Impact of probiotic administration on serum C-reactive protein concentrations: systematic review and meta-analysis of randomized control trials

We conducted this systematic review and meta-analysis of prospective studies to determine the effect of probiotic administration on serum C-reactive protein (CRP) concentrations. We searched PubMed-Medline, Web of Science, the Cochrane, and Google Scholar databases (until May 2016) to identify prospective studies evaluating the impact of probiotic administration on CRP. We used a random effects models and generic inverse variance methods to synthesize quantitative data, followed by a leave-one-out method for sensitivity analysis. The systematic review registration number was: CRD42016039457. From a total of 425 entries identified via searches, 20 studies were included in the final analysis. The meta-analysis indicated a significant reduction in serum CRP following probiotic administration with a weighted mean difference (WMD) of -1.35 mg/L, (95% confidence interval (CI) -2.15 to -0.55, I² 65.1%). The WMDs for interleukin 10 (IL10) was -1.65 pg/dL, (95% CI -3.45 to 0.14, I² 3.1%), and -0.45 pg/mL, (95% CI -1.38 to 0.48, I² 10.2%) for tumor necrosis factor alpha (TNF-α). These findings were robust in sensitivity analyses. This meta-analysis suggests that probiotic administration may significantly reduce serum CRP while having no significant effect on serum IL10 and TNF-α

Treatment with GLP1 receptor agonists reduce serum CRP concentrations in patients with type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials

Aim: To undertake a systematic review and meta-analysis of randomized controlled trials of the effect of Glucagon-like peptide-1 receptor agonist (GLP-1 RAs) therapy on serum C-reactive protein (CRP) concentrations. Method: PubMed-Medline, SCOPUS, Web of Science and Google Scholar databases were searched for the period up until March 16 2016. Prospective studies evaluating the impact of GLP-1 RAs on serum CRP were identified. A random effects model (using the DerSimonian-Laird method) and generic inverse variance methods were used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I2 index. Random effects meta-regression was performed using unrestricted maximum likelihood method to evaluate the impact of potential moderator. International Prospective Register for Systematic Reviews (PROSPERO) number CRD42016036868. Results: Meta-analysis of the data from 7 treatment arms revealed a significant reduction in serum CRP concentrations following treatment with GLP-1 RAs (WMD –2.14 (mg/dL), 95% CI -3.51, –0.78, P=0.002; I2 96.1%). Removal of one study in the meta-analysis did not change the result in the sensitivity analysis (WMD –2.14(mg/dL), 95% CI -3.51, –0.78, P=0.002; I2 96.1%), indicating that our results could not be solely attributed to the effect of a single study. Random effects meta-regression was performed to evaluate the impact of potential moderator on the estimated effect size. Changes in serum CRP concentration were associated with the duration of treatment (slope –0.097, 95% CI –0.158, -0.042, P<0.001). Conclusions: This meta-analysis suggests that GLP-1 RAs therapy causes a significant reduction in CRP

The effect of ginger supplementation on serum C-reactive protein, lipid profile and glycaemia: a systematic review and meta-analysis

Aim: To undertake a systematic review and meta-analysis of prospective studies to determine the effect of ginger supplementation on serum C-reactive protein (CRP), lipid profile, and glycaemia. Method: PubMed-MEDLINE, Web of Science, Cochrane Database, and Google Scholar databases were searched (up until July 2016) to identify prospective studies evaluating the impact of ginger supplementation on serum CRP. Random-effects model meta-analysis was used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I2 index. Systematic review registration: CRD42016035973. Results: From a total of 265 entries identified via searches, 9 studies were included in the final selection. The meta-analysis indicated a significant reduction in serum CRP concentrations following ginger supplementation [weighted mean difference (WMD)-0.84 mg/L (95% CI -1.38 to -0.31, I2 56.3%)]. The WMD for fasting blood glucose and HbA1c was -1.35 mg/dl (95% CI -2.04 to -0.58, I2 12.1%) and -1.01 (95% CI -1.28 to -0.72, I2 9.4%), respectively. Moreover, high-density lipoprotein and triglyceride significantly improved after ginger administration [1.16 mg/dl (95% CI 0.52 to 1.08, I2 12.3%) and -1.63 mg/dl (95% CI -3.10 to -0.17, I2 8.1%), respectively]. These findings were robust in sensitivity analyses. Random-effects meta-regression revealed that changes in serum CRP levels were independent of the dosage of ginger supplementation (slope -0.20; 95% CI -0.95 to 0.55; p=0.60). Conclusions: This meta-analysis suggests that ginger supplementation significantly reduces serum CRP and improves glycaemia indexes and lipid profile. Randomized control trials with larger sample size and with a longer-term follow-up period should be considered for future investigations

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

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill &amp; Melinda Gates Foundation

From Condition Monitoring to Maintenance Management in Electric Power System Generation with focus on Wind Turbines

With increase in the number of sensors installed on sub-assemblies of industrial components, the amount of data collected is rapidly increasing. These data hold information in the areas of operation of the system and evolution of health condition of the components. Therefore, extracting the knowledge from the data can bring about significant improvements in the aforementioned areas. This dissertation provides a path for achieving such an objective. It starts by analyzing the data at the sub-assembly level of the components and creates four frameworks for analysis of operation and maintenance (O&amp;M) for past, present and future horizons at the component level. These frameworks allow improvement in operation, maintenance planning, cost reduction, efficiency and performance of the industrial components. Next, the dissertation evaluates whether such models can be linked with system level analysis and how providing such a link could provide additional improvements for system operators. Finally, preventive maintenance (PM) in generation maintenance scheduling (GMS) in electric power systems is reviewed and updated with recent advancements such as connection to the electricity market and detailed implementation of health condition indicators into the maintenance models. In particular, maintenance scheduling through game theory in deregulated power system, for offshore wind farm (OWF) and an islanded microgrid (MG) are investigated. The results demonstrate improvements in reducing cost and increasing profit for the market agents and system operators as well as asset owners. Moreover, the models also deliver an insight on how direct integration of the collected operation data through the developed component level models can assist in improving the operation and management of maintenance for the system.QC 20180206</p

Reliability Analysis of A Radial Distributed Generation Distribution System

Distributed Generation (DG) plays an important role in current power systems with high demand growth. DG provides an alternative to the traditional electricity sources like oil, gas, coal, water, etc. and can also be used to enhance the current electrical system. DG distribution is likely to improve the reliability of a power distribution system by at least partially minimizing unplanned power interruptions to customers due to loss of utility generators or due to faults in transmission and distribution lines/equipments. In this paper, a typical distribution system is considered and to show the reliability enhancement of the system, different components (fuses, disconnects, DGs) are step by step taken into account and added to the system in five cases. Analytical methodology is used for the analysis. The results demonstrate that DG does improve the reliability of the distribution system

Impact of vitamin D supplementation on C-reactive protein; a systematic review and meta-analysis of randomized controlled trials

Abstract Background To evaluate the effect of vitamin D supplementation on C-reactive protein (CRP) through a systematic review and meta-analysis of randomized control trials (RCTs). Methods PubMed-Medline, SCOPUS, Google Scholar and Web of Science databases were searched (up until April 2016) to identify RCTs evaluating the impact of vitamin D supplementation on CRP. We used random effects models (using DerSimonian-Laird method) as well as the generic inverse variance methods for quantitative data synthesis. For sensitivity analysis, we applied leave-one-out approach. To examine the heterogeneity we used I2 index. Registration code: CRD42016036932. Results Among 1274 search items, 24 studies met the inclusion criteria in the final evaluation. Pooling the data together indicated a non-significant decrease in CRP level following administration of vitamin D (weighted mean difference [WMD] -0.26(mg/l), (95% CI -0.75 to 0.22, N = 26 arms, heterogeneity p = 0.042; I2 54.2%). The WMDs for IL6 was 0.67 pg/ml, (95% CI 0.29 to 1.06, N = 16 arms, heterogeneity p = 0.234; I2 19.1%), 0.43 pg/ml, (95% CI 0.08 to 1.05, N = 26 arms, heterogeneity p = 0.120; I2 42.1%), for IL10, and −0.11 pg/ml, (95% CI -0.53 to 0.30, N = 12 arms, heterogeneity p = 0.423; I2 9.2%) for TNF-α, 4.03 pg/ml, (95% CI 3.50 to 4.57, N = 3 arms, heterogeneity p = 0.752; I2 8.1%) for adiponectin. Sensitivity analyses confirmed the robustness of the findings. Conclusions This study provided evidence that vitamin D supplementation had no impact on serum CRP, IL10, and TNF-α, while significantly increased serum IL6. We recommend RCTs with longer period of follow-up time (12 months) for future studies to provide explicit results

Ghrelin, food intake, and botanical extracts: A Review

A kind of growth hormone secretagogue (GHS), ghrelin, was first isolated from the rat stomach and plays a major role in the activation of the growth hormone secretagogue receptor 1a (GHS-R1a) resulting the release of growth hormone (GH). The preproghrelin gene is placed on chromosome 3, at locus 3p25 –2 in humans and constitutes five exons and three introns. Ghrelin is most plentifully expressed in particular cells in the oxyntic glands of the gastric epithelium, initially named X/A-like cells. Almost 60-70% of circulating ghrelin is secreted by the stomach. Plasma ghrelin concentration alters throughout the day. Ghrelin has been suggested to act as a meal initiator because of its appetite-stimulating influences in free feeding rats in short period. In addition to ghrelin’s function as a meal motivator, it seems to contribute in long-term energy balance and nutritional status. In addition, many studies have been carried out in order to investigate the effects of natural and medicinal plants and botanical extracts on appetite, food intake, energy hemostasis, and the level of related hormones including ghrelin. Due to the importance of ghrelin in nutritional and medical sciences, this review was performed to understand new aspects of this hormone’s function

The effects of Ramadan fasting on growth parameters: A narrative review

Abstract Ramadan fasting is prescribed by Quran for every able‐bodied, adult Muslim and is considered an obligatory act of worship. During Ramadan, the majority of Muslims eat two major meals- one before dawn (Sahar) and another immediately after the sunset (Iftar). Islamic fasting, due to its particular nature, may cause metabolic and hormonal changes in the body, which are different from those in regular fasting. To the best of our knowledge, no comprehensive study has been conducted on changes in growth parameters during fasting periods. Therefore, the aim of this review, which is based on scientific literature review, was to describe the effects of fasting on growth parameters in humans