Bayesian Maximum Entropy Geostatistical Estimation of BTEX and Styrene in the United States Gulf Region Using Observational Data

The United States’ gulf region is home to a plethora of oil refineries, petroleum industrial plants, and other industrial plants. Such industry is a common source of Volatile Organic Compounds (VOCs), including benzene, toluene, ethylbenzene, and xylenes (BTEX) and styrene. Benzene is a known carcinogen, and work is under way to study the association of BTEX and styrene with novel neurologic health endpoints in the United States Gulf Region. However, information on exposure to these VOCs is limited, existing air quality models are not adequate, and observational data is sparse. The goal of this work is therefore to develop a Bayesian Maximum Entropy (BME) model to obtain geostatistical estimates of benzene, BTEX, and styrene across the US Gulf Region from 2006 through 2017 and assess the performance this BME model. The BME model developed uses a global offset that captures geographical trends at a coarse regional scale and temporal trends at fine temporal resolution. A covariance analysis of the offset-removed data revealed that a large proportion of the variability of these VOCs follow a nugget (i.e. purely random) model. The nugget proportion was 33%, 46% and 51% for BTEX, Benzene and Styrene. The r2 cross validation statistics was found to be 0.66, 0.53 and 0.65 for BTEX, Benzene and Styrene log-concentrations, and 0.29, 0.19 and 0.11 for BTEX, Benzene and Styrene concentrations. These results indicate that estimation performance is better for log concentrations and more moderate for raw concentrations. The performance for log concentrations may have been inflated by the procedure used to log transform non detect values, and by the limited ability of the global offset to capture fine scale geographical trends, so these issues should be explored further in future works.Master of Science in Environmental Engineerin

Human estrogen sulfotransferase (SULT1E1) pharmacogenomics: gene resequencing and functional genomics

1. Estrogens are used as drugs and estrogen exposure is a risk factor for hormone-dependent diseases such as breast cancer. Sulfate conjugation is an important pathway for estrogen metabolism. The sulfotransferase (SULT) enzyme SULT1E1 has the lowest K(m) values for estrogens and catecholestrogens of the 10 known human SULT isoforms. 2. We previously cloned and characterized the human SULT1E1 cDNA and gene as steps toward pharmacogenetic studies. In the present experiments, we set out to determine whether common, functionally significant genetic polymorphisms might exist for SULT1E1. As a first step, we ‘resequenced' the eight SULT1E1 exons and exon–intron splice junctions as well as portions of the 5′-flanking region using DNA from 60 African-American and 60 Caucasian-American subjects. 3. In all, 23 polymorphisms, 22 single nucleotide polymorphisms (SNPs) and one insertion deletion were observed. There were three nonsynonymous coding SNPs (cSNPs) that altered the following encoded amino acids: Asp22Tyr, Ala32Val and Pro253His. Among these, 12 pairs of SNPs were tightly linked. In addition, 12 unambiguous SULT1E1 haplotypes were identified, including six that were common to both populations studied. 4. Transient expression in COS-1 cells of constructs containing the three nonsynonymous cSNPs showed significant decreases in SULT1E1 activity for the Tyr22 and Val32 allozymes, with corresponding decreases in levels of immunoreactive protein. There were no changes in levels of either activity or immunoreactive protein for the His253 allozyme. Apparent K(m) values of the Val32 allozyme for the two cosubstrates for the reaction, 17β-estradiol and 3′-phosphoadenosine 5′-phosphosulfate, were not significantly different from those of the wild-type enzyme, but there was a two- to three-fold increase in K(m) values for the His253 allozyme and a greater than five-fold increase for the Tyr22 allozyme. 5. These observations raise the possibility that genetically determined variation in SULT1E1-catalyzed estrogen sulfation might contribute to the pathophysiology of estrogen-dependent diseases as well as variation in the biotransformation of exogenously administered estrogens