130,516 research outputs found
Detection of latent tuberculosis in immunosuppressed patients with autoimmune diseases: performance of a Mycobacterium tuberculosis antigen-specific interferon gamma assay
No full textOBJECTIVE: To analyse the performance of a new M. tuberculosis-specific interferon gamma (IFNgamma) assay in patients with chronic inflammatory diseases who receive immunosuppressive drugs, including tumour necrosis factor alpha (TNFalpha) inhibitors. METHODS: Cellular immune responses to the M. tuberculosis-specific antigens ESAT-6, CFP-10, TB7.7 were prospectively studied in 142 consecutive patients treated for inflammatory rheumatic conditions. Results were compared with tuberculin skin tests (TSTs). Association of both tests with risk factors for latent M. tuberculosis infection (LTBI) and BCG vaccination were determined and the influence of TNFalpha inhibitors, corticosteroids, and disease modifying antirheumatic drugs (DMARDs) on antigen-specific and mitogen-induced IFNgamma secretion was analysed. RESULTS: 126/142 (89%) patients received immunosuppressive therapy. The IFNgamma assay was more closely associated with the presence of risk factors (odds ratio (OR) = 23.8 (95% CI 5.14 to 110) vs OR = 2.77 (1.22 to 6.27), respectively; p = 0.009), but less associated with BCG vaccination than the TST (OR = 0.47 (95% CI 0.15 to 1.47) vs OR = 2.44 (0.74 to (8.01), respectively; p = 0.025). Agreement between the IFNgamma assay and TST results was low (kappa = 0.17; 95% CI 0.02 to 0.32). The odds for a positive IFNgamma assay strongly increased with increasing prognostic relevance of LTBI risk factors. Neither corticosteroids nor conventional DMARDs significantly affected IFNgamma responses, but the odds for a positive IFNgamma assay were decreased in patients treated with TNFalpha inhibitors (OR = 0.21 (95% CI 0.07 to 0.63), respectively; p = 0.006). CONCLUSIONS: These results demonstrate that the performance of the M. tuberculosis antigen-specific IFNgamma ELISA is better than the classic TST for detection of LTBI in patients receiving immunosuppressive therapy for treatment of systemic autoimmune disorders
Biphenyl substituted lysine derivatives as recognition elements for the matrix metalloproteinases MMP-2 and MMP-9
No full textMatrix metalloproteinases (MMPs) are an important factor in cancer progression and metastasis, especially gelatinases MMP-2 and MMP-9. A simple methodology for their detection and monitoring is highly desirable. Molecular probes have been very widely and successfully applied to study the activity of MMPs in cellular processes in vitro. We thus synthesized a small compound library of MMP-2 and MMP-9 binding probes based on drug molecules and endowed with free amine groups for the functionalization of transducer surfaces. In this study, we combined experimental results obtained by a kinetic fluorogenic peptide substrate cleavage assay with molecular modeling studies in order to assess the ability of the probe to bind to their target enzymes. The synthesized biphenyl substituted lysine derivatives showed IC50-values in the low nanomolar concentration range against MMP-2 (ligands 3a-d: 3 nM to 8 μM, ligands 4a-d: 45 nM to 350 μM) and low micromolar range against MMP-9 (ligands 3a-d: 350 nM to 60 μM, ligands 4a-d: 5 μM to 600 μM), with a selectivity up to more than 160-fold for MMP-2. The experimental results correlated well with molecular modelling with FleXAID and X-score functions. We showed that in our compound series, the side chain remained far away from the S1′ cavity and the ligand for all the docked minima. Ligands 4a-d with their free amine group on the side chain may thus be bound to transducer surfaces for the fabrication of sensors, while retaining their activity against their target enzymes
MeSH term explosion and author rank improve expert recommendations
Get PDFInformation 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
Get PDFThe 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"
Get PDFBoth 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.
Natural variations at position 93 of the invariant Va24-Ja18 alpha chain of human iNKT cell TCRs strongly impact on CD1d binding
No full textHuman invariant natural killer T (NKT) cell TCRs bind to CD1d via an "invariant" Vá24-Já18 chain (iNKTá) paired to semi-invariant V?11 chains (iNKTâ). Single-amino acid variations at position 93 (p93) of iNKTá, immediately upstream of the “invariant” CDR3á region, have been reported in a substantial proportion of human iNKT cell clones (4-30%). Although p93, a serine in most human iNKT cell TCRs, makes no contact with CD1d, it could affect CD1d-binding by altering the conformation of the crucial CDR3á loop. By generating recombinant refolded iNKT cell TCRs, we show that natural single-nucleotide variations in iNKTá, translating to serine, threonine, asparagine or isoleucine at p93, exert a powerful effect on CD1d binding, with up to 28-fold differences in affinity between these variants. This effect was observed with CD1d loaded with either the artificial á-galactosylceramide antigens KRN7000 or OCH, or the endogenous glycolipid â-galactosylceramide, and its importance for autoreactive recognition of endogenous lipids was demonstrated by the binding of variant iNKT cell TCR tetramers to cell-surface expressed CD1d. The serine-containing variant showed the strongest CD1d-binding, offering an explanation for its predominance in vivo. Complementary molecular dynamics modeling studies were consistent with an impact of p93 on the conformation of the CDR3á loo
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
Mobility function after total hip replacement surgery recovery prediction of statistical analysis methods
No full textMatulis G. Mobility function after total hip replacement surgery recovery prediction of statistical analysis methods, master thesis / research adviser: Ph. D. L. Pauliukėnas; Lithuanian University of Health Scien-ces, Faculty of Medicine, Department of Physics, Mathematics and Biophysics. - Kaunas, 2017 - 49 s. The aim: to find basic statistical analysis of prognostic factors that best describes the mobility function recovery after hip replacement surgery. Research objectives: 1. For the purposes of statistical analysis techniques to identify predictors of attributes that best describes the function: 1.1 postural change and maintenance; 1.2 the seizure of items, storage and maintenance; 1.3 turn and move; 1.4 the movement in transportation. 2. For the purposes of statistical analysis methods provide assessment identified mobility features. 3. The results are compared with the control group. Research methods: physical examination, evaluation of certain criteria, questionnaire, statistical data analysis. The questionnaire evaluated for hip mobility, making certain movements. Systematic study material using the statistical software package. The participants: Patients (men and women) from 38 m. up to 87 m. Results: A questionnaire was developed based on the scientific literature. The survey questionnaire prepared by integrating the International Functioning, Disability and Health classification of the questionnaire scales, choosing “I can move freely”, “have difficulty”, “can not move”. The questionnaire we applied in practice. The completed questionnaire by email after 3 weeks was recovered and investigators performed the data analysis. Conclusions: 1.1. The application of statistical methods for the analysis found that postural change and retention of the best predictors of daily operational features. 1.2. It was found that the seizure of items, storage and retention of the best predictors of daily activities characterizing features. 1.3. It was found that the turn and movement of the best predictors of daily activities characterizing features. 1.4. It was found that the movement of transport using the best predictors of daily activities characterizing features. 2. The analysis identified three possible values that describe recovery and provides mobility assessment: “I can move freely”, “have difficulty” and “can not move”. 3. The results confirmed the expediency of the questionnaire
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