305 research outputs found

    Ageing and the Drosophila circadian clock

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    The Carrington event not observed in most ice core nitrate records

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    The Carrington Event of 1859 is considered to be among the largest space weather events of the last 150 years. We show that only one out of 14 well-resolved ice core records from Greenland and Antarctica has a nitrate spike dated to 1859. No sharp spikes are observed in the Antarctic cores studied here. In Greenland numerous spikes are observed in the 40 years surrounding 1859, but where other chemistry was measured, all large spikes have the unequivocal signal, including co-located spikes in ammonium, formate, black carbon and vanillic acid, of biomass burning plumes. It seems certain that most spikes in an earlier core, including that claimed for 1859, are also due to biomass burning plumes, and not to solar energetic particle (SEP) events. We conclude that an event as large as the Carrington Event did not leave an observable, widespread imprint in nitrate in polar ice. Nitrate spikes cannot be used to derive the statistics of SEPs

    Comment on “Low time resolution analysis of ice cores cannot detect impulsive nitrate events” by D. F. Smart et al.

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    Smart et al. (2014) suggested that the detection of nitrate spikes in polar ice cores from solar energetic particle (SEP) events could be achieved if an analytical system with sufficiently high resolution was used. Here we show that the spikes they associate with SEP events are not reliably recorded in cores from the same location, even when the resolution is clearly adequate. We explain the processes that limit the effective resolution of ice cores. Liquid conductivity data suggest that the observed spikes are associated with sodium or another nonacidic cation, making it likely that they result from deposition of sea salt or similar aerosol that has scavenged nitrate, rather than from a primary input of nitrate in the troposphere. We consider that there is no evidence at present to support the identification of any spikes in nitrate as representing SEP events. Although such events undoubtedly create nitrate in the atmosphere, we see no plausible route to using nitrate spikes to document the statistics of such events

    Genetic Analysis Workshop 17 mini-exome simulation

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    The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated

    Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

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    Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging

    Ferments in the Field: Introductory Reflections on the Past, Present and Future of Communication Studies

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    Journal of Communication (JoC) published its special issue “Ferment in the Field” in 1983 (vol. 33, no. 3). Thirty-five years later there still is a great interest in discussing the origins, current state, and prospects of our field. This special issue titled Ferments in the Field: The Past, Present and Future of Communication Studies presents 20 articles, plus this introduction, with the intention to assess the field and provoke discussions about the status of communication studies. This introductory article provides an overview of the contributions and discusses major trends in communication studies that have shaped the field since the original “ferment” issue. They include: (a) communication studies on a global scale, (b) researching communication in the fast-changing digital media environment, (c) the importance of critical communication studies, (d) the new critical and materialist turn, and (e) praxis communication and ways to address power imbalance in knowledge production

    The genetic basis of the comorbidity between cannabis use and major depression

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    Background and aims—While the prevalence of major depression is elevated amongst cannabis users, the role of genetics in this pattern of comorbidity is not clear. This study aimed to estimate the heritability of cannabis use and major depression, quantify the genetic overlap between these two traits, and localize regions of the genome that segregate in families with cannabis use and major depression. Design—Family-based univariate and bivariate genetic analysis. Setting—San Antonio, Texas, USA Participants—Genetics of Brain Structure and Function study (GOBS) participants: 1,284 Mexican-Americans from 75 large multi-generation families and an additional 57 genetically unrelated spouses. Measurements—Phenotypes of lifetime history of cannabis use and major depression, measured using the semi-structured MINI-Plus interview. Genotypes measured using ~1M single nucleotide polymorphisms (SNPs) on Illumina BeadChips. A sub-selection of these SNPs were used to build multipoint identity-by-descent matrices for linkage analysis. Findings—Both cannabis use (h2=0.614, p=1.00×10−6, SE=0.151) and major depression (h2=0.349, p=1.06×10−5, SE=0.100) are heritable traits, and there is significant genetic correlation between the two (ρg=0.424, p=0.0364, SE=0.195). Genome-wide linkage scans identify a significant univariate linkage peak for major depression on chromosome 22 (LOD=3.144 at 2cM), with a suggestive peak for cannabis use on chromosome 21 (LOD=2.123 at 37cM). A significant pleiotropic linkage peak influencing both cannabis use and major depression was identified on chromosome 11, using a bivariate model (LOD=3.229 at 112cM). Follow-up of this pleiotropic signal identified a SNP 20kb upstream of NCAM1 (rs7932341) that shows significant bivariate association (p=3.10×10−5). However this SNP is rare (7 minor allele carriers) and does not drive the linkage signal observed. Conclusions—There appears to be significant genetic overlap between cannabis use and major depression among Mexican-Americans, a pleiotropy that appears to be localized to a region on chromosome 11q23 that has been previously linked to these phenotypes

    Genome-wide significant loci for addiction and anxiety

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    Background Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. Methods Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. Results Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD = 3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD = 2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg = 0.550–0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD = 3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD = 3.425). Conclusions This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics
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