The effects of vitamin D supplementation on serum lipid profiles in people with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials

IntroductionPeople with type 2 diabetes (T2D) are highly susceptible to the development of cardiovascular diseases. Previous studies have suggested that the application of vitamin D may offer potential benefits in improving lipid profiles, but these effects remain controversial.MethodsThis systematic review and meta-analysis focused on the effects of vitamin D supplementation on serum lipid profiles in people with T2D. Randomized controlled trials (RCTs) assessing the effects of vitamin D supplementation on lipid profiles and published before September 19th, 2023, were identified in PubMed, Embase, and Cochrane Library. This review protocol was registered in the PROSPERO (CRD42023461136). The random-effects model was employed to estimate unstandardized mean differences (MD) and 95% confidence intervals (CIs). The quality of studies was assessed by the Cochrane Risk of Bias tool 2.ResultsOverall, 20 RCTs involving 1711 participants were included. Results indicated that vitamin D supplementation significantly improves serum high-density lipoprotein (HDL) (MD: 1.63 mg/dL, 95% CI: 0.19 to 3.08, P = 0.03), and triglyceride (TG) levels (MD: -8.56 mg/dL, 95% CI: -15.23 to -1.89, P = 0.01). However, vitamin D supplementation failed to improve low-density lipoprotein (LDL) levels and total cholesterol (TC) levels. Subgroup analyses and meta-regressions suggested that higher doses of vitamin D supplementation and shorter duration of intervention were more likely to have favorable effects on lipid profiles. Moreover, participants with lower baseline BMI and higher serum 25-hydroxy vitamin D levels exhibited greater improvements in lipid profiles following vitamin D supplementation.ConclusionsThis meta-analysis highlighted the effects of vitamin D supplementation on improving serum HDL and TG levels while not exhibiting significant improvements in LDL and TC levels. Further long-term and high-quality studies are still needed to draw more precise conclusions.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=461136

Measuring the X-ray luminosities of DESI groups from eROSITA Final Equatorial-Depth Survey: I. X-ray luminosity - halo mass scaling relation

We use the eROSITA Final Equatorial-Depth Survey (eFEDS) to measure the rest-frame 0.1-2.4 keV band X-ray luminosities of $\sim$ 600,000 DESI groups using two different algorithms in the overlap region of the two observations. These groups span a large redshift range of $0.0 \le z_g \le 1.0$ and group mass range of $10^{10.76}h^{-1}M_{\odot} \le M_h \le 10^{15.0}h^{-1}M_{\odot}$. (1) Using the blind detection pipeline of eFEDS, we find that 10932 X-ray emission peaks can be cross matched with our groups, $\sim 38 \%$ of which have signal-to-noise ratio $\rm{S}/\rm{N} \geq 3$ in X-ray detection. Comparing to the numbers reported in previous studies, this matched sample size is a factor of $\sim 6$ larger. (2) By stacking X-ray maps around groups with similar masses and redshifts, we measure the average X-ray luminosity of groups as a function of halo mass in five redshift bins. We find, in a wide halo mass range, the X-ray luminosity, $L_{\rm X}$, is roughly linearly proportional to $M_{h}$, and is quite independent to the redshift of the groups. (3) We use a Poisson distribution to model the X-ray luminosities obtained using two different algorithms and obtain best-fit $L_{\rm X}=10^{28.46\pm0.03}M_{h}^{1.024\pm0.002}$ and $L_{\rm X}=10^{26.73 \pm 0.04}M_{h}^{1.140 \pm 0.003}$ scaling relations, respectively. The best-fit slopes are flatter than the results previously obtained, but closer to a self-similar prediction.Comment: 15 pages, 13 figures, accepted for publication in MNRA

Model tests of the raw-water pipeline under the excessive stacking load

To investigate the effect of excessive stacking loadings on the deformation of raw-water pipelines, a model test was designed based on the analogous theory in this paper. The design of the model box, selection of pipeline material, and preparation of remolded soil were conducted, respectively. A theoretical formula was derived to convert the results of the model test into actual ones. Then, the field test data and three-dimensional numerical values were employed to verify the correctness of the model test results. Finally, the stresses of pipelines were discussed under different loading conditions, pipe diameters, buried depths, and compactness of underlying soils, and the guidelines for pipeline protection were proposed based on the results of the model tests. It can lay a solid theoretical and practical foundation for the protection of buried pipelines

Assessment of socio-techno-economic factors affecting the market adoption and evolution of 5G networks: Evidence from the 5G-PPP CHARISMA project

5G networks are rapidly becoming the means to accommodate the complex demands of vertical sectors. The European project CHARISMA is aiming to develop a hierarchical, distributed-intelligence 5G architecture, offering low latency, security, and open access as features intrinsic to its design. Finding its place in such a complex landscape consisting of heterogeneous technologies and devices, requires the designers of the CHARISMA and other similar 5G architectures, as well as other related market actors to take into account the multiple technical, economic and social aspects that will affect the deployment and the rate of adoption of 5G networks by the general public. In this paper, a roadmapping activity identifying the key technological and socio-economic issues is performed, so as to help ensure a smooth transition from the legacy to future 5G networks. Based on the fuzzy Analytical Hierarchy Process (AHP) method, a survey of pairwise comparisons has been conducted within the CHARISMA project by 5G technology and deployment experts, with several critical aspects identified and prioritized. The conclusions drawn are expected to be a valuable tool for decision and policy makers as well as for stakeholders

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe