96 research outputs found

    Diagnosis of aortic graft infection : a case definition by the management of aortic graft infection collaboration (MAGIC)

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    Objective/Background The management of aortic graft infection (AGI) is highly complex and in the absence of a universally accepted case definition and evidence-based guidelines, clinical approaches and outcomes vary widely. The objective was to define precise criteria for diagnosing AGI. Methods A process of expert review and consensus, involving formal collaboration between vascular surgeons, infection specialists, and radiologists from several English National Health Service hospital Trusts with large vascular services (Management of Aortic Graft Infection Collaboration [MAGIC]), produced the definition. Results Diagnostic criteria from three categories were classified as major or minor. It is proposed that AGI should be suspected if a single major criterion or two or more minor criteria from different categories are present. AGI is diagnosed if there is one major plus any criterion (major or minor) from another category. (i) Clinical/surgical major criteria comprise intraoperative identification of pus around a graft and situations where direct communication between the prosthesis and a nonsterile site exists, including fistulae, exposed grafts in open wounds, and deployment of an endovascular stent-graft into an infected field (e.g., mycotic aneurysm); minor criteria are localized AGI features or fever ≄38°C, where AGI is the most likely cause. (ii) Radiological major criteria comprise increasing perigraft gas volume on serial computed tomography (CT) imaging or perigraft gas or fluid (≄7 weeks and ≄3 months, respectively) postimplantation; minor criteria include other CT features or evidence from alternative imaging techniques. (iii) Laboratory major criteria comprise isolation of microorganisms from percutaneous aspirates of perigraft fluid, explanted grafts, and other intraoperative specimens; minor criteria are positive blood cultures or elevated inflammatory indices with no alternative source. Conclusion This AGI definition potentially offers a practical and consistent diagnostic standard, essential for comparing clinical management strategies, trial design, and developing evidence-based guidelines. It requires validation that is planned in a multicenter, clinical service database supported by the Vascular Society of Great Britain & Ireland

    The ‘mosaic habitat’ concept in human evolution: past and present

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    The habitats preferred by hominins and other species are an important theme in palaeoanthropology, and the ‘mosaic habitat’ (also referred to as habitat heterogeneity) has been a central concept in this regard for the last four decades. Here we explore the development of this concept – loosely defined as a range of different habitat types, such as woodlands, riverine forest and savannah within a limited spatial area– in studies of human evolution in the last sixty years or so. We outline the key developments that took place before and around the time when the term ‘mosaic’ came to wider palaeoanthropological attention. To achieve this we used an analysis of the published literature, a study of illustrations of hominin evolution from 1925 onwards and an email survey of senior researchers in palaeoanthropology and related fields. We found that the term mosaic starts to be applied in palaeoanthropological thinking during the 1970’s due to the work of a number of researchers, including Karl Butzer and Glynn Isaac , with the earliest usage we have found of ‘mosaic’ in specific reference to hominin habitats being by Adriaan Kortlandt (1972). While we observe a steady increase in the numbers of publications reporting mosaic palaeohabitats, in keeping with the growing interest and specialisation in various methods of palaeoenvironmental reconstruction, we also note that there is a lack of critical studies that define this habitat, or examine the temporal and spatial scales associated with it. The general consensus within the field is that the concept now requires more detailed definition and study to evaluate its role in human evolution

    Operation and performance of the ATLAS semiconductor tracker

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    The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74±0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, Ύ-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations

    Measurement of the correlation between flow harmonics of different order in lead-lead collisions at √sNN = 2.76 TeV with the ATLAS detector

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    Correlations between the elliptic or triangular flow coefficients vm (m=2 or 3) and other flow harmonics vn (n=2 to 5) are measured using √sNN=2.76 TeV Pb+Pb collision data collected in 2010 by the ATLAS experiment at the LHC, corresponding to an integrated luminosity of 7 ÎŒb−1. The vm−vn correlations are measured in midrapidity as a function of centrality, and, for events within the same centrality interval, as a function of event ellipticity or triangularity defined in a forward rapidity region. For events within the same centrality interval, v3 is found to be anticorrelated with v2 and this anticorrelation is consistent with similar anticorrelations between the corresponding eccentricities, Δ2 and Δ3. However, it is observed that v4 increases strongly with v2, and v5 increases strongly with both v2 and v3. The trend and strength of the vm−vn correlations for n=4 and 5 are found to disagree with Δm−Δn correlations predicted by initial-geometry models. Instead, these correlations are found to be consistent with the combined effects of a linear contribution to vn and a nonlinear term that is a function of v22 or of v2v3, as predicted by hydrodynamic models. A simple two-component fit is used to separate these two contributions. The extracted linear and nonlinear contributions to v4 and v5 are found to be consistent with previously measured event-plane correlations

    Search for Wâ€Č→tb→qqbb decays in pp collisions at √s=8 TeV with the ATLAS detector

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    A search for a massive Wâ€Č gauge boson decaying to a top quark and a bottom quark is performed with the ATLAS detector in pp collisions at the LHC. The dataset was taken at a centre-of-mass energy of √s=8 TeV and corresponds to 20.3 fb−1 of integrated luminosity. This analysis is done in the hadronic decay mode of the top quark, where novel jet substructure techniques are used to identify jets from high-momentum top quarks. This allows for a search for high-mass Wâ€Č bosons in the range 1.5–3.0 TeV. b-tagging is used to identify jets originating from b-quarks. The data are consistent with Standard Model background-only expectations, and upper limits at 95 % confidence level are set on the Wâ€Č→tb cross section times branching ratio ranging from 0.16pb to 0.33pb for left-handed Wâ€Č bosons, and ranging from 0.10pb to 0.21pb for Wâ€Č bosons with purely right-handed couplings. Upper limits at 95 % confidence level are set on the Wâ€Č-boson coupling to tb as a function of the Wâ€Č mass using an effective field theory approach, which is independent of details of particular models predicting a Wâ€Čboson

    Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design

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    Importance Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER-Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. Methods RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. Discussion RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero

    Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

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    Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2‱72 (95% uncertainty interval [UI] 2‱66–2‱79) in 2000 to 2‱31 (2‱17–2‱46) in 2019. Global annual livebirths increased from 134‱5 million (131‱5–137‱8) in 2000 to a peak of 139‱6 million (133‱0–146‱9) in 2016. Global livebirths then declined to 135‱3 million (127‱2–144‱1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2‱1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27‱1% (95% UI 26‱4–27‱8) of global livebirths. Global life expectancy at birth increased from 67‱2 years (95% UI 66‱8–67‱6) in 2000 to 73‱5 years (72‱8–74‱3) in 2019. The total number of deaths increased from 50‱7 million (49‱5–51‱9) in 2000 to 56‱5 million (53‱7–59‱2) in 2019. Under-5 deaths declined from 9‱6 million (9‱1–10‱3) in 2000 to 5‱0 million (4‱3–6‱0) in 2019. Global population increased by 25‱7%, from 6‱2 billion (6‱0–6‱3) in 2000 to 7‱7 billion (7‱5–8‱0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58‱6 years (56‱1–60‱8) in 2000 to 63‱5 years (60‱8–66‱1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

    Global burden of 87 risk factors in 204 countries and territories, 1990Ăąïżœïżœ2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 riskĂąïżœïżœoutcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 riskĂąïżœïżœoutcome pairs included in GBD 2017 no longer met inclusion criteria and 47 riskĂąïżœïżœoutcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51Ăąïżœïżœ12·1) deaths (19·2% 16·9Ăąïżœïżœ21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12Ăąïżœïżœ9·31) deaths (15·4% 14·6Ăąïżœïżœ16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253Ăąïżœïżœ350) DALYs (11·6% 10·3Ăąïżœïżœ13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0Ăąïżœïżœ9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10Ăąïżœïżœ24 years, alcohol use for those aged 25Ăąïżœïżœ49 years, and high systolic blood pressure for those aged 50Ăąïżœïżœ74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

    ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

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    This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton–proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb−1 of collisions at a centre-of-mass energy of s√=8 TeV, although in some case an additional 4.7 fb−1 of collision data at s√=7 TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.An erratum to this article can be found at http://dx.doi.org/10.1140/epjc/s10052-016-3935-
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