821 research outputs found

    Rest Interval Length Does Not Affect Total Exercise Volume During Lower Body Resistance Training

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    Please refer to the pdf version of the abstract located adjacent to the title

    Challenges of open innovation: the paradox of firm investment in open-source software

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    Open innovation is a powerful framework encompassing the generation, capture, and employment of intellectual property at the firm level. We identify three fundamental challenges for firms in applying the concept of open innovation: finding creative ways to exploit internal innovation, incorporating external innovation into internal development, and motivating outsiders to supply an ongoing stream of external innovations. This latter challenge involves a paradox, why would firms spend money on R&D efforts if the results of these efforts are available to rival firms? To explore these challenges, we examine the activity of firms in opensource software to support their innovation strategies. Firms involved in open-source software often make investments that will be shared with real and potential rivals. We identify four strategies firms employ – pooled R&D/product development, spinouts, selling complements and attracting donated complements – and discuss how they address the three key challenges of open innovation. We conclude with suggestions for how similar strategies may apply in other industries and offer some possible avenues for future research on open innovation

    A quantitatively-modeled homozygosity mapping algorithm, qHomozygosityMapping, utilizing whole genome single nucleotide polymorphism genotyping data

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    Homozygosity mapping is a powerful procedure that is capable of detecting recessive disease-causing genes in a few patients from families with a history of inbreeding. We report here a homozygosity mapping algorithm for high-density single nucleotide polymorphism arrays that is able to (i) correct genotyping errors, (ii) search for autozygous segments genome-wide through regions with runs of homozygous SNPs, (iii) check the validity of the inbreeding history, and (iv) calculate the probability of the disease-causing gene being located in the regions identified. The genotyping error correction restored an average of 94.2% of the total length of all regions with run of homozygous SNPs, and 99.9% of the total length of them that were longer than 2 cM. At the end of the analysis, we would know the probability that regions identified contain a disease-causing gene, and we would be able to determine how much effort should be devoted to scrutinizing the regions. We confirmed the power of this algorithm using 6 patients with Siiyama-type α1-antitrypsin deficiency, a rare autosomal recessive disease in Japan. Our procedure will accelerate the identification of disease-causing genes using high-density SNP array data

    Learners' decisions for attending Pediatric Grand Rounds: a qualitative and quantitative study

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    BACKGROUND: Although grand rounds plays a major educational role at academic medical centers, there has been little investigation into the factors influencing the learners' decision to attend. Greater awareness of attendees' expectations may allow grand rounds planners to better accommodate the learners' perspective, potentially making continuing education activities more attractive and inviting. METHODS: We used both qualitative (part A) and quantitative (part B) techniques to investigate the motivators and barriers to grand rounds attendance. Part A investigated contextual factors influencing attendance as expressed through attendee interviews. Transcripts of the interviews were analyzed using grounded theory techniques. We created a concept map linking key factors and their relationships. In part B we quantified the motivators and barriers identified during the initial interviews through a survey of the grand rounds audience. RESULTS: Sixteen persons voluntarily took part in the qualitative study (part A) by participating in one of seven group interview sessions. Of the 14 themes that emerged from these sessions, the most frequent factors motivating attendance involved competent practice and the need to know. All sessions discussed intellectual stimulation, social interaction, time constraints and convenience, licensure, content and format, and absence of cost for attending sessions. The 59 respondents to the survey (part B) identified clinically-useful topics (85%), continuing education credit (46%), cutting-edge research (27%), networking (22%), and refreshments (8%) as motivators and non-relevant topics (44%) and too busy to attend (56%) as barriers. CONCLUSION: Greater understanding of the consumers' perspective can allow planners to tailor the style, content, and logistics to make grand rounds more attractive and inviting

    Severe aortic and arterial aneurysms associated with a TGFBR2 mutation.

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    BACKGROUND: A 24-year-old man presented with previously diagnosed Marfan\u27s syndrome. Since the age of 9 years, he had undergone eight cardiovascular procedures to treat rapidly progressive aneurysms, dissection and tortuous vascular disease involving the aortic root and arch, the thoracoabdominal aorta, and brachiocephalic, vertebral, internal thoracic and superior mesenteric arteries. Throughout this extensive series of cardiovascular surgical repairs, he recovered without stroke, paraplegia or renal impairment. INVESTIGATIONS: CT scans, arteriogram, genetic mutation screening of transforming growth factor beta receptors 1 and 2. DIAGNOSIS: Diffuse and rapidly progressing vascular disease in a patient who met the diagnostic criteria for Marfan\u27s syndrome, but was later rediagnosed with Loeys-Dietz syndrome. Genetic testing also revealed a de novo mutation in transforming growth factor beta receptor 2. MANAGEMENT: Regular cardiovascular surveillance for aneurysms and dissections, and aggressive surgical treatment of vascular disease

    A computational approach to chemical etiologies of diabetes.

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    Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases

    A population-specific reference panel empowers genetic studies of Anabaptist populations

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    Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server

    CSI-OMIM - Clinical Synopsis Search in OMIM

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    <p>Abstract</p> <p>Background</p> <p>The OMIM database is a tool used daily by geneticists. Syndrome pages include a Clinical Synopsis section containing a list of known phenotypes comprising a clinical syndrome. The phenotypes are in free text and different phrases are often used to describe the same phenotype, the differences originating in spelling variations or typing errors, varying sentence structures and terminological variants.</p> <p>These variations hinder searching for syndromes or using the large amount of phenotypic information for research purposes. In addition, negation forms also create false positives when searching the textual description of phenotypes and induce noise in text mining applications.</p> <p>Description</p> <p>Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic information using UMLS and MESH. Using a grammar based method, annotated phrases are clustered into groups denoting similar phenotypes. These groups of synonymous expressions enable precise search, as query terms can be matched with the many variations that appear in OMIM, while avoiding over-matching expressions that include the query term in a negative context. On the basis of these clusters, we computed pair-wise similarity among syndromes in OMIM. Using this new similarity measure, we identified 79,770 new connections between syndromes, an average of 16 new connections per syndrome. Our project is Web-based and available at <url>http://fohs.bgu.ac.il/s2g/csiomim</url></p> <p>Conclusions</p> <p>The resulting enhanced search functionality provides clinicians with an efficient tool for diagnosis. This search application is also used for finding similar syndromes for the candidate gene prioritization tool S2G.</p> <p>The enhanced OMIM database we produced can be further used for bioinformatics purposes such as linking phenotypes and genes based on syndrome similarities and the known genes in Morbidmap.</p
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