Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Policy attitudes, ideological values and social representations

This article reviews research on policy attitudes and ideological values from the perspective of social representations theory. In the first part of the paper, key features of lay political thinking are presented, its pragmatic imperative, its focus on communication and the social functions of shared knowledge. Objectification transforms abstract and group-neutral ideological values into concrete and socially useful knowledge, in particular stereotypes of value-conforming and value-violating groups. Such shared understandings of intergroup relations provide citizens with common reference knowledge which provides the cognitive and cultural basis of policy attitudes. Social representations theory further suggests that lay knowledge reflects the social context in which it has been elaborated (anchoring), an aspect which allows conceptualising aggregate-level differences in policy attitudes. In the second part of the paper, a model of lay conceptions of social order is outlined which organises four shared conceptions of social order, along with the stereotype-based thinking associated with each conception: Moral order, Free Market, Social diversity and Structural inequality. We conclude by arguing that policy attitudes are symbolic devices expressed to justify or to challenge existing social arrangements.

Discovery of the faithfulness gene: a model of transmission and transformation of scientific information.

The purpose of this paper is to study the diffusion and transformation of scientific information in everyday discussions. Based on rumour models and social representations theory, the impact of interpersonal communication and pre-existing beliefs on transmission of the content of a scientific discovery was analysed. In three experiments, a communication chain was simulated to investigate how laypeople make sense of a genetic discovery first published in a scientific outlet, then reported in a mainstream newspaper and finally discussed in groups. Study 1 (N=40) demonstrated a transformation of information when the scientific discovery moved along the communication chain. During successive narratives, scientific expert terminology disappeared while scientific information associated with lay terminology persisted. Moreover, the idea of a discovery of a faithfulness gene emerged. Study 2 (N=70) revealed that transmission of the scientific message varied as a function of attitudes towards genetic explanations of behaviour (pro-genetics vs. anti-genetics). Pro-genetics employed more scientific terminology than anti-genetics. Study 3 (N=75) showed that endorsement of genetic explanations was related to descriptive accounts of the scientific information, whereas rejection of genetic explanations was related to evaluative accounts of the information.

Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies

The work presented evaluates the statistical characteristics of regional bias and expected error in reconstructions of real positron emission tomography (PET) data of human brain fluoro-deoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task of evaluating radioisotope uptake in regions-of-interest (ROIs) is investigated. An assessment of bias and variance in uptake measurements is carried out with simulated data. Then, by using three different transition matrices with different degrees of accuracy and a components of variance model for statistical analysis, it is shown that the characteristics obtained from real human FDG brain data are consistent with the results of the simulation studies.

Elaboration d'un cadre d'évaluation de l'impact du processus communautaire sur la santé des aîné(e)s à Yverdon.

Contexte et cadre: L'Institut universitaire de médecine sociale et préventive (IUMSP) de Lausanne a été mandaté par la Fondation Leenaards pour élaborer un cadre pour l'évaluation de l'impact d'un processus communautaire sur la santé des aînés dans la ville d'Yverdon, appelé "Quartiers solidaires". "Quartiers solidaires" est une méthodologie de développement communautaire, créée par l'unité de travail social communautaire de Pro Senectute Vaud. Elle a pour but d'améliorer la qualité de vie actuelle et future des personnes âgées au sein de leur quartier. Pour atteindre cet objectif, les habitants, et en particulier les aînés, sont invités à devenir auteurs et acteurs de leurs propres projets en créant une communauté locale. Le projet "Quartiers solidaires" à Yverdon s'inscrit par ailleurs dans le cadre d'un projet communal de politique d'action sociale de la ville, Qualité de vie, s'appliquant au niveau de la ville et impliquant divers acteurs et instances. L'IUMSP propose, pour l'élaboration de ce cadre, d'utiliser un outil : le "modèle de catégorisation des résultats". Cet outil, appelé aussi SMOC (Swiss Model for Outcome Classification), permet à tous les partenaires impliqués dans le projet Quartiers solidaires d'établir ensemble un état de situation à laquelle ils sont confrontés (c'est à dire une analyse des problèmes auxquels ils doivent faire face), ainsi qu'une théorie d'action (c'est à dire un schéma qui structure les activités, en cours et planifiées, selon les divers objectifs visés). Cet outil, caractérisé par sa démarche participative, a été utilisé dans le cadre d'ateliers réunissant les différentes parties prenantes du projet. [...] Le modèle est basé sur la santé dans sa définition la plus large (telle que définie par l'OMS), englobant donc la qualité de vie, et est en adéquation avec l'approche écologique, qui repose sur une vision élargie des déterminants de la santé. [Auteurs, p. 7-8]

Postglacial recolonization at a snail's pace (Trochulus villosus): confronting competing refugia hypotheses using model selection.

