220 research outputs found

    Genomic insights into the conservation status of the world’s last remaining Sumatran rhinoceros populations

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    Highly endangered species like the Sumatran rhinoceros are at risk from inbreeding. Five historical and 16 modern genomes from across the species range show mutational load, but little evidence for local adaptation, suggesting that future inbreeding depression could be mitigated by assisted gene flow among populations. Small populations are often exposed to high inbreeding and mutational load that can increase the risk of extinction. The Sumatran rhinoceros was widespread in Southeast Asia, but is now restricted to small and isolated populations on Sumatra and Borneo, and most likely extinct on the Malay Peninsula. Here, we analyse 5 historical and 16 modern genomes from these populations to investigate the genomic consequences of the recent decline, such as increased inbreeding and mutational load. We find that the Malay Peninsula population experienced increased inbreeding shortly before extirpation, which possibly was accompanied by purging. The populations on Sumatra and Borneo instead show low inbreeding, but high mutational load. The currently small population sizes may thus in the near future lead to inbreeding depression. Moreover, we find little evidence for differences in local adaptation among populations, suggesting that future inbreeding depression could potentially be mitigated by assisted gene flow among populations

    Age, period, and cohort analysis of regular dental care behavior and edentulism: A marginal approach

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    <p>Abstract</p> <p>Background</p> <p>To analyze the regular dental care behavior and prevalence of edentulism in adult Danes, reported in sequential cross-sectional oral health surveys by the application of a marginal approach to consider the possible clustering effect of birth cohorts.</p> <p>Methods</p> <p>Data from four sequential cross-sectional surveys of non-institutionalized Danes conducted from 1975-2005 comprising 4330 respondents aged 15+ years in 9 birth cohorts were analyzed. The key study variables were seeking dental care on an annual basis (ADC) and edentulism. For the analysis of ADC, survey year, age, gender, socio-economic status (SES) group, denture-wearing, and school dental care (SDC) during childhood were considered. For the analysis of edentulism, only respondents aged 35+ years were included. Survey year, age, gender, SES group, ADC, and SDC during childhood were considered as the independent factors. To take into account the clustering effect of birth cohorts, marginal logistic regressions with an independent correlation structure in generalized estimating equations (GEE) were carried out, with PROC GENMOD in SAS software.</p> <p>Results</p> <p>The overall proportion of people seeking ADC increased from 58.8% in 1975 to 86.7% in 2005, while for respondents aged 35 years or older, the overall prevalence of edentulism (35+ years) decreased from 36.4% in 1975 to 5.0% in 2005. Females, respondents in the higher SES group, in more recent survey years, with no denture, and receiving SDC in all grades during childhood were associated with higher probability of seeking ADC regularly (<it>P </it>< 0.05). The interaction of SDC and age (<it>P </it>< 0.0001) was significant. The probabilities of seeking ADC were even higher among subjects with SDC in all grades and aged 45 years or older. Females, older age group, respondents in earlier survey years, not seeking ADC, lower SES group, and not receiving SDC in all grades were associated with higher probability of being edentulous (<it>P </it>< 0.05).</p> <p>Conclusions</p> <p>With the use of GEE, the potential clustering effect of birth cohorts in sequential cross-sectional oral health survey data could be appropriately considered. The success of Danish dental health policy was demonstrated by a continued increase of regular dental visiting habits and tooth retention in adults because school dental care was provided to Danes in their childhood.</p

    Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

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    The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

    Measurement of the production cross section for W-bosons in association with jets in pp collisions at s=7 TeV with the ATLAS detector

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    This Letter reports on a first measurement of the inclusive W + jets cross section in proton-proton collisions at a centre-of-mass energy of 7 TeV at the LHC, with the ATLAS detector. Cross sections, in both the electron and muon decay modes of the W-boson, are presented as a function of jet multiplicity and of the transverse momentum of the leading and next-to-leading jets in the event. Measurements are also presented of the ratio of cross sections sigma (W + >= n)/sigma(W + >= n - 1) for inclusive jet multiplicities n = 1-4. The results, based on an integrated luminosity of 1.3 pb(-1), have been corrected for all known detector effects and are quoted in a limited and well-defined range of jet and lepton kinematics. The measured cross sections are compared to particle-level predictions based on perturbative QCD. Next-to-leading order calculations, studied here for n <= 2, are found in good agreement with the data. Leading-order multiparton event generators, normalized to the NNLO total cross section, describe the data well for all measured jet multiplicitie

