82 research outputs found

    Treatment for Anogenital Molluscum Contagiosum

    Get PDF
    There is no evidence from comparative trials to suggest a single best treatment method for anogenital molluscum contagiosum. Randomized controlled trials suggest self-administered topical imiquimod or podophyllotoxin cream is effective for resolving lesions. (Strength of Recommendation: B, based on inconsistent or limited quality patient-oriented evidence). There are no comparative trials of other commonly used treatments, such as carbon dioxide laser, cryotherapy, or curettage

    The First HET Planet: A Companion to HD 37605

    Full text link
    We report the first detection of a planetary-mass companion to a star using the High Resolution Spectrograph (HRS) of the Hobby-Eberly Telescope (HET). The HET-HRS now gives routine radial velocity precision of 2-3 m/s for high SNR observations of quiescent stars. The planetary-mass companion to the metal-rich K0V star HD37605 has an orbital period of 54.23 days, an orbital eccentricity of 0.737, and a minimum mass of 2.84 Jupiter masses. The queue-scheduled operation of the Hobby-Eberly Telescope enabled us to discovery of this relatively short-period planet with a total observation time span of just two orbital periods. The ability of queue-scheduled large-aperture telescopes to respond quickly to interesting and important results demonstrates the power of this new approach in searching for extra-solar planets as well as in other ares of research requiring rapid response time critical observations.Comment: 4 Pages, 2 figures. Accepted in Astrophysical Journal Letters, http://austral.as.utexas.edu/planets/hd37605/hd37605.htm

    Signal transducer and activator of transcription 1 (STAT1) gain-of-function mutations and disseminated coccidioidomycosis and histoplasmosis

    Get PDF
    Background: Impaired signaling in the IFN-g/IL-12 pathway causes susceptibility to severe disseminated infections with mycobacteria and dimorphic yeasts. Dominant gain-of-function mutations in signal transducer and activator of transcription 1 (STAT1) have been associated with chronic mucocutaneous candidiasis. Objective: We sought to identify the molecular defect in patients with disseminated dimorphic yeast infections. Methods: PBMCs, EBV-transformed B cells, and transfected U3A cell lines were studied for IFN-g/IL-12 pathway function. STAT1 was sequenced in probands and available relatives. Interferon-induced STAT1 phosphorylation, transcriptional responses, protein-protein interactions, target gene activation, and function were investigated. Results: We identified 5 patients with disseminated Coccidioides immitis or Histoplasma capsulatum with heterozygous missense mutations in the STAT1 coiled-coil or DNA-binding domains. These are dominant gain-of-function mutations causing enhanced STAT1 phosphorylation, delayed dephosphorylation, enhanced DNA binding and transactivation, and enhanced interaction with protein inhibitor of activated STAT1. The mutations caused enhanced IFN-g–induced gene expression, but we found impaired responses to IFN-g restimulation. Conclusion: Gain-of-function mutations in STAT1 predispose to invasive, severe, disseminated dimorphic yeast infections, likely through aberrant regulation of IFN-g–mediated inflammationFil: Sampaio, Elizabeth P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz. Laboratorio de Leprologia; BrasilFil: Hsu, Amy P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Pechacek, Joseph. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Hannelore I.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Erasmus Medical Center. Department of Medical Microbiology and Infectious Disease; Países BajosFil: Dias, Dalton L.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Paulson, Michelle L.. Clinical Research Directorate/CMRP; Estados UnidosFil: Chandrasekaran, Prabha. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Rosen, Lindsey B.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Carvalho, Daniel S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz, Laboratorio de Leprologia; BrasilFil: Ding, Li. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Vinh, Donald C.. McGill University Health Centre. Division of Infectious Diseases; CanadáFil: Browne, Sarah K.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Datta, Shrimati. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Milner, Joshua D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Kuhns, Douglas B.. Clinical Services Program; Estados UnidosFil: Long Priel, Debra A.. Clinical Services Program; Estados UnidosFil: Sadat, Mohammed A.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses. Infectious Diseases Susceptibility Unit; Estados UnidosFil: Shiloh, Michael. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: De Marco, Brendan. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Alvares, Michael. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Gillman, Jason W.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Ramarathnam, Vivek. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: de la Morena, Maite. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Bezrodnik, Liliana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moreira, Ileana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; ArgentinaFil: Uzel, Gulbu. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Johnson, Daniel. University of Chicago. Comer Children; Estados UnidosFil: Spalding, Christine. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Zerbe, Christa S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Wiley, Henry. National Eye Institute. Clinical Trials Branch; Estados UnidosFil: Greenberg, David E.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Hoover, Susan E.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Rosenzweig, Sergio D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses Infectious Diseases Susceptibility Unit; Estados Unidos. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Primary Immunodeficiency Clinic; Estados UnidosFil: Galgiani, John N.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Holland, Steven M.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unido

    Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

    Get PDF
    We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

    Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

    Get PDF
    As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

    Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

    Get PDF
    How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)

    Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

    Get PDF
    BACKGROUND: Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 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 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS: The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION: At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING: Bill & Melinda Gates Foundation

    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.

    Get PDF
    The Global Burden of Diseases, Injuries and Risk Factors 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

    Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

    Get PDF
    The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030
    corecore