101 research outputs found

    White rice, brown rice and the risk of type 2 diabetes: a systematic review and meta-analysis

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    Objective Intake of white rice has been associated with elevated risk for type 2 diabetes (T2D), while studies on brown rice are conflicting. To inform dietary guidance, we synthesised the evidence on white rice and brown rice with T2D risk. Design Systematic review and meta-analysis. Data sources PubMed, EMBASE and Cochrane databases were searched through November 2021. Eligibility criteria Prospective cohort studies of white and brown rice intake on T2D risk (≥1 year), and randomised controlled trials (RCTs) comparing brown rice with white rice on cardiometabolic risk factors (≥2 weeks). Data extraction and synthesis Data were extracted by the primary reviewer and two additional reviewers. Meta-analyses were conducted using random-effects models and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed using the Newcastle Ottawa Scale for prospective cohort studies and the Cochrane Risk of Bias Tool for RCTs. Strength of the meta-evidence was assessed using NutriGrade. Results Nineteen articles were included: 8 cohort studies providing 18 estimates (white rice: 15 estimates, 25 956 cases, n=5 77 426; brown rice: 3 estimates, 10 507 cases, n=1 97 228) and 11 RCTs (n=1034). In cohort studies, white rice was associated with higher risk of T2D (pooled RR, 1.16; 95% CI: 1.02 to 1.32) comparing extreme categories. At intakes above ~300 g/day, a dose–response was observed (each 158 g/day serving was associated with 13% (11%–15%) higher risk of T2D). Intake of brown rice was associated with lower risk of T2D (pooled RR, 0.89; 95% CI: 0.81 to 0.97) comparing extreme categories. Each 50 g/day serving of brown rice was associated with 13% (6%–20%) lower risk of T2D. Cohort studies were considered to be of good or fair quality. RCTs showed an increase in high-density lipoprotein-cholesterol (0.06 mmol/L; 0.00 to 0.11 mmol/L) in the brown compared with white rice group. No other significant differences in risk factors were observed. The majority of RCTs were found to have some concern for risk of bias. Overall strength of the meta-evidence was moderate for cohort studies and moderate and low for RCTs. Conclusion Intake of white rice was associated with higher risk of T2D, while intake of brown rice was associated with lower risk. Findings from substitution trials on cardiometabolic risk factors were inconsistent

    Search for the doubly heavy baryon Ξbc+\it{\Xi}_{bc}^{+} decaying to J/ψΞc+J/\it{\psi} \it{\Xi}_{c}^{+}

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    A first search for the Ξbc+J/ψΞc+\it{\Xi}_{bc}^{+}\to J/\it{\psi}\it{\Xi}_{c}^{+} decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9fb19\,\mathrm{fb}^{-1} recorded at centre-of-mass energies of 7, 8, and 13TeV13\mathrm{\,Te\kern -0.1em V}. Two peaking structures are seen with a local (global) significance of 4.3(2.8)4.3\,(2.8) and 4.1(2.4)4.1\,(2.4) standard deviations at masses of 6571MeV ⁣/c26571\,\mathrm{Me\kern -0.1em V\!/}c^2 and 6694MeV ⁣/c26694\,\mathrm{Me\kern -0.1em V\!/}c^2, respectively. Upper limits are set on the Ξbc+\it{\Xi}_{bc}^{+} baryon production cross-section times the branching fraction relative to that of the Bc+J/ψDs+B_{c}^{+}\to J/\it{\psi} D_{s}^{+} decay at centre-of-mass energies of 8 and 13TeV13\mathrm{\,Te\kern -0.1em V}, in the Ξbc+\it{\Xi}_{bc}^{+} and in the Bc+B_{c}^{+} rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to 20GeV ⁣/c20\,\mathrm{Ge\kern -0.1em V\!/}c, respectively. Upper limits are presented as a function of the Ξbc+\it{\Xi}_{bc}^{+} mass and lifetime.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-005.html (LHCb public pages

    Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980�2015: a systematic analysis for the Global Burden of Disease Study 2015

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    Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14�294 geography�year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95 uncertainty interval 61·4�61·9) in 1980 to 71·8 years (71·5�72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7�17·4), to 62·6 years (56·5�70·2). Total deaths increased by 4·1 (2·6�5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0 (15·8�18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1 (12·6�16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1 (11·9�14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1, 39·1�44·6), malaria (43·1, 34·7�51·8), neonatal preterm birth complications (29·8, 24·8�34·9), and maternal disorders (29·1, 19·3�37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146�000 deaths, 118�000�183�000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393�000 deaths, 228�000�532�000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost YLLs) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

    Study of the lineshape of the chi(c1) (3872) state

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    A study of the lineshape of the chi(c1) (3872) state is made using a data sample corresponding to an integrated luminosity of 3 fb(-1) collected in pp collisions at center-of-mass energies of 7 and 8 TeV with the LHCb detector. Candidate chi(c1)(3872) and psi(2S) mesons from b-hadron decays are selected in the J/psi pi(+)pi(-) decay mode. Describing the lineshape with a Breit-Wigner function, the mass splitting between the chi(c1 )(3872) and psi(2S) states, Delta m, and the width of the chi(c1 )(3872) state, Gamma(Bw), are determined to be (Delta m=185.598 +/- 0.067 +/- 0.068 Mev,)(Gamma BW=1.39 +/- 0.24 +/- 0.10 Mev,) where the first uncertainty is statistical and the second systematic. Using a Flatte-inspired model, the mode and full width at half maximum of the lineshape are determined to be (mode=3871.69+0.00+0.05 MeV.)(FWHM=0.22-0.04+0.13+0.07+0.11-0.06-0.13 MeV, ) An investigation of the analytic structure of the Flatte amplitude reveals a pole structure, which is compatible with a quasibound D-0(D) over bar*(0) state but a quasivirtual state is still allowed at the level of 2 standard deviations

    Measurement of the CKM angle γγ in B±DK±B^\pm\to D K^\pm and B±Dπ±B^\pm \to D π^\pm decays with DKS0h+hD \to K_\mathrm S^0 h^+ h^-

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    A measurement of CPCP-violating observables is performed using the decays B±DK±B^\pm\to D K^\pm and B±Dπ±B^\pm\to D \pi^\pm, where the DD meson is reconstructed in one of the self-conjugate three-body final states KSπ+πK_{\mathrm S}\pi^+\pi^- and KSK+KK_{\mathrm S}K^+K^- (commonly denoted KSh+hK_{\mathrm S} h^+h^-). The decays are analysed in bins of the DD-decay phase space, leading to a measurement that is independent of the modelling of the DD-decay amplitude. The observables are interpreted in terms of the CKM angle γ\gamma. Using a data sample corresponding to an integrated luminosity of 9fb19\,\text{fb}^{-1} collected in proton-proton collisions at centre-of-mass energies of 77, 88, and 13TeV13\,\text{TeV} with the LHCb experiment, γ\gamma is measured to be (68.75.1+5.2)\left(68.7^{+5.2}_{-5.1}\right)^\circ. The hadronic parameters rBDKr_B^{DK}, rBDπr_B^{D\pi}, δBDK\delta_B^{DK}, and δBDπ\delta_B^{D\pi}, which are the ratios and strong-phase differences of the suppressed and favoured B±B^\pm decays, are also reported

    The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

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    BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden

    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

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries
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