18 research outputs found

    Human iPSC ‐derived endothelial cells promote CNS remyelination via BDNF and mTORC1 pathway

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    Damage of myelin is a component of many diseases in the central nervous system (CNS). The activation and maturation of the quiescent oligodendrocyte progenitor cells (OPCs) are the crucial cellular processes for CNS remyelination, which is influenced by neuroinflammation in the lesion microenvironment. Endothelial cells derived from human induced pluripotent stem cells (hiPSC‐ECs) have shown promise in restoring function in various preclinical animal models. Here we ask whether and whether transplantation of hiPSC‐ECs could benefit remyelination in a mouse model of CNS demyelination. Our results show that in vitro, hiPSC‐ECs increase OPC proliferation, migration and differentiation via secreted soluble factors including brain‐derived neurotrophic factor (BDNF). hiPSC‐ECs also promote the survival of oligodendrocyte lineage cells in vitro and in vivo. Transplantation of hiPSC‐ECs into a toxin‐induced demyelination lesion in mouse corpus callosum (CC) leads to increased density of oligodendrocyte lineage cells and level of myelin in demyelinated area, correlated with a decreased neuroinflammation and an increased proportion of pro‐regenerative M2 phenotype in microglia/macrophages. The hiPSC‐EC‐exposed oligodendrocyte lineage cells showed significant increase in the level of phosphorylated S6 ribosomal protein (pS6) both in vitro and in vivo, indicating an involvement of mTORC1 pathway. These results suggest that hiPSC‐ECs may benefit myelin protection and regeneration which providing a potential source of cell therapy for a wide range of diseases and injuries associated with myelin damage

    Impact of Second Primary Malignancy Post–Autologous Transplantation on Outcomes of Multiple Myeloma: A CIBMTR Analysis

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    The overall survival (OS) has improved significantly in multiple myeloma (MM) over the last decade with the use of proteasome inhibitor and immunomodulatory drug-based combinations, followed by high-dose melphalan and autologous hematopoietic stem cell transplantation (auto-HSCT) and subsequent maintenance therapies in eligible newly diagnosed patients. However, clinical trials using auto-HSCT followed by lenalidomide maintenance have shown an increased risk of second primary malignancies (SPM), including second hematological malignancies (SHM). We evaluated the impact of SPM and SHM on progression-free survival (PFS) and OS in patients with MM after auto-HSCT using CIBMTR registry data. Adult patients with MM who underwent first auto-HSCT in the United States with melphalan conditioning regimen from 2011 to 2018 and received maintenance therapy were included (n = 3948). At a median follow-up of 37 months, 175 (4%) patients developed SPM, including 112 (64%) solid, 36 (20%) myeloid, 24 (14%) SHM, not otherwise specified, and 3 (2%) lymphoid malignancies. Multivariate analysis demonstrated that SPM and SHM were associated with an inferior PFS (hazard ratio [HR] 2.62, P \u3c .001 and HR 5.01, P \u3c .001, respectively) and OS (HR 3.85, P \u3c .001 and HR 8.13, P \u3c .001, respectively). In patients who developed SPM and SHM, MM remained the most frequent primary cause of death (42% vs 30% and 53% vs 18%, respectively). We conclude the development of SPM and SHM leads to a poor survival in patients with MM and is an important survivorship challenge. Given the median survival for MM continues to improve, continued vigilance is needed to assess the risks of SPM and SHM with maintenance therapy post-auto-HSCT

    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

    Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. 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

    Intralobar sequestration

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    Bronchopulmonary sequestration is a rare anomaly of the lung which is characterized by the presence of a mass of lung tissue which has no connection with the normal bronchopulmonary tree. Sequestration is of two types - intralobar and extralobar, of which intralobar is the more common one. Patients typically present with recurrent hemoptysis, which at times can be massive or with recurrent respiratory tract infections. This case is being presented to highlight the radiological as well as the intraoperative appearance of this rare anomaly

    Just quit: A modern way to quit smoking

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    One of the leading causes of early death nowadays is smoking. There are many applications available to assist individuals quit smoking, but many are inefficient as they require a lot of user involvement. These programs rely on the user to consistently track their smoking lapses and evaluate their success, which is quite unpleasant and demanding for the user. JustQuit is an application that has been developed for smokers who are motivated to quit. The application\u27s goal is to assist users in effectively quitting smoking by automatically identifying their smoking behavior using a machine learning approach and lowering reliance on the user to monitor their progress. The application offers a novel approach to this issue by gathering data from wearable sensors and utilizing machine learning techniques to predict the user\u27s smoking habit. The software will include elements like a points system, awards, and achievements based on the user\u27s successes acting as a motivation factor
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