Comparando os efeitos do letrozol e os efeitos do tratamento de rotina da síndrome dos ovários policísticos na melhora dos sintomas de hiperandrogenismo

Polycystic ovary syndrome (PCOS) is one of the common forms of chronic anovulation associated with an increase in androgens. This disorder is associated with important morbidities during reproductive years. The objective of this research was to compare the effects of letrozole and routine treatment (oral Ethinylestradiol, cyproterone acetate and metformin) of polycystic ovary syndrome in improving symptoms of hyperandrogenism (hirsutism, acne).This is an applied-experimental study in which, 80 patients diagnosed with PCOS (polycystic ovary syndrome) were randomly divided into two groups. The first group was treated with 2.5 mg of Letrozole daily and the second group was treated with 500 mg of metformin once per day, 100 mg of cyproterone acetate once per day since 5-15 days of menstruation and oral Ethinylestradiol daily since 5 -25 days of menstrual cycles and they were followed-up regularly and periodically in the endocrinology clinic. After collecting data, they were analyzed using spss Software. No significant difference was found between two groups in the improvement of the hirsutism (p = 0.27). No significant difference was found between two groups in the improvement of acne (p = 0.54). In addition, the results of this study did not show any significant difference between the two groups in terms of acne and hirsutism improvement in the 6-month follow up.Based on the results of this study, two groups did not differ significantly. However, given the reduction in Ferriman-Gallwey score, letrozole can be a suitable drug for treating the symptoms of hyperandrogenism. Extensive studies are required in this regard to prove this assumption.El síndrome de ovario poliquístico (SOP) es una de las formas comunes de anovulación crónica asociada con un aumento de los andrógenos. Este trastorno se asocia con importantes morbilidades durante los años reproductivos. El objetivo de esta investigación fue comparar los efectos del letrozol y el tratamiento de rutina (etinilestradiol oral, acetato de ciproterona y metformina) del síndrome de ovario poliquístico para mejorar los síntomas de hiperandrogenismo (hirsutismo, acné).Este es un estudio experimental aplicado en el que 80 pacientes diagnosticados con SOP (síndrome de ovario poliquístico) se dividieron aleatoriamente en dos grupos. El primer grupo se trató con 2,5 mg de letrozol al día y el segundo grupo se trató con 500 mg de metformina una vez al día, 100 mg de acetato de ciproterona una vez al día desde los 5 a 15 días de menstruación y etinilestradiol oral diariamente de 5 a 25 días. de ciclos menstruales y fueron seguidos regularmente y periódicamente en la clínica de endocrinología. Después de recopilar los datos, se analizaron utilizando el software 21 de spss.No se encontraron diferencias significativas entre los dos grupos en la mejora del hirsutismo (p = 0,27). No se encontraron diferencias significativas entre los dos grupos en la mejora del acné (p = 0.54). Además, los resultados de este estudio no mostraron diferencias significativas entre los dos grupos en cuanto a la mejoría del acné y el hirsutismo en el seguimiento de 6 meses.Sobre la base de los resultados de este estudio, dos grupos no difirieron significativamente. Sin embargo, dada la reducción en la puntuación de Ferriman-Gallwey, el letrozol puede ser un fármaco adecuado para tratar los síntomas de hiperandrogenismo. Se requieren estudios extensos a este respecto para probar este supuesto.A síndrome do ovário policístico (SOP) é uma das formas mais comuns de anovulação crônica associada a um aumento de andrógenos. Este distúrbio está associado a importantes morbidades durante os anos reprodutivos. O objetivo desta pesquisa foi comparar os efeitos do tratamento com letrozol e rotina (Etinilestradiol oral, acetato de ciproterona e metformina) da síndrome dos ovários policísticos na melhora dos sintomas de hiperandrogenismo (hirsutismo, acne).Este é um estudo experimental-aplicado no qual 80 pacientes diagnosticados com SOP (síndrome do ovário policístico) foram divididos aleatoriamente em dois grupos. O primeiro grupo foi tratado com 2,5 mg de Letrozole diariamente e o segundo grupo foi tratado com 500 mg de metformina uma vez por dia, 100 mg de acetato de ciproterona uma vez por dia desde 5-15 dias da menstruação e Etinilestradiol oral diariamente desde 5 -25 dias de ciclos menstruais e eles foram acompanhados regularmente e periodicamente na clínica de endocrinologia. Depois de coletar os dados, eles foram analisados usando o spss 21Software.Nenhuma diferença significativa foi encontrada entre os dois grupos na melhora do hirsutismo (p = 0,27). Nenhuma diferença significativa foi encontrada entre os dois grupos na melhora da acne (p = 0,54). Além disso, os resultados deste estudo não mostraram diferença significativa entre os dois grupos em termos de melhora da acne e do hirsutismo no seguimento de 6 meses.Com base nos resultados deste estudo, dois grupos não diferiram significativamente. No entanto, dada a redução no escore de Ferriman-Gallwey, o letrozol pode ser um medicamento adequado para tratar os sintomas do hiperandrogenismo. Estudos extensos são necessários a esse respeito para provar essa suposição

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

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

Polymer-supported dichloroiodate as a new polymeric oxidation reagent for novel and selective oxidation of benzylic alcohols under mild aprotic conditions

