Stability and robustness of blood variables in an antidoping context.

Introduction:  With the setting up of the newly Athlete's Biological Passport antidoping programme, novel guidelines have been introduced to guarantee results beyond reproach. We investigated in this context, the effect of storage time on the variables commonly measured for the haematological passport. We also wanted to assess for these variables, the within and between analyzer variations. Methods:  Blood samples were obtained from top level male professional cyclists (27 samples for the first part of the study and 102 for the second part) taking part to major stage races. After collection, they were transported under refrigerated conditions (2 °C < T < 12 °C), delivered to the antidoping laboratory, analysed and then stored at approximately 4 °C to conduct analysis at different time points up to 72 h after delivery. A mixed-model procedure was used to determine the stability of the different variables. Results:  As expected haemoglobin concentration was not affected by storage and showed stability for at least 72 h. Under the conditions of our investigation, the reticulocytes percentage showed a much better stability than previous published data (> 48 h) and the technical comparison of the haematology analyzer demonstrated excellent results. Conclusion:  In conclusion, our data clearly demonstrate that as long as the World Anti-Doping Agency's guidelines are followed rigorously, all blood results reach the quality level required in the antidoping context.

School burnout in adolescents : Differences in background variables and exploration of school-related stress at the end of compulsory schooling

The aim of this study is to contribute to a better understanding of the risk factors associated with school burnout, which has recently been described as a syndrome of emotional exhaustion due to school demands, cynical and detached attitude towards school and feelings of inadequacy as a student (Salmela-Aro, Kiuru, Pietikainen & Jokela, 2008a). The research focuses on students in the last years of compulsory schooling, period in which burnout has not received much attention yet. A total of 342 adolescents (Mean age = 14.84) were asked to complete questionnaires about school burnout, school-related stress and background variables. The results showed differences in school burnout by gender, grade level and school track, with girls, last grade of compulsory school and high-track classes, showing the highest scores. No difference was observed with respect to grade retention. Several types of school stress were identified, with stress type Success related to pressures to succeed and concerns about the academic future being the highest. Finally, stress and burnout were strongly and positively correlated, and the type of stress Success was the best predictor of overall Burnout, Exhaustion and Inadequacy dimension scores. The results are discussed in relation to their theoretical relevance and implications for the prevention of school burnout in adolescents.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

Mining the human phenome using allelic scores that index biological intermediates.

It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.

Obesity-related phenotypes are associated to parental longevity in a Swiss population-based study

METHODS. We analyzed data from a population-based sample of 2561 participants (1163 men and 1398 women) aged 55-75 years from the city of Lausanne, Switzerland (CoLaus study). Participants were stratified by the number of parents (0, 1, 2) who survived to 85 years or more. Trend across these strata was assessed using a non-parametric kmean test. The associations of parental age (independent covariate used as a proxy for longevity) with fasting blood glucose, blood pressures, blood lipids, body mass index (BMI), weight, height or liver enzymes (continuous dependent variables) were analyzed using multiple linear regressions. Models were adjusted for age, sex, alcohol consumption, smoking and educational level, and BMI for liver enzymes. RESULTS. For subjects with 0 (N = 1298), 1 (N = 991) and 2 (N = 272) long-lived parents, median BMI (interquartile range) was 25.4 (6.5), 24.9 (6.1) and 23.7 (4.8) kg/m2 in women (P <0.001), and 27.3 (4.8), 27.0 (4.5) and 25.9 (4.9) kg/m2 in men (P = 0.04), respectively; median weight was 66.5 (16.1), 65.0 (16.4) and 63.4 (13.7) kg in women (P = 0.003), and 81.5 (17.0), 81.4 (16.4) and 80.3 (17.1) kg in men (P = 0.36). Median height was 161 (8), 162 (9) and 163 (8) cm in women (P = 0.005) and 173 (9), 174 (9) and 174 (11) cm in men (P = 0.09). The corresponding medians for AST (Aspartate Aminotransferase) were 31 (13), 29 (11) and 28 (10) U/L (P = 0.002), and 28 (17), 27 (14) and 26 (19) U/L for ALT (Alanin Aminotransferase, P = 0.053) in men. In multivariable analyses, greater parental longevity was associated with lower BMI, lower weight and taller stature in women (P < 0.01) and lower AST in men (P = 0.011). No significant associations were observed for the other variables analyzed. Sensitivity analyses restricted to subjects whose parents were dead (N = 1844) led to similar results, with even stronger associations of parental longevity with liver enzymes in men. CONCLUSIONS. In women, increased parental longevity was associated with smaller BMI, attributable to lower weight and taller stature. In men, the association of increased parental longevity with lower liver enzymes, independently of BMI, suggests that parental longevity may be associated with decreased nonalcoholic fatty liver disease.

Clinical chemistry variables in normal elderly and healthy ambulatory populations: comparison with reference values.

Laboratory values of the most commonly assayed clinical chemistry variables were determined in selected elderly and healthy ambulatory populations. The upper and lower limits (2.5 and 97.5 fractiles) were compared with the adult reference values in use in university hospitals of Switzerland. The results suggest that conventional adult reference values can be used for most variables in the elderly and that these values are also useful in an ambulatory population.

Definition of key variables for the induction of optimal NY-ESO-1-specific T cells in HLA transgene mice.

An attractive treatment of cancer consists in inducing tumor-eradicating CD8(+) CTL specific for tumor-associated Ags, such as NY-ESO-1 (ESO), a strongly immunogenic cancer germ line gene-encoded tumor-associated Ag, widely expressed on diverse tumors. To establish optimal priming of ESO-specific CTL and to define critical vaccine variables and mechanisms, we used HLA-A2/DR1 H-2(-/-) transgenic mice and sequential immunization with immunodominant DR1- and A2-restricted ESO peptides. Immunization of mice first with the DR1-restricted ESO(123-137) peptide and subsequently with mature dendritic cells (DCs) presenting this and the A2-restriced ESO(157-165) epitope generated abundant, circulating, high-avidity primary and memory CD8(+) T cells that efficiently killed A2/ESO(157-165)(+) tumor cells. This prime boost regimen was superior to other vaccine regimes and required strong Th1 cell responses, copresentation of MHC class I and MHC class II peptides by the same DC, and resulted in upregulation of sphingosine 1-phosphate receptor 1, and thus egress of freshly primed CD8(+) T cells from the draining lymph nodes into circulation. This well-defined system allowed detailed mechanistic analysis, which revealed that 1) the Th1 cytokines IFN-gamma and IL-2 played key roles in CTL priming, namely by upregulating on naive CD8(+) T cells the chemokine receptor CCR5; 2) the inflammatory chemokines CCL4 (MIP-1beta) and CCL3 (MIP-1alpha) chemoattracted primed CD4(+) T cells to mature DCs and activated, naive CD8(+) T cells to DC-CD4 conjugates, respectively; and 3) blockade of these chemokines or their common receptor CCR5 ablated priming of CD8(+) T cells and upregulation of sphingosine 1-phosphate receptor 1. These findings provide new opportunities for improving T cell cancer vaccines.

Identifying Pertinent Variables for Nonresponse Follow-Up Surveys : Lessons Learned from 4 Cases in Switzerland

All social surveys suffer from different types of errors, of which one of the most studied is non-response bias. Non-response bias is a systematic error that occurs because individuals differ in their accessibility and propensity to participate in a survey according to their own characteristics as well as those from the survey itself. The extent of the problem heavily depends on the correlation between response mechanisms and key survey variables. However, non-response bias is difficult to measure or to correct for due to the lack of relevant data about the whole target population or sample. In this paper, non-response follow-up surveys are considered as a possible source of information about non-respondents. Non-response follow-ups, however, suffer from two methodological issues: they themselves operate through a response mechanism that can cause potential non-response bias, and they pose a problem of comparability of measure, mostly because the survey design differs between main survey and non-response follow-up. In order to detect possible bias, the survey variables included in non-response surveys have to be related to the mechanism of participation, but not be sensitive to measurement effects due to the different designs. Based on accumulated experience of four similar non-response follow-ups, we studied the survey variables that fulfill these conditions. We differentiated socio-demographic variables that are measurement-invariant but have a lower correlation with non-response and variables that measure attitudes, such as trust, social participation, or integration in the public sphere, which are more sensitive to measurement effects but potentially more appropriate to account for the non-response mechanism. Our results show that education level, work status, and living alone, as well as political interest, satisfaction with democracy, and trust in institutions are pertinent variables to include in non-response follow-ups of general social surveys. - See more at: https://ojs.ub.uni-konstanz.de/srm/article/view/6138#sthash.u87EeaNG.dpuf

Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.