130,480 research outputs found

    MeSH term explosion and author rank improve expert recommendations

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    Information 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

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    The 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"

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    Both 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.

    A. D. Fricke, author

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    Black and white photograph of author, A. D. Fricke

    Dispelling the Myths Behind First-author Citation Counts

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    We 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

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    At 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

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    This 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

    IL15 induces a potent antitumor activity in NK cells isolated from malignant pleural effusions and overcomes the inhibitory effect of pleural fluid

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    Natural Killer (NK) cells are capable of recognizing and killing cancer cells and play an important role in tumor immunosurveillance. However, tumor-infiltrating NK cells are frequently impaired in their functional capability. A remarkable exception is represented by NK cells isolated from malignant pleural effusions (PE) that are not anergic and, upon IL2-induced activation, efficiently kill tumor cells. Although IL2 is used in various clinical trials, severe side effects may occur in treated patients. In this study, we investigated whether also other clinical-grade cytokines could induce strong cytotoxicity in NK cells isolated from pleural fluid of patients with primary or metastatic tumors of different origins. We show that PE-NK cells, cultured for short-time intervals with IL15, maintain the CD56brightphenotype, a high expression of the main activating receptors, produce cytokines and kill tumor cells in vitro similarly to those treated with IL2. Moreover, IL15-activated PE-NK cells could greatly reduce the growth of established tumors in mice. This in vivo antitumor effect correlated with the ability of IL15-activated PE-NK cells to traffic from periphery to the tumor site. Finally, we show that IL15 can counteract the inhibitory effect of the tumor pleural microenvironment. Our study suggests that IL15-activated NK cells isolated from pleural fluid (otherwise discarded after thoracentesis) may represent a suitable source of effector cells to be used in adoptive immunotherapy of cancer

    Identification of diverse innate lymphoid cells in human decidua.

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    Innate lymphoid cells (ILCs) are developmentally related cells that play an important role in innate defenses and tissue remodeling. So far, only natural killer (NK) cells have been identified and functionally characterized in human decidua where they contribute to induction of immune suppression, neo-angiogenesis, and tissue building/remodeling. The presence of other ILC subsets in human decidua has not been yet characterized. Here we identify in human decidua, during early pregnancy, two subsets of decidual group 3 ILC (ILC3), including lymphoid tissue inducer (LTi)-like cells and natural cytotoxicity receptors (NCRs)(+)ILC3 and interferon-(IFN)γ-producing ILC1, different from NK cells. Decidual LTi-like cells produced interleukin -17 (IL-17) and tumor necrosis factor (TNF), while NCR(+)ILC3 released IL-22 and IL-8. Importantly, NCR(+)ILC3 and LTi-like cells established functional interactions with stromal cells. Decidual LTi-like cells differentiated into NCR(+)ILC3, whereas they marginally contributed to NK cell generation. Our data suggest that decidual ILC3 may play a role in innate defenses and in vessel and tissue building, thus contributing to maintenance of pregnancy.Mucosal Immunology advance online publication, 23 July 2014; doi:10.1038/mi.2014.63
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