Abstract : We describe a new universal computing element for future embedded applications. Our polymorphic architecture contains course-grain reconfigurable processors, memory, and network. Each application is compiled into a set of programs for the nodes, and a set of configuration files for the chip. These configuration files optimize the chip for the kinds of tasks that the application demands, creating efficient SIMD engines for the stream-oriented portions of applications and efficient thread machines for the control-intensive portions. To efficiently program our polymorphic architecture, we created a number of abstract machine models that efficiently implement different models of computation and then created a set of virtual machine simulators to allow software development before the hardware was present. These virtual machine interfaces also allow an embedded system to evolve as new hardware or software components are added since they represent a stable, parameterized abstract interface between the hardware and the software.
Abstract Background: Systematic reviews of health economic evaluations (SR-HEs) provide a critical tool for synthesizing published literature to guide decision makers towards implementing evidence-based policy and healthcare practice. However, the quality of the methodology and reporting of SRs is often flawed due to insufficiencies in their design, conduct and reporting. Meta-research has led to methodological improvements in many research fields but is not widely established in health economic evidence synthesis. To enable future meta-research on SR-HEs, we will create a database of SR-HEs and provide a bibliometric analysis of this literature. Methods: We will perform a systematic search in MEDLINE for systematic reviews with/without meta-analyses of health economic evaluations. We will include studies that performed a systematic review of cost-effectiveness, cost-minimization, cost-utility, cost-benefit, and/or cost-consequence analyses. We will automatically extract data from Ovid MEDLINE and Web of Science to conduct a bibliometric analysis by examining publication, citation, and collaboration patterns. Discussion: Our study will provide a map of SR-HEs accompanied by a thorough bibliographic analysis of this research field. Our publicly accessible database can be used to assist future research and meta-research efforts in the field of health economics. Our bibliometric analysis will provide insights into the evolution of this research field over the years in terms of publications, citations, and scientific collaborations. Preregistration: 10.17605/OSF.IO/PV6XJ
Abstract We have generated a list of highly influential biomedical researchers based on Scopus citation data from the period 1996‐2011. Of the 15,153,100 author identifiers in Scopus, approximately 1% (n=149,655) have an h‐index >=20. Of those, we selected 532 authors who belonged to the 400 with highest total citation count (>=25,142 citations) and/or the 400 with highest h‐index (>=76). Of those, we selected the top‐400 living core biomedical researchers based on a normalized score combining total citations and h‐index. Another 62 authors whose focus is outside biomedicine had a normalized score that was at least as high as the score of the 400th core biomedical researcher. We provide information on the profile of these most influential authors, including the most common Medical Subject Heading terms in their articles that are also specific to their work, most common journals where they publish, number of papers with over 100 citations that they have published as first/single, last, or middle authors, and impact score adjusted for authorship positions, given that crude citation indices and authorship positions are almost totally orthogonal. We also show for each researcher the distribution of their papers across 4 main levels (basic‐to‐applied) of research. We discuss technical issues, limitations and caveats, comparisons against other lists of highly‐cited researchers, and potential uses of this resource.
Once daily administration of aminoglycosides in patients without pre-existing renal impairment is as effective as multiple daily dosing, has a lower risk of nephrotoxicity, and no greater risk of ototoxicity. Given the additional convenience and reduced cost, once daily dosing should be the preferred mode of administration.
ESR1 is a susceptibility gene for fractures, and XbaI determines fracture risk by mechanisms independent of BMD. Our study demonstrates the value of adequately powered studies with standardized genotyping and clinical outcomes in defining effects of common genetic variants on complex diseases.
<p>PDF - 45KB, Number of CEC papers in sub-areas of genomics by year.</p>
Abstract Purpose: Various studies examining the relationship between tumor suppressor protein TP53 overexpression and/or TP53 gene mutations and the response to chemotherapy and clinical outcome in patients with osteosarcoma have yielded inconclusive results. The purpose of the current study was to evaluate the relation of TP53 status with response to chemotherapy and/or clinical outcome in osteosarcoma. Experimental Design: We conducted a meta-analysis of 16 studies (n = 499 patients) that evaluated the correlation between TP53 status and histologic response to chemotherapy and 2-year survival. Data were synthesized in summary receiver operating characteristic curves and with summary likelihood ratios (LRs) and risk ratios. Results: The quantitative synthesis showed that TP53 status is not a prognostic factor for the response to chemotherapy. The positive LR was 1.21 (95% confidence interval, 0.86–1.71), and the negative LR was 0.91 (95% confidence interval, 0.77–1.07). There was no significant between-study heterogeneity. TP53-positive status tended to be associated with a worse 2-year survival, but the overall results were not formally statistically significant. The association was formally significant in studies that clearly stated that measurements were blinded to outcomes (risk ratio, 2.05; 95% confidence interval, 1.23–3.44), and in studies using reverse transcription-PCR for evaluating TP53 alterations (risk ratio, 1.76; 95% confidence interval, 1.07–2.91). Conclusions: TP53 status is not associated with the histologic response to chemotherapy in patients with osteosarcoma, whereas TP53 gene alterations may be associated with decreased survival.
