93 research outputs found

    Global surveillance of cancer survival 1995-2009: analysis of individual data for 25,676,887 patients from 279 population-based registries in 67 countries (CONCORD-2)

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    BACKGROUND: Worldwide data for cancer survival are scarce. We aimed to initiate worldwide surveillance of cancer survival by central analysis of population-based registry data, as a metric of the effectiveness of health systems, and to inform global policy on cancer control. METHODS: Individual tumour records were submitted by 279 population-based cancer registries in 67 countries for 25·7 million adults (age 15-99 years) and 75,000 children (age 0-14 years) diagnosed with cancer during 1995-2009 and followed up to Dec 31, 2009, or later. We looked at cancers of the stomach, colon, rectum, liver, lung, breast (women), cervix, ovary, and prostate in adults, and adult and childhood leukaemia. Standardised quality control procedures were applied; errors were corrected by the registry concerned. We estimated 5-year net survival, adjusted for background mortality in every country or region by age (single year), sex, and calendar year, and by race or ethnic origin in some countries. Estimates were age-standardised with the International Cancer Survival Standard weights. FINDINGS: 5-year survival from colon, rectal, and breast cancers has increased steadily in most developed countries. For patients diagnosed during 2005-09, survival for colon and rectal cancer reached 60% or more in 22 countries around the world; for breast cancer, 5-year survival rose to 85% or higher in 17 countries worldwide. Liver and lung cancer remain lethal in all nations: for both cancers, 5-year survival is below 20% everywhere in Europe, in the range 15-19% in North America, and as low as 7-9% in Mongolia and Thailand. Striking rises in 5-year survival from prostate cancer have occurred in many countries: survival rose by 10-20% between 1995-99 and 2005-09 in 22 countries in South America, Asia, and Europe, but survival still varies widely around the world, from less than 60% in Bulgaria and Thailand to 95% or more in Brazil, Puerto Rico, and the USA. For cervical cancer, national estimates of 5-year survival range from less than 50% to more than 70%; regional variations are much wider, and improvements between 1995-99 and 2005-09 have generally been slight. For women diagnosed with ovarian cancer in 2005-09, 5-year survival was 40% or higher only in Ecuador, the USA, and 17 countries in Asia and Europe. 5-year survival for stomach cancer in 2005-09 was high (54-58%) in Japan and South Korea, compared with less than 40% in other countries. By contrast, 5-year survival from adult leukaemia in Japan and South Korea (18-23%) is lower than in most other countries. 5-year survival from childhood acute lymphoblastic leukaemia is less than 60% in several countries, but as high as 90% in Canada and four European countries, which suggests major deficiencies in the management of a largely curable disease. INTERPRETATION: International comparison of survival trends reveals very wide differences that are likely to be attributable to differences in access to early diagnosis and optimum treatment. Continuous worldwide surveillance of cancer survival should become an indispensable source of information for cancer patients and researchers and a stimulus for politicians to improve health policy and health-care systems

    The genetic architecture of the human cerebral cortex

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    INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

    Muon reconstruction performance of the ATLAS detector in proton–proton collision data at √s = 13 TeV

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    This article documents the performance of the ATLAS muon identification and reconstruction using the LHC dataset recorded at √s = 13 TeV in 2015. Using a large sample of J/ψ→ΌΌ and Z→ΌΌ decays from 3.2 fb−1 of pp collision data, measurements of the reconstruction efficiency, as well as of the momentum scale and resolution, are presented and compared to Monte Carlo simulations. The reconstruction efficiency is measured to be close to 99% over most of the covered phase space (|η| 2.2, the pT resolution for muons from Z→ΌΌ decays is 2.9 % while the precision of the momentum scale for low-pT muons from J/ψ→ΌΌ decays is about 0.2%

    Measurement of the dependence of transverse energy production at large pseudorapidity on the hard-scattering kinematics of proton-proton collisions at √s=2.76 TeV with ATLAS

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    The relationship between jet production in the central region and the underlying-event activity in a pseudorapidity-separated region is studied in 4.0 pb-1 of s=2.76 TeV pp collision data recorded with the ATLAS detector at the LHC. The underlying event is characterised through measurements of the average value of the sum of the transverse energy at large pseudorapidity downstream of one of the protons, which are reported here as a function of hard-scattering kinematic variables. The hard scattering is characterised by the average transverse momentum and pseudorapidity of the two highest transverse momentum jets in the event. The dijet kinematics are used to estimate, on an event-by-event basis, the scaled longitudinal momenta of the hard-scattered partons in the target and projectile beam-protons moving toward and away from the region measuring transverse energy, respectively. Transverse energy production at large pseudorapidity is observed to decrease with a linear dependence on the longitudinal momentum fraction in the target proton and to depend only weakly on that in the projectile proton. The results are compared to the predictions of various Monte Carlo event generators, which qualitatively reproduce the trends observed in data but generally underpredict the overall level of transverse energy at forward pseudorapidity

    Measurement of W boson angular distributions in events with high transverse momentum jets at s√= 8 TeV using the ATLAS detector

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    The W boson angular distribution in events with high transverse momentum jets is measured using data collected by the ATLAS experiment from proton–proton collisions at a centre-of-mass energy at the Large Hadron Collider, corresponding to an integrated luminosity of . The focus is on the contributions to processes from real W emission, which is achieved by studying events where a muon is observed close to a high transverse momentum jet. At small angular separations, these contributions are expected to be large. Various theoretical models of this process are compared to the data in terms of the absolute cross-section and the angular distributions of the muon from the leptonic W decay.Fil: Aaboud, M.. UniversitĂ© Mohamed Premier and LPTPM; MarruecosFil: Aad, G.. Aix-Marseille UniversitĂ© ; FranciaFil: Abbott, B.. Oklahoma State University; Estados UnidosFil: Abdallah, J.. Academia Sinica; ChinaFil: Abdinov, O.. Azerbaijan Academy of Sciences; AzerbaiyĂĄnFil: Alconada Verzini, MarĂ­a Josefina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Alonso, Francisco. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Arduh, Francisco Anuar. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Dova, Maria Teresa. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Hoya, JoaquĂ­n. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Monticelli, Fernando Gabriel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Wahlberg, Hernan Pablo. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Bossio Sola, Jonathan David. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Marceca, Gino. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Otero y Garzon, Gustavo Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Piegaia, Ricardo Nestor. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Sacerdoti, Sabrina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Zibell. A.. Julius-Maximilians-UniversitĂ€t ; AlemaniaFil: Zieminska, D.. Indiana University; Estados UnidosFil: Zimine, N. I.. Joint Institute for Nuclear Research; RusiaFil: Zimmermann, C.. UniversitĂ€t Mainz ; AlemaniaFil: Zimmermann, S.. Albert-Ludwigs-UniversitĂ€t ; AlemaniaFil: Zinonos, Z.. Georg-August-UniversitĂ€t ; AlemaniaFil: Zinser, M.. UniversitĂ€t Mainz ; AlemaniaFil: Ziolkowski, M.. UniversitĂ€t Siegen ; AlemaniaFil: Ćœivković, L.. University of Belgrade ; SerbiaFil: Zobernig, G.. University of Wisconsin; Estados UnidosFil: Zoccoli, A.. UniversitĂ  di Bologna ; ItaliaFil: Nedden, M. zur. Humboldt University; AlemaniaFil: Zurzolo, G.. UniversitĂ  di Napoli; ItaliaFil: Zwalinski, L.. Cern - European Organization For Nuclear Research; SuizaFil: The ATLAS Collaboration. No especifica

    Constraints on new phenomena via Higgs boson couplings and invisible decays with the ATLAS detector

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    Abstract: The ATLAS experiment at the LHC has measured the Higgs boson couplings and mass, and searched for invisible Higgs boson decays, using multiple production and decay channels with up to 4.7 fb−1 of pp collision data at−1at TeV. In the current study, the measured production and decay rates of the observed Higgs boson in the γγ, ZZ, W W , ZÎł, bb, τ τ , and ΌΌ decay channels, along with results from the associated production of a Higgs boson with a top-quark pair, are used to probe the scaling of the couplings with mass. Limits are set on parameters in extensions of the Standard Model including a composite Higgs boson, an additional electroweak singlet, and two-Higgs-doublet models. Together with the measured mass of the scalar Higgs boson in the γγ and ZZ decay modes, a lower limit is set on the pseudoscalar Higgs boson mass of mA&gt; 370 GeV in the “hMSSM” simplified Minimal Supersymmetric Standard Model. Results from direct searches for heavy Higgs bosons are also interpreted in the hMSSM. Direct searches for invisible Higgs boson decays in the vector-boson fusion and associated production of a Higgs boson with W/Z (Z → ℓℓ, W/Z → jj) modes are statistically combined to set an upper limit on the Higgs boson invisible branching ratio of 0.25. The use of the measured visible decay rates in a more general coupling fit improves the upper limit to 0.23, constraining a Higgs portal model of dark matter.[Figure not available: see fulltext.

    Measurements of the Higgs boson production and decay rates and coupling strengths using pp collision data at √S=7 and 8 TeV in the ATLAS experiment

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    Combined analyses of the Higgs boson production and decay rates as well as its coupling strengths to vector bosons and fermions are presented. The combinations include the results of the analyses of the H -> gamma gamma, ZZ*, WW*, Z gamma, b (b) over bar, tau tau and mu mu decay modes, and the constraints on the associated production with a pair of top quarks and on the off-shell coupling strengths of the Higgs boson. The results are based on the LHC proton-proton collision datasets, with integrated luminosities of up to 4.7 fb(-1) at root s = 7 TeV and 20.3 fb(-1) at root s = 8 TeV, recorded by the ATLAS detector in 2011 and 2012. Combining all production modes and decay channels, the measured signal yield, normalised to the Standard Model expectation, is 1.18(-0.14)(+0.15). The observed Higgs boson production and decay rates are interpreted in a leading-order coupling framework, exploring a wide range of benchmark coupling models both with and without assumptions on the Higgs boson width and on the Standard Model particle content in loop processes. The data are found to be compatible with the Standard Model expectations for a Higgs boson at a mass of 125.36 GeV for all models considered

    Search for heavy lepton resonances decaying to a Z boson and a lepton in pp collisions at √s=8 TeV with the ATLAS detector

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    A search for heavy leptons decaying to a Z boson and an electron or a muon is presented. The search is based on pp collision data taken at s√=8 TeV by the ATLAS experiment at the CERN Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb−1. Three high-transverse-momentum electrons or muons are selected, with two of them required to be consistent with originating from a Z boson decay. No significant excess above Standard Model background predictions is observed, and 95% confidence level limits on the production cross section of high-mass trilepton resonances are derived. The results are interpreted in the context of vector-like lepton and type-III seesaw models. For the vector-like lepton model, most heavy lepton mass values in the range 114–176 GeV are excluded. For the type-III seesaw model, most mass values in the range 100–468 GeV are excluded
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