Characterization of fecal contamination targeting 16S rRNA bacteroides molecular markers in the Santa Cruz River, Arizona

Understanding the origins, transport and fate of contamination is essential to effective management of water resources and public health. Individuals and organizations with management responsibilities need to understand the risks to ecosystems and to humans from contact with contamination. Managers also need to understand how key contaminants vary over time and space in order to design and prioritize mitigation strategies. Tumacacori National Historic Park (NHP) is responsible for management of its water resources for the benefit of the park and for the health of its visitors. The existence of microbial contaminants in the park poses risks that must be considered in park planning and operations. The water quality laboratory at the Maricopa Agricultural Center (in collaboration with stakeholder groups and individuals located in the ADEQ-targeted watersheds) identified biological changes in surface water quality in impaired reaches rivers to determine the sources of Escherichia coli (E. coli); bacteria utilizing innovative water quality microbial/bacterial source tracking methods. The end goal was to support targeted watershed groups and ADEQ towards E. coli reductions. In the field monitoring was conducted by the selected targeted watershed groups in conjunction with The University of Arizona Maricopa Agricultural Center Water Quality Laboratory. This consisted of collecting samples for Bacteroides testing from multiple locations on select impaired reaches, to determine contamination resulting from cattle, human recreation, and other contributions. Such testing was performed in conjunction with high flow and base flow conditions in order to accurately portray water quality conditions and variations. Microbial monitoring was conducted by The University of Arizona Water Quality Laboratory at the Maricopa Agricultural Center using genetic typing to differentiate among two categories of Bacteroides: human and all (total). Testing used microbial detection methodologies and molecular source tracking techniques.^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^