Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Adolescents' beliefs about marijuana use: a comparison of regular users, past users and never/occasional users.

A questionnaire investigating adolescents' opinions and experiences regarding marijuana use was administered to 163 adolescents and young adults (96 boys and 67 girls) aged 13 to 20 (mean age = 16.8, s.d. = 1.5). Items referred to marijuana and other substances' dangerousness, representations regarding the positive and negative consequences of marijuana use. Responses were compared according to marijuana use status (classified into never/occasional use, current regular use and past regular use). Results show that adolescents' opinions differ according to their experience with marijuana use. Current regular users evaluate marijuana as less dangerous, but alcohol and heroin as more dangerous in comparison with never/occasional and past users. Current and past users are more likely to define marijuana as a medical drug and a plant used in agriculture, and less likely to define it as an illegal drug. Current and past users evaluate marijuana use as a way to cope with stress, to relax to a greater extent than do never/occasional users do. The latter attribute more negative consequences to marijuana use such as diminished driving ability and school performance and a pathway to hard drugs.

The forgotten face of regular physical exercise: a 'natural' anti-atherogenic activity.

Humans are not programmed to be inactive. The combination of both accelerated sedentary lifestyle and constant food availability disturbs ancient metabolic processes leading to excessive storage of energy in tissue, dyslipidaemia and insulin resistance. As a consequence, the prevalence of Type 2 diabetes, obesity and the metabolic syndrome has increased significantly over the last 30 years. A low level of physical activity and decreased daily energy expenditure contribute to the increased risk of cardiovascular morbidity and mortality following atherosclerotic vascular damage. Physical inactivity leads to the accumulation of visceral fat and consequently the activation of the oxidative stress/inflammation cascade, which promotes the development of atherosclerosis. Considering physical activity as a 'natural' programmed state, it is assumed that it possesses atheroprotective properties. Exercise prevents plaque development and induces the regression of coronary stenosis. Furthermore, experimental studies have revealed that exercise prevents the conversion of plaques into a vulnerable phenotype, thus preventing the appearance of fatal lesions. Exercise promotes atheroprotection possibly by reducing or preventing oxidative stress and inflammation through at least two distinct pathways. Exercise, through laminar shear stress activation, down-regulates endothelial AT1R (angiotensin II type 1 receptor) expression, leading to decreases in NADPH oxidase activity and superoxide anion production, which in turn decreases ROS (reactive oxygen species) generation, and preserves endothelial NO bioavailability and its protective anti-atherogenic effects. Contracting skeletal muscle now emerges as a new organ that releases anti-inflammatory cytokines, such as IL-6 (interleukin-6). IL-6 inhibits TNF-α (tumour necrosis factor-α) production in adipose tissue and macrophages. The down-regulation of TNF-α induced by skeletal-muscle-derived IL-6 may also participate in mediating the atheroprotective effect of physical activity.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations.

Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time.

Challenging the "inoffensiveness" of regular cannabis use by its associations with other current risky substance use--a census of 20-year-old Swiss men.

3,537 men enrolling in 2007 for mandatory army recruitment procedures were assessed for the co-occurrence of risky licit substance use among risky cannabis users. Risky cannabis use was defined as at least twice weekly; risky alcohol use as 6+ drinks more than once/monthly, or more than 20 drinks per week; and risky tobacco use as daily smoking. Ninety-five percent of all risky cannabis users reported other risky use. They began using cannabis earlier than did non-risky users, but age of onset was unrelated to other risky substance use. A pressing public health issue among cannabis users stems from risky licit substance use warranting preventive efforts within this age group.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Effects of regular insulin or insulin LISPRO on glucose metabolism after an oral glucose load in patients with type 2 diabetes mellitus.

Seven obese Type 2 diabetic patients were studied for two 4-h periods after ingestion of a glucose load to determine the effects of preprandial subcutaneous injection of Insulin Lispro (5 min before the meal) or regular insulin (20 min before the meal) on glucose metabolism. Glucose production and utilisation were measured using a dual isotope method. After Lispro, the mean postprandial increase in plasma glucose was 29% lower and the increase in insulin concentration 25% higher than after regular insulin (p < 0.05). Suppression of endogenous glucose production was similar with both types of insulin. Thus, preprandial injection of Lispro reduced postprandial glucose increments in Type 2 diabetic patients as compared to regular insulin. This effect is best explained by the increased postprandial bioavailability of Lispro.

Comparison of cannabinoid concentrations in oral fluid and whole blood between occasional and regular cannabis smokers prior to and after smoking a cannabis joint.

A cross-over controlled administration study of smoked cannabis was carried out on occasional and heavy smokers. The participants smoked a joint (11 % Δ9-tetrahydrocannabinol (THC)) or a matching placebo on two different occasions. Whole blood (WB) and oral fluid (OF) samples were collected before and up to 3.5 h after smoking the joints. Pharmacokinetic analyses were obtained from these data. Questionnaires assessing the subjective effects were administered to the subjects during each session before and after the smoking time period. THC, 11-hydroxy-THC (11-OH-THC) and 11-nor-9-carboxy-THC (THCCOOH) were analyzed in the blood by gas chromatography or liquid chromatography (LC)-tandem mass spectrometry (MS/MS). The determination of THC, THCCOOH, cannabinol (CBN), and Δ9-tetrahydrocannabinolic acid A (THC-A) was carried out on OF only using LC-MS/MS. In line with the widely accepted assumption that cannabis smoking results in a strong contamination of the oral cavity, we found that THC, and also THC-A, shows a sharp, high concentration peak just after smoking, with a rapid decrease in these levels within 3 h. No obvious differences were found between both groups concerning THC median maximum concentrations measured either in blood or in OF; these levels were equal to 1,338 and 1,041 μg/L in OF and to 82 and 94 μg/L in WB for occasional and heavy smokers, respectively. The initial WB THCCOOH concentration was much higher in regular smokers than in occasional users. Compared with the occasional smokers, the sensation of confusion felt by the regular smokers was much less while the feeling of intoxication remained almost unchanged.

Challenging the "inoffensiveness" of regular cannabis use by its associations with other current risky substance use--a census of 20-year-old Swiss men.

3,537 men enrolling in 2007 for mandatory army recruitment procedures were assessed for the co-occurrence of risky licit substance use among risky cannabis users. Risky cannabis use was defined as at least twice weekly; risky alcohol use as 6+ drinks more than once/monthly, or more than 20 drinks per week; and risky tobacco use as daily smoking. Ninety-five percent of all risky cannabis users reported other risky use. They began using cannabis earlier than did non-risky users, but age of onset was unrelated to other risky substance use. A pressing public health issue among cannabis users stems from risky licit substance use warranting preventive efforts within this age group.