12 research outputs found

    Bone morphogenic protein-4 availability in the cardiac microenvironment controls inflammation and fibrosis in autoimmune myocarditis

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    Myocarditis is an inflammatory heart disease that leads to loss of cardiomyocytes and frequently precipitates fibrotic remodeling of the myocardium, culminating in heart failure. However, the molecular mechanisms underlying immune cell control and maintenance of tissue integrity in the inflamed cardiac microenvironment remain elusive. In this study, we found that bone morphogenic protein-4 (BMP4) gradients maintain cardiac tissue homeostasis by single-cell transcriptomics analyses of inflamed murine and human myocardial tissues. Cardiac BMP pathway dysregulation was reflected by reduced BMP4 serum concentration in patients with myocarditis. Restoration of BMP signaling by antibody-mediated neutralization of the BMP inhibitors gremlin-1 and gremlin-2 ameliorated T cell-induced myocardial inflammation in mice. Moreover, progression to inflammatory cardiomyopathy was blocked through the reduction of fibrotic remodeling and preservation of cardiomyocyte integrity. These results unveil the BMP4–gremlin axis as a druggable pathway for the treatment of myocardial inflammation, limiting the severe sequelae of cardiac fibrosis and heart failure

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

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    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

    Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

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    Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

    Short Codes with Near-ML Universal Decoding: Are Random Codes Good Enough?

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    Short blocklength codes have an important role in machine-type and ultra-low-latency communications. Unfortunately, reducing the blocklength makes it very challenging to achieve good error-correcting performance. There exist near-ML decoding algorithms with manageable complexity for short blocklength codes, such as ordered statistics decoding and the more recent guessing random additive noise decoding algorithm. These algorithms have the additional advantage that they are universal, in the sense that they can decode any linear block code. For this reason, some recent works have attempted to construct unstructured linear codes for use with universal decoders using sophisticated techniques, such as reinforcement learning. In this work, we first describe a genetic-algorithm-aided (GA-aided) construction method for unstructured codes and we then compare a very simple random construction to both the GA-aided construction and the reinforcement learning construction. Our simulation results indicate that, while some care should be taken when selecting an unstructured code, sophisticated and complex code construction methods may not be necessary in the sense that they lead to minimal improvements

    Methods for managing miscarriage:a network meta-analysis

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    BACKGROUND: Miscarriage, defined as the spontaneous loss of a pregnancy before 24 weeks’ gestation, is common with approximately 25% of women experiencing a miscarriage in their lifetime. An estimated 15% of pregnancies end in miscarriage. Miscarriage can lead to serious morbidity, including haemorrhage, infection, and even death, particularly in settings without adequate healthcare provision. Early miscarriages occur during the first 14 weeks of pregnancy, and can be managed expectantly, medically or surgically. However, there is uncertainty about the relative effectiveness and risks of each option. OBJECTIVES: To estimate the relative effectiveness and safety profiles for the different management methods for early miscarriage, and to provide rankings of the available methods according to their effectiveness, safety, and side‐effect profile using a network meta‐analysis. SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth’s Trials Register (9 February 2021), ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) (12 February 2021), and reference lists of retrieved studies. SELECTION CRITERIA: We included all randomised controlled trials assessing the effectiveness or safety of methods for miscarriage management. Early miscarriage was defined as less than or equal to 14 weeks of gestation, and included missed and incomplete miscarriage. Management of late miscarriages after 14 weeks of gestation (often referred to as intrauterine fetal deaths) was not eligible for inclusion in the review. Cluster‐ and quasi‐randomised trials were eligible for inclusion. Randomised trials published only as abstracts were eligible if sufficient information could be retrieved. We excluded non‐randomised trials. DATA COLLECTION AND ANALYSIS: At least three review authors independently assessed the trials for inclusion and risk of bias, extracted data and checked them for accuracy. We estimated the relative effects and rankings for the primary outcomes of complete miscarriage and composite outcome of death or serious complications. The certainty of evidence was assessed using GRADE. Relative effects for the primary outcomes are reported subgrouped by the type of miscarriage (incomplete and missed miscarriage). We also performed pairwise meta‐analyses and network meta‐analysis to determine the relative effects and rankings of all available methods. MAIN RESULTS: Our network meta‐analysis included 78 randomised trials involving 17,795 women from 37 countries. Most trials (71/78) were conducted in hospital settings and included women with missed or incomplete miscarriage. Across 158 trial arms, the following methods were used: 51 trial arms (33%) used misoprostol; 50 (32%) used suction aspiration; 26 (16%) used expectant management or placebo; 17 (11%) used dilatation and curettage; 11 (6%) used mifepristone plus misoprostol; and three (2%) used suction aspiration plus cervical preparation. Of these 78 studies, 71 (90%) contributed data in a usable form for meta‐analysis. Complete miscarriage Based on the relative effects from the network meta‐analysis of 59 trials (12,591 women), we found that five methods may be more effective than expectant management or placebo for achieving a complete miscarriage: · suction aspiration after cervical preparation (risk ratio (RR) 2.12, 95% confidence interval (CI) 1.41 to 3.20, low‐certainty evidence), · dilatation and curettage (RR 1.49, 95% CI 1.26 to 1.75, low‐certainty evidence), · suction aspiration (RR 1.44, 95% CI 1.29 to 1.62, low‐certainty evidence), · mifepristone plus misoprostol (RR 1.42, 95% CI 1.22 to 1.66, moderate‐certainty evidence), · misoprostol (RR 1.30, 95% CI 1.16 to 1.46, low‐certainty evidence). The highest ranked surgical method was suction aspiration after cervical preparation. The highest ranked non‐surgical treatment was mifepristone plus misoprostol. All surgical methods were ranked higher than medical methods, which in turn ranked above expectant management or placebo. Composite outcome of death and serious complications Based on the relative effects from the network meta‐analysis of 35 trials (8161 women), we found that four methods with available data were compatible with a wide range of treatment effects compared with expectant management or placebo: · dilatation and curettage (RR 0.43, 95% CI 0.17 to 1.06, low‐certainty evidence), · suction aspiration (RR 0.55, 95% CI 0.23 to 1.32, low‐certainty evidence), · misoprostol (RR 0.50, 95% CI 0.22 to 1.15, low‐certainty evidence), · mifepristone plus misoprostol (RR 0.76, 95% CI 0.31 to 1.84, low‐certainty evidence). Importantly, no deaths were reported in these studies, thus this composite outcome was entirely composed of serious complications, including blood transfusions, uterine perforations, hysterectomies, and intensive care unit admissions. Expectant management and placebo ranked the lowest when compared with alternative treatment interventions. Subgroup analyses by type of miscarriage (missed or incomplete) agreed with the overall analysis in that surgical methods were the most effective treatment, followed by medical methods and then expectant management or placebo, but there are possible subgroup differences in the effectiveness of the available methods.  AUTHORS' CONCLUSIONS: Based on relative effects from the network meta‐analysis, all surgical and medical methods for managing a miscarriage may be more effective than expectant management or placebo. Surgical methods were ranked highest for managing a miscarriage, followed by medical methods, which in turn ranked above expectant management or placebo. Expectant management or placebo had the highest chance of serious complications, including the need for unplanned or emergency surgery. A subgroup analysis showed that surgical and medical methods may be more beneficial in women with missed miscarriage compared to women with incomplete miscarriage. Since type of miscarriage (missed and incomplete) appears to be a source of inconsistency and heterogeneity within these data, we acknowledge that the main network meta‐analysis may be unreliable. However, we plan to explore this further in future updates and consider the primary analysis as separate networks for missed and incomplete miscarriage.

    MUSCLE COMPOSITION IN RESPIRATORY ACIDOSIS

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    Plant-parasitic nematodes are major agricultural pests worldwide and novel approaches to control them are sorely needed. We report the draft genome sequence of the root-knot nematode Meloidogyne incognita, a biotrophic parasite of many crops, including tomato, cotton and coffee. Most of the assembled sequence of this asexually reproducing nematode, totaling 86 Mb, exists in pairs of homologous but divergent segments. This suggests that ancient allelic regions in M. incognita are evolving toward effective haploidy, permitting new mechanisms of adaptation. The number and diversity of plant cell wall-degrading enzymes in M. incognita is unprecedented in any animal for which a genome sequence is available, and may derive from multiple horizontal gene transfers from bacterial sources. Our results provide insights into the adaptations required by metazoans to successfully parasitize immunocompetent plants, and open the way for discovering new antiparasitic strategie

    Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

    No full text
    BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic
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