450 research outputs found

    Microbial colonization patterns predict the outcomes of surgical treatment of infrabony defect

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    Aim: To explore the impact of bacterial load and microbial colonization patterns on the clinical outcomes of periodontal surgery at deep intrabony defects. Materials and Methods: One hundred and twenty-two patients with advanced chronic periodontitis and at least one intrabony defect of 43mm were recruited in 10 centres. Before recruitment, the infection control phase of periodontal therapy was completed. After surgical access and debridement, the regenerative material was applied in the test subjects, and omitted in the controls. At baseline and 1 year following the interventions, clinical attachment levels (CAL), pocket probing depths (PPD), recession (REC), full-mouth plaque scores and full-mouth bleeding scores were assessed. Microbial colonization of the defect-associated pocket was assessed using a DNA\u2013DNA checkerboard analysis. Results: Total bacterial load and counts of red complex bacteria were negatively associated with CAL gains 1 year following treatment. The probability of achieving above median CAL gains (43 mm) was significantly decreased by higher total bacterial counts, higher red complex and T. forsythensis counts immediately before surgery. Conclusions: Presence of high bacterial load and specific periodontal pathogen complexes in deep periodontal pockets associated with intrabony defects had a significant negative impact on the 1 year outcome of surgical/regenerative treatmen

    Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

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    The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lowerstratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system¿s climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.This work uses S2S Project data. S2S is a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP). This work was initiated by the Stratospheric Network for the Assessment of Predictability (SNAP), a joint activity of SPARC (WCRP) and the S2S Project (WWRP–WCRP). The work of Rachel W.-Y. Wu is funded through ETH grant ETH-05 19-1. Support from the Swiss National Science Foundation through projects PP00P2_170523 and PP00P2_198896 to Daniela I. V. Domeisen is gratefully acknowledged. Chaim I. Garfinkel and Chen Schwartz are supported by the ISF–NSFC joint research program (grant no. 3259/19). The work of Marisol Osman was supported by UBACyT20020170100428BA and PICT-2018-03046 projects. The work of Alvaro de la Cámara is funded by the Spanish Ministry of Science and Innovation through project PID2019-109107GB-I00. Blanca Ayarzagüena and Natalia Calvo acknowledge the support of the Spanish Ministry of Science and Innovation through the JeDiS (RTI2018-096402-B-I00) project. Froila M. Palmeiro and Javier García-Serrano have been partially supported by the Spanish ATLANTE project (PID2019-110234RB-C21) and Ramón y Cajal program (RYC-2016-21181), respectively. Neil P. Hindley and Corwin J. Wright are supported by UK Natural Environment Research Council (NERC), grant number NE/S00985X/1. Corwin J. Wright is also supported by a Royal Society University Research Fellowship UF160545. Seok-Woo Son and Hera Kim are supported by the Basic Science Research Program through the National Research Foundation of Korea (2017R1E1A1A01074889). This material is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling program under award no. DE-SC0022070 and National Science Foundation (NSF) IA 1947282. This work was also supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Pu Lin is supported by award NA18OAR4320123 from the National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce. Zachary D. Lawrence was partially supported under NOAA award NA20NWS4680051; Zachary D. Lawrence and Judith Perlwitz also acknowledge support from US federally appropriated funds

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

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    A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

    Jet size dependence of single jet suppression in lead-lead collisions at sqrt(s(NN)) = 2.76 TeV with the ATLAS detector at the LHC

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    Measurements of inclusive jet suppression in heavy ion collisions at the LHC provide direct sensitivity to the physics of jet quenching. In a sample of lead-lead collisions at sqrt(s) = 2.76 TeV corresponding to an integrated luminosity of approximately 7 inverse microbarns, ATLAS has measured jets with a calorimeter over the pseudorapidity interval |eta| < 2.1 and over the transverse momentum range 38 < pT < 210 GeV. Jets were reconstructed using the anti-kt algorithm with values for the distance parameter that determines the nominal jet radius of R = 0.2, 0.3, 0.4 and 0.5. The centrality dependence of the jet yield is characterized by the jet "central-to-peripheral ratio," Rcp. Jet production is found to be suppressed by approximately a factor of two in the 10% most central collisions relative to peripheral collisions. Rcp varies smoothly with centrality as characterized by the number of participating nucleons. The observed suppression is only weakly dependent on jet radius and transverse momentum. These results provide the first direct measurement of inclusive jet suppression in heavy ion collisions and complement previous measurements of dijet transverse energy imbalance at the LHC.Comment: 15 pages plus author list (30 pages total), 8 figures, 2 tables, submitted to Physics Letters B. All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/HION-2011-02

    Measurement of the cross section for isolated-photon plus jet production in pp collisions at √s=13 TeV using the ATLAS detector

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    The dynamics of isolated-photon production in association with a jet in proton–proton collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset with an integrated luminosity of 3.2 fb−1. Photons are required to have transverse energies above 125 GeV. Jets are identified using the anti- algorithm with radius parameter and required to have transverse momenta above 100 GeV. Measurements of isolated-photon plus jet cross sections are presented as functions of the leading-photon transverse energy, the leading-jet transverse momentum, the azimuthal angular separation between the photon and the jet, the photon–jet invariant mass and the scattering angle in the photon–jet centre-of-mass system. Tree-level plus parton-shower predictions from Sherpa and Pythia as well as next-to-leading-order QCD predictions from Jetphox and Sherpa are compared to the measurements

