223 research outputs found

    Evaluation of Serum 1,5 Anhydroglucitol Levels as a Clinical Test to Differentiate Subtypes of Diabetes

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    OBJECTIVE: Assignment of the correct molecular diagnosis in diabetes is necessary for informed decisions regarding treatment and prognosis. Better clinical markers would facilitate discrimination and prioritization for genetic testing between diabetes subtypes. Serum 1,5 anhydroglucitol (1,5AG) levels were reported to differentiate maturity-onset diabetes of the young due to HNF1A mutations (HNF1A-MODY) from type 2 diabetes, but this requires further validation. We evaluated serum 1,5AG in a range of diabetes subtypes as an adjunct for defining diabetes etiology. RESEARCH DESIGN AND METHODS: 1,5AG was measured in U.K. subjects with: HNF1A-MODY (n = 23), MODY due to glucokinase mutations (GCK-MODY, n = 23), type 1 diabetes (n = 29), latent autoimmune diabetes in adults (LADA, n = 42), and type 2 diabetes (n = 206). Receiver operating characteristic curve analysis was performed to assess discriminative accuracy of 1,5AG for diabetes etiology. RESULTS: Mean (SD range) 1,5AG levels were: GCK-MODY 13.06 microg/ml (5.74-29.74), HNF1A-MODY 4.23 microg/ml (2.12-8.44), type 1 diabetes 3.09 microg/ml (1.45-6.57), LADA 3.46 microg/ml (1.42-8.45), and type 2 diabetes 5.43 (2.12-13.23). Levels in GCK-MODY were higher than in other groups (P < 10(-4) vs. each group). HNF1A-MODY subjects showed no difference in unadjusted 1,5AG levels from type 2 diabetes, type 1 diabetes, and LADA. Adjusting for A1C revealed a difference between HNF1A-MODY and type 2 diabetes (P = 0.001). The discriminative accuracy of unadjusted 1,5AG levels was 0.79 for GCK-MODY versus type 2 diabetes and 0.86 for GCK-MODY versus HNF1A-MODY but was only 0.60 for HNF1A-MODY versus type 2 diabetes. CONCLUSIONS: In our dataset, serum 1,5AG performed well in discriminating GCK-MODY from other diabetes subtypes, particularly HNF1A-MODY. Measurement of 1,5AG levels could inform decisions regarding MODY diagnostic testing

    Using Semantic Web technologies in the development of data warehouses: A systematic mapping

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    The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043

    A unified framework for managing provenance information in translational research

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    <p>Abstract</p> <p>Background</p> <p>A critical aspect of the NIH <it>Translational Research </it>roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the <it>provenance </it>metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate "domain semantics", which is essential to support domain-specific querying and analysis by scientists.</p> <p>Results</p> <p>We identify a common set of challenges in managing provenance information across the <it>pre-publication </it>and <it>post-publication </it>phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata:</p> <p>(a) Provenance <b>collection </b>- during data generation</p> <p>(b) Provenance <b>representation </b>- to support interoperability, reasoning, and incorporate domain semantics</p> <p>(c) Provenance <b>storage </b>and <b>propagation </b>- to allow efficient storage and seamless propagation of provenance as the data is transferred across applications</p> <p>(d) Provenance <b>query </b>- to support queries with increasing complexity over large data size and also support knowledge discovery applications</p> <p>We apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for <it>Trypanosoma cruzi </it>(<it>T.cruzi </it>SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness.</p> <p>Conclusions</p> <p>The SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis.</p

    A multi-disciplinary perspective on emergent and future innovations in peer review [version 2; referees: 2 approved]

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    Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments

    A multi-disciplinary perspective on emergent and future innovations in peer review

    Get PDF
    Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments
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