Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

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

Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings: Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing

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

Mechanisms involved in death and survival of lymphocytes exposed to palmitic acid.

Ácidos graxos podem atuar na apoptose ativando e/ou desativando sinais que regulam este processo. Células Jurkat (linhagem de linfócitos-T) foram tratadas com ácido palmítico (PA) (50, 100 e 150µM) e avaliada a ativação de vias de morte e de sobrevivência. O tratamento com PA induziu apoptose pela ativação da via intrínseca de maneira dose-dependente. A exposição destas células ao PA elevou a expressão do receptor de insulina e de GLUT-4, obtendo-se correlação positiva com a apoptose. O mesmo foi observado em linfócitos humanos expostos ao PA e de linfócitos de ratos em jejum. O tratamento das células Jurkat com insulina após exposição ao PA promoveu a ativação da via de sinalização insulínica. O PA aumentou a captação de glicose, mas observou-se diminuição de sua oxidação e o acúmulo de lípides. Assim, a via de sinalização da insulina e o metabolismo de glicose não oxidativo são estimulados como parte de uma coordenada resposta de sobrevivência de linfócitos expostos ao PA em baixas concentrações, mas em altas concentrações ocorre apoptose.Fatty acids affect apoptosis pathway activating or deactivating signals that regulate this process. Jurkat cells (T-lymphocyte lineage) were treated with sub-lethal concentrations of palmitic acid (PA) (50, 100 e 150µM) and the cell death and survival signaling pathways were investigated. PA induced apoptosis in a dose dependent manner activating the intrinsic pathway. Jurkat cells exposed to PA showed increased insulin receptor and GLUT-4 expression and a positive correlation with apoptosis was obtained. Similar effect was observed in human lymphocytes exposed to PA and lymphocytes from fasted rats. Insulin treatment of Jurkat cells after PA exposure promoted the activation of the insulin signaling pathway. Glucose uptake was increased in the presence of PA, however, its oxidation was diminished and ncreased of lipids accumulation. Therefore, insulin signaling and non oxidative glucose metabolism are stimulated as a part of a coordinated response to survival of lymphocytes exposed to low concentration of PA but in high concentration it induces apoptosis

Mechanisms involved in death and survival of lymphocytes exposed to palmitic acid.

Ácidos graxos podem atuar na apoptose ativando e/ou desativando sinais que regulam este processo. Células Jurkat (linhagem de linfócitos-T) foram tratadas com ácido palmítico (PA) (50, 100 e 150µM) e avaliada a ativação de vias de morte e de sobrevivência. O tratamento com PA induziu apoptose pela ativação da via intrínseca de maneira dose-dependente. A exposição destas células ao PA elevou a expressão do receptor de insulina e de GLUT-4, obtendo-se correlação positiva com a apoptose. O mesmo foi observado em linfócitos humanos expostos ao PA e de linfócitos de ratos em jejum. O tratamento das células Jurkat com insulina após exposição ao PA promoveu a ativação da via de sinalização insulínica. O PA aumentou a captação de glicose, mas observou-se diminuição de sua oxidação e o acúmulo de lípides. Assim, a via de sinalização da insulina e o metabolismo de glicose não oxidativo são estimulados como parte de uma coordenada resposta de sobrevivência de linfócitos expostos ao PA em baixas concentrações, mas em altas concentrações ocorre apoptose.Fatty acids affect apoptosis pathway activating or deactivating signals that regulate this process. Jurkat cells (T-lymphocyte lineage) were treated with sub-lethal concentrations of palmitic acid (PA) (50, 100 e 150µM) and the cell death and survival signaling pathways were investigated. PA induced apoptosis in a dose dependent manner activating the intrinsic pathway. Jurkat cells exposed to PA showed increased insulin receptor and GLUT-4 expression and a positive correlation with apoptosis was obtained. Similar effect was observed in human lymphocytes exposed to PA and lymphocytes from fasted rats. Insulin treatment of Jurkat cells after PA exposure promoted the activation of the insulin signaling pathway. Glucose uptake was increased in the presence of PA, however, its oxidation was diminished and ncreased of lipids accumulation. Therefore, insulin signaling and non oxidative glucose metabolism are stimulated as a part of a coordinated response to survival of lymphocytes exposed to low concentration of PA but in high concentration it induces apoptosis

Soybean and sunflower oil‐induced insulin resistance correlates with impaired GLUT4 protein expression and translocation specifically in white adipose tissue

Free fatty acids are known for playing a crucial role in the development of insulin resistance. High fat intake is known for impairing insulin sensitivity; however, the effect of vegetable‐oil injections have never been investigated. The present study investigated the effects of daily subcutaneous injections (100 µL) of soybean (SB) and sunflower (SF) oils, during 7 days. Both treated groups developed insulin resistance as assessed by insulin tolerance test. The mechanism underlying the SB‐ and SF‐induced insulin resistance was shown to involve GLUT4. In SB‐ and SF‐treated animals, the GLUT4 protein expression was reduced ∼20% and 10 min after an acute in vivo stimulus with insulin, the plasma membrane GLUT4 content was ∼60% lower in white adipose tissue (WAT). No effects were observed in skeletal muscle. Additionally, both oil treatments increased mainly the content of palmitic acid (∼150%) in WAT, which can contribute to explain the GLUT4 regulations. Altogether, the present study collects evidence that those oil treatments might generate insulin resistance by targeting GLUT4 expression and translocation specifically in WAT. These alterations are likely to be caused due to the specific local increase in saturated fatty acids that occurred as a consequence of oil daily injections282114121FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP03/08548-3; 07/50554-

Soybean and sunflower oil-induced insulin resistance correlates with impaired GLUT4 protein expression and translocation specifically in white adipose tissue

Free fatty acids are known for playing a crucial role in the development of insulin resistance. High fat intake is known for impairing insulin sensitivity; however, the effect of vegetable-oil injections have never been investigated. The present study investigated the effects of daily subcutaneous injections (100 mu L) of soybean (SB) and sunflower (SF) oils, during 7 days. Both treated groups developed insulin resistance as assessed by insulin tolerance test. The mechanism underlying the SB- and SF-induced insulin resistance was shown to involve GLUT4. In SB- and SF-treated animals, the GLUT4 protein expression was reduced similar to 20% and 10 min after an acute it? vivo stimulus with insulin, the plasma membrane GLUT4 content was similar to 60% lower in white adipose tissue (WAT). No effects were observed in skeletal muscle. Additionally, both oil treatments increased mainly the content of palmitic acid (similar to 150%) in WAT, which can contribute to explain the GLUT4 regulations. Altogether, the present study collects evidence that those oil treatments might generate insulin resistance by targeting GLUT4 expression and translocation specifically in WAT. These alterations are likely to be caused due to the specific local increase in saturated fatty acids that occurred as a consequence of oil daily injections. Copyright (C) 2010 John Wiley & Sons, Ltd.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP[03/08548-3]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP[07/50554-1

Lonomia obliqua (Lepidoptera, Saturniidae) caterpillar bristle extract induces direct lysis by cleaving erythrocyte membrane glycoproteins

Lonomia obliqua caterpillar bristle extract induces hemolysis in vitro on washed human and rat erythrocytes, in either the absence or presence of exogenous lecithin. In the former condition, phospholipases A(2) are key enzymes involved in hemolysis. However, the mechanism whereby this extract causes direct hemolysis is not known. Thus, the aim of this study was to investigate the hemolytic mechanism of the crude extract of the caterpillar L obliqua on human erythrocytes in the absence of lecithin. The extract significantly increased the erythrocyte osmotic fragility and promoted the removal of glycophorins A and C, and band 3 from the erythrocyte membrane. The use of Ca(2+) and Mg(2+) ions significantly potentiated glycoprotein removal, remarkably of erythrocyte band 3. The composition of fatty acids was analyzed by HPLC in both L obliqua caterpillar bristle extract and human erythrocyte membranes incubated with the extract. The levels of unsaturated fatty acids were remarkably augmented in erythrocytes incubated with the extract than in control erythrocytes, modifying thereby the saturated/unsaturated fatty acid ratio. Altogether, evidence is provided here that the interplay of at least three mechanisms of action accounts for the direct activity of the bristle extract on erythrocyte membrane, leading to hemolysis: the removal of glycoproteins and band 3; the insertion of fatty acids; and the action of phospholipases. Such mechanisms might affect erythrocyte flexibility and deformability, which may induce hemolysis by increasing erythrocyte fragility. However, whether the direct hemolytic activity of L obliqua caterpillar is the major cause of intravascular hemolysis during envenomation still needs further investigation. (C) 2010 Elsevier Ltd. All rights reserved.FAPESP[00/11432-9]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP[01/07643-7]FAPESP[08/02996-8]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)CNPq[303711/2007-8]Fundacao Butantan and Secretaria de Ciencia e Tecnologia do Estado do Tocantins (SECT-TO)Fundação ButantanSecretaria de Ciencia e Tecnologia do Estado do Tocantins (SECT-TO