Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Factors and processes shaping the population structure and distribution of genetic variation across the species range of the freshwater snail radix balthica (Pulmonata, Basommatophora)

Background: Factors and processes shaping the population structure and spatial distribution of genetic diversity across a species' distribution range are important in determining the range limits. We comprehensively analysed the influence of recurrent and historic factors and processes on the population genetic structure, mating system and the distribution of genetic variability of the pulmonate freshwater snail Radix balthica. This analysis was based on microsatellite variation and mitochondrial haplotypes using Generalised Linear Statistical Modelling in a Model Selection framework. Results: Populations of R. balthica were found throughout North-Western Europe with range margins marked either by dispersal barriers or the presence of other Radix taxa. Overall, the population structure was characterised by distance independent passive dispersal mainly along a Southwest-Northeast axis, the absence of isolation-by-distance together with rather isolated and genetically depauperated populations compared to the variation present in the entire species due to strong local drift. A recent, climate driven range expansion explained most of the variance in genetic variation, reducing at least temporarily the genetic variability in this area. Other factors such as geographic marginality and dispersal barriers play only a minor role. Conclusions: To our knowledge, such a population structure has rarely been reported before. It might nevertheless be typical for passively dispersed, patchily distributed taxa (e.g. freshwater invertebrates). The strong local drift implied in such a structure is expected to erode genetic variation at both neutral and coding loci and thus probably diminish evolutionary potential. This study shows that the analysis of multiple factors is crucial for the inference of the processes shaping the distribution of genetic variation throughout species ranges. Additional files Additional file 1: Distribution of Radix taxa. Spatial distribution of the Radix MOTU as defined in Pfenninger et al. 2006 plus an additional, newly discovered taxon. This map is the basis for the inference of the species range of R. balthica. Additional file 2: Sampling site table and spatial distribution of diversity indices, selfing estimates and inferred population bottlenecks for R. balthica. Table of sampling site code, geographical position in decimal degrees latitude and longitude, number of individuals analysed with microsatellites (Nnuc), expected heterozygosity (HE) and standard deviation across loci, mean rarefied number of alleles per microsatellite locus (A) and their standard deviation, number of individuals analysed for mitochondrial variation (Nmt), rarefied number of mitochondrial COI haplotypes (Hmt), number of individuals measured for body size (Nsize). Figures A1 - A3 show a graphical representation of the spatial distribution of He, Hmt and, s, respectively. Additional file 3: Assessment of environmental marginality. PCA (principle component analysis) on 35 climatic parameters for the period from 1960 - 2000 from publicly availableWorldClim data. Additional file 4: Inference of a recent climate driven range expansion in R. balthica. Analysis of the freshwater benthos long term monitoring data of the Swedish national monitoring databases at the Swedish University of Agricultural Sciences SLU with canonical correspondence analysis

Polymorphisms of the TUB Gene Are Associated with Body Composition and Eating Behavior in Middle-Aged Women

BACKGROUND: The TUB gene, encoding an evolutionary conserved protein, is highly expressed in the hypothalamus and might act as a transcription factor. Mutations in TUB cause late-onset obesity, insulin-resistance and neurosensory deficits in mice. An association of common variants in the TUB gene with body weight in humans has been reported. METHODS/FINDINGS: The aim was to investigate the relationship of single nucleotide polymorphisms (SNPs) of the TUB gene (rs2272382, rs2272383 and rs1528133) with both anthropometry and self-reported macronutrient intake from a validated food frequency questionnaire. These associations were studied in a population-based, cross-sectional study of 1680 middle-aged Dutch women, using linear regression analysis. The minor allele C of the rs1528133 SNP was significantly associated with increased weight (+1.88 kg, P = 0.022) and BMI (+0.56 units, P = 0.05). Compared with non-carriers, both AG heterozygotes and AA homozygotes of the rs2272382 SNP derived less energy from fat (AG: -0.55+/-0.28%, P = 0.05, AA: -0.95+/-0.48%, P = 0.047). However, both genotypes were associated with an increased energy intake from carbohydrates (0.69+/-0.33%, P = 0.04 and 1.68+/-0.56%, P = 0.003, respectively), mainly because of a higher consumption of mono- and disaccharides. Both these SNPs, rs2272382 and rs1528133, were also associated with a higher glycemic load in the diet. The glycemic load was higher among those with AG and AA genotypes for the variant rs2272382 than among the wild types (+1.49 (95% CI: -0.27-3.24) and +3.89 (95% CI: 0.94-6.85) units, respectively). Carriers of the minor allele C of rs1528133 were associated with an increased glycemic load of 1.85 units compared with non-carriers. CONCLUSIONS: Genetic variation of the TUB gene was associated with both body composition and macronutrient intake, suggesting that TUB might influence eating behavior

Molecular mechanisms of severe acute respiratory syndrome (SARS)

Severe acute respiratory syndrome (SARS) is a new infectious disease caused by a novel coronavirus that leads to deleterious pulmonary pathological features. Due to its high morbidity and mortality and widespread occurrence, SARS has evolved as an important respiratory disease which may be encountered everywhere in the world. The virus was identified as the causative agent of SARS due to the efforts of a WHO-led laboratory network. The potential mutability of the SARS-CoV genome may lead to new SARS outbreaks and several regions of the viral genomes open reading frames have been identified which may contribute to the severe virulence of the virus. With regard to the pathogenesis of SARS, several mechanisms involving both direct effects on target cells and indirect effects via the immune system may exist. Vaccination would offer the most attractive approach to prevent new epidemics of SARS, but the development of vaccines is difficult due to missing data on the role of immune system-virus interactions and the potential mutability of the virus. Even in a situation of no new infections, SARS remains a major health hazard, as new epidemics may arise. Therefore, further experimental and clinical research is required to control the disease

Meta-analysis of genome-wide association studies for extraversion:Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP <5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P <5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.Peer reviewe

MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people

While an estimated 14-20% of young adults experience mental health conditions worldwide, the best strategies for prevention and management are not fully understood. The ubiquity of smartphone use among young people makes them excellent candidates for collecting data about lived experiences and their relationships to mental health. However, not much is known about the factors affecting young peoples’ willingness to share information about their mental health. OBJECTIVE: We aim to understand the data governance and engagement strategies influencing young peoples’ (aged 16-24) participation in app-based studies of mental health. We hypothesize that willingness to participate in research is influenced by involvement  in how their data is collected, shared, and used. METHODS: Here, we describe the MindKind Study, which employs mixed methods to understand the feasibility of global, smartphone-based studies of youth mental health. A pilot 12-week app-based substudy will query participants’ willingness to engage with remote mental health studies. Participants will be randomized into one of four different data governance models designed to understand their preferences, as well as the acceptability of models that allow them more or less control over how their data are accessed and used. Enrolees will receive one of two different engagement strategies. A companion qualitative study will employ a deliberative democracy approach to examine the preferences, concerns and expectations of young people, with respect to remote mental health research. We also detail our engagement with young people as co-researchers in this study. This pilot study is being conducted in India, South Africa and the United Kingdom. CONCLUSION: This study is expected to generate new insights into the feasibility of, and best practices for, remote smartphone-based studies of mental health in youth and represents an important step toward understanding which approaches could help people better manage their mental health