8 research outputs found
Efficacy of autologous platelet rich plasma for ovarian rejuvenation in infertile women having poor ovarian reserve
Background: Poor ovarian reserve (POR) is a condition in which the ovary loses its normal reproductive potential and compromising fertility. Normal function of the ovaries and adequate good quality follicles are responsible for the reproductive process of a woman. Various treatment methods exist for POR, but the present study was conducted to observe the effectiveness of platelet rich plasma infusion through measurement of AMH and AFC values and pregnancy outcomes.Methods: This prospective observational study was done in the department of reproductive endocrinology and infertility from July 2019 to June 2022. A total of 60 patients with poor ovarian reserve were recruited maintaining inclusion and exclusion criteria.Results: Mean age of the participants was 36.4 years, with 78.32% of the participants being housewives and 21.68% being service workers. 65.38% had education below SSC levels. 72.46% had primary infertility while 27.54% had secondary infertility. At first cycle, compared to baseline counts, mean±SD AMH had increased by 0.04±0.15 ng/dl, and mean±SD AFC had increased by 1.34±1.89 in number. During second cycle post-PRP, the mean difference of AMH and AFC was 0.18±0.21 ng/dl and 2.17±1.71 in a positive manner. By final follow-up, pregnancy rate was 20% among patients.Conclusions: The study observed significant improvement in AMH and AFC values following PRP infusion. The improvement of both values was gradual, and increase of AMH values were observed up to second post-PRP menstrual cycle, while AFC increased till third cycle post-PRP. Among 60 patient twelve (12) had pregnancy (20%)
Intrauterine instillation of granulocyte colony stimulating factor for infertile women with thin endometrium in intrauterine insemination cycle: a non-randomized clinical trial
Background: Endometrial thickness is one of the major factors for a receptive endometrium and successful implantation. Thin endometrium, generally measuring <7 mm are thought to be less able to support implantation and pregnancy. Several adjuvants have been investigated for their efficacy on thin endometrium in assisted reproductive technology. Granulocyte colony stimulating factor (G-CSF) is a glycoprotein that promotes endometrial stromal cell decidualization via cyclic adenosine monophosphate mediator and induces endometrial proliferation and differentiation. This study was done to evaluate the effect of G-CSF in improving endometrial thickness and pregnancy rate in infertile patients undergoing stimulated IUI (intrauterine instillation) having thin endometrium.Methods: This was a non-randomized clinical trial done among 40 infertile patients with thin endometrium (<7 mm) on the day of ovulation trigger in stimulated IUI patients. Study subjects were non randomly allocated into 2 groups. In group A 20 patients received intrauterine instillation of G-CSF (300 mcg/0.5 ml) via intrauterine catheter on triggering day and in group B another 20 patients received intrauterine instillation of 0.5 ml normal saline in the same procedure. After 48 hours endometrial thickness was measured in both groups. IUI was done on the same day. Pregnancy was detected by serum beta hCG level after 14 days of IUI.Results: In both groups most of the respondents were aged between 30-34 years, 14 (70%) in group A and 11 (55%) in group B. The mean±SD of age 32.4±3.1 in group A, 32.2±3.4 in group B and P value was 0.9. In group A the minimum endometrial thickness on day of ovulation trigger was 4.4 mm and after 48 hours of treatment with G-CSF, it was found 6.3 mm. The maximum endometrial thickness recorded in group A was 6.9 mm and it also increased to 8.7 mm after G-CSF treatment and followed by in group B min thickness 4.8 mm increase to 5.2 mm and max thickness 6.8 mm increased to 8.7 mm. The mean±SD of ET (mm) on the day of ovarian trigger was 5.8±0.8 which increased to 7.4±0.8 in group A and followed by 5.9±0.6 to 7.1±0.9 in group B. ET mean change (mean±SD) for group A was 1.6±0.7 which was greater than the group B 1.3±0.8. Pregnancy rate was 2 (10%) in group A and 1(5%) in group B.Conclusions: Mean increase in endometrial thickness and pregnancy rate was higher in G-CSF group than normal saline group, but the difference was not statistically significant
Effects of autologous stem cell therapy for fertility enhancement among women with premature ovarian insufficiency
Background: Premature ovarian insufficiency (POI) is a condition where the ovary loses its normal reproductive potential earlier than 40 years, compromising fertility. There is no treatment for POI, only ovum or embryo donation. Autologous stem cell ovarian transplant (ASCOT) may be a procedure that creates new eggs in the ovaries of women with POI. The aim of the study was to find out the efficacy of ASCOT in patients suffering from POI.
Methods: A total of 50 patients were included according to inclusion and exclusion criteria in this prospective observational study. POI was confirmed with low levels of anti-mullerian hormone (AMH) (<0.5 ng/dl), high level of follicle stimulating hormone (FSH) >25 ng/ml, and or a low number of antral follicle count (AFC) (<3 in each ovary).
Results: Results showed that after stem cell therapy, mean AMH values increased by 0.48±0.306 and mean FSH values increased by 2.73±3.98 but the difference was not statistically significant. AFC values significantly decreased by 1.33±0.625 at 1st post-stem-cell cycle. During the second cycle, AMH and AFC increased by 0.110±0.051 and 4.63±1.49, respectively, and FSH decreased by 7.4±2.78. In third cycle, AMH & FSH was significantly increased by 0.820±0.44 & 4.120±0.470 and FSH has been decreased by 2.150±3.625. The increase in AMH & AFC was statistically significant, and the decrease in FSH was not statistically significant compared to baseline values.
Conclusions: The study showed that autologous stem cell therapy can have a significant effect on women’s ovarian function and fertility. It showed that ASCOT can increase AMH and AFC, and decrease FSH in patients with POI, with a total pregnancy rate of 4% after the third cycle follow-up
Functional and structural analysis of predicted proteins obtained from homo sapiens' minisatellite 33.15-tagged transcript pAKT-45 variants
The spermatozoa are transcriptionally dormant entities which have been recognized to be an archive of mRNA, coding for a variety of functionally crucial cellular proteins. This significant repository of mRNA is predicted to be associated with early embryogenesis and postfertilization. The mRNA transcripts which are tagged with minisatellites have been involved in the regulation of the gene functions as well as their organization. However, very little information is available regarding the expression of the transcripts tagged with minisatellites in spermatozoa. Therefore, in order to understand the functions and the conformational behavior of the proteins expressed from these minisatellite-tagged transcripts, we have performed a detailed in silico analysis using the sequences of the transcripts. The protein predicted from KF274549 showed the functionalities similar to uncharacterized C4orf26 proteins, while that obtained from KF274557 predicted to be a metallophosphoesterase. Furthermore, the structural folds in the structure of these predicted proteins were analyzed by using the homology modeling and their conformational behaviors in the explicit water conditions were analyzed by using the techniques of Molecular Dynamics (MD) simulations. This detailed analysis will facilitate the understanding of these proteins in the spermatozoon region and can be used for uncovering other attributes of the metabolic network
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Green cardamom increases Sirtuin-1 and reduces inflammation in overweight or obese patients with non-alcoholic fatty liver disease: a double-blind randomized placebo-controlled clinical trial
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Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019
Summary
Background
Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes.
Methods
We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest.
Findings
From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths.
Interpretation
The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere