Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

A global marine sedimentary response to the end-Permian mass extinction: Examples from southern Turkey and the western United States

The end-Permian mass extinction greatly diminished marine diversity and brought about a whole-scale restructuring of marine ecosystems; these ecosystem changes also profoundly affected the sedimentary record. Data presented here, attained through facies analyses of strata deposited during the immediate aftermath of the end-Permian mass extinction (southern Turkey) and at the close of the Early Triassic (southwestern United States), in combination with a literature review, show that sedimentary systems were profoundly affected by: (1) a reduction in biotic diversity and abundance and (2) long-term environmental fluctuations that resulted from the end-Permian crisis. Lower Triassic strata display widespread microbialite and carbonate seafloor fan development and contain indicators of suppressed infaunal bioturbation such as flat-pebble conglomerates and wrinkle structures (facies considered unusual in post-Cambrian subtidal deposits). Our observations suggest that depositional systems, too, respond to biotic crises, and that certain facies may act as barometers of ecologic and environmental change independent of fossil assemblage analyses. Close investigation of facies changes during other critical times in Earth history may serve as an important tool in interpreting the ecology of metazoans and their environment.

Resistance to extreme strategies, rather than prosocial preferences, can explain human cooperation in public goods games.

The results of numerous economic games suggest that humans behave more cooperatively than would be expected if they were maximizing selfish interests. It has been argued that this is because individuals gain satisfaction from the success of others, and that such prosocial preferences require a novel evolutionary explanation. However, in previous games, imperfect behavior would automatically lead to an increase in cooperation, making it impossible to decouple any form of mistake or error from prosocial cooperative decisions. Here we empirically test between these alternatives by decoupling imperfect behavior from prosocial preferences in modified versions of the public goods game, in which individuals would maximize their selfish gain by completely (100%) cooperating. We found that, although this led to higher levels of cooperation, it did not lead to full cooperation, and individuals still perceived their group mates as competitors. This is inconsistent with either selfish or prosocial preferences, suggesting that the most parsimonious explanation is imperfect behavior triggered by psychological drives that can prevent both complete defection and complete cooperation. More generally, our results illustrate the caution that must be exercised when interpreting the evolutionary implications of economic experiments, especially the absolute level of cooperation in a particular treatment.

Time invested in the global respiratory care of cystic fibrosis paediatrics patients.

INTRODUCTION: Respiratory therapy is a keystone of the treatment for cystic fibrosis (CF) lung disease, but it is time consuming. OBJECTIVES: We aimed to assess the total time spent on respiratory therapy, including chest physiotherapy (CPT) and physical activity (PA), as well as inhalation therapy (IT) and maintenance of materials (MM) to rationalise and optimise treatment. METHODS: A cross-sectional prospective study in a paediatric CF cohort. A questionnaire was developed to look at the time spent on respiratory care over 3 months. Enrolled in this study are all CF patients aged from 6 to 16 years (the exclusion criterion was lung transplantation). RESULTS: Of the 40 enrolled patients, 22 participated (13 boys and 9 girls), with a mean age of 11 years. The patients spent approximately 19.46 h per week (standard deviation ± 7.53, 8.00-35.25 h) on therapy: CPT (30.58%), IT (15.11%), PA (50%) and MM (4.32%), without statistical significance between sexes. CONCLUSION: In our cohort, CF patients spent an average of nearly 20 h a week in respiratory therapy, within a wide range of between 8 h to almost 36 h a week. PA consumes almost half of the time. Physicians have to take into consideration the burden of the treatment, to optimise the therapy.

Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

Contribution of the Global Regulator Gene gacA to Persistence and Dissemination of Pseudomonas fluorescens Biocontrol Strain CHA0 Introduced into Soil Microcosms.

Structural and regulatory genes involved in the synthesis of antimicrobial metabolites are essential for the biocontrol activity of fluorescent pseudomonads and, in principle, amenable to genetic engineering for strain improvement. An eventual large-scale release of such bacteria raises the question of whether such genes also contribute to the persistence and dissemination of the bacteria in soil ecosystems. Pseudomonas fluorescens wild-type strain CHA0 protects plants against a variety of fungal diseases and produces several antimicrobial metabolites. The regulatory gene gacA globally controls antibiotic production and is crucial for disease suppression in CHA0. This gene also regulates the production of extracellular protease and phospholipase. The contribution of gacA to survival and vertical translocation of CHA0 in soil microcosms of increasing complexity was studied in coinoculation experiments with the wild type and a gacA mutant which lacks antibiotics and some exoenzymes. Both strains were marked with spontaneous resistance to rifampin. In a closed system with sterile soil, strain CHA0 and the gacA mutant multiplied for several weeks, whereas these strains declined exponentially in nonsterile soil of different Swiss origins. The gacA mutant was less persistent in nonrhizosphere raw soil than was the wild type, but no competitive disadvantage when colonizing the rhizosphere and roots of wheat was found in the particular soil type and during the period studied. Vertical translocation was assessed after strains had been applied to undisturbed, long (60-cm) or short (20-cm) soil columns, both planted with wheat. A smaller number of cells of the gacA mutant than of the wild type were detected in the percolated water and in different depths of the soil column. Single-strain inoculation gave similar results in all microcosms tested. We conclude that mutation in a single regulatory gene involved in antibiotic and exoenzyme synthesis can affect the survival of P. fluorescens more profoundly in unplanted soil than in the rhizosphere.

Predicting current and future spatial community patterns of plant functional traits

Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.

The global activator GacA of Pseudomonas aeruginosa PAO positively controls the production of the autoinducer N-butyryl-homoserine lactone and the formation of the virulence factors pyocyanin, cyanide, and lipase.

The global activator GacA, a highly conserved response regulator in Gram-negative bacteria, is required for the production of exoenzymes and secondary metabolites in Pseudomonas spp. The gacA gene of Pseudomonas aeruginosa PAO1 was isolated and its role in cell-density-dependent gene expression was characterized. Mutational inactivation of gacA resulted in delayed and reduced formation of the cell-density signal N-butyryl-L-homoserine lactone (BHL), of the cognate transcriptional activator RhIR (VsmR), and of the transcriptional activator LasR, which is known to positively regulate RhIR expression. Amplification of gacA on a multicopy plasmid caused precocious and enhanced production of BHL, RhIR and LasR. In parallel, the gacA gene dosage markedly influenced the BHL/RhIR-dependent formation of the cytotoxic compounds pyocyanin and cyanide and the exoenzyme lipase. However, the concentrations of another known cell-density signal of P. aeruginosa, N-oxododecanoyl-L-homoserine lactone, did not always match BHL concentrations. A model accounting for these observations places GacA function upstream of LasR and RhIR in the complex, cell-density-dependent signal-transduction pathway regulating several exoproducts and virulence factors of P. aeruginosa via BHL.

La pertinence de la Global Health pour la Suisse

L'une des premières activités du groupe spécialisé "Global Health", créé au sein de la société de discipline médicale Santé Publique Suisse, a été de formuler une définition appropriée au contexte helvétique du terme de "Global Health" (santé globale). La "Global Health est un espace destiné à la recherche, à la pratique et aux règles y afférents, qui met la priorité sur l'amélioration de la santé, en général, et sur un accès équitable à la santé pour tous, en particulier. La Global Health répond aux questions de santé transnationales et s'intéresse aux déterminants et aux possibilités de solution. Elle implique beaucoup de disciplines, tant du secteur médical que d'autres domaines, promouvant ainsi la collaboration interdisciplinaire; elle encourage la bonne gouvernance pour anticiper et s'adapter à un environnement qui change rapidement ". A l'avenir, une plateforme sera créée dans le but d'offrir un accès aux expériences internationales et de les fructifier en Suisse mais aussi de partager les expériences acquises ici localement, avec des partenaires internationaux tels que les associations européenne et mondiale de santé publique. Last but not least, le groupe spécialisé susmentionné va plaider pour une compréhension large et commune de la Global Health.