268 research outputs found

    SysZNF: the C2H2 zinc finger gene database

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    C2H2 zinc finger (C2H2-ZNF) genes are one of the largest and most complex gene super-families in metazoan genomes, with hundreds of members in the human and mouse genome. The ongoing investigation of this huge gene family requires computational support to catalog genotype phenotype comparisons of C2H2-ZNF genes between related species and finally to extend the worldwide knowledge on the evolution of C2H2-ZNF genes in general. Here, we systematically collected all the C2H2-ZNF genes in the human and mouse genome and constructed a database named SysZNF to deposit available datasets related to these genes. In the database, each C2H2-ZNF gene entry consists of physical location, gene model (including different transcript forms), Affymetrix gene expression probes, protein domain structures, homologs (and synteny between human and mouse), PubMed references as well as links to relevant public databases. The clustered organization of the C2H2-ZNF genes is highlighted. The database can be searched using text strings or sequence information. The data are also available for batch download from the web site. Moreover, the graphical gene model/protein view system, sequence retrieval system and some other tools embedded in SysZNF facilitate the research on the C2H2 type ZNF genes under an integrative view. The database can be accessed from the URL http://epgd.biosino.org/SysZNF

    RA-specific expression profiles and new candidate genes

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    Objective: To identify rheumatoid arthritis- (RA)-specific profiles of differentially expressed genes. Methods: Synovial tissues from RA and osteoarthritis (OA) patients and from normal joints were selected according to their disease-characteristic histology. Gene expression was analyzed using DNA microarrays (GeneChip; Unigene-array) and representational difference analysis (RDA). Data were validated on larger cohorts of patients by RT-PCR. Results: Nine hundred and eighty genes were significantly regulated in RA synovial tissue as compared with non-RA. Specialized cluster analysis identified a set of 312 genes as sufficient of unequivocally discriminating RA from non-RA patterns (class discovery). Genes of highest regulation were associated with leukocyte activation (chemokines, chemokine receptors, B- and T-cell genes), endothelial and angiogenic activation, tissue destruction and remodelling [MMP-3, BMP-4, TIMPs]. Interestingly, a large set of genes was down-regulated in RA (TGF-ÎČ superfamily, apoptosis-related genes, transcription factors). Osteopontin-like genes (n=46) — up-regulated in RA — and glutathione peroxidase-3-like genes (n=85) — down-regulated in RA — yielded the highest correlation coefficients (>0.94). Megakaryocyte stimulating factor (MSF), down-regulated in a subset of RA, may hold the key to subclassification: a loss-of-function mutation in the MSF-encoding gene leads to synovial hyperplasia in camptodactyly–arthropathy–coxa vara–pericarditis syndrome, and, as in RA, also to pericardial involvement. A further candidate, vitamin-D3-up-regulated protein-1 (VDUP-1), is regulated like MSF and predisposes to premature coronary artery disease when mutated, again a feature of a subset of RA. Conclusion: RA specific gene profiles were identified and are useful to improve diagnostics of the disease. Novel gene candidates not yet in the focus of RA pathogenesis have been identified that are likely to further the understanding of RA

    Development of the Liverpool Adverse Drug Reaction Avoidability Assessment Tool

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    Aim To develop and test a new tool to assess the avoidability of adverse drug reactions that is suitable for use in paediatrics but which is also applicable to a variety of other settings. Methods The study involved multiple phases. Preliminary work involved using the Hallas scale and a modification of the existing Hallas scale, to assess two different sets of adverse drug reaction (ADR) case reports. Phase 1 defined, modified and refined a new tool using multidisciplinary teams. Phase 2 involved the assessment of 50 ADR case reports from a prospective study of paediatric inpatients by individual assessors. Phase 3 compared assessments with the new tool for individuals and groups in comparison to the ‘gold standard’ (the avoidability outcome set by a panel of senior investigators: an experienced clinical pharmacologist, paediatrician and pharmacist). Main Outcome Measures Inter-rater reliability (IRR), measure of disagreement and utilization of avoidability categories. Results Preliminary work—Pilot phase: results for the original Hallas cases were fair and pairwise kappa scores ranged from 0.21 to 0.36. Results for the modified Hallas cases were poor, pairwise kappa scores ranged from 0.06 to 0.16. Phase 1: on initial use of the new tool, agreement between the two multidisciplinary groups was found on 13/20 cases with a kappa score of 0.29 (95% CI -0.04 to 0.62). Phase 2: the assessment of 50 ADR case reports by six individual reviewers yielded pairwise kappa scores ranging from poor to good 0.12 to 0.75 and percentage exact agreement (%EA) ranged from 52–90%. Phase 3: Percentage exact agreement ranged from 35–70%. Overall, individuals had better agreement with the ‘gold standard’. Conclusion Avoidability assessment is feasible but needs careful attention to methods. The Liverpool ADR avoidability assessment tool showed mixed IRR. We have developed and validated a method for assessing the avoidability of ADRs that is transparent, more objective than previous methods and that can be used by individuals or groups

