44 research outputs found

    A more fine-grained measure towards animal welfare: a study with regards to gender differences in Spanish students

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    The environmental issue is nowadays taking more importance in the environmental awareness all around the world, and in this field, animal consideration is more and more spread. A highlighted part in globalisation is the animal welfare awareness. This article presents a study comparing attitudes towards animals among secondary and university students in reference to gender. It was carried out on 1394 Spanish participants from 11 to 26 years. The instrument used in the study is the reviewed version of the Animal Welfare Attitude Scale which was renamed as “Animal Welfare Attitude-Revised Scale” (AWA-R Scale), with a Cronbach a reliability value of 0.85. It is subdivided into four components namely C1: animal abuse for pleasure or due to ignorance; C2: leisure with animals; C3: farm animals; and C4: animal abandonment. These components have been deeply detailed by a confirmatory factor analysis (CFA), which highly contributes to define the position of participants for the different dimensions of animal welfare. It is concluded that significant differences exist between males’ and females’ attitudes in all components of the AWA-R Scale. It is also suggested that two social characteristics—people’s attitudes towards animals and towards environmental protection—are, at the very least, coexistent and may indeed be interdependent. These differences between gender in matters of socialisation could thus be reflected in environmental attitudes, and also in others related to them, i.e. animal welfare attitudes

    Population Genetics and Economic Growth

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    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Accuracy versus precision in boosted top tagging with the ATLAS detector

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    Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p

    Driver mutations of cancer epigenomes

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    Acute exercise modulates cigarette cravings and brain activation in response to smoking-related images: an fMRI study

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    Rationale Substances of misuse (such as nicotine) are associated with increases in activation within the mesocorticolimbic brain system, a system thought to mediate the rewarding effects of drugs of abuse. Pharmacological treatments have been designed to reduce cigarette cravings during temporary abstinence. Exercise has been found to be an effective tool for controlling cigarette cravings. Objective The objective of this study is to assess the effect of exercise on regional brain activation in response to smoking related images during temporary nicotine abstinence. Method In a randomized crossover design, regular smokers (n=10) undertook an exercise (10 min moderate-intensity stationary cycling) and control (passive seating for same duration) session, following 15 h of nicotine abstinence. Following treatments, participants entered a functional Magnetic Resonance Imaging (fMRI) scanner. Subjects viewed a random series of smoking and neutral images for 3 s, with an average inter-stimulus-interval (ISI) of 10 s. Self-reported cravings were assessed at baseline, mid-, and post-treatments. Results A significant interaction effect (time by group) was found, with self-reported cravings lower during and following exercise. During control scanning, significant activation was recorded in areas associated with reward (caudate nucleus), motivation (orbitofrontal cortex) and visuo-spatial attention (parietal lobe, parahippocampal, and fusiform gyrus). Post-exercise scanning showed hypoactivation in these areas with a concomitant shift of activation towards areas identified in the ‘brain default mode’ (Broadmanns Area 10). Conclusion The study confirms previous evidence that a single session of exercise can reduce cigarette cravings, and for the first time provides evidence of a shift in regional activation in response to smoking cues
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