14 research outputs found
Calcified Algae for Tissue Engineering.
This book presents the latest advances in marine structures and related biomaterials for applications in both soft- and hard-tissue engineering, as well as controlled drug delivery
Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013
Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0-65·6) in 1990, to 71·5 years (UI 71·0-71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8-48·2) to 54·9 million (UI 53·6-56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade. Funding Bill & Melinda Gates Foundation
Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015
Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe
Soy lecithin supplementation alters macrophage phagocytosis and lymphocyte response to concanavalin A: a study in alloxan-induced diabetic rats
Dietary soy lecithin supplementation decreases hyperlipidemia and influences lipid metabolism. Although this product is used by diabetic patients, there are no data about the effect of soy lecithin supplementation on the immune system. The addition of phosphatidylcholine, the main component of lecithin, to a culture of lymphocytes has been reported to alter their function. If phosphatidylcholine changes lymphocyte functions in vitro as previously shown, then it could also affect immune cells in vivo. In the present study, the effect of dietary soy lecithin oil macrophage phagocytic capacity and on lymphocyte number in response to concanavalin A (ConA) stimulation was investigated in non-diabetic and alloxan-induced diabetic rats. Supplementation was carried Out daily with 2 g kg(-1) b.w. lecithin during 7 days. After that, blood was drawn from fasting rats and peritoneal macrophages and mesenteric lymph node lymphocytes were collected to determine the phospholipid content. Plasma triacylglycerol (TAG), total and HDL cholesterol and glucose levels were also determined. Lymphocytes were stimulated by Conk The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) dye reduction method and flow cytometry were employed to evaluate lymphocyte metabolism and cell number, respectively. Soy lecithin supplementation significantly increased both macrophage phagocytic capacity (+29%) in non-diabetic rats and the lymphocyte number in diabetic rats (+92%). It is unlikely that plasma lipid levels indirectly affect immune cells, since plasma cholesterol, TAG, or phospholipid content was not modified by lecithin supplementation. In Conclusion, lymphocyte and macrophage function were altered by lecithin supplementation, indicating ail immunomodulatory effect of phosphatidylcholine. Copyright (C) 2008 John Wiley & Sons, Ltd.CNPQ[473412/2003-9]Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação HerbariumFundação AraucáriaFundacao Araucaria and Fundacao Herbariu
Perfil escolar e as habilidades cognitivas e de linguagem de crianças e adolescentes do espectro do autismo
Genetic and biochemical biomarkers related to oxidative stress in patients with schizophrenia
We evaluated the association of glutathione S-transferase polymorphisms (GSTT1 and GSTM1) and oxidative stress biomarkers in patients with schizophrenia. A total of 162 subjects were studied: 53 had schizophrenia (Total Study Group-TSG), and 109 without the disorder (Total Control Group-TCG). To analyze oxidative stress, TSG was distributed into treatment-responsive schizophrenia (N = 26) and treatment-resistant (N = 27) versus control group (N = 36). Peripheral blood collection for analysis of polymorphisms, malondialdehyde (MDA) and trolox equivalent antioxidant capacity (TEAC); a questionnaire or a medical record for clinical profile and lifestyle was also applied. Frequency of genotypes did not differ significantly between the groups. The patients had a significantly reduced frequency of the combination GSTT1-null/GSTM1-present (13 versus 30%) and significantly higher plasma MDA levels, but similar TEAC values. Smoking, diabetes mellitus (DM), systemic arterial hypertension (SAH) and family history (FH) significantly prevailed in patients (TSG) compared to controls (TCG). High sensitivity and specificity values for MDA (area under the curve >0.90) were observed. Reduced frequency of the combination GSTT1-null/GSTM1-present in patients suggests exposure to oxidative stress, represented by increased MDA and mainly aggravated by smoking, SAH, DM and FH. High sensitivity and specificity identifies the potential of MDA as a marker of oxidative stress in schizophrenia182CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQsem informaçãoWe thank the CNPq (National Council for Scientific and Technological Development) for financial support as well as FAMERP (Medical School of São José do Rio Preto, SP), NPBIM (Research Center in Biochemistry and Molecular Biology - FAMERP) and LQBOA (Bio-Organic and Environmental Chemistry LaboratoryIBILCE/UNESP) for supporting the researc
Phenotypic characteristics of commonly used inbred mouse strains
202103 bcvcAccepted ManuscriptRGC1-ZVN0Publishe
Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015
Background
In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).
Methods
We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.
Findings
In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8–61·8) and varied widely by country, ranging from 85·5 (84·2–86·5) in Iceland to 20·4 (15·4–24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r2=0·88) and the MDG index (r2=0·92), whereas the non-MDG index had a weaker relation with SDI (r2=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0–10·4), and gains on the MDG index (a median change of 10·0 [6·7–13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1–8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened.
Interpretation
GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs