519 research outputs found
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Does habitat stability structure intraspecific genetic diversity? It’s complicated...
Regional phylogeographic studies have long been conducted in the southeastern United States for a variety of species. With some exceptions, many of these studies focus on single species or single clades of organisms, and those considering multiple species tend to focus on deep historical breaks causing differentiation. However, in many species more recent factors may be influencing genetic diversity. To understand the roles of historic and contemporary processes in structuring genetic diversity, we reanalyzed existing genetic data from Southeast of North America using approaches gleaned from phylogeographic and landscape genetic literature that were implemented across species including AMOVAs, PCoAs, Species Distribution Modelling, and tests of isolation by distance, environment, and habitat instability. Genetic variance was significantly partitioned by ecoregions, watersheds, and across phylogeographic breaks in the majority of species. Similarly, genetic variation was significantly associated with some combination of geographic or environmental distance or habitat instability in most species. Patterns of genetic variation were largely idiosyncratic across species. While habitat instability over time is significantly correlated with genetic diversity in some species, it appears generally less important than isolation by geographic or environmental distance. Our results suggest that many factors, both historical and contemporary, impact genetic diversity within a species, and more so, that these patterns aren’t always similar in closely related species. This supports the importance of species- specific factors and cautions against assumptions that closely related species will respond to historical and contemporary forces in similar ways
Transient protein accumulation at the center of the T cell antigen-presenting cell interface drives efficient IL-2 secretion
Athletes’ Relationships with Training Scale (ART)
The Athletes’ Relationships with Training Scale (ART)* is a self-report measure of unhealthy training behaviors and beliefs in athletes. The ART was designed for use by clinicians and athletic trainers to help identify athletes who are engaging in unhealthy training practices which could be associated with an eating disorder. The ART may also be helpful for tracking clinical outcomes in athletes with eating disorders who are receiving treatment. This record contains the 15-item ART as well as scoring instructions and guidelines for interpreting total scores
Intimate mixtures of Scots pine and Sitka spruce do not increase resilience to spring drought
Understanding how we can increase the resilience of forest systems to future extreme drought events is increasingly important as these events become more frequent and intense. Diversifying production forests using intimate mixtures of trees with complementary functional traits is considered as one promising silvicultural approach that may increase drought resilience. However, the direction and magnitude of the drought response of mixed-species stands relative to monospecific stands of the same species can vary with species identity, relative abundance and levels of competition in a focal tree's immediate neighbourhood. Using a long-term experiment where tree-level mortality and the neighbourhood composition of each tree was known, we assessed the radial growth response of 24-year-old Scots pine (Pinus sylvestris) and Sitka spruce (Picea sitchensis) trees in intimately mixed and monospecific stands to a short-duration, high-intensity spring drought in Scotland. Mixing proportions included 25:75, 50:50 and 75:25 of P. sylvestris and P. sitchensis. At the species level, Scots pine was more drought resistant and resilient than Sitka spruce, while Sitka spruce showed higher recovery. Surprisingly, neither pre-drought tree size nor neighbourhood competition were significantly associated with resistance or resilience to drought, and trees of both species within monospecific stands showed higher recovery and resilience than trees growing in mixed stands. Our study suggests intimate mixtures of these two species may not be an effective way to mitigate the negative impacts of future extreme spring drought events. Given that these two species comprise almost 70% of coniferous forests in the UK, our results highlight the pressing need to better understand their vulnerability to drought and the conditions under which intimate mixtures of these species could be beneficial or detrimental. Such knowledge is essential if we are to enable forest managers to effectively plan how to adapt these forests to the challenges of a changing climate
An administrative data merging solution for dealing with missing data in a clinical registry: adaptation from ICD-9 to ICD-10
<p>Abstract</p> <p>Background</p> <p>We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance.</p> <p>Methods</p> <p>A multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year.</p> <p>Results</p> <p>The prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit.</p> <p>Conclusion</p> <p>The ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.</p
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