The localization of Last Glacial Maximum (LGM) refugia is crucial information to understand a species' history and predict its reaction to future climate changes. However, many phylogeographical studies often lack sampling designs intensive enough to precisely localize these refugia. The hairy land snail Trochulus villosus has a small range centred on Switzerland, which could be intensively covered by sampling 455 individuals from 52 populations. Based on mitochondrial DNA sequences (COI and 16S), we identified two divergent lineages with distinct geographical distributions. Bayesian skyline plots suggested that both lineages expanded at the end of the LGM. To find where the origin populations were located, we applied the principles of ancestral character reconstruction and identified a candidate refugium for each mtDNA lineage: the French Jura and Central Switzerland, both ice-free during the LGM. Additional refugia, however, could not be excluded, as suggested by the microsatellite analysis of a population subset. Modelling the LGM niche of T. villosus, we showed that suitable climatic conditions were expected in the inferred refugia, but potentially also in the nunataks of the alpine ice shield. In a model selection approach, we compared several alternative recolonization scenarios by estimating the Akaike information criterion for their respective maximum-likelihood migration rates. The 'two refugia' scenario received by far the best support given the distribution of genetic diversity in T. villosus populations. Provided that fine-scale sampling designs and various analytical approaches are combined, it is possible to refine our necessary understanding of species responses to environmental changes.

French version of the Family Attitude Scale: Psychometric properties and relation of attitudes to the respondent's psychiatric status.

The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Network-based scoring system for genome-scale metabolic reconstructions

Background: Network reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood. Results: Here, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results. Conclusions: We foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

Different likelihood ratio approaches to evaluate the strength of evidence of MDMA tablet comparisons

Two likelihood ratio (LR) approaches are presented to evaluate the strength of evidence of MDMA tablet comparisons. The first one is based on a more 'traditional' comparison of MDMA tablets by using distance measures (e.g., Pearson correlation distance or a Euclidean distance). In this approach, LRs are calculated using the distribution of distances between tablets of the same-batch and that of different-batches. The second approach is based on methods used in some other fields of forensic comparison. Here LRs are calculated based on the distribution of values of MDMA tablet characteristics within a specific batch and from all batches. The data used in this paper must be seen as examples to illustrate both methods. In future research the methods can be applied to other and more complex data. In this paper, the methods and their results are discussed, considering their performance in evidence evaluation and several practical aspects. With respect to evidence in favor of the correct hypothesis, the second method proved to be better than the first one. It is shown that the LRs in same-batch comparisons are generally higher compared to the first method and the LRs in different-batch comparisons are generally lower. On the other hand, for operational purposes (where quick information is needed), the first method may be preferred, because it is less time consuming. With this method a model has to be estimated only once in a while, which means that only a few measurements have to be done, while with the second method more measurements are needed because each time a new model has to be estimated.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.

Why do they separate it or not? Attitudes and behaviors towards organic waste separation

This article shows the results of an exploratory study related to the separation of organic waste in order to offer suggestions for the improvement of waste disposal communication campaigns. The overall objective is to analyze attitude and behavior of those who do and those who do not separate organic waste, related to a specific promotional campaign carried out in two neighborhoods, in the municipality of Badalona (Spain), within the framework of the study of proenvironmental attitudes and behaviors and based on the Psychosocial Four Spheres Model. 1,010 interviews were conducted and data was analyzed using Chi-Squared Automatic Interaction Detector (CHAID). Waste separation behavior was used as a dependent variable. The reasons given to explain why people do or do not separate organic waste and sociodemographic variables, have been introduced as independent variables. In accordance with the Four Spheres Model, results show significant differences in waste separation. Based on the profiles obtained, we find some predictive variables that facilitate the development of communication campaigns according to the requirements of each community.