2 resultados para Industrial pollutants

em DigitalCommons@The Texas Medical Center


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Cytochrome P450s, a superfamily of heme enzymes found in most living organisms. They are responsible for metabolism of many therapeutic drugs, industrial pollutants, carcinogens, and additives to foodstuffs, as well as some endogenous compounds including fatty acids and steroids. First pass drug metabolism studies represent mainly liver and small intestine elimination, and are viewed as the standard to predict therapeutic outcome. However, drug plasma levels determined after administration do not always correlate with therapeutic efficacy of the drug. Therefore, a possible explanation may come by understanding drug metabolism in extrahepatic tissues and/or at the site of drug action. Identification and characterization of novel tissue specific isoforms of P450 generated by alternative splicing of known P450 genes or as yet unidentified genes is essential to predict pharmacological outcome of drugs or the fate of a carcinogen that act at sites remote from liver. ^ Using RT-PCR, brain-specific cytochrome P450s were detected in samples of human autopsy brain. So far, we have identified two human brain variants including P450 2D7 and P450 1A1. We have shown the presence of the P450 1A1 brain specific splice variant in African Americans, Caucasians and Indians albeit different patterns of liver to brain variant ratio were seen distributed throughout each population. Interestingly, the splice variant was detected only in the brain but not in any other tissues from the same individual. Homology modeling was used to compare the variant 3D structure to the liver form structure and differences in the substrate access channels and substrate binding sites were noticed. Automated computational docking was used to predict the metabolic fate of the potent carcinogenic substrate, benzo[a]pyrene. P450 1A1 brain variant showed no binding orientations that could produce the active metabolite, whereas P450 1A1 liver form did reveal orientations capable of generating active carcinogenic product. In vitro P32 labeling studies verified the docking predictions. Therefore, the data support the hypothesis that P450 brain splice variants mediate the metabolism of xenobiotics by mechanisms distinct from the well-studied liver counterparts. ^

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Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^