Comorbidities Of Skin Disease In The Homeless And Medical Students Perspectives

The homeless population is at increased risk for skin disease. Exposure to the elements and lack of access to medical care contribute to the problem. To date there have been few studies analyzing the medical comorbidities that put homeless patients at increased risk for skin disease. The aim of this study is to discover what medical conditions are associated with skin disease to allow physicians to better screen their homeless patients for skin disease. The secondary aim of this study is to determine whether medical students are being adequately trained to recognize medical conditions associated with skin disease. Data from the Collaborative Initiative to Help End Chronic Homelessness (CICH) was used to look for diseases associated with skin conditions in the homeless population. Positive correlations with hearing problems, bronchitis, adjustment reaction disorder and eye problems were found. Medical students did not generally identify these as correlated with skin disease. Numerous social conditions were associated with skin disease, with medical students identifying some, but not others. When seen in a homeless patient, these conditions should signal the clinician to screen for skin disease

Haplotype structure in commercial maize breeding programs in relation to key founder lines

Key message High-density haplotype analysis revealed significant haplotype sharing between ex-PVPs registered from 1976 to 1992 and key maize founders, and uncovered similarities and differences in haplotype sharing patterns by company and heterotic group. Abstract Proprietary inbreds developed by the private seed industry have been the major source for driving genetic gain in successful North American maize hybrids for decades. Much of the history of industry germplasm can be traced back to key founder lines, some of which were pivotal in the development of prominent heterotic groups. Previous studies have summarized pedigree-based relationships, genetic diversity and population structure among commercial inbreds with expired Plant Variety Protection (ex-PVP). However, less is known about the extent of haplotype sharing between historical founders and ex-PVPs. A better understanding of the relationships between founders and ex-PVPs provides insight into the haplotype and heterotic group structure among industry germplasm. We performed high-density haplotype analysis with 11.3 million SNPs on 212 maize inbreds, which included 157 ex-PVPs registered 1976–1992 and 55 public lines relevant to PVPs. Among these lines were 12 key founders identified in literature review: 207, A632, B14, B37, B73, LH123HT, LH82, Mo17, Oh43, OH7, PHG39 and Wf9. Our results revealed that, on average, 81.6% of an ex-PVP’s genome is shared with at least 1 of these 12 founder lines and more than half when limited to B73, Mo17 and 207. Quantifiable similarities and contrasts among heterotic groups and major US seed industry companies were also observed. The results from this study provide high-resolution haplotype data on ex-PVP germplasm, confirm founder relationship trends observed in previous studies, uncover region-specific haplotype structure differences and demonstrate how haplotype sharing analysis can be used as a tool to explore germplasm diversity

Creating an Online CME Module: Early Detection and Diagnosis of Dementia and Alzheimer’s Disease

Introduction. The number of individuals living with dementia and Alzheimer’s disease (AD) in the United States is growing annually; only 40% are properly diagnosed. Primary care providers should identify individuals with cognitive impairment and provide options for care; early diagnosis of dementia and AD helps patients and families plan for the future, increases quality of life, and allows for treatment options.https://scholarworks.uvm.edu/comphp_gallery/1192/thumbnail.jp

Impacts of Geographic Distance on Peritoneal Dialysis Utilization: Refining Models of Treatment Selection

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/1/hesr12489.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/2/hesr12489-sup-0001-AuthorMatrix.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/3/hesr12489_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/4/hesr12489-sup-0002-Appendix.pd

Contrasting influences of Drosophila white/mini-white on ethanol sensitivity in two different behavioral assays

Background The fruit fly Drosophila melanogaster has been used extensively to investigate genetic mechanisms of ethanol-related behaviors. Many past studies in flies, including studies from our laboratory, have manipulated gene expression using transposons carrying the genetic-phenotypic marker mini-white, a derivative of the endogenous gene white. Whether the mini-white transgenic marker or the endogenous white gene influence behavioral responses to acute ethanol exposure in flies has not been systematically investigated. Methods We manipulated mini-white and white expression via (i) transposons marked with mini-white, (ii) RNAi against mini-white and white and (iii) a null allele of white. We assessed ethanol sensitivity and tolerance using a previously described eRING assay (based on climbing in the presence of ethanol) and an assay based on ethanol-induced sedation. Results In eRING assays, ethanol-induced impairment of climbing correlated inversely with expression of the mini-white marker from a series of transposon insertions. Additionally, flies harboring a null allele of white or flies with RNAi-mediated knockdown of mini-white were significantly more sensitive to ethanol in eRING assays than controls expressing endogenous white or the mini-white marker. In contrast, ethanol sensitivity and rapid tolerance measured in the ethanol sedation assay were not affected by decreased expression of mini-white or endogenous white in flies. Conclusions Ethanol sensitivity measured in the eRING assay is noticeably influenced by white and mini-white, making eRING problematic for studies on ethanol-related behavior in Drosophila using transgenes marked with mini-white. In contrast, the ethanol sedation assay described here is a suitable behavioral paradigm for studies on ethanol sedation and rapid tolerance in Drosophila including those that use widely available transgenes marked with mini-white

Unexpected Learning: Development of the CoP and Its Members #generational-shift

Our research explores how multigenerational CoPs may provide graduate students, particularly doctoral students, the space to explore and develop their professional identities and find their scholarly voices

DGIdb 5.0: Rebuilding the Drug-Gene Interaction Database for precision medicine and drug discovery platforms

The Drug-Gene Interaction Database (DGIdb, https://dgidb.org) is a publicly accessible resource that aggregates genes or gene products, drugs and drug-gene interaction records to drive hypothesis generation and discovery for clinicians and researchers. DGIdb 5.0 is the latest release and includes substantial architectural and functional updates to support integration into clinical and drug discovery pipelines. The DGIdb service architecture has been split into separate client and server applications, enabling consistent data access for users of both the application programming interface (API) and web interface. The new interface was developed in ReactJS, and includes dynamic visualizations and consistency in the display of user interface elements. A GraphQL API has been added to support customizable queries for all drugs, genes, annotations and associated data. Updated documentation provides users with example queries and detailed usage instructions for these new features. In addition, six sources have been added and many existing sources have been updated. Newly added sources include ChemIDplus, HemOnc, NCIt (National Cancer Institute Thesaurus), Drugs@FDA, HGNC (HUGO Gene Nomenclature Committee) and RxNorm. These new sources have been incorporated into DGIdb to provide additional records and enhance annotations of regulatory approval status for therapeutics. Methods for grouping drugs and genes have been expanded upon and developed as independent modular normalizers during import. The updates to these sources and grouping methods have resulted in an improvement in FAIR (findability, accessibility, interoperability and reusability) data representation in DGIdb

Automating the packing heuristic design process with genetic programming

The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains