Body Mass Index: A Scientific Evidence-Based Inquiry

OBJECTVE: To objectively and critically assess body mass index and to propose alternatives for relating body weight and height that are evidence-based and that eliminate or reduce the limitations of the body mass index. METHODS: To analyze the relations involving weight and height, we used 2 databases as follows: 1) children and adolescents from Brazil, the United States, and Switzerland; and 2) 538 university students. We performed mathematical simulations with height data ranging from 115 to 190 cm and weight data ranging from 25 to 105 kg. We selected 3 methods to analyze the relation of weight and height as follows: body mass index - weight (kg)/height (m²); reciprocal of the ponderal index - height (cm)/weight1/3 (kg); and ectomorphy. Using the normal range from 20 to 25 kg/m² for the body mass index in the reference height of 170 cm, we identified the corresponding ranges of 41 to 44 cm/kg1/3 for the reciprocal of the ponderal index, and of 1.45 to 3.60 for ectomorphy. RESULTS: The mathematical simulations showed a strong association among the 3 methods with an absolute concordance to a height of 170 cm, but with a tendency towards discrepancy in the normal ranges, which had already been observed for the heights of 165 and 175 cm. This made the direct convertibility between the indices unfeasible. The reciprocal of the ponderal index and ectomorphy with their cut points comprised a larger age range in children and adolescents and a wider and more central range in the university students, both for the reported (current) and desired weights. CONCLUSION: The reciprocal of the ponderal index and ectomorphy are stronger and are more mathematically logical than body mass index; in addition, they may be applied with the same cut points for normal from the age of 5 ½ years on.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Visualisation of human rad52 protein and its complexes with hRad51 and DNA.

The human Rad52 protein stimulates joint molecule formation by hRad51, a homologue of Escherichia coli RecA protein. Electron microscopic analysis of hRad52 shows that it self-associates to form ring structures with a diameter of approximately 10 nm. Each ring contains a hole at its centre. hRad52 binds to single and double-stranded DNA. In the ssDNA-hRad52 complexes, hRad52 was distributed along the length of the DNA, which exhibited a characteristic "beads on a string" appearance. At higher concentrations of hRad52, "super-rings" (approximately 30 nm) were observed and the ssDNA was collapsed upon itself. In contrast, in dsDNA-hRad52 complexes, some regions of the DNA remained protein-free while others, containing hRad52, interacted to form large protein-DNA networks. Saturating concentrations of hRad51 displaced hRad52 from ssDNA, whereas dsDNA-Rad52 complexes (networks) were more resistant to hRad51 invasion and nucleoprotein filament formation. When Rad52-Rad51-DNA complexes were probed with gold-conjugated hRad52 antibodies, the presence of globular hRad52 structures within the Rad51 nucleoprotein filament was observed. These data provide the first direct visualisation of protein-DNA complexes formed by the human Rad51 and Rad52 recombination/repair proteins.

Two different 3D biogeochemical models for the NW mediterranean sea: validation with Meris data and intercomparison

Report for the scientific sojourn carried out at the University of New South Wales from February to June the 2007. Two different biogeochemical models are coupled to a three dimensional configuration of the Princeton Ocean Model (POM) for the Northwestern Mediterranean Sea (Ahumada and Cruzado, 2007). The first biogeochemical model (BLANES) is the three-dimensional version of the model described by Bahamon and Cruzado (2003) and computes the nitrogen fluxes through six compartments using semi-empirical descriptions of biological processes. The second biogeochemical model (BIOMEC) is the biomechanical NPZD model described in Baird et al. (2004), which uses a combination of physiological and physical descriptions to quantify the rates of planktonic interactions. Physical descriptions include, for example, the diffusion of nutrients to phytoplankton cells and the encounter rate of predators and prey. The link between physical and biogeochemical processes in both models is expressed by the advection-diffusion of the non-conservative tracers. The similarities in the mathematical formulation of the biogeochemical processes in the two models are exploited to determine the parameter set for the biomechanical model that best fits the parameter set used in the first model. Three years of integration have been carried out for each model to reach the so called perpetual year run for biogeochemical conditions. Outputs from both models are averaged monthly and then compared to remote sensing images obtained from sensor MERIS for chlorophyll.

Still in the Era of Area Studies? Political-Scientific Perspectives on European Competition Policy in the 2000s

This note reviews the political-scientific literature on European competition policy (ECP) in the 2000s. Based on a data set extracted from four well-known journals, and using an upfront methodology and explicit criteria, it analyzes the literature both quantitatively and qualitatively. On the quantitative side, it shows that, although a few sub-policy areas are still neglected, ECP is not the under-researched policy it used to be. On the qualitative side, the literature has greatly improved since the 1990s: Almost all articles now present a clear research question, and most advance specific theoretical claims/hypotheses. Yet, improvements can be made on research design, statistical testing, and, above all, state-of-the-art theorizing (e.g. in the game-theoretical treatment of delegation problems). Indeed, it is paradoxical that ECP specialists do not pay more attention to theoretical questions which are so central to the actual policy area they study.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience.

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners. JEL classification: O31, O33, O38. Key words: Determinants R&D cooperation, industry-university flows, PhD research workers.

The gap between scientific evidence and clinical practice : 5-aminosalicylates are frequently used for the treatment of Crohn's disease

BACKGROUND: There is uncertain evidence of effectiveness of 5-aminosalicylates (5-ASA) to induce and maintain response and remission of active Crohn's disease (CD), and weak evidence to support their use in post-operative CD. AIM: To assess the frequency and determinants of 5-ASA use in CD patients and to evaluate the physicians' perception of clinical response and side effects to 5-ASA. METHODS: Data from the Swiss Inflammatory Bowel Disease Cohort, which collects data since 2006 on a large sample of IBD patients, were analysed. Information from questionnaires regarding utilisation of treatments and perception of response to 5-ASA were evaluated. Logistic regression modelling was performed to identify factors associated with 5-ASA use. RESULTS: Of 1420 CD patients, 835 (59%) were ever treated with 5-ASA from diagnosis to latest follow-up. Disease duration >10 years and colonic location were both significantly associated with 5-ASA use. 5-ASA treatment was judged to be successful in 46% (378/825) of treatment episodes (physician global assessment). Side effects prompting stop of therapy were found in 12% (98/825) episodes in which 5-ASA had been stopped. CONCLUSIONS: 5-Aminosalicylates were frequently prescribed in patients with Crohn's disease in the Swiss IBD cohort. This observation stands in contrast to the scientific evidence demonstrating a very limited role of 5-ASA compounds in the treatment of Crohn's disease.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Pigments and plasters discovered in the House of Diana (Cosa, Grosseto, Italy): An integrated study between art history, archaeology and scientific analyses

The pigments and the plasters of the Roman frescoes discovered at the House of Diana (Cosa, Grosseto, Italy) were analysed using non-destructive and destructive mineralogical and chemical techniques. The characterization of both pigments and plasters was performed through optical microscopy, scanning electron microscopy and electron microprobe analysis. The pigments were identified by Raman spectroscopy and submitted to stable isotope analysis. The results were integrated with the archaeological data in order to determine and reconstruct the provenance, trade patterns and the employment of the raw materials used for the elaboration of the frescoes.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Why Public Health Agencies Cannot Depend on Good Laboratory Practices as a Criterion for Selecting Data: The Case of Bisphenol A

In their safety evaluations of bisphenol A (BPA), the U.S. Food and Drug Administration (FDA) and a counterpart in Europe, the European Food Safety Authority (EFSA), have given special prominence to two industry-funded studies that adhered to standards defined by Good Laboratory Practices (GLP). These same agencies have given much less weight in risk assessments to a large number of independently replicated non-GLP studies conducted with government funding by the leading experts in various fields of science from around the world. OBJECTIVES: We reviewed differences between industry-funded GLP studies of BPA conducted by commercial laboratories for regulatory purposes and non-GLP studies conducted in academic and government laboratories to identify hazards and molecular mechanisms mediating adverse effects. We examined the methods and results in the GLP studies that were pivotal in the draft decision of the U.S. FDA declaring BPA safe in relation to findings from studies that were competitive for U.S. National Institutes of Health (NIH) funding, peer-reviewed for publication in leading journals, subject to independent replication, but rejected by the U.S. FDA for regulatory purposes. DISCUSSION: Although the U.S. FDA and EFSA have deemed two industry-funded GLP studies of BPA to be superior to hundreds of studies funded by the U.S. NIH and NIH counterparts in other countries, the GLP studies on which the agencies based their decisions have serious conceptual and methodologic flaws. In addition, the U.S. FDA and EFSA have mistakenly assumed that GLP yields valid and reliable scientific findings (i.e., "good science"). Their rationale for favoring GLP studies over hundreds of publically funded studies ignores the central factor in determining the reliability and validity of scientific findings, namely, independent replication, and use of the most appropriate and sensitive state-of-the-art assays, neither of which is an expectation of industry-funded GLP research. CONCLUSIONS: Public health decisions should be based on studies using appropriate protocols with appropriate controls and the most sensitive assays, not GLP. Relevant NIH-funded research using state-of-the-art techniques should play a prominent role in safety evaluations of chemicals.

Impactia: automating the study of the scientific production

Introduction The Andalusian Public Health System Virtual Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA) was set up in June 2006. It consists of a regional government action with the aim of democratizing the health professional access to quality scientific information, regardless of the professional workplace. Andalusia is a region with more than 8 million inhabitants, with 100,000 health professionals for 41 hospitals, 1,500 primary healthcare centres, and 28 centres for non-medical attention purposes (research, management, and educational centres). Objectives The Department of Development, Research and Investigation (R+D+i) of the Andalusian Regional Government has, among its duties, the task of evaluating the hospitals and centres of the Andalusian Public Health System (SSPA) in order to distribute its funding. Among the criteria used is the evaluation of the scientific output, which is measured using bibliometry. It is well-known that the bibliometry has a series of limitations and problems that should be taken into account, especially when it is used for non-information sciences, such us career, funding, etc. A few years ago, the bibliometric reports were done separately in each centre, but without using preset and well-defined criteria, elements which are basic when we need to compare the results of the reports. It was possible to find some hospitals which were including Meeting Abstracts in their figures, while others do not, and the same was happening with Erratum and many other differences. Therefore, the main problem that the Department of R+D+i had to deal with, when they were evaluating the health system, was that bibliometric data was not accurate and reports were not comparable. With the aim of having an unified criteria for the whole system, the Department of R+D+i ordered the BV-SSPA to do the year analysis of the scientific output of the system, using some well defined criteria and indicators, among whichstands out the Impact Factor. Materials and Methods As the Impact Factor is the bibliometric indicator that the virtual library is asked to consider, it is necessary to use the database Web of Science (WoS), since it is its owner and editor. The WoS includes the databases Science Citation Index (SCI), Social Sciences Citation Index (SSCI) and Arts & Humanities Citation Index. To gather all the documents, SCI and SSCI are used; to obtain the Impact Factor and quartils, it is used the Journal Citation Reports, JCR. Unlike other bibliographic databases, such us MEDLINE, the bibliometric database WoS includes the address of all the authors. In order to retrieve all the scientific output of the SSPA, we have done general searches, which are afterwards processed by a tool developed by our library. We have done nine different searches using the field ‘address’; eight of them including ‘Spain’ and each one of the eight Andalusian Regions, and the other one combining ‘Spain’ with all those cities where there are health centres, since we have detected that there are some authors that do not use the region in their signatures. These are some of the search strategies: AD=Malaga and AD=Spain AD=Sevill* and AD=Spain AD=SPAIN AND (AD=GUADIX OR AD=BAZA OR AD=MOTRIL) Further more, the field ‘year’ is used to determine the period. To exploit the data, the BV-SSPA has developed a tool called Impactia. It is a web application which uses a database to store the information of the documents generated by the SSPA. Impactia allows the user to automatically process the retrieved documents, assigning them to their correspondent centres. In order to do the classification of documents automaticaly, it was necessary to detect the huge variability of names of the centres that the authors use in their signatures. Therefore, Impactia knows that if an author signs as “Hospital Universitario Virgen Macarena”, “HVM” or “Hosp. Virgin Macarena”, he belongs to the same centre. The figure attached shows the variability found for the Empresa Publica Hospital de Poniente. Besides the documents from WoS, Impactia includes the documents indexed in Scopus and in other databases, where we do bibliographic searches using similar strategies to the later ones. Aware that in the health centres and hospitals there is a lot of grey literature that is not gathered in databases, Impactia allows the centres to feed the application with these documents, so that all the SSPA scientific output is gathered and organised in a centralized place. The ones responsible of localizing this gray literature are the librarians of each one of the centres. They can also do statements to the documents and indicators that are collected and calculated by Impactia. The bulk upload of documents from WoS and Scopus into Impactia is monthly done. One of the main issues that we found during the development of Impactia was the need of dealing with duplicated documents obtained from different sources. Taking into account that sometimes titles might be written differently, with slashes, comas, and so on, Impactia detects the duplicates using the field ‘DOI’ if it is available or comparing the fields: page start, page end and ISSN. Therefore it is possible to guarantee the absence of duplicates. Results The data gathered in Impactia becomes available to the administrative teams and hospitals managers, through an easy web page that allows them to know at any moment, and with just one click, the detailed information of the scientific output of their hospitals, including useful graphs such as percentage of document types, journals where their scientists usually publish, annual comparatives, bibliometric indicators and so on. They can also compare the different centres of the SSPA. Impactia allows the user to download the data from the application, so that he can work with this information or include them in their centres’ reports. This application saves the health system many working hours. It was previously done manually by forty one librarians, while now it is done by only one person in the BV-SSPA during two days a month. To sum up, the benefits of Impactia are: It has shown its effectiveness in the automatic classification, treatment and analysis of the data. It has become an essential tool for all managers to evaluate quickly and easily the scientific production of their centers. It optimizes the human resources of the SSPA, saving time and money. It is the reference point for the Department of R+D+i to do the scientific health staff evaluation.