> do not conform to the structuring of genetic variation. More studies on insects and other invertebrates are needed to better understand the scope of this phenomenon. The results of this study will be crucial in designing further experiments to understand the evolution of hostplant utilization in this species.</p> </div

    Pairwise F<sub>ST</sub> values between populations calculated from the microsatellite data.

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    <p>Numbers to the left of the diagonal are calculated in Arlequin without correcting for the presence of null alleles. Values in bold are significantly greater than zero. Numbers to the right of the diagonal are F<sub>ST</sub> values calculated in FreeNA after ENA correction for null alleles. Population abbreviations are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041058#pone-0041058-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041058#pone-0041058-g002" target="_blank">Figure 2</a>.</p

    Pairwise F<sub>ST</sub> values between subspecies calculated from the microsatellite data.

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    <p>Numbers to the left of the diagonal are calculated in Arlequin without correcting for the presence of null alleles. Values in bold are significantly greater than zero. Numbers to the right of the diagonal are F<sub>ST</sub> values calculated in FreeNA after ENA correction for null alleles.</p

    The statistical parsimony network of 35 <i>Polygonia faunus</i> mitochondrial haplotypes identified in the study, reconstructed using the software TCS v1.21.

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    <p>Each circle represents a haplotype and is approximately proportional in area to the number of individuals possessing the haplotype. The smallest circles represent missing haplotypes. Each haplotype is named using the following convention: The alphabets preceding the hyphen indicate the subspecies as listed in b), and the alphabets following the hyphen indicate the populations in which the haplotype was recovered, with each population abbreviated according to the list in d). Widespread haplotypes, i.e., those occurring in more than two populations, have a ‘WS’ after the hyphen. For the three haplotypes found in more than one subspecies, c) lists the numbers of individuals for each; d) is the legend to the patterns representing each population on the network.</p
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