    A Large Hadron Electron Collider at CERN

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    This document provides a brief overview of the recently published report on the design of the Large Hadron Electron Collider (LHeC), which comprises its physics programme, accelerator physics, technology and main detector concepts. The LHeC exploits and develops challenging, though principally existing, accelerator and detector technologies. This summary is complemented by brief illustrations of some of the highlights of the physics programme, which relies on a vastly extended kinematic range, luminosity and unprecedented precision in deep inelastic scattering. Illustrations are provided regarding high precision QCD, new physics (Higgs, SUSY) and electron-ion physics. The LHeC is designed to run synchronously with the LHC in the twenties and to achieve an integrated luminosity of O(100) fb−1^{-1}. It will become the cleanest high resolution microscope of mankind and will substantially extend as well as complement the investigation of the physics of the TeV energy scale, which has been enabled by the LHC

    Methods to detect faulty splices in the superconducting magnet system of the LHC

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    The incident of 19 September 2008 at the LHC was caused by a faulty inter-magnet splice of about 200 nΩ resistance. Cryogenic and electrical techniques have been developed to detect other abnormal splices, either between or inside the magnets. The existing quench protection system can be used to detect internal splices with R>20 nΩ. Since this system does not cover the bus between magnets, the cryogenic system is used to measure the rate of temperature rise due to ohmic heating. Accuracy of a few mK/h, corresponding to a few Watts, has been achieved, allowing detection of excess resistance, if it is more than 40 nΩ in a cryogenic subsector (two optical cells). Follow-up electrical measurements are made in regions identified by the cryogenic system. These techniques have detected two abnormal internal magnet splices of 100 nΩ and 50 nΩ respectively. In 2009, this ad hoc system will be replaced with a permanent one to monitor all splices at the nΩ level

    Investigating the potential for students to contribute to climate data rescue: Introducing the Climate Data Rescue Africa project (CliDaR‐Africa)

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    The majority of available climate data in global digital archives consist of data only from the 1940s or 1950s onwards, and many of these series have gaps and/or are available for only a subset of the variables which were actually observed. However, there exist billions of historical weather observations from the 1700s, 1800s, and early 1900s that are still in hard- copy form and are at risk of being lost forever due to deterioration. An assessment of changes in climate extremes in several IPCC regions was not possible in IPCC AR6 WGI owing, in many cases, to the lack of available data. One such region is Africa, where the climate impact research and the ability to predict climate change impacts are hindered by the paucity of access to consistent good- quality historical observational data. The aim of this innovative project was to use classroom- based participatory learning to help transcribe some of the many meteorological observations from Africa that are thus far unavailable to researchers. This project transcribed quickly and ef-fectively station series by enrolling the help of second- year undergraduate stu-dents at Maynooth University in Ireland. The newly digitized African data will increase the temporal and spatial coverage of data in this important data- sparse region. Students gained new skills while helping the global scientific community unearth new insight into past African climate. The project managed to transcribe 79 months of data at Andapa in Madagascar and 56 months of data for Macenta in Guinea. The digitized data will be openly and freely shared with the scientific and wider community via the Pangaea data repository, the C3S Climate Data Store, and the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) data centre in the US. The pro-ject model has the potential for a broader roll- out to other educational contexts and there is no shortage of data to be rescued. This paper provides details of the project, and all supporting information such as project guidelines and templates to enable other organizations to instigate similar programs

    Robust computational reconstitution – a new method for the comparative analysis of gene expression in tissues and isolated cell fractions

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    BACKGROUND: Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-specific gene expression under diverse conditions is therefore a central aim of biomedical research. The present study compares gene expression profiles in whole tissues and isolated cell fractions purified from these tissues in patients with rheumatoid arthritis and osteoarthritis. RESULTS: The expression profiles of the whole tissues were compared to computationally reconstituted expression profiles that combine the expression profiles of the isolated cell fractions (macrophages, fibroblasts, and non-adherent cells) according to their relative mRNA proportions in the tissue. The mRNA proportions were determined by trimmed robust regression using only the most robustly-expressed genes (1/3 to 1/2 of all measured genes), i.e. those showing the most similar expression in tissue and isolated cell fractions. The relative mRNA proportions were determined using several different chip evaluation methods, among which the MAS 5.0 signal algorithm appeared to be most robust. The computed mRNA proportions agreed well with the cell proportions determined by immunohistochemistry except for a minor number of outliers. Genes that were either regulated (i.e. differentially-expressed in tissue and isolated cell fractions) or robustly-expressed in all patients were identified using different test statistics. CONCLUSION: Robust Computational Reconstitution uses an intermediate number of robustly-expressed genes to estimate the relative mRNA proportions. This avoids both the exclusive dependence on the robust expression of individual, highly cell type-specific marker genes and the bias towards an equal distribution upon inclusion of all genes for computation
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