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The potential of μ + μ − colliders to investigate the fourth standard model family fermions predicted by flavor democracy is analyzed. It is shown that muon colliders are advantageous for both pair production of fourth family fermions and resonance production of fourth family quarkonia. Also, isosinglet quark production at μ + μ − colliders is investigated. ; Scopus ; Wos

Nanotechnology products such as titanium dioxide nanoparticles (TiO2-NPs) can be used for viral infections because of their unique characteristics. The current study aimed to determine the impact of TiO2-NPs on HPV type 1 and 2 infections. The characterization of these NPs was performed using dynamic light scattering (DLS), field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD). The MTT assay was used to determine the toxic impacts of TiO2-NPs on BHK-21 cells. The efficiency of TiO2-NPs was performed using several parameters, including TCID50 and RT-PCR assays. An indirect immunofluorescence assay (IFA) was performed to estimate the inhibitory impact of TiO2-NPs on viral antigen expression, and Acyclovir was used as a reference medicine. When the human papilloma type 1 and 2 viruses exposed to TiO2-NPs at high doses (100 μg/mL) produced 0.3, 1.1, 2.3, and 3.3 log10 TCID50 decreases in infective virus load when compared with control viruses (P<0.0001), these TiO2-NPs doses were related to 24.9%, 35.1%, 47.2%, 59.5%, and 66.6% inhibition percentages that were determined depending on the viral titer as compared to virus control. It is concluded that TiO2-NPs have strong potential for the treatment of face and labial lesions caused by papillomaviruses 1 and 2 and could be used in topical formulations.

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity "broadspectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested, many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to be relatively inexpensive, it should help us address stages and types of cancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for future research is offered. (C) 2015 The Authors. Published by Elsevier Ltd. ; Funding Agencies|Terry Fox Foundation Grant [TF-13-20]; UAEU Program for Advanced Research (UPAR) [31S118]; NIH [AR47901, R21CA188818, R15 CA137499-01, F32CA177139, P20RR016477, P20GM103434, R01CA170378, U54CA149145, U54CA143907, R01-HL107652, R01CA166348, R01GM071725, R01 CA109335-04A1, 109511R01CA151304CA168997 A11106131R03CA1711326 1P01AT003961RO1 CA100816P01AG034906 R01AG020642P01AG034906-01A1R01HL108006]; NIH NRSA Grant [F31CA154080]; NIH (NIAID) R01: Combination therapies for chronic HBV, liver disease, and cancer [AI076535]; Sky Foundation Inc. Michigan; University of Glasgow; Beatson Oncology Centre Fund; Spanish Ministry of Economy and Competitivity, ISCIII [PI12/00137, RTICC: RD12/0036/0028]; FEDER from Regional Development European Funds (European Union), Consejeria de Ciencia e Innovacion [CTS-6844, CTS-1848]; Consejeria de Salud of the Junta de Andalucia [PI-0135-2010, PI-0306-2012]; ISCIII [PIE13/0004]; FEDER funds; United Soybean Board; NIH NCCAM Grant [K01AT007324]; NIH NCI Grant [R33 CA161873-02]; Michael Cuccione Childhood Cancer Foundation Graduate Studentship; Ovarian and Prostate Cancer Research Trust, UK; West Virginia Higher Education Policy Commission/Division of Science Research; National Institutes of Health; Italian Association for Cancer Research (AIRC) [IG10636, 15403]; GRACE Charity, UK; Breast Cancer Campaign, UK; Michael Cuccione Childhood Cancer Foundation Postdoctoral Fellowship; Connecticut State University; Swedish Research Council; Swedish Research Society; University of Texas Health Science Centre at Tyler, Elsa U. Pardee Foundation; CPRIT; Cancer Prevention and Research Institute of Texas; NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK); NIH National Institute on Alcohol Abuse and Alcoholism (NIAAA); Gilead and Shire Pharmaceuticals; NIH/NCI [1R01CA20009, 5R01CAl27258-05, R21CA184788, NIH P30 CA22453, NCI RO1 28704]; Scottish Governments Rural and Environment Science and Analytical Services Division; National Research Foundation; United Arab Emirates University; Terry Fox Foundation; Novartis Pharmaceutical; Aveo Pharmaceutical; Roche; Bristol Myers Squibb; Bayer Pharmaceutical; Pfizer; Kyowa Kirin; NIH/NIAID Grant [A1076535]; Auckland Cancer Society; Cancer Society of New Zealand; NIH Public Service Grant from the National Cancer Institute [CA164095]; Medical Research Council CCU-Program Grant on cancer metabolism; EU Marie Curie Reintegration Grant [MC-CIG-303514]; Greek National funds through the Operational Program Educational and Lifelong Learning of the National Strategic Reference Framework (NSRF)-Research Funding Program THALES [MIS 379346]; COST Action CM1201 `Biomimetic Radical Chemistry; Duke University Molecular Cancer Biology T32 Training Grant; National Sciences Engineering and Research Council Undergraduate Student Research Award in Canada; Charles University in Prague projects [UNCE 204015, PRVOUK P31/2012]; Czech Science Foundation projects [15-03834Y, P301/12/1686]; Czech Health Research Council AZV project [15-32432A]; Internal Grant Agency of the Ministry of Health of the Czech Republic project [NT13663-3/2012]; National Institute of Aging [P30AG028716-01]; NIH/NCI training grants to Duke University [T32-CA059365-19, 5T32-CA059365]; Ministry of Education, Culture, Sports, Science and Technology, Japan [24590493]; Ministry of Health and Welfare [CCMP101-RD-031, CCMP102-RD-112]; Tzu-Chi University of Taiwan [61040055-10]; Svenska Sallskapet for Medicinsk Forskning; Cancer Research Wales; Albert Hung Foundation; Fong Family Foundation; Welsh Government A4B scheme; NIH NCI; University of Glasgow, Beatson Oncology Centre Fund, CRUK [C301/A14762]; NIH Intramural Research Program; National Science Foundation; American Cancer Society; National Cancer Center [NCC-1310430-2]; National Research Foundation [NRF-2005-0093837]; Sol Goldman Pancreatic Cancer Research Fund Grant [80028595]; Lustgarten Fund Grant [90049125, NIHR21CA169757]; Alma Toorock Memorial for Cancer Research; National Research Foundation of Korea (NRF); Ministry of Science, ICT & Future Planning (MSIP), Republic of Korea [2011-0017639, 2011-0030001]; Ministry of Education of Taiwan [TMUTOP103005-4]; International Life Sciences Institute; United States Public Health Services Grants [NIH R01CA156776]; VA-BLR&D Merit Review Grant [5101-BX001517-02]; V Foundation; Pancreatic Cancer Action Network; Damon Runyon Cancer Research Foundation; Childrens Cancer Institute Australia; University Roma Tre; Italian Association for Cancer Research (AIRC-Grant) [IG15221]; Carlos III Health Institute; Feder funds [AM: CP10/00539, PI13/02277]; Basque Foundation for Science (IKERBASQUE); Marie Curie CIG Grant [2012/712404]; Canadian Institutes of Health Research; Avon Foundation for Women [OBC-134038]; Canadian Institutes of Health [MSH-136647, MOP 64308]; Bayer Healthcare System G4T (Grants4Targets); NIH NIDDK; NIH NIAAA; Shire Pharmaceuticals; Harvard-MIT Health Sciences and Technology Research Assistantship Award; Italian Ministry of University; University of Italy; Auckland Cancer Society Research Centre (ACSRC); German Federal Ministry of Education and Research (Bundesministerium fur Bildung und Forschung, BMBF) [16SV5536K]; European Commission [FP7 259679 "IDEAL"]; Cinque per Mille dellIRPEF-Finanziamento della Ricerca Sanitaria; European Union Seventh Framework Programme (FP7) [278570]; AIRC [10216, 13837]; European Communitys Seventh Framework Program FP7 [311876]; Canadian Institute for Health Research [MOP114962, MOP125857]; Fonds de Recherche Quebec Sante [22624]; Terry Fox Research Institute [1030]; FEDER; MICINN [SAF2012-32810]; Junta de Castilla y Leon [BIO/SA06/13]; ARIMMORA project [FP7-ENV-2011]; European Union; NIH NIDDK [K01DK077137, R03DK089130]; NIH NCI grants [R01CA131294, R21 CA155686]; Avon Foundation; Breast Cancer Research Foundation Grant [90047965]; National Institute of Health, NINDS Grant [K08NS083732]; AACR-National Brain Tumor Society Career Development Award for Translational Brain Tumor Research [13-20-23-SIEG]; Department of Science and Technology, New Delhi, India [SR/FT/LS-063/2008]; Yorkshire Cancer Research; Wellcome Trust, UK; Italian Ministry of Economy and Finance Project CAMPUS-QUARC, within program FESR Campania Region; National Cancer Institute [5P01CA073992]; IDEA Award from the Department of Defense [W81XWH-12-1-0515]; Huntsman Cancer Foundation; University of Miami Clinical and Translational Science Institute (CTSI) Pilot Research Grant [CTSI-2013-P03]; SEEDS You Choose Awards; DoD [W81XVVH-11-1-0272, W81XWH-13-1-0182]; Kimmel Translational Science Award [SKF-13-021]; ACS Scholar award [122688-RSG-12-196-01-TBG]; National Cancer Institute, Pancreatic Cancer Action Network, Pew Charitable Trusts; American Diabetes Association; Elsa U. Pardee Foundation; Scientific Research Foundation for the Returned Oversea Scholars, State Education Ministry and Scientific and Technological Innovation Project, Harbin [2012RFLX5011]; United States National Institutes of Health [ES019458]; California Breast Cancer Research Program [17UB-8708]; National Institutes of Health through the RCMI-Center for Environmental Health [G1200MD007581]; NIH/National Heart, Lung, and Blood Institute Training Grant [T32HL098062]; European FP7-TuMIC [HEALTH-F2-2008-201662]; Italian Association for Cancer research (AIRC) Grant IG [11963]; Regione Campania L.R:N.5; European National Funds [PON01-02388/1 2007-2013]

Background: An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods: We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings: Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3·0%. The largest health spending growth rates were in upper-middle-income (5·9) and lower-middle-income groups (5·0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4·6%, and health spending increased from $51 to $120 per capita. In 2014, 59·2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29·1% and 58·0% of spending was OOP spending and 35·7% and 3·0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1·8%, and reached US$37·6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation: Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.

Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Funding Bill & Melinda Gates Foundation. ; We would like to thank the countless individuals who have contributed to the Global Burden of Disease Study 2015 in various capacities. The data reported here have been supplied by the US Renal Data System (USRDS). Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Collection of these data was made possible by the US Agency for International Development (USAID) under the terms of cooperative agreement GPO-A-00-08-000_D3-00. Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. Parts of this material are based on data and information provided by the Canadian institute for Health Information. However, the analyses, conclusions, opinions and statements expressed herein are those of the author and not those of the Canadian Institute for Health information. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with license no SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law, 2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. This paper uses data from SHARE Waves 1, 2, 3 (SHARELIFE), 4 and 5 (DOIs: 10.6103/SHARE.w1.500, 10.6103/SHARE.w2.500, 10.6103/SHARE.w3.500, 10.6103/SHARE.w4.500, 10.6103/SHARE.w5.500), see Börsch-Supan and colleagues, 2013, for methodological details. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: number 211909, SHARE-LEAP: number 227822, SHARE M4: number 261982). Additional funding from the German Ministry of Education and Research, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, and OGHA_04-064) and from various national funding sources is gratefully acknowledged. This study has been realised using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation. The following individuals would like to acknowledge various forms of institutional support: Simon I Hay is funded by a Senior Research Fellowship from the Wellcome Trust (#095066), and grants from the Bill & Melinda Gates Foundation (OPP1119467, OPP1093011, OPP1106023 and OPP1132415). Amanda G Thrift is supported by a fellowship from the National Health and Medical Research Council (GNT1042600). Panniyammakal Jeemon is supported by the Wellcome Trust-DBT India Alliance, Clinical and Public Health, Intermediate Fellowship (2015–2020). Boris Bikbov, Norberto Percio, and Giuseppe Remuzzi acknowledge that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). Amador Goodridge acknowledges funding from Sistema Nacional de Investigadores de Panamá-SNI. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). Lijing L Yan is supported by the National Natural Sciences Foundation of China grants (71233001 and 71490732). Olanrewaju Oladimeji is an African Research Fellow at Human Sciences Research Council (HSRC) and Doctoral Candidate at the University of KwaZulu-Natal (UKZN), South Africa, and would like to acknowledge the institutional support by leveraging on the existing organisational research infrastructure at HSRC and UKZN. Nicholas Steel received funding from Public Health England as a Visiting Scholar in the Institute for Health Metrics and Evaluation in 2016. No individuals acknowledged received additional compensation for their efforts. ; Peer-reviewed ; Publisher Version

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. Funding Bill & Melinda Gates Foundation. ; We thank the countless individuals who have contributed to the Global Burden of Disease Study 2015 in various capacities. The data reported here have been supplied by the United States Renal Data System (USRDS). Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Collection of these data was made possible by USAID under the terms of cooperative agreement GPO-A-00-08-000_D3-00. Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. Parts of this material are based on data and information provided by the Canadian institute for Health Information. However, the analyses, conclusions, opinions and statements expressed herein are those of the author and not those of the Canadian Institute for Health information. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence number SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law–2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. The following individuals acknowledge various forms of institutional support. Simon I Hay is funded by a Senior Research Fellowship from the Wellcome Trust (#095066), and grants from the Bill & Melinda Gates Foundation (OPP1119467, OPP1093011, OPP1106023 and OPP1132415). Panniyammakal Jeemon is supported by a Clinical and Public Health Intermediate Fellowship from the Wellcome Trust-DBT India Alliance (2015–20). Luciano A Sposato is partly supported by the Edward and Alma Saraydar Neurosciences Fund, London Health Sciences Foundation, London, ON, Canada. George A Mensah notes that the views expressed in this Article are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute, National Institutes of Health, or the United States Department of Health and Human Services. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). Ana Maria Nogales Vasconcelos acknowledges that her team in Brazil received funding from Ministry of Health (process number 25000192049/2014-14). Rodrigo Sarmiento-Suarez receives institutional support from Universidad de Ciencias Aplicadas y Ambientales, UDCA, Bogotá, Colombia. Ulrich O Mueller and Andrea Werdecker gratefully acknowledge funding by the German National Cohort BMBF (grant number OIER 1301/22). Peter James was supported by the National Cancer Institute of the National Institutes of Health (Award K99CA201542). Brett M Kissela would like to acknowledge NIH/NINDS R-01 30678. Louisa Degenhardt is supported by an Australian National Health and Medical Research Council Principal Research fellowship. Daisy M X Abreu received institutional support from the Brazilian Ministry of Health (Proc number 25000192049/2014-14). Jennifer H MacLachlan receives funding support from the Australian Government Department of Health and Royal Melbourne Hospital Research Funding Program. Miriam Levi acknowledges institutional support received from CeRIMP, Regional Centre for Occupational Diseases and Injuries, Tuscany Region, Florence, Italy. Tea Lallukka reports funding from The Academy of Finland (grant 287488). No individuals acknowledged received additional compensation for their efforts. ; Peer-reviewed ; Publisher Version