130,451 research outputs found
Bovine spongiform encephalopathy infection alters endogenous retrovirus expression in distinct brain regions of cynomolgus macaques (<it>Macaca fascicularis</it>)
No full textAbstract Background Prion diseases such as bovine spongiform encephalopathies (BSE) are transmissible neurodegenerative diseases which are presumably caused by an infectious conformational isoform of the cellular prion protein. Previous work has provided evidence that in murine prion disease the endogenous retrovirus (ERV) expression is altered in the brain. To determine if prion-induced changes in ERV expression are a general phenomenon we used a non-human primate model for prion disease. Results Cynomolgus macaques (Macaca fasicularis) were infected intracerebrally with BSE-positive brain stem material from cattle and allowed to develop prion disease. Brain tissue from the basis pontis and vermis cerebelli of the six animals and the same regions from four healthy controls were subjected to ERV expression profiling using a retrovirus-specific microarray and quantitative real-time PCR. We could show that Class I gammaretroviruses HERV-E4-1, ERV-9, and MacERV-4 increase expression in BSE-infected macaques. In a second approach, we analysed ERV-K-(HML-2) RNA and protein expression in extracts from the same cynomolgus macaques. Here we found a significant downregulation of both, the macaque ERV-K-(HML-2) Gag protein and RNA in the frontal/parietal cortex of BSE-infected macaques. Conclusions We provide evidence that dysregulation of ERVs in response to BSE-infection can be detected on both, the RNA and the protein level. To our knowledge, this is the first report on the differential expression of ERV-derived structural proteins in prion disorders. Our findings suggest that endogenous retroviruses may induce or exacerbate the pathological consequences of prion-associated neurodegeneration.</p
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
The R&D Tax Incentives
No full textThis article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&D tax incentives
Whole transcriptome analysis in brains from BSE-infected macaques
No full textPrion diseases are neurodegenerative disorders that affect both humans and animals. The molecular mechanisms underlying prion replication and subsequent degeneration of the central nervous system are still poorly understood. In an attempt to identify molecules that are putatively involved in the etiology of these diseases, we conducted a whole transcriptome analysis with brain tissue from BSE-infected and uninfected cynomolgus macaques (M. fascicularis). Total RNA from the gyrus frontalis region of seven BSE-infected and five noninfected control macaques was isolated. The integrity of the RNA was assessed using an Agilent 2100 Bioanalyzer. The RNA was reverse-transcribed, labeled and analyzed on an GeneChip® Rhesus Macaque Genome Array (Affymetrix) containing 52,024 Macaca mulatta probe sets to monitor the gene expression of approximately 47,000 transcripts. Bioinformatic analysis revealed that about 100 transcripts were significantly up-or down-regulated more than twofold. Beside others, we found up-regulation of α1-antichymotrypsin, which has also been described in scrapie-infected mice and Alzheimer’s disease. We are currently validating the most interesting candidates using quantitative RT-PCR. Our approach may help to identify genes that are crucial to prion disease processes and may become potential targets for diagnostic and therapeutic strategies
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