    Measurement of the branching ratio Γ(Λb⁰ → ψ(2S)Λ0)/Γ(Λb⁰ → J/ψΛ0) with the ATLAS detector

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    An observation of the Λb0ψ(2S)Λ0\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0 decay and a comparison of its branching fraction with that of the Λb0J/ψΛ0\Lambda_b^0 \rightarrow J/\psi \Lambda^0 decay has been made with the ATLAS detector in proton--proton collisions at s=8\sqrt{s}=8\,TeV at the LHC using an integrated luminosity of 20.620.6\,fb1^{-1}. The J/ψJ/\psi and ψ(2S)\psi(2S) mesons are reconstructed in their decays to a muon pair, while the Λ0pπ\Lambda^0\rightarrow p\pi^- decay is exploited for the Λ0\Lambda^0 baryon reconstruction. The Λb0\Lambda_b^0 baryons are reconstructed with transverse momentum pT>10p_{\rm T}>10\,GeV and pseudorapidity η<2.1|\eta|<2.1. The measured branching ratio of the Λb0ψ(2S)Λ0\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0 and Λb0J/ψΛ0\Lambda_b^0 \rightarrow J/\psi \Lambda^0 decays is Γ(Λb0ψ(2S)Λ0)/Γ(Λb0J/ψΛ0)=0.501±0.033(stat)±0.019(syst)\Gamma(\Lambda_b^0 \rightarrow \psi(2S)\Lambda^0)/\Gamma(\Lambda_b^0 \rightarrow J/\psi\Lambda^0) = 0.501\pm 0.033 ({\rm stat})\pm 0.019({\rm syst}), lower than the expectation from the covariant quark model.Comment: 12 pages plus author list (28 pages total), 5 figures, 1 table, published on Physics Letters B 751 (2015) 63-80. All figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/BPHY-2013-08

    Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

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    This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

    Measurement of W± and Z-boson production cross sections in pp collisions at √s=13 TeV with the ATLAS detector

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    See paper for full list of authors - 17 pages plus author list + cover pages (34 pages total), 5 figures, 3 tables, submitted to Phys. Lett. B, All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2015-03/International audienceMeasurements of the W±±νW^{\pm} \rightarrow \ell^{\pm} \nu and Z+Z \rightarrow \ell^+ \ell^- production cross sections (where ±=e±,μ±\ell^{\pm}=e^{\pm},\mu^{\pm}) in proton-proton collisions at s=13\sqrt{s}=13 TeV are presented using data recorded by the ATLAS experiment at the Large Hadron Collider, corresponding to a total integrated luminosity of 81 pb1^{-1}. The total inclusive W±W^{\pm}-boson production cross sections times the single-lepton-flavour branching ratios are σW+tot=11.78±0.02(stat)±0.32(sys)±0.59(lumi)\sigma_{W^+}^{tot}= 11.78 \pm 0.02 (stat) \pm 0.32 (sys) \pm 0.59 (lumi) nb and σWtot=8.75±0.02(stat)±0.24(sys)±0.44(lumi)\sigma_{W^-}^{tot} = 8.75 \pm 0.02 (stat) \pm 0.24 (sys) \pm 0.44 (lumi) nb for W+W^+ and WW^-, respectively. The total inclusive ZZ-boson production cross section times leptonic branching ratio, within the invariant mass window 66<m<11666 < m_{\ell\ell} < 116 GeV, is σZtot=1.97±0.01(stat)±0.04(sys)±0.10(lumi)\sigma_{Z}^{tot} = 1.97 \pm 0.01 (stat) \pm 0.04 (sys) \pm 0.10 (lumi) nb. The W+W^+, WW^-, and ZZ-boson production cross sections and cross-section ratios within a fiducial region defined by the detector acceptance are also measured. The cross-section ratios benefit from significant cancellation of experimental uncertainties, resulting in σW+fid/σWfid=1.295±0.003(stat)±0.010(sys)\sigma_{W^+}^{fid}/\sigma_{W^-}^{fid} = 1.295 \pm 0.003 (stat) \pm 0.010 (sys) and σW±fid/σZfid=10.31±0.04(stat)±0.20(sys)\sigma_{W^{\pm}}^{fid}/\sigma_{Z}^{fid} = 10.31 \pm 0.04 (stat) \pm 0.20 (sys). Theoretical predictions, based on calculations accurate to next-to-next-to-leading order for quantum chromodynamics and next-to-leading order for electroweak processes and which employ different parton distribution function sets, are compared to these measurements

    Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at sqrt [ s ] = 13TeV

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    A search for physics beyond the Standard Model, in final states with at least one high transverse momentum charged lepton (electron or muon) and two additional high transverse momentum leptons or jets, is performed using 3.2 fb−1 of proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015 at √s = 13 TeV. The upper end of the distribution of the scalar sum of the transverse momenta of leptons and jets is sensitive to the production of high-mass objects. No excess of events beyond Standard Model predictions is observed. Exclusion limits are set for models of microscopic black holes with two to six extra dimensions
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