38 research outputs found

    Singapore's health-care system:key features, challenges, and shifts

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    Since Singapore became an independent nation in 1965, the development of its health-care system has been underpinned by an emphasis on personal responsibility for health, and active government intervention to ensure access and affordability through targeted subsidies and to reduce unnecessary costs. Singapore is achieving good health outcomes, with a total health expenditure of 4·47% of gross domestic product in 2016. However, the health-care system is contending with increased stress, as reflected in so-called pain points that have led to public concern, including shortages in acute hospital beds and intermediate and long-term care (ILTC) services, and high out-of-pocket payments. The main drivers of these challenges are the rising prevalence of non-communicable diseases and rapid population ageing, limitations in the delivery and organisation of primary care and ILTC, and financial incentives that might inadvertently impede care integration. To address these challenges, Singapore's Ministry of Health implemented a comprehensive set of reforms in 2012 under its Healthcare 2020 Masterplan. These reforms substantially increased the capacity of public hospital beds and ILTC services in the community, expanded subsidies for primary care and long-term care, and introduced a series of financing health-care reforms to strengthen financial protection and coverage. However, it became clear that these measures alone would not address the underlying drivers of system stress in the long term. Instead, the system requires, and is making, much more fundamental changes to its approach. In 2016, the Ministry of Health encapsulated the required shifts in terms of the so-called Three Beyonds—namely, beyond health care to health, beyond hospital to community, and beyond quality to value

    Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

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    To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events42Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases

    Detectable clonal mosaicism and its relationship to aging and cancer

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    In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases

    Measurement of CP asymmetries and branching fraction ratios of B− decays to two charm mesons

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    The CPCP asymmetries of seven BB^- decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9fb19\text{fb}^{-1} of proton-proton collisions collected by the LHCb experiment. Decays involving a D0D^{*0} or DsD^{*-}_s meson are analysed by reconstructing only the D0D^0 or DsD^-_s decay products. This paper presents the first measurement of ACP(BDsD0)\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0) and ACP(BDsD0)\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0}), and the most precise measurement of the other five CPCP asymmetries. There is no evidence of CPCP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.The CP asymmetries of seven B^{−} decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9 fb1^{−1} of proton-proton collisions collected by the LHCb experiment. Decays involving a D0^{*0} or Ds {D}_s^{\ast -} meson are analysed by reconstructing only the D0^{0} or Ds {D}_s^{-} decay products. This paper presents the first measurement of ACP \mathcal{A} ^{CP}(B^{−}Ds {D}_s^{\ast -} D0^{0}) and ACP \mathcal{A} ^{CP}(B^{−}Ds {D}_s^{-} D0^{∗0}), and the most precise measurement of the other five CP asymmetries. There is no evidence of CP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.[graphic not available: see fulltext]The CPCP asymmetries of seven BB^- decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9 fb19\text{ fb}^{-1} of proton-proton collisions collected by the LHCb experiment. Decays involving a D0D^{*0} or DsD^{*-}_s meson are analysed by reconstructing only the D0D^0 or DsD^-_s decay products. This paper presents the first measurement of ACP(BDsD0)\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0) and ACP(BDsD0)\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0}), and the most precise measurement of the other five CPCP asymmetries. There is no evidence of CPCP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured

    Helium identification with LHCb

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    The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at √(s) = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb-1. A total of around 105 helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10^12). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei

    Momentum scale calibration of the LHCb spectrometer

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    For accurate determination of particle masses accurate knowledge of the momentum scale of the detectors is crucial. The procedure used to calibrate the momentum scale of the LHCb spectrometer is described and illustrated using the performance obtained with an integrated luminosity of 1.6 fb-1 collected during 2016 in pp running. The procedure uses large samples of J/ψ → μ + μ - and B+ → J/ψ K + decays and leads to a relative accuracy of 3 × 10-4 on the momentum scale

    Curvature-bias corrections using a pseudomass method

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    Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy √(s)=13 TeV during 2016, 2017 and 2018. The biases are determined using Z→μ + μ - decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10-4 GeV-1 level, improves the Z→μ + μ - mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    The Physics of the B Factories

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