989 research outputs found

    Moving from evidence-based medicine to evidence-based health.

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    While evidence-based medicine (EBM) has advanced medical practice, the health care system has been inconsistent in translating EBM into improvements in health. Disparities in health and health care play out through patients' limited ability to incorporate the advances of EBM into their daily lives. Assisting patients to self-manage their chronic conditions and paying attention to unhealthy community factors could be added to EBM to create a broader paradigm of evidence-based health. A perspective of evidence-based health may encourage physicians to consider their role in upstream efforts to combat socially patterned chronic disease

    Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

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    We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information

    How large should whales be?

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    The evolution and distribution of species body sizes for terrestrial mammals is well-explained by a macroevolutionary tradeoff between short-term selective advantages and long-term extinction risks from increased species body size, unfolding above the 2g minimum size induced by thermoregulation in air. Here, we consider whether this same tradeoff, formalized as a constrained convection-reaction-diffusion system, can also explain the sizes of fully aquatic mammals, which have not previously been considered. By replacing the terrestrial minimum with a pelagic one, at roughly 7000g, the terrestrial mammal tradeoff model accurately predicts, with no tunable parameters, the observed body masses of all extant cetacean species, including the 175,000,000g Blue Whale. This strong agreement between theory and data suggests that a universal macroevolutionary tradeoff governs body size evolution for all mammals, regardless of their habitat. The dramatic sizes of cetaceans can thus be attributed mainly to the increased convective heat loss is water, which shifts the species size distribution upward and pushes its right tail into ranges inaccessible to terrestrial mammals. Under this macroevolutionary tradeoff, the largest expected species occurs where the rate at which smaller-bodied species move up into large-bodied niches approximately equals the rate at which extinction removes them.Comment: 7 pages, 3 figures, 2 data table

    A genome-wide association study identifies protein quantitative trait loci (pQTLs)

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    There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8Γ—10 -57), CCL4L1 (p = 3.9Γ—10-21), IL18 (p = 6.8Γ—10-13), LPA (p = 4.4Γ—10-10), GGT1 (p = 1.5Γ—10-7), SHBG (p = 3.1Γ—10-7), CRP (p = 6.4Γ—10-6) and IL1RN (p = 7.3Γ—10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8Γ—10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. Β© 2008 Melzer et al

    Density functional theory study of the multimode Jahn-Teller effect – ground state distortion of benzene cation

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    The multideterminental-DFT approach performed to analyze Jahn-Teller (JT) active molecules is described. Extension of this method for the analysis of the adiabatic potential energy surfaces and the multimode JT effect is presented. Conceptually a simple model, based on the analogy between the JT distortion and reaction coordinates gives further information about microscopic origin of the JT effect. Within the harmonic approximation the JT distortion can be expressed as a linear combination of all totally symmetric normal modes in the low symmetry minimum energy conformation, which allows calculating the Intrinsic Distortion Path, IDP, exactly from the high symmetry nuclear configuration to the low symmetry energy minimum. It is possible to quantify the contribution of different normal modes to the distortion, their energy contribution to the total stabilization energy and how their contribution changes along the IDP. It is noteworthy that the results obtained by both multideterminental-DFT and IDP methods for different classes of JT active molecules are consistent and in agreement with available theoretical and experimental values. As an example, detailed description of the ground state distortion of benzene cation is given

    Changing atmospheric CO2 concentration was the primary driver of early Cenozoic climate

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    The Early Eocene Climate Optimum (EECO, which occurred about 51 to 53 million years ago)1, was the warmest interval of the past 65 million years, with mean annual surface air temperature over ten degrees Celsius warmer than during the pre-industrial period2–4. Subsequent global cooling in the middle and late Eocene epoch, especially at high latitudes, eventually led to continental ice sheet development in Antarctica in the early Oligocene epoch (about 33.6 million years ago). However, existing estimates place atmospheric carbon dioxide (CO2) levels during the Eocene at 500–3,000 parts per million5–7, and in the absence of tighter constraints carbon–climate interactions over this interval remain uncertain. Here we use recent analytical and methodological developments8–11 to generate a new high-fidelity record of CO2 concentrations using the boron isotope (Ξ΄11Ξ’) composition of well preserved planktonic foraminifera from the Tanzania Drilling Project, revising previous estimates6. Although species-level uncertainties make absolute values difficult to constrain, CO2 concentrations during the EECO were around 1,400 parts per million. The relative decline in CO2 concentration through the Eocene is more robustly constrained at about fifty per cent, with a further decline into the Oligocene12. Provided the latitudinal dependency of sea surface temperature change for a given climate forcing in the Eocene was similar to that of the late Quaternary period13, this CO2 decline was sufficient to drive the well documented high- and low-latitude cooling that occurred through the Eocene14. Once the change in global temperature between the pre-industrial period and the Eocene caused by the action of all known slow feedbacks (apart from those associated with the carbon cycle) is removed2–4, both the EECO and the late Eocene exhibit an equilibrium climate sensitivity relative to the pre-industrial period of 2.1 to 4.6 degrees Celsius per CO2 doubling (66 per cent confidence), which is similar to the canonical range (1.5 to 4.5 degrees Celsius15), indicating that a large fraction of the warmth of the early Eocene greenhouse was driven by increased CO2 concentrations, and that climate sensitivity was relatively constant throughout this period

    Evaluating the Quality of Research into a Single Prognostic Biomarker: A Systematic Review and Meta-analysis of 83 Studies of C-Reactive Protein in Stable Coronary Artery Disease

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    Background Systematic evaluations of the quality of research on a single prognostic biomarker are rare. We sought to evaluate the quality of prognostic research evidence for the association of C-reactive protein (CRP) with fatal and nonfatal events among patients with stable coronary disease. Methods and Findings We searched MEDLINE (1966 to 2009) and EMBASE (1980 to 2009) and selected prospective studies of patients with stable coronary disease, reporting a relative risk for the association of CRP with death and nonfatal cardiovascular events. We included 83 studies, reporting 61,684 patients and 6,485 outcome events. No study reported a prespecified statistical analysis protocol; only two studies reported the time elapsed (in months or years) between initial presentation of symptomatic coronary disease and inclusion in the study. Studies reported a median of seven items (of 17) from the REMARK reporting guidelines, with no evidence of change over time. The pooled relative risk for the top versus bottom third of CRP distribution was 1.97 (95% confidence interval [CI] 1.78–2.17), with substantial heterogeneity (I2 = 79.5). Only 13 studies adjusted for conventional risk factors (age, sex, smoking, obesity, diabetes, and low-density lipoprotein [LDL] cholesterol) and these had a relative risk of 1.65 (95% CI 1.39–1.96), I2 = 33.7. Studies reported ten different ways of comparing CRP values, with weaker relative risks for those based on continuous measures. Adjusting for publication bias (for which there was strong evidence, Egger's p<0.001) using a validated method reduced the relative risk to 1.19 (95% CI 1.13–1.25). Only two studies reported a measure of discrimination (c-statistic). In 20 studies the detection rate for subsequent events could be calculated and was 31% for a 10% false positive rate, and the calculated pooled c-statistic was 0.61 (0.57–0.66). Conclusion Multiple types of reporting bias, and publication bias, make the magnitude of any independent association between CRP and prognosis among patients with stable coronary disease sufficiently uncertain that no clinical practice recommendations can be made. Publication of prespecified statistical analytic protocols and prospective registration of studies, among other measures, might help improve the quality of prognostic biomarker research

    Fortified breakfast cereal consumed daily for 12 wk leads to a significant improvement in micronutrient intake and micronutrient status in adolescent girls: a randomised controlled trial

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    Background: Poor micronutrient status is reported among adolescents across Europe and USA. This may be related to the well-documented decline in the regular consumption of breakfast by this group. The regular consumption of a breakfast cereal offers a possible means to improve micronutrient status; fortified cereal is likely to have enhanced benefit. A study was conducted to determine the efficacy of the regular consumption of a fortified cereal with milk, compared with unfortified cereal, consumed either as a breakfast or a supper, in improving micronutrient intake and micronutrient status of adolescent girls. Methods: A randomised, double-blind, placebo-controlled intervention trial was conducted in girls recruited at ages 16–19 years, from schools and colleges in Sheffield, UK. Girls were randomised to receive 50 g fortified or unfortified cereal, with 150 ml semi-skimmed milk, daily, for 12 weeks, as a breakfast or as a supper. Dietary intake was estimated using a 4-d food diary and blood collected for the assessment of nutritional status. Within-group changes were tested using a paired sample t test; two-way ANOVA was used to analyse effects of the intervention, with cereal type and time of consumption as factors, correcting for baseline values. The analysis was conducted on 71 girls who completed the study. Results: Consumption of unfortified cereal elicited an increase in the intake of vitamins B1, B2 and B6; consumption of fortified cereal elicited increases in vitamins B1, B2, B6, B12, folate and iron (P < 0.001) and of vitamin D (P = 0.007), all increases were significantly greater than for unfortified cereal. Consumption of the fortified cereal also led to a significant improvement in biomarkers of status for vitamins B2, B12, folate and of iron, compared with girls receiving the unfortified cereal, and maintained vitamin D status, in contrast with the girls receiving the unfortified cereal (P < 0.001). Conclusions: The daily consumption of cereal with milk for 12 weeks by adolescent girls, increased intakes of micronutrients. The consumption of fortified cereal elicited greater increases than for unfortified cereal and improved biomarkers of micronutrient status. The findings justify strategies to encourage the consumption of fortified cereal with milk by adolescents, either as a breakfast or a supper

    Histone H3 Localizes to the Centromeric DNA in Budding Yeast

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    During cell division, segregation of sister chromatids to daughter cells is achieved by the poleward pulling force of microtubules, which attach to the chromatids by means of a multiprotein complex, the kinetochore. Kinetochores assemble at the centromeric DNA organized by specialized centromeric nucleosomes. In contrast to other eukaryotes, which typically have large repetitive centromeric regions, budding yeast CEN DNA is defined by a 125 bp sequence and assembles a single centromeric nucleosome. In budding yeast, as well as in other eukaryotes, the Cse4 histone variant (known in vertebrates as CENP-A) is believed to substitute for histone H3 at the centromeric nucleosome. However, the exact composition of the CEN nucleosome remains a subject of debate. We report the use of a novel ChIP approach to reveal the composition of the centromeric nucleosome and its localization on CEN DNA in budding yeast. Surprisingly, we observed a strong interaction of H3, as well as Cse4, H4, H2A, and H2B, but not histone chaperone Scm3 (HJURP in human) with the centromeric DNA. H3 localizes to centromeric DNA at all stages of the cell cycle. Using a sequential ChIP approach, we could demonstrate the co-occupancy of H3 and Cse4 at the CEN DNA. Our results favor a H3-Cse4 heterotypic octamer at the budding yeast centromere. Whether or not our model is correct, any future model will have to account for the stable association of histone H3 with the centromeric DNA
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