9 resultados para project database

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As part of a collaborative project on the epidemiology of craniofacial anomalies, funded by the National Institutes for Dental and Craniofacial Research and channeled through the Human Genetics Programme of the World Health Organization, the International Perinatal Database of Typical Orofacial Clefts (IPDTOC) was established in 2003. IPDTOC is collecting case-by-case information on cleft lip with or without cleft palate and on cleft palate alone from birth defects registries contributing to at least one of three collaborative organizations: European Surveillance Systems of Congenital Anomalies (EUROCAT) in Europe, National Birth Defects Prevention Network (NBDPN) in the United States, and International Clearinghouse for Birth Defects Surveillance and Research (ICBDSR) worldwide. Analysis of the collected information is performed centrally at the ICBDSR Centre in Rome, Italy, to maximize the comparability of results. The present paper, the first of a series, reports data on the prevalence of cleft lip with or without cleft palate from 54 registries in 30 countries over at least 1 complete year during the period 2000 to 2005. Thus, the denominator comprises more than 7.5 million births. A total of 7704 cases of cleft lip with or without cleft palate (7141 livebirths, 237 stillbirths, 301 terminations of pregnancy, and 25 with pregnancy outcome unknown) were available. The overall prevalence of cleft lip with or without cleft palate was 9.92 per 10,000. The prevalence of cleft lip was 3.28 per 10,000, and that of cleft lip and palate was 6.64 per 10,000. There were 5918 cases (76.8%) that were isolated, 1224 (15.9%) had malformations in other systems, and 562 (7.3%) occurred as part of recognized syndromes. Cases with greater dysmorphological severity of cleft lip with or without cleft palate were more likely to include malformations of other systems.

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In recent years, analysis of the genomes of many organisms has received increasing international attention. The bulk of the effort to date has centred on the Human Genome Project and analysis of model organisms such as yeast, Drosophila and Caenorhabditis elegans. More recently, the revolution in genome sequencing and gene identification has begun to impact on infectious disease organisms. Initially, much of the effort was concentrated on prokaryotes, but small eukaryotic genomes, including the protozoan parasites Plasmodium, Toxoplasma and trypanosomatids (Leishmania, Trypanosoma brucei and T. cruzi), as well as some multicellular organisms, such as Brugia and Schistosoma, are benefiting from the technological advances of the genome era. These advances promise a radical new approach to the development of novel diagnostic tools, chemotherapeutic targets and vaccines for infectious disease organisms, as well as to the more detailed analysis of cell biology and function.Several networks or consortia linking laboratories around the world have been established to support these parasite genome projects[1] (for more information, see http://www.ebi.ac.uk/ parasites/paratable.html). Five of these networks were supported by an initiative launched in 1994 by the Specific Programme for Research and Tropical Diseases (TDR) of the WHO[2, 3, 4, 5, 6]. The Leishmania Genome Network (LGN) is one of these[3]. Its activities are reported at http://www.ebi.ac.uk/parasites/leish.html, and its current aim is to map and sequence the genome of Leishmania by the year 2002. All the mapping, hybridization and sequence data are also publicly available from LeishDB, an AceDB-based genome database (http://www.ebi.ac.uk/parasites/LGN/leissssoft.html).

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Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

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Mountain ranges are biodiversity hotspots worldwide and provide refuge to many organisms under contemporary climate change. Gathering field information on mountain biodiversity over time is of primary importance to understand the response of biotic communities to climate changes. For plants, several long-term observation sites and networks of mountain biodiversity are emerging worldwide to gather field data and monitor altitudinal range shifts and community composition changes under contemporary climate change. Most of these monitoring sites, however, focus on alpine ecosystems and mountain summits, such as the global observation research initiative in alpine environments (GLORIA). Here we describe the Alps Vegetation Database, a comprehensive community level archive (GIVD ID EU-00-014) which aims at compiling all available geo-referenced vegetation plots from lowland forests to alpine grasslands across the greatest mountain range in Europe: the Alps. This research initiative was funded between 2008 and 2011 by the Danish Council for Independent Research and was part of a larger project to compare cross-scale plant community structure between the Alps and the Scandes. The Alps Vegetation Database currently harbours 35,731 geo-referenced vegetation plots and 5,023 valid taxa across Mediterranean, temperate and alpine environments. The data are mainly used by the main contributors of the Alps Vegetation Database in an ecoinformatics approach to test hypotheses related to plant macroecology and biogeography, but external proposals for joint collaborations are welcome.

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The aim of the Permanent.Plot.ch project is the conservation of historical data about permanent plots in Switzerland and the monitoring of vegetation in a context of environmental changes (mainly climate and land use). Permanent plots are currently being recognized as valuable tools to monitor long-term effects of environmental changes on vegetation. Often used in short studies (3 to 5 years), they are generally abandoned at the end of projects. However, their full potential might only be revealed after 10 or more years, once the location is lost. For instance, some of the oldest permanent plots in Switzerland (first half of the 20th century) were nearly lost, although they are now very valuable data. The Permanent.Plot.ch national database (GIVD ID EU-CH-001), by storing historical and recent data, will allow to ensuring future access to data from permanent vegetation plots. As the database contains some private data, it is not directly available on internet but an overview of the data can be downloaded from internet (http://www.unil.ch/ppch) and precise data are available on request.

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90Y-labelled radiopharmaceuticals offer promising prospects for radionuclide therapies of tumours, e.g. radioimmunotherapies (RIT), (EANM, 2007), peptide receptor radiotherapies (PRRT), (Otte et al., 1998), and selective internal radiotherapies (SIRT), (Salem and Thurston, 2006). 90Y, an almost pure high-energy beta radiation emitter (Eβ,max = 2.28 MeV), is a favourable radionuclide for therapeutic purposes. However, when preparing and performing these therapies, high activities of 90Y (>1 GBq) are to be manipulated and technicians, physicians and nurses may receive high skin exposures to the hands. If radiation protection standards are low, the exposure of staff can exceed the annual skin dose limit of 500 mSv. Within a particular work package (WP4) of the ORAMED project, comprehensive measurements in nuclear medicine departments of several hospitals in 6 European countries were carried out. The study focussed on 90Y-labelled substances such as Zevalin® and DOTATOC to achieve a representative database on staff exposure. This paper summarises the most important results and conclusions for individual monitoring of skin exposure of staff.

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Résumé: L'automatisation du séquençage et de l'annotation des génomes, ainsi que l'application à large échelle de méthodes de mesure de l'expression génique, génèrent une quantité phénoménale de données pour des organismes modèles tels que l'homme ou la souris. Dans ce déluge de données, il devient très difficile d'obtenir des informations spécifiques à un organisme ou à un gène, et une telle recherche aboutit fréquemment à des réponses fragmentées, voir incomplètes. La création d'une base de données capable de gérer et d'intégrer aussi bien les données génomiques que les données transcriptomiques peut grandement améliorer la vitesse de recherche ainsi que la qualité des résultats obtenus, en permettant une comparaison directe de mesures d'expression des gènes provenant d'expériences réalisées grâce à des techniques différentes. L'objectif principal de ce projet, appelé CleanEx, est de fournir un accès direct aux données d'expression publiques par le biais de noms de gènes officiels, et de représenter des données d'expression produites selon des protocoles différents de manière à faciliter une analyse générale et une comparaison entre plusieurs jeux de données. Une mise à jour cohérente et régulière de la nomenclature des gènes est assurée en associant chaque expérience d'expression de gène à un identificateur permanent de la séquence-cible, donnant une description physique de la population d'ARN visée par l'expérience. Ces identificateurs sont ensuite associés à intervalles réguliers aux catalogues, en constante évolution, des gènes d'organismes modèles. Cette procédure automatique de traçage se fonde en partie sur des ressources externes d'information génomique, telles que UniGene et RefSeq. La partie centrale de CleanEx consiste en un index de gènes établi de manière hebdomadaire et qui contient les liens à toutes les données publiques d'expression déjà incorporées au système. En outre, la base de données des séquences-cible fournit un lien sur le gène correspondant ainsi qu'un contrôle de qualité de ce lien pour différents types de ressources expérimentales, telles que des clones ou des sondes Affymetrix. Le système de recherche en ligne de CleanEx offre un accès aux entrées individuelles ainsi qu'à des outils d'analyse croisée de jeux de donnnées. Ces outils se sont avérés très efficaces dans le cadre de la comparaison de l'expression de gènes, ainsi que, dans une certaine mesure, dans la détection d'une variation de cette expression liée au phénomène d'épissage alternatif. Les fichiers et les outils de CleanEx sont accessibles en ligne (http://www.cleanex.isb-sib.ch/). Abstract: The automatic genome sequencing and annotation, as well as the large-scale gene expression measurements methods, generate a massive amount of data for model organisms. Searching for genespecific or organism-specific information througout all the different databases has become a very difficult task, and often results in fragmented and unrelated answers. The generation of a database which will federate and integrate genomic and transcriptomic data together will greatly improve the search speed as well as the quality of the results by allowing a direct comparison of expression results obtained by different techniques. The main goal of this project, called the CleanEx database, is thus to provide access to public gene expression data via unique gene names and to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and crossdataset comparisons. A consistent and uptodate gene nomenclature is achieved by associating each single gene expression experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of genes from model organisms, such as human and mouse. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing crossreferences to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resources, such as cDNA clones or Affymetrix probe sets. The Affymetrix mapping files are accessible as text files, for further use in external applications, and as individual entries, via the webbased interfaces . The CleanEx webbased query interfaces offer access to individual entries via text string searches or quantitative expression criteria, as well as crossdataset analysis tools, and crosschip gene comparison. These tools have proven to be very efficient in expression data comparison and even, to a certain extent, in detection of differentially expressed splice variants. The CleanEx flat files and tools are available online at: http://www.cleanex.isbsib. ch/.

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The EpiNet project has been established to facilitate investigator-initiated clinical research in epilepsy, to undertake epidemiological studies, and to simultaneously improve the care of patients who have records created within the EpiNet database. The EpiNet database has recently been adapted to collect detailed information regarding status epilepticus. An incidence study is now underway in Auckland, New Zealand in which the incidence of status epilepticus in the greater Auckland area (population: 1.5 million) will be calculated. The form that has been developed for this study can be used in the future to collect information for randomized controlled trials in status epilepticus. This article is part of a Special Issue entitled "Status Epilepticus".