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

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    The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

    piggyBac is an effective tool for functional analysis of the Plasmodium falciparum genome

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    <p>Abstract</p> <p>Background</p> <p>Much of the <it>Plasmodium falciparum </it>genome encodes hypothetical proteins with limited homology to other organisms. A lack of robust tools for genetic manipulation of the parasite limits functional analysis of these hypothetical proteins and other aspects of the <it>Plasmodium </it>genome. Transposon mutagenesis has been used widely to identify gene functions in many organisms and would be extremely valuable for functional analysis of the <it>Plasmodium </it>genome.</p> <p>Results</p> <p>In this study, we investigated the lepidopteran transposon, <it>piggyBac</it>, as a molecular genetic tool for functional characterization of the <it>Plasmodium falciparum </it>genome. Through multiple transfections, we generated 177 unique <it>P. falciparum </it>mutant clones with mostly single <it>piggyBac </it>insertions in their genomes. Analysis of <it>piggyBac </it>insertion sites revealed random insertions into the <it>P. falciparum </it>genome, in regards to gene expression in parasite life cycle stages and functional categories. We further explored the possibility of forward genetic studies in <it>P. falciparum </it>with a phenotypic screen for attenuated growth, which identified several parasite genes and pathways critical for intra-erythrocytic development.</p> <p>Conclusion</p> <p>Our results clearly demonstrate that <it>piggyBac </it>is a novel, indispensable tool for forward functional genomics in <it>P. falciparum </it>that will help better understand parasite biology and accelerate drug and vaccine development.</p

    Predicting new venture survival and growth: does the fog lift?

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    This paper investigates whether new venture performance becomes easier to predict as the venture ages: does the fog lift? To address this question we primarily draw upon a theoretical framework, initially formulated in a managerial context by Levinthal (Adm Sci Q 36(3):397–420, 1991) that sees new venture sales as a random walk but survival being determined by the stock of available resources (proxied by size). We derive theoretical predictions that are tested with a 10-year cohort of 6579 UK new ventures in the UK. We observe that our ability to predict firm growth deteriorates in the years after entry—in terms of the selection environment, the ‘fog’ seems to thicken. However, our survival predictions improve with time—implying that the ‘fog’ does lift

    Investigation of type 1 diabetes and coeliac disease susceptibility loci for association with juvenile idiopathic arthritis

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    BACKGROUND: There is strong evidence suggesting that juvenile idiopathic arthritis (JIA) shares many susceptibility loci with other autoimmune diseases. OBJECTIVE: To investigate variants robustly associated with type 1 diabetes (T1D) or coeliac disease (CD) for association with JIA. METHODS: Sixteen single-nucleotide polymorphisms (SNPs) already identified as susceptibility loci for T1D/CD were selected for genotyping in patients with JIA (n=1054) and healthy controls (n=3129). Genotype and allele frequencies were compared using the Cochrane-Armitage trend test implemented in PLINK. RESULTS: One SNP in the LPP gene, rs1464510, showed significant association with JIA (p(trend)=0.002, OR=1.18, 95% CI 1.06 to 1.30). A second SNP, rs653178 in ATXN2, also showed nominal evidence for association with JIA (p(trend)=0.02, OR=1.13, 95% CI 1.02 to 1.25). The SNP, rs17810546, in IL12A showed subtype-specific association with enthesitis-related arthritis (ERA) subtype (p(trend)=0.005, OR=1.88, 95% CI 1.2 to 2.94). CONCLUSIONS: Evidence for a novel JIA susceptibility locus, LPP, is presented. Association at the SH2B3/ATXN2 locus, previously reported to be associated with JIA in a US series, also supports this region as contributing to JIA susceptibility. In addition, a subtype-specific association of IL12A with ERA is identified. All findings will require validation in independent JIA cohorts
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