147 research outputs found

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

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    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

    Age- and gender-specific risk of death after first hospitalization for heart failure

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    <p>Abstract</p> <p>Background</p> <p>Hospitalization for heart failure (HF) is associated with high-in-hospital and short- and long-term post discharge mortality. Age and gender are important predictors of mortality in hospitalized HF patients. However, studies assessing short- and long-term risk of death stratified by age and gender are scarce.</p> <p>Methods</p> <p>A nationwide cohort was identified (ICD-9 codes 402, 428) and followed through linkage of national registries. The crude 28-day, 1-year and 5-year mortality was computed by age and gender. Cox regression models were used for each period to study sex differences adjusting for potential confounders (age and comorbidities).</p> <p>Results</p> <p>14,529 men, mean age 74 ± 11 years and 14,524 women, mean age 78 ± 11 years were identified. Mortality risk after admission for HF increased with age and the risk of death was higher among men than women. Hazard ratio's (men versus women and adjusted for age and co-morbidity) were 1.21 (95%CI 1.14 to 1.28), 1.26 (95% CI 1.21 to 1.31), and 1.28 (95%CI 1.24 to 1.31) for 28 days, 1 year and 5 years mortality, respectively.</p> <p>Conclusions</p> <p>This study clearly shows age- and gender differences in short- and long-term risk of death after first hospitalization for HF with men having higher short- and long-term risk of death than women. As our study population includes both men and women from all ages, the estimates we provide maybe a good reflection of 'daily practice' risk of death and therefore be valuable for clinicians and policymakers.</p

    Review of the literature and suggestions for the design of rodent survival studies for the identification of compounds that increase health and life span

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    Much of the literature describing the search for agents that increase the life span of rodents was found to suffer from confounds. One-hundred-six studies, absent 20 contradictory melatonin studies, of compounds or combinations of compounds were reviewed. Only six studies reported both life span extension and food consumption data, thereby excluding the potential effects of caloric restriction. Six other studies reported life span extension without a change in body weight. However, weight can be an unreliable surrogate measure of caloric consumption. Twenty studies reported that food consumption or weight was unchanged, but it was unclear whether these data were anecdotal or systematic. Twenty-nine reported extended life span likely due to induced caloric restriction. Thirty-six studies reported no effect on life span, and three a decrease. The remaining studies suffer from more serious confounds. Though still widely cited, studies showing life span extension using short-lived or “enfeebled” rodents have not been shown to predict longevity effects in long-lived animals. We suggest improvements in experimental design that will enhance the reliability of the rodent life span literature. First, animals should receive measured quantities of food and its consumption monitored, preferably daily, and reported. Weights should be measured regularly and reported. Second, a genetically heterogeneous, long-lived rodent should be utilized. Third, chemically defined diets should be used. Fourth, a positive control (e.g., a calorically restricted group) is highly desirable. Fifth, drug dosages should be chosen based on surrogate endpoints or accepted cross-species scaling factors. These procedures should improve the reliability of the scientific literature and accelerate the identification of longevity and health span-enhancing agents

    Colony-level differences in the scaling rules governing wood ant compound eye structure

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    Differential organ growth during development is essential for adults to maintain the correct proportions and achieve their characteristic shape. Organs scale with body size, a process known as allometry that has been studied extensively in a range of organisms. Such scaling rules, typically studied from a limited sample, are assumed to apply to all members of a population and/or species. Here we study scaling in the compound eyes of workers of the wood ant, Formica rufa, from different colonies within a single population. Workers' eye area increased with body size in all the colonies showing a negative allometry. However, both the slope and intercept of some allometric scaling relationships differed significantly among colonies. Moreover, though mean facet diameter and facet number increased with body size, some colonies primarily increased facet number whereas others increased facet diameter, showing that the cellular level processes underlying organ scaling differed among colonies. Thus, the rules that govern scaling at the organ and cellular levels can differ even within a single population

    Why education in public schools should include religious ideals

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    This article aims to open a new line of debate about religion in public schools by focusing on religious ideals. The article begins with an elucidation of the concept ‘religious ideals’ and an explanation of the notion of reasonable pluralism, in order to be able to explore the dangers and positive contributions of religious ideals and their pursuit on a liberal democratic society. We draw our examples of religious ideals from Christianity and Islam, because these religions have most adherents in Western liberal democracies that are the focus of this article. The fifth and most important section "Reasonable pluralism and the inclusion of religious ideals in public secondary schools" provides three arguments for our claim that public schools should include religious ideals, namely that they are important to religious people, that they are conducive for the development of pupils into citizens of a liberal democracy, and that the flourishing of pupils as adults is advanced by encountering religious ideals. We also offer a more practical reason: religious ideals can more easily be included within public education than religious dogmas and rules

    MTH1 deficiency selectively increases non-cytotoxic oxidative DNA damage in lung cancer cells: more bad news than good?

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    Representative images of “Comets” and the corresponding intensity profiles, showing (i) ~ 5% Tail DNA damage, typical of the NSCLC cells treated with no siRNA or scramble siRNA, and analysed by regular Fpg-modified alkaline comet assay (0.8 U Fpg/gel); and (ii) comets showing ~ 10% tail DNA, typical of the NSCLC cells treated with MTH1 siRNA. Superimposed on the Comet images are the image analysis software (Komet 5.5, Andor Technology) determined boundaries demarcating the ‘Comet head’ (pink circle) and ‘tail extent’ (vertical orange line) (Barber RC, Hickenbotham P, Hatch T, Kelly D, Topchiy N, Almeida GM, et al. Radiation-induced transgenerational alterations in genome stability and DNA damage. Oncogene. 2006;25(56):7336–7342). % tail DNA = 100 - % head DNA; % head DNA = (integrated optical head intensity / (integrated optical head intensity + integrated optical tail intensity)) × 100. (PDF 1431 kb
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