131,783 research outputs found
Discoidin Domain Receptor 1 is a novel modulator of megakaryocyte-collagen interactions
Growing evidence demonstrates that extracellular matrices regulate many aspects of megakaryocyte (MK) development; however, among the different extracellular matrix receptors, integrin alpha 2 beta 1 and glycoprotein VI are the only collagen receptors studied in platelets and MKs. In this study, we demonstrate the expression of the novel collagen receptor discoidin domain receptor 1 (DDR1) by human MKs at both mRNA and protein levels and provide evidence of DDR1 involvement in the regulation of MK motility on type I collagen through a mechanism based on the activity of SHP1 phosphatase and spleen tyrosine kinase (Syk). Specifically, we demonstrated that inhibition of DDR1 binding to type I collagen, preserving the engagement of the other collagen receptors, glycoprotein VI, alpha 2 beta 1, and LAIR-1, determines a decrease in MK migration due to the reduction in SHP1 phosphatase activity and consequent increase in the phosphorylation level of its main substrate Syk. Consistently, inhibition of Syk activity restored MK migration on type I collagen. In conclusion, we report the expression and function of a novel collagen receptor on human MKs, and we point out that an increasing level of complexity is necessary to better understand MK-collagen interactions in the bone marrow environment
MeSH term explosion and author rank improve expert recommendations
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
Donald Rubel speaking at dedication exercises of Ann Preston Hall
Unveiling of the Cornerstone and Dedication of Ann Preston Hall, Founders Day, March 11. Mr. Donald Rubel, Chairman of the Board of Corporators, is addressing the group. Seated on the platform are: Mrs. John B. Kelly, Dr. Irene E. Maher, President Louise Pearce, in foreground. In background, next to the cornerstone, can be sen Mr. Horace Fleisher, Dr. Russell E. Teague, Miss Alda L. Ditchfield. Standing in the front of the platform is Mrs. Anna D. Wolf, who gave the address at the Nurses Commencement and Capping
Going Beyond Counting First Authors in Author Co-citation Analysis
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"
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.
Dispelling the Myths Behind First-author Citation Counts
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
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
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
Renal Protective Effects of Aliskiren Beyond Its Antihypertensive Property in a Mouse Model of Progressive Fibrosis
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