The Center investigators seek to understand potential health risks posed by complex exposure scenarios present at hazardous waste sites, using a novel `seeing the whole picture' exposomic approach. Several of the proposed projects will use cutting-edge analytical chemistry, sequencing and other approaches to produce high-dimensional ?omic? data with thousands of parallel measurements on a specific endpoint. These data will be analyzed to identify biological processes that are perturbed in complex environmental exposure scenarios. Several projects will rely on a carefully maintained biorepository of mammalian cell lines and biospecimens from human populations exposed to arsenic, benzene, formaldehyde, trichloroethene, and benzo(a)pyrene. The Data Science and Laboratory Core (Core E) will support the data science, analytical chemistry and biospecimen processing and storage needs of the Center and is critical to the success of the program. Specifically, the Data Science component will support the acquisition, storage, analysis, and sharing of large, complex datasets through the development of tools, infrastructure and expertise. It will develop data-driven, machine-learning methods to find patterns in high-dimensional data sets in order to understand biological perturbations and potential health risks associated with exposures. As these methods require a lot of computing power, existing powerful Linux servers will be adapted to host and analyze the data. Core E leaders will work with the Berkeley Research Computing group to develop ways to annotate and share the data and analysis protocols with the project leaders and ultimately the greater scientific community. The Laboratory component will support the processing, storage and management of human biospecimens and cell lines, leveraging years of expertise in this area. It will innovatively connect with the Community Engagement Core B (CEC) to advise on the development of study protocols and to analyze arsenic, nitrate, chromium, pesticides, and chlorinated hydrocarbons in water samples, for the pilot Domestic Well Intervention Study of the CEC. By leveraging expertise from the research projects, the Laboratory component will enable the CEC and the Center as a whole to respond to community issues and needs, and pursue interventions to improve drinking water quality for affected communities. In conclusion, Core E is an integral and critical component of the overall program that supports the data science and laboratory needs of all projects and the CEC.
Our Center's novel `seeing the whole picture' exposomic approach will assess the health risks of hazardous sites by generating high-dimensional biological and exposure data in human biospecimens, water and soil samples and cell-lines, using cell-based bioassays, sequencing and analytical chemistry approaches. Core E, the Data Science and Laboratory Core will support: (a) the acquisition, storage, analysis, and sharing of large, complex datasets; and (b) a carefully-maintained biorepository of human biospecimens and cell lines, as well as bioassay and analytical capabilities, to support these goals.
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| Castriota, Felicia; Acevedo, Johanna; Ferreccio, Catterina et al. (2018) Obesity and increased susceptibility to arsenic-related type 2