On the construction of LIECE models for the serotonin receptor 5-HT[Formula: see text]R

Computer-aided approaches to ligand design need to balance accuracy with speed. This is particularly true for one of the key parameters to be optimized during ligand development, the free energy of binding ([Formula: see text]G[Formula: see text]). Here, we developed simple models based on the Linear Interaction Energy approximation to free energy calculation for a G protein-coupled receptor, the serotonin receptor 2A, and critically evaluated their accuracy. Several lessons can be taken from our calculations, providing information on the influence of the docking software used, the conformational state of the receptor, the cocrystallized ligand, and its comparability to the training/test ligands

The Main Patterns in the Trend Change of Stomach Cancer Incidence amongst Selected African Countries

Aim. The current study aimed to investigate the trend changes of stomach cancer incidence amongst African countries and identify the main patterns. Methods. The annual reports of stomach cancer incidence rate (per 100,000 people) for males and females in 53 African countries from 1990 to 2016 were maintained from the World Health Organization archive. The growth mixture model was used for fitting the models in Mplus 7.4. The estimated linear trend in each pattern was characterized by intercept (the rate at 1990) and slope (the observed biennial trend changes), and finally, each country was grouped into a cluster with the most similar pattern. Results. Three main patterns for males and two main patterns for females were determined. For males, the first cluster, containing Cape Verde, Central African Republic, and Mauritius, showed a sharp fall, while countries in the second pattern including Algeria, Cote d'Ivoire, Egypt, Gambia, Libya, Malawi, Morocco, Namibia, Nigeria, and Tunisia were categorized in a pattern with a slight decrease, and other 43 countries were in the third pattern with a moderate falling trend. For females, 19 countries including Angola, Botswana, Burundi, Cape Verde, Central African Republic, Congo Republic, Equatorial Guinea, Ethiopia, Gabon, Kenya, Mali, Mauritius, Rwanda, Sao Tome and Principe, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe were categorized in the moderate-to-high falling pattern, but the other 34 countries had a gentle downward pattern. Conclusion. Although most of the observed trends of stomach cancer were falling, only a few countries had experienced a favorable decreasing trend (three countries in male incidence and nineteen countries in female incidence). Therefore, taking effective actions to accelerate the observed falling trends seems necessary

Impact of menopause on relapse rate and disability level in patients with multiple sclerosis (MS): a systematic review and meta-analysis

Abstract Background Menopause is a physiologic phase in women’s lives. Findings regarding multiple sclerosis (MS) course through menopause are diverse. So, we designed this systematic review and meta-analysis to estimate the impact of menopause on relapse rate, and disability status in women with MS. Methods PubMed, Scopus, EMBASE, Web of Science, and google scholar were systematically searched by two independent researchers on January 1st, 2023. They also evaluated conference abstracts, and references of the included studies. In addition, data regarding the total number of participants, name of the first author of the publication, publication year, country of origin, disease duration, disease type, annual relapse rate, and Expanded Disability Status Scale (EDSS) before and after menopause were recorded. Results A literature search revealed 1024 records. Twenty-one full texts were evaluated, and finally, four studies were included for meta-analysis. Mean ARR before menopause ranged between 0.21 and 0.37, and after menopause ranged between 0.13 and 0.08. The SMD of mean ARR ranged between − 1.04, and − 0.29, while the pooled SMD was estimated as -0.52(95% CI: -0.88, -0.15) (I2 = 73.6%, P = 0.02). The mean EDSS before menopause ranged between 1.5 and 2, and after menopause ranged between 2 and 3.1. The SMD of EDSS ranged between 0.46, and 0.71. The pooled SMD of EDSS change (after menopause-before menopause) estimated as 0.56(95% CI: 0.38, 0.73)(I2 = 0, P = 0.4). Conclusion The result of this systematic review and meta-analysis show that menopause can be associated with relapse rate reduction, unlike increase in disease-related disability in women with MS

Effects of Averrhoa Carambola Hydro-Alcoholic Extract on Liver Histopathological Changes in Rats with a High-Fat Diet

Background & Objective: In the present study the effects of Averrhoa carambola fruit hydro-alcoholic extract on hepatic tissue, liver enzymes, and serum lipids were investigated in rats submitted to a high-fat diet. Materials & Methods: In this experimental study, 30 male Wistar rats were randomly divided to 3 equal groups as follows: (1) control, (2) rats fed a high-fat diet and (3) rats receiving a high fat diet and hydro-alcoholic extract of Averrhoa carambola (A. carambola) at a dose of (200 mg/kg bw). Rats received a high-fat diet for one month. Then, two rats were selected from each diet group and hyperlipidemia was confirmed by measurement of serum triglyceride and serum cholesterol levels. After confirming hyperlipidemia, rats of group 3 were orally treated by Averrhoa carambola (200 mg/kg bw) for 21 days. At the end of the experiment, serum liver enzymes, serum cholesterol and triglyceride levels were assayed. Afterward, for histopathological investigation, hepatic tissue samples were prepared and routine tissue processing protocol was performed. Results: The administration of Averrhoa carambola fruit extract significantly reduced serum triglyceride and cholesterol when compared with the hyperlipidemic group (P < 0.05 and P < 0.001 respectively). Serum ALT and AST in rats that received Averrhoa carambola fruit extract significantly decreased compared to hyperlipidemic group (P< 0.05). In the histopathological examination, degeneration, vacuolation and intra-cytoplasmic accumulations in the treated group were improved in comparison with the hyperlipidemic group. Conclusion: These results showed that the Averrhoa carambola fruit extract can protect against hyperlipidemia- induced liver damage in rats

Screening of Clinically Approved and Investigation Drugs as Potential Inhibitors of SARS-CoV-2 Main Protease and Spike Receptor-Binding Domain Bound with ACE2 COVID19 Target Proteins: A Virtual Drug Repurposing Study

In this virtual drug repurposing study, we used 7922 FDA approved drugs and compounds in clinical investigation from NPC database. Both apo and holo forms of SARS-CoV-2 Main Protease as well as Spike Protein/ACE2 were used for virtual screening. Initially, docking was performed for these compounds at target binding sites. The compounds were then sorted according to their docking scores which represent binding energies. The first 100 compounds from each docking simulations were initially subjected to short (10 ns) MD simulations (in total 300 ligand-bound complexes), and average binding energies during MD simulations were calculated using the MM/GBSA method. Then, the selected promising hit compounds based on average MM/GBSA scores were used in long (100-ns and 500-ns) MD simulations. In total around 15 µs MD simulations were performed in this study. Both docking and MD simulations binding free energy calculations showed that holo form of the target protein is more appropriate choice for virtual drug screening studies. These numerical calculations have shown that the following 8 compounds can be considered as SARS-CoV-2 Main Protease inhibitors: Pimelautide, Rotigaptide, Telinavir, Ritonavir, Pinokalant, Terlakiren, Cefotiam and Cefpiramide. In addition, following 5 compounds were identified as potential SARS-CoV-2 ACE-2/Spike protein domain inhibitors: Denopamine, Bometolol, Naminterol, Rotigaptide and Benzquercin. These compounds can be clinically tested and if the simulation results validated, they may be considered to be used as treatment for COVID-19

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

BackgroundAccurate 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. MethodsTo 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. FindingsDuring 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. InterpretationFertility 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. FundingBill & Melinda Gates Foundation

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

BackgroundAccurate 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.MethodsTo 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.FindingsDuring 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.InterpretationFertility 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.</p