Natural intraepithelial lymphocyte populations rise during necrotic enteritis in chickens

Intraepithelial lymphocytes (IEL) reside in the epithelium at the interface between the contents of the intestinal lumen and the sterile environment of the lamina propria. Because of this strategic location, IEL play a crucial role in various immunological processes, ranging from pathogen control to tissue stability. In mice and humans, IEL exhibit high diversity, categorized into induced IEL (conventional CD4 and CD8αβ T cells) and natural IEL (TCRαβCD8αα, TCRγδ, and TCRneg IEL). In chickens, however, the subpopulations of IEL and their functions in enteric diseases remain unclear. Thus, we conducted this study to investigate the role of IEL populations during necrotic enteritis (NE) in chickens. At 14 days of age, sixty-three Specific-pathogen-free (SPF) birds were randomly assigned to three treatments: Control (sham challenge), Eimeria maxima challenge (EM), and Eimeria maxima + Clostridium Perfringens (C. Perfringens) co-challenge (EM/CP). The EM and EM/CP birds were infected with Eimeria maxima at day 14 of age, and EM/CP birds were additionally orally inoculated with C. perfringens at days 18 and 19 of age. Birds were weighed at days 18, 20, and 26 of age to assess body weight gain (BWG). At 20 days of age (1 day-post C. perfringens infection; dpi), and 26 days of age (7 dpi), 7 birds per treatment were euthanized, and jejunum was harvested for gross lesion scores, IEL isolation, and gene expression. The EM/CP birds exhibited subclinical NE disease, lower BWG and shorter colon length. The Most changes in the IEL populations were observed at 1 dpi. The EM/CP group showed substantial increases in the total number of natural IEL subsets, including TCRαβ+CD4-CD8-, TCRαβ+CD8αα+, TCRγδ+, TCRneg and innate CD8α (iCD8α) cells by at least two-fold. However, by 7 dpi, only the number of TCRαβ+CD4-CD8- and TCRαβ+CD8αα+ IEL maintained their increase in the EM/CP group. The EM/CP group had significantly higher expression of proinflammatory cytokines (IL-1β and IFN-γ) and Osteopontin (OPN) in the jejunum at 1 dpi. These findings suggest that natural IEL with innate and innate-like functions might play a critical role in the host response during subclinical NE, potentially conferring protection against C. perfringens infection

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or $1132 (1119–1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that $54·8 billion in development assistance for health was disbursed in 2020. Of this,$13·7 billion was targeted toward the COVID-19 health response. $12·3 billion was newly committed and$1·4 billion was repurposed from existing health projects. $3·1 billion (22·4$2·4 billion (17·9%) was for supply chain and logistics. Only $714·4 million (7·7$1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world

کلامِ پروین شاکر میں تلمیحات

Parveen Shakir (1952-1994) is probably the most prominent Urdu poetess of all times who has earned the great fame and honour which is often dreamed by the poets. She is also one of those poets who had a considerable social status too besides her poetic fame, and this was only because she was a learned genius. This is the reason that her verses are empowered by URDU TALMEEHAAT (Famous and historic alludes). TALMEEH is one of the most powerful sources which give one's poetry the virtue of sublimity and enlightened it by different pieces of knowledge. It also makes the words of a poet wiser. Perveen Shakir's verses are also seemed full of vision and wisdom by her meaningful TALMEEHAAT. Besides many other characteristics this quality also emphasizes the importance of her poetry.</p

Image_1_Natural intraepithelial lymphocyte populations rise during necrotic enteritis in chickens.tif

Intraepithelial lymphocytes (IEL) reside in the epithelium at the interface between the contents of the intestinal lumen and the sterile environment of the lamina propria. Because of this strategic location, IEL play a crucial role in various immunological processes, ranging from pathogen control to tissue stability. In mice and humans, IEL exhibit high diversity, categorized into induced IEL (conventional CD4 and CD8αβ T cells) and natural IEL (TCRαβCD8αα, TCRγδ, and TCRneg IEL). In chickens, however, the subpopulations of IEL and their functions in enteric diseases remain unclear. Thus, we conducted this study to investigate the role of IEL populations during necrotic enteritis (NE) in chickens. At 14 days of age, sixty-three Specific-pathogen-free (SPF) birds were randomly assigned to three treatments: Control (sham challenge), Eimeria maxima challenge (EM), and Eimeria maxima + Clostridium Perfringens (C. Perfringens) co-challenge (EM/CP). The EM and EM/CP birds were infected with Eimeria maxima at day 14 of age, and EM/CP birds were additionally orally inoculated with C. perfringens at days 18 and 19 of age. Birds were weighed at days 18, 20, and 26 of age to assess body weight gain (BWG). At 20 days of age (1 day-post C. perfringens infection; dpi), and 26 days of age (7 dpi), 7 birds per treatment were euthanized, and jejunum was harvested for gross lesion scores, IEL isolation, and gene expression. The EM/CP birds exhibited subclinical NE disease, lower BWG and shorter colon length. The Most changes in the IEL populations were observed at 1 dpi. The EM/CP group showed substantial increases in the total number of natural IEL subsets, including TCRαβ+CD4-CD8-, TCRαβ+CD8αα+, TCRγδ+, TCRneg and innate CD8α (iCD8α) cells by at least two-fold. However, by 7 dpi, only the number of TCRαβ+CD4-CD8- and TCRαβ+CD8αα+ IEL maintained their increase in the EM/CP group. The EM/CP group had significantly higher expression of proinflammatory cytokines (IL-1β and IFN-γ) and Osteopontin (OPN) in the jejunum at 1 dpi. These findings suggest that natural IEL with innate and innate-like functions might play a critical role in the host response during subclinical NE, potentially conferring protection against C. perfringens infection.</p

Impact of COVID-19 on Patients Hospitalized with ST-Segment Elevation Myocardial Infarction in the United States during the Early Pandemic: An Analysis of Outcomes, Care Delivery, and Racial Disparities in Mortality

The COVID-19 pandemic has impacted healthcare delivery to patients with ST-segment elevation myocardial infarction (STEMI). The aim of our retrospective study was to determine the effect of COVID-19 on inpatient STEMI outcomes and to investigate changes in cardiac care delivery during 2020. We utilized the National Inpatient Sample database to examine inpatient mortality and cardiac procedures among STEMI patients with and without COVID-19. In our study, STEMI patients with COVID-19 had higher inpatient mortality (47.4% vs. 11.2%, aOR: 3.8, 95% CI: 3.2–4.6, p p p = 0.004) when compared to STEMI patients without COVID-19. STEMI patients with COVID-19 also received significantly less invasive cardiac procedures (coronary angiograms: 30.4% vs. 50.8%, p p p p < 0.001) when compared to STEMI patients without COVID-19. Our findings are the result of complications of SARS-CoV2 infection as well as alterations in healthcare delivery due to the burden of the COVID-19 pandemic