A mild and efficient procedure has been proposed for oxidation of benzylic alcohols to the corresponding carbonyl compounds using polymer-supported dichloroiodate (PSDI). The oxidations were carried out in acetonitrile solution, affording the corresponding aldehydes or ketones in high substrate conversion and short reaction time under mild aprotic conditions. Excellent selectivity was observed between primary benzyl alcohols and secondary ones as well as non-benzylic alcohols in the oxidation reactions. The catalyst can be easily prepared and regenerated

Investigating the Polymorphism of Bone Morphogenetic Protein Receptor-1B (BMPR1B) Gene in Markhoz Goat Breed

Reproductive traits in livestock species are genetically controlled by the action of single genes with a major effect, commonly known as fecundity genes. One of the genes involved in controlling prolificacy is BMPR1B (FecB), a dominant autosomal gene located in chromosome 6 responsible for the fecundity and twinning rate in sheep and goat species. Markhoz goat is a valuable Iranian genetic resource endangered by extinction. Increasing the genetic variability and reproductive performances of Markhoz goat could preserve and enhance its economic value. This study was carried out to detect possible polymorphisms in BMPR1B gene in a sample of 100 Markhoz goats from Iran. DNA samples were screened by PCR–RFLP to assess the presence of the previously reported FecB mutation. Finally, the amplicons from seven goats out of the 100 samples were sequenced. The results showed that all the analyzed individuals did not carry the previously reported FecB mutant allele. However, our findings revealed two novel possible mutations in exon 8 of BMPR1B gene (775A > G and 777G > A) that need further investigations

Investigating the polymorphism of bone morphogenetic protein receptor-1B (BMPR1B) gene in Markhoz goat breed

Reproductive traits in livestock species are genetically controlled by the action of single genes with a major effect, commonly known as fecundity genes. One of the genes involved in controlling prolificacy is BMPR1B (FecB), a dominant autosomal gene located in chromosome 6 responsible for the fecundity and twinning rate in sheep and goat species. Markhoz goat is a valuable Iranian genetic resource endangered by extinction. Increasing the genetic variability and reproductive performances of Markhoz goat could preserve and enhance its economic value. This study was carried out to detect possible polymorphisms in BMPR1B gene in a sample of 100 Markhoz goats from Iran. DNA samples were screened by PCR–RFLP to assess the presence of the previously reported FecB mutation. Finally, the amplicons from seven goats out of the 100 samples were sequenced. The results showed that all the analyzed individuals did not carry the previously reported FecB mutant allele. However, our findings revealed two novel possible mutations in exon 8 of BMPR1B gene (775A>G and 777G>A) that need further investigations.Simple Summary TheBMPR1Bgene is one of the major genes involved in controlling prolificacy in small ruminant species. The research was conducted to detect possible polymorphisms inBMPR1Bgene in a population of Markhoz goats, a valuable genetic resource of Iran. The results showed that all the analyzed individuals did not carry the previously reported FecB mutant allele. Moreover, we reported for the first time two novel possible mutations in exon 8 ofBMPR1Bgene that are noteworthy of further investigation. Reproductive traits in livestock species are genetically controlled by the action of single genes with a major effect, commonly known as fecundity genes. One of the genes involved in controlling prolificacy isBMPR1B(FecB), a dominant autosomal gene located in chromosome 6 responsible for the fecundity and twinning rate in sheep and goat species. Markhoz goat is a valuable Iranian genetic resource endangered by extinction. Increasing the genetic variability and reproductive performances of Markhoz goat could preserve and enhance its economic value. This study was carried out to detect possible polymorphisms inBMPR1Bgene in a sample of 100 Markhoz goats from Iran. DNA samples were screened by PCR-RFLP to assess the presence of the previously reported FecB mutation. Finally, the amplicons from seven goats out of the 100 samples were sequenced. The results showed that all the analyzed individuals did not carry the previously reported FecB mutant allele. However, our findings revealed two novel possible mutations in exon 8 ofBMPR1Bgene (775A > G and 777G > A) that need further investigations

Bioinformatics analysis and machine learning approach applied to the identification of novel key genes involved in non-alcoholic fatty liver disease

Abstract Non-alcoholic fatty liver disease (NAFLD) comprises a range of chronic liver diseases that result from the accumulation of excess triglycerides in the liver, and which, in its early phases, is categorized NAFLD, or hepato-steatosis with pure fatty liver. The mortality rate of non-alcoholic steatohepatitis (NASH) is more than NAFLD; therefore, diagnosing the disease in its early stages may decrease liver damage and increase the survival rate. In the current study, we screened the gene expression data of NAFLD patients and control samples from the public dataset GEO to detect DEGs. Then, the correlation betweenbetween the top selected DEGs and clinical data was evaluated. In the present study, two GEO datasets (GSE48452, GSE126848) were downloaded. The dysregulated expressed genes (DEGs) were identified by machine learning methods (Penalize regression models). Then, the shared DEGs between the two training datasets were validated using validation datasets. ROC-curve analysis was used to identify diagnostic markers. R software analyzed the interactions between DEGs, clinical data, and fatty liver. Ten novel genes, including ABCF1, SART3, APC5, NONO, KAT7, ZPR1, RABGAP1, SLC7A8, SPAG9, and KAT6A were found to have a differential expression between NAFLD and healthy individuals. Based on validation results and ROC analysis, NR4A2 and IGFBP1b were identified as diagnostic markers. These key genes may be predictive markers for the development of fatty liver. It is recommended that these key genes are assessed further as possible predictive markers during the development of fatty liver

Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan–Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein–protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC