874 resultados para Epidemiological studies


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Studies suggest that depression affects glucose metabolism, and therefore is a risk factor for insulin resistance. The association between depression and insulin resistance has been investigated in a number of studies, but there is no agreement on the results. The objective of this study is to survey the epidemiological studies, identify the ones that measured the association of depression (as exposure) with insulin resistance (as outcome), and perform a systematic review to assess the reliability and strength of the association. For high quality reporting, and assessment, this systematic review used the outlined procedures, guidelines and recommendations for reviews in health care, suggested by the Centre for Reviews and Dissemination, along with recommendations from the STROBE group (Strengthening the Reporting of Observational Studies in Epidemiology). Ovid MEDLINE 1996 to April Week 1 2010, was used to identify the relevant epidemiological studies. To identify the most relevant set of articles for this systematic review, a set of inclusion and exclusion criteria were applied. Six studies that met the specific criteria were selected. Key information from identified studies was tabulated, and the methodological quality, internal and external validity, and the strength of the evidence of the selected studies were assessed. The result from the tabulated data of the reviewed studies indicates that the studies either did not apply a case definition for insulin resistance in their investigation, or did not state a specific value for the index used to define insulin resistance. The quality assessment of the reviewed studies indicates that to assess the association between insulin resistance and depression, specifying a case definition for insulin resistance is important. The case definition for insulin resistance is defined by the World Health Organization and the European Group for the Study of Insulin Resistance as the insulin sensitivity index of the lowest quartile or lowest decile of a general population, respectively. Three studies defined the percentile cut-off point for insulin resistance, but did not give the insulin sensitivity index value. In these cases, it is not possible to compare the results. Three other studies did not define the cut-off point for insulin resistance. In these cases, it is hard to confirm the existence of insulin resistance. In conclusion, to convincingly answer our question, future studies need to adopt a clear case definition, define a percentile cut-off point and reference population, and give value of the insulin resistance measure at the specified percentile.^

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Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

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Background. Research has shown that elevations of only 10 mmHg diastolic blood pressure (BP) and 5 mmHg systolic BP are associated with substantial (as large as 50%) increases in risks for cardiovascular disease, a leading cause of death, worldwide. Epidemiological studies have found that particulate matter (PM) increases blood pressure (BP) and many biological mechanisms which may suggest that the organic matter of PM contributes to the increase in BP. To understand components of PM which may contribute to the increase in BP, this study focuses on diesel particulate matter (DPM) and polycyclic aromatic hydrocarbons (PAHs). To our knowledge, there have been only four epidemiological studies on BP and DPM, and no epidemiological studies on BP and PAHs. ^ Objective. Our objective was to evaluate the association between prevalent hypertension and two ambient exposures: DPM and PAHs amongst the Mano a Mano cohort. ^ Methods. The Mano a Mano cohort which was established by the M.D. Anderson Cancer Center in 2001, is comprised of individuals of Mexican origin residing in Houston, TX. Using geographical information systems, we linked modeled annual estimates of PAHs and DPM at the census track level from the U.S. Environmental Protection Agency's National-Scale Air Toxics Assessment to residential addresses of cohort members. Mixed-effects logistic regression models were applied to determine associations between DPM and PAHs and hypertension while adjusting for confounders. ^ Results. Ambient levels of DPM, categorized into quartiles, were not statistically associated with hypertension and did not indicate a dose response relationship. Ambient levels of PAHs, categorized into quartiles, were not associated with hypertension, but did indicate a dose response relationship in multiple models (for example: Q2: OR = 0.98; 95% CI, 0.73–1.31, Q3: OR = 1.08; 95% CI, 0.82–1.41, Q4: OR = 1.26; 95% CI, 0.94–1.70). ^ Conclusion. This is the first assessment to analyze the relationship between ambient levels of PAHs and hypertension and it is amongst a few studies investigating the association between ambient levels of DPM and hypertension. Future analyses are warranted to explore the effects DPM and PAHs using different categorizations in order to clarify their relationships with hypertension.^

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Exposure to air pollutants in urban locales has been associated with increased risk for chronic diseases including cardiovascular disease (CVD) and pulmonary diseases in epidemiological studies. The exact mechanism explaining how air pollution affects chronic disease is still unknown. However, oxidative stress and inflammatory pathways have been posited as likely mechanisms. ^ Data from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Mexican-American Cohort Study (2003-2009) were used to examine the following aims, respectively: 1) to evaluate the association between long-term exposure to ambient particulate matter (PM) (PM10 and PM2.5) and nitrogen oxides (NO x) and telomere length (TL) among approximately 1,000 participants within MESA; and 2) to evaluate the association between traffic-related air pollution with self-reported asthma, diabetes, and hypertension among Mexican-Americans in Houston, Texas. ^ Our results from MESA were inconsistent regarding associations between long-term exposure to air pollution and shorter telomere length based on whether the participants came from New York (NY) or Los Angeles (LA). Although not statistically significant, we observed a negative association between long-term air pollution exposure and mean telomere length for NY participants, which was consistent with our hypothesis. Positive (statistically insignificant) associations were observed for LA participants. It is possible that our findings were more influenced by both outcome and exposure misclassification than by the absence of a relationship between pollution and TL. Future studies are needed that include longitudinal measures of telomere length as well as focus on effects of specific constituents of PM and other pollutant exposures on changes in telomere length over time. ^ This research provides support that Mexican-American adults who live near a major roadway or in close proximity to a dense street network have a higher prevalence of asthma. There was a non-significant trend towards an increased prevalence of adult asthma with increasing residential traffic exposure especially for residents who lived three or more years at their baseline address. Even though the prevalence of asthma is low in the Mexican-origin population, it is the fastest growing minority group in the U.S. and we would expect a growing number of Mexican-Americans who suffer from asthma in the future. Future studies are needed to better characterize risks for asthma associated with air pollution in this population.^

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Left ventricular outflow tract (LVOT) defects are an important group of congenital heart defects (CHDs) because of their associated mortality and long-term complications. LVOT defects include aortic valve stenosis (AVS), coarctation of aorta (CoA), and hypoplastic left heart syndrome (HLHS). Despite their clinical significance, their etiology is not completely understood. Even though the individual component phenotypes (AVS, CoA, and HLHS) may have different etiologies, they are often "lumped" together in epidemiological studies. Though "lumping" of component phenotypes may improve the power to detect associations, it may also lead to ambiguous findings if these defects are etiologically distinct. This is due to potential for effect heterogeneity across component phenotypes. ^ This study had two aims: (1) to identify the association between various risk factors and both the component (i.e., split) and composite (i.e., lumped) LVOT phenotypes, and (2) to assess the effect heterogeneity of risk factors across component phenotypes of LVOT defects. ^ This study was a secondary data analysis. Primary data were obtained from the Texas Birth Defect Registry (TBDR). TBDR uses an active surveillance method to ascertain birth defects in Texas. All cases of non complex LVOT defects which met our inclusion criteria during the period of 2002–2008 were included in the study. The comparison groups included all unaffected live births for the same period (2002–2008). Data from vital statistics were used to evaluate associations. Statistical associations between selected risk factors and LVOT defects was determined by calculating crude and adjusted prevalence ratio using Poisson regression analysis. Effect heterogeneity was evaluated using polytomous logistic regression. ^ There were a total of 2,353 cases of LVOT defects among 2,730,035 live births during the study period. There were a total of 1,311 definite cases of non-complex LVOT defects for analysis after excluding "complex" cardiac cases and cases associated with syndromes (n=168). Among infant characteristics, males were at a significantly higher risk of developing LVOT defects compared to females. Among maternal characteristics, significant associations were seen with maternal age > 40 years (compared to maternal age 20–24 years) and maternal residence in Texas-Mexico border (compared to non-border residence). Among birth characteristics, significant associations were seen with preterm birth and small for gestation age LVOT defects. ^ When evaluating effect heterogeneity, the following variables had significantly different effects among the component LVOT defect phenotypes: infant sex, plurality, maternal age, maternal race/ethnicity, and Texas-Mexico border residence. ^ This study found significant associations between various demographic factors and LVOT defects. While many findings from this study were consistent with results from previous studies, we also identified new factors associated with LVOT defects. Additionally, this study was the first to assess effect heterogeneity across LVOT defect component phenotypes. These findings contribute to a growing body of literature on characteristics associated with LVOT defects. ^

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Birth defects are a leading cause of infant mortality in the United States. About one in 33 births in the United States is diagnosed with birth defects. Common birth defects include neural tube defects, Down syndrome and oral clefts. The present study focused on oral clefts. ^ Oral clefts refer to the malformation of lip, mouth or both. Birth prevalence of oral clefts in Texas is about 11 per 10,000 births. Etiologically, oral clefts have been classified into two groups, cleft lip with or without cleft palate (CL±P) and isolated cleft palate (CP). In spite of their high prevalence and clinical significance, the etiology of oral clefts in humans has not been well understood. Though a number of risk factors have been identified in epidemiological studies, most of them do not explain the majority of the cases. The need to identify novel risk factors associated with oral clefts provided the motivation for this study. The present study focused on maternal exposure to several hazardous air pollutants. A common subgroup of hazardous air pollutants is the volatile organic compounds found in petroleum derivatives. Four important hydrocarbons in this group are benzene, toluene, ethyl benzene and xylenes (BTEX). ^ The specific aim of this study was to evaluate the association between maternal exposure to environmental levels of BTEX and oral clefts among offspring in Texas for the period 1999-2008. ^ A case-control study design was used to assess if maternal exposure to BTEX increased the risk of oral clefts. The Texas Birth Defects Registry provided data on cases of non-syndromic oral clefts delivered in Texas during the period 1999-2008. Census tract level maternal exposure to BTEX concentrations were obtained from the Hazardous Air Pollutant Exposure Model (HAPEM) developed by the U.S. Environmental Protection Agency. Unconditional logistic regression was used to assess the relationship between maternal exposure to BTEX levels and risk of oral clefts in offspring. ^ In the selected population, mothers who had high estimated exposure to any of the BTEX compounds were not more likely to deliver an offspring with oral clefts. Future research efforts will focus on additional birth defects and thorough assessment of additional potential confounders.^

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Existen pocas publicaciones sobre claves de identificación de larvas de trips. Sin embargo, el tema es de interés básico para detectar el rango de hospedantes de los trips. Algunas especies son capaces de transmitir Tospovirus, agentes causales de la peste negra y otras enfermedades. El insecto adquiere el virus sólo como larva. Una clave de larvas será una herramienta útil para estudios epidemiológicos. La identificación de larvas es difícil porque tienen menos caracteres distintivos que los adultos; además, los individuos crecen constantemente. Las larvas obtenidas para este trabajo se recolectaron del campo sobre varias malezas y algunas plantas nativas y cultivadas. También se criaron en chauchas de poroto o polen y miel diluida a partir de adultos identificados. En este trabajo se presenta una descripción breve del segundo estadío larval de Frankliniella australis Morgan, F. gemina Bagnall, F. occidentalis Pergande, F. schultzei Trybom, F. valdiviana Sakimura et O'Neil y Thrips tabaci Lindeman y una clave para separar estas especies. Estación Experimental Agropecuaria INTA Mendoza.

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In order to determine the presence of Fusarium spp. in atmospheric dust and rainfall dust, samples were collected during September 2007, and July, August, and October 2008. The results reveal the prevalence of airborne Fusarium species coming from the atmosphere of the South East coast of Spain. Five different Fusarium species were isolated from the settling dust: Fusarium oxysporum, F. solani, F. equiseti, F. dimerum, and F. proliferatum. Moreover, rainwater samples were obtained during significant rainfall events in January and February 2009. Using the dilution-plate method, 12 fungal genera were identified from these rainwater samples. Specific analyses of the rainwater revealed the presence of three species of Fusarium: F. oxysporum, F. proliferatum and F. equiseti. A total of 57 isolates of Fusarium spp. obtained from both rainwater and atmospheric rainfall dust sampling were inoculated onto melon (Cucumis melo L.) cv. Piñonet and tomato (Lycopersicon esculentum Mill.) cv. San Pedro. These species were chosen because they are the main herbaceous crops in Almeria province. The results presented in this work indicate strongly that spores or propagules of Fusarium are able to cross the continental barrier carried by winds from the Sahara (Africa) to crop or coastal lands in Europe. Results show differences in the pathogenicity of the isolates tested. Both hosts showed root rot when inoculated with different species of Fusarium, although fresh weight measurements did not bring any information about the pathogenicity. The findings presented above are strong indications that long-distance transmission of Fusarium propagules may occur. Diseases caused by species of Fusarium are common in these areas. They were in the past, and are still today, a problem for greenhouses crops in Almería, and many species have been listed as pathogens on agricultural crops in this region. Saharan air masses dominate the Mediterranean regions. The evidence of long distance dispersal of Fusarium spp. by atmospheric dust and rainwater together with their proved pathogenicity must be taken into account in epidemiological studies.

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La mejora de la calidad del aire es una tarea eminentemente interdisciplinaria. Dada la gran variedad de ciencias y partes involucradas, dicha mejora requiere de herramientas de evaluación simples y completamente integradas. La modelización para la evaluación integrada (integrated assessment modeling) ha demostrado ser una solución adecuada para la descripción de los sistemas de contaminación atmosférica puesto que considera cada una de las etapas involucradas: emisiones, química y dispersión atmosférica, impactos ambientales asociados y potencial de disminución. Varios modelos de evaluación integrada ya están disponibles a escala continental, cubriendo cada una de las etapas antesmencionadas, siendo el modelo GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) el más reconocido y usado en el contexto europeo de toma de decisiones medioambientales. Sin embargo, el manejo de la calidad del aire a escala nacional/regional dentro del marco de la evaluación integrada es deseable. Esto sin embargo, no se lleva a cabo de manera satisfactoria con modelos a escala europea debido a la falta de resolución espacial o de detalle en los datos auxiliares, principalmente los inventarios de emisión y los patrones meteorológicos, entre otros. El objetivo de esta tesis es presentar los desarrollos en el diseño y aplicación de un modelo de evaluación integrada especialmente concebido para España y Portugal. El modelo AERIS (Atmospheric Evaluation and Research Integrated system for Spain) es capaz de cuantificar perfiles de concentración para varios contaminantes (NO2, SO2, PM10, PM2,5, NH3 y O3), el depósito atmosférico de especies de azufre y nitrógeno así como sus impactos en cultivos, vegetación, ecosistemas y salud como respuesta a cambios porcentuales en las emisiones de sectores relevantes. La versión actual de AERIS considera 20 sectores de emisión, ya sea equivalentes a sectores individuales SNAP o macrosectores, cuya contribución a los niveles de calidad del aire, depósito e impactos han sido modelados a través de matrices fuentereceptor (SRMs). Estas matrices son constantes de proporcionalidad que relacionan cambios en emisiones con diferentes indicadores de calidad del aire y han sido obtenidas a través de parametrizaciones estadísticas de un modelo de calidad del aire (AQM). Para el caso concreto de AERIS, su modelo de calidad del aire “de origen” consistió en el modelo WRF para la meteorología y en el modelo CMAQ para los procesos químico-atmosféricos. La cuantificación del depósito atmosférico, de los impactos en ecosistemas, cultivos, vegetación y salud humana se ha realizado siguiendo las metodologías estándar establecidas bajo los marcos internacionales de negociación, tales como CLRTAP. La estructura de programación está basada en MATLAB®, permitiendo gran compatibilidad con software típico de escritorio comoMicrosoft Excel® o ArcGIS®. En relación con los niveles de calidad del aire, AERIS es capaz de proveer datos de media anual y media mensual, así como el 19o valor horario más alto paraNO2, el 25o valor horario y el 4o valor diario más altos para SO2, el 36o valor diario más alto para PM10, el 26o valor octohorario más alto, SOMO35 y AOT40 para O3. En relación al depósito atmosférico, el depósito acumulado anual por unidad de area de especies de nitrógeno oxidado y reducido al igual que de azufre pueden ser determinados. Cuando los valores anteriormente mencionados se relacionan con características del dominio modelado tales como uso de suelo, cubiertas vegetales y forestales, censos poblacionales o estudios epidemiológicos, un gran número de impactos puede ser calculado. Centrándose en los impactos a ecosistemas y suelos, AERIS es capaz de estimar las superaciones de cargas críticas y las superaciones medias acumuladas para especies de nitrógeno y azufre. Los daños a bosques se calculan como una superación de los niveles críticos de NO2 y SO2 establecidos. Además, AERIS es capaz de cuantificar daños causados por O3 y SO2 en vid, maíz, patata, arroz, girasol, tabaco, tomate, sandía y trigo. Los impactos en salud humana han sido modelados como consecuencia de la exposición a PM2,5 y O3 y cuantificados como pérdidas en la esperanza de vida estadística e indicadores de mortalidad prematura. La exactitud del modelo de evaluación integrada ha sido contrastada estadísticamente con los resultados obtenidos por el modelo de calidad del aire convencional, exhibiendo en la mayoría de los casos un buen nivel de correspondencia. Debido a que la cuantificación de los impactos no es llevada a cabo directamente por el modelo de calidad del aire, un análisis de credibilidad ha sido realizado mediante la comparación de los resultados de AERIS con los de GAINS para un escenario de emisiones determinado. El análisis reveló un buen nivel de correspondencia en las medias y en las distribuciones probabilísticas de los conjuntos de datos. Las pruebas de verificación que fueron aplicadas a AERIS sugieren que los resultados son suficientemente consistentes para ser considerados como razonables y realistas. En conclusión, la principal motivación para la creación del modelo fue el producir una herramienta confiable y a la vez simple para el soporte de las partes involucradas en la toma de decisiones, de cara a analizar diferentes escenarios “y si” con un bajo coste computacional. La interacción con políticos y otros actores dictó encontrar un compromiso entre la complejidad del modeladomedioambiental con el carácter conciso de las políticas, siendo esto algo que AERIS refleja en sus estructuras conceptual y computacional. Finalmente, cabe decir que AERIS ha sido creado para su uso exclusivo dentro de un marco de evaluación y de ninguna manera debe ser considerado como un sustituto de los modelos de calidad del aire ordinarios. ABSTRACT Improving air quality is an eminently inter-disciplinary task. The wide variety of sciences and stakeholders that are involved call for having simple yet fully-integrated and reliable evaluation tools available. Integrated AssessmentModeling has proved to be a suitable solution for the description of air pollution systems due to the fact that it considers each of the involved stages: emissions, atmospheric chemistry, dispersion, environmental impacts and abatement potentials. Some integrated assessment models are available at European scale that cover each of the before mentioned stages, being the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model the most recognized and widely-used within a European policy-making context. However, addressing air quality at the national/regional scale under an integrated assessment framework is desirable. To do so, European-scale models do not provide enough spatial resolution or detail in their ancillary data sources, mainly emission inventories and local meteorology patterns as well as associated results. The objective of this dissertation is to present the developments in the design and application of an Integrated Assessment Model especially conceived for Spain and Portugal. The Atmospheric Evaluation and Research Integrated system for Spain (AERIS) is able to quantify concentration profiles for several pollutants (NO2, SO2, PM10, PM2.5, NH3 and O3), the atmospheric deposition of sulfur and nitrogen species and their related impacts on crops, vegetation, ecosystems and health as a response to percentual changes in the emissions of relevant sectors. The current version of AERIS considers 20 emission sectors, either corresponding to individual SNAP sectors or macrosectors, whose contribution to air quality levels, deposition and impacts have been modeled through the use of source-receptor matrices (SRMs). Thesematrices are proportionality constants that relate emission changes with different air quality indicators and have been derived through statistical parameterizations of an air qualitymodeling system (AQM). For the concrete case of AERIS, its parent AQM relied on the WRF model for meteorology and on the CMAQ model for atmospheric chemical processes. The quantification of atmospheric deposition, impacts on ecosystems, crops, vegetation and human health has been carried out following the standard methodologies established under international negotiation frameworks such as CLRTAP. The programming structure isMATLAB ® -based, allowing great compatibility with typical software such as Microsoft Excel ® or ArcGIS ® Regarding air quality levels, AERIS is able to provide mean annual andmean monthly concentration values, as well as the indicators established in Directive 2008/50/EC, namely the 19th highest hourly value for NO2, the 25th highest daily value and the 4th highest hourly value for SO2, the 36th highest daily value of PM10, the 26th highest maximum 8-hour daily value, SOMO35 and AOT40 for O3. Regarding atmospheric deposition, the annual accumulated deposition per unit of area of species of oxidized and reduced nitrogen as well as sulfur can be estimated. When relating the before mentioned values with specific characteristics of the modeling domain such as land use, forest and crops covers, population counts and epidemiological studies, a wide array of impacts can be calculated. When focusing on impacts on ecosystems and soils, AERIS is able to estimate critical load exceedances and accumulated average exceedances for nitrogen and sulfur species. Damage on forests is estimated as an exceedance of established critical levels of NO2 and SO2. Additionally, AERIS is able to quantify damage caused by O3 and SO2 on grapes, maize, potato, rice, sunflower, tobacco, tomato, watermelon and wheat. Impacts on human health aremodeled as a consequence of exposure to PM2.5 and O3 and quantified as losses in statistical life expectancy and premature mortality indicators. The accuracy of the IAM has been tested by statistically contrasting the obtained results with those yielded by the conventional AQM, exhibiting in most cases a good agreement level. Due to the fact that impacts cannot be directly produced by the AQM, a credibility analysis was carried out for the outputs of AERIS for a given emission scenario by comparing them through probability tests against the performance of GAINS for the same scenario. This analysis revealed a good correspondence in the mean behavior and the probabilistic distributions of the datasets. The verification tests that were applied to AERIS suggest that results are consistent enough to be credited as reasonable and realistic. In conclusion, the main reason thatmotivated the creation of this model was to produce a reliable yet simple screening tool that would provide decision and policy making support for different “what-if” scenarios at a low computing cost. The interaction with politicians and other stakeholders dictated that reconciling the complexity of modeling with the conciseness of policies should be reflected by AERIS in both, its conceptual and computational structures. It should be noted however, that AERIS has been created under a policy-driven framework and by no means should be considered as a substitute of the ordinary AQM.

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The last decade, scientific studies have indicated an association between air pollution to which people are exposed and wide range of adverse health outcomes. We have developed a tool which is based on a model (MM5-CMAQ) running over Europe with 50 km spatial resolution, based on EMEP annual emissions, to produce a short-term forecast of the impact on health. In order to estimate the mortality change (forecasted for the next 24 hours) we have chosen a log-linear (Poisson) regression form to estimate the concentration-response function. The parameters involved in the C-R function have been estimated based on epidemiological studies, which have been published. Finally, we have derived the relationship between concentration change and mortality change from the C-R function which is the final health impact function.

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Recent epidemiological studies indicate beneficial effects of moderate ethanol consumption in ischemic heart disease. Most studies, however, focus on the effect of long-term consumption of ethanol. In this study, we determined whether brief exposure to ethanol immediately before ischemia also produces cardioprotection. In addition, because protein kinase C (PKC) has been shown to mediate protection of the heart from ischemia, we determined the role of specific PKC isozymes in ethanol-induced protection. We demonstrated that (i) brief exposure of isolated adult rat cardiac myocytes to 10–50 mM ethanol protected against damage induced by prolonged ischemia; (ii) an isozyme-selective ɛPKC inhibitor developed in our laboratory inhibited the cardioprotective effect of acute ethanol exposure; (iii) protection of isolated intact adult rat heart also occurred after incubation with 10 mM ethanol 20 min before global ischemia; and (iv) ethanol-induced cardioprotection depended on PKC activation because it was blocked by chelerythrine and GF109203X, two PKC inhibitors. Consumption of 1–2 alcoholic beverages in humans leads to blood alcohol levels of ≈10 mM. Therefore, our work demonstrates that exposure to physiologically attainable ethanol levels minutes before ischemia provides cardioprotection that is mediated by direct activation of ɛPKC in the cardiac myocytes. The potential clinical implications of our findings are discussed.

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The partial molecular characterization of multiple sclerosis (MS)-associated retrovirus (MSRV), a novel retrovirus previously called LM7, is reported. MSRV has been isolated repeatedly from leptomeningeal, choroid plexus and from Epstein–Barr virus-immortalized B cells of MS patients. A strategy based on reverse transcriptase PCR with RNA-purified extracellular virions yielded an initial pol fragment from which other regions of the retroviral genome were subsequently obtained by sequence extension. MSRV-specific PCR primers amplified a pol region from RNA present at the peak of reverse transcriptase activity, coinciding with extracellular viral particles in sucrose density gradients. The same sequence was detected in noncellular RNA from MS patient plasma and in cerebrospinal fluid from untreated MS patients. MSRV is related to, but distinct from, the endogenous retroviral sequence ERV9. Whether MSRV represents an exogenous retrovirus with closely related endogenous elements or a replication-competent, virion-producing, endogenous provirus is as yet unknown. Further molecular epidemiological studies are required to determine precisely the apparent association of virions containing MSRV RNA with MS.

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Vesicular stomatitis New Jersey virus (VSV-NJ) is a rhabdovirus that causes economically important disease in cattle and other domestic animals in endemic areas from southeastern United States to northern South America. Its negatively stranded RNA genome is capable of undergoing rapid evolution, which allows phylogenetic analysis and molecular epidemiology studies to be performed. Previous epidemiological studies in Costa Rica showed the existence of at least two distinct ecological zones of high VSV-NJ activity, one located in the highlands (premontane tropical moist forest) and the other in the lowlands (tropical dry forest). We wanted to test the hypothesis that the viruses circulating in these ecological zones were genetically distinct. For this purpose, we sequenced the hypervariable region of the phosphoprotein gene for 50 VSV-NJ isolates from these areas. Phylogenetic analysis showed that viruses from each ecological zone had distinct genotypes. These genotypes were maintained in each area for periods of up to 8 years. This evolutionary pattern of VSV-NJ suggests an adaptation to ecological factors that could exert selective pressure on the virus. As previous data indicated an absence of virus adaptation to factors related to the bovine host (including immunological pressure), it appears that VSV genetic divergence represents positive selection to adapt to specific vectors and/or reservoirs at each ecological zone.

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Nonsyndromic clefting of the lip and palate in humans has a highly complex etiology, with both multiple genetic loci and exposure to teratogens influencing susceptibility. Previous studies using mouse models have examined only very small portions of the genome. Here we report the findings of a genome-wide search for susceptibility genes for teratogen-induced clefting in the AXB and BXA set of recombinant inbred mouse strains. We compare results obtained using phenytoin (which induces cleft lip) and 6-aminonicotinamide (which induces cleft palate). We use a new statistical approach based on logistic regression suitable for these categorical data to identify several chromosomal regions as possible locations of clefting susceptibility loci, and we review candidate genes located within each region. Because cleft lip and cleft palate do not frequently co-aggregate in human families and because these structures arise semi-independently during development, these disorders are usually considered to be distinct in etiology. Our data, however, implicate several of the same chromosomal regions for both forms of clefting when teratogen-induced. Furthermore, different parental strain alleles are usually associated with clefting of the lip versus that of the palate (i.e., allelic heterogeneity). Because several other chromosomal regions are associated with only one form of clefting, locus heterogeneity also appears to be involved. Our findings in this mouse model suggest several priority areas for evaluation in human epidemiological studies.

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Enhanced activity of receptor tyrosine kinases such as the PDGF β-receptor and EGF receptor has been implicated as a contributing factor in the development of malignant and nonmalignant proliferative diseases such as cancer and atherosclerosis. Several epidemiological studies suggest that green tea may prevent the development of cancer and atherosclerosis. One of the major constituents of green tea is the polyphenol epigallocathechin-3 gallate (EGCG). In an attempt to offer a possible explanation for the anti-cancer and anti-atherosclerotic activity of EGCG, we examined the effect of EGCG on the PDGF-BB–, EGF-, angiotensin II-, and FCS-induced activation of the 44 kDa and 42 kDa mitogen-activated protein (MAP) kinase isoforms (p44mapk/p42mapk) in cultured vascular smooth muscle cells (VSMCs) from rat aorta. VSMCs were treated with EGCG (1–100 μM) for 24 h and stimulated with the above mentioned agonists for different time periods. Stimulation of the p44mapk/p42mapk was detected by the enhanced Western blotting method using phospho-specific MAP kinase antibodies that recognized the Tyr204-phosphorylated (active) isoforms. Treatment of VSMCs with 10 and 50 μM EGCG resulted in an 80% and a complete inhibition of the PDGF-BB–induced activation of MAP kinase isoforms, respectively. In striking contrast, EGCG (1–100 μM) did not influence MAP kinase activation by EGF, angiotensin II, and FCS. Similarly, the maximal effect of PDGF-BB on the c-fos and egr-1 mRNA expression as well as on intracellular free Ca2+ concentration was completely inhibited in EGCG-treated VSMCs, whereas the effect of EGF was not affected. Quantification of the immunoprecipitated tyrosine-phosphorylated PDGF-Rβ, phosphatidylinositol 3′-kinase, and phospholipase C-γ1 by the enhanced Western blotting method revealed that EGCG treatment effectively inhibits tyrosine phosphorylation of these kinases in VSMCs. Furthermore, we show that spheroid formation of human glioblastoma cells (A172) and colony formation of sis-transfected NIH 3T3 cells in semisolid agar are completely inhibited by 20–50 μM EGCG. Our findings demonstrate that EGCG is a selective inhibitor of the tyrosine phosphorylation of PDGF-Rβ and its downstream signaling pathway. The present findings may partly explain the anti-cancer and anti-atherosclerotic activity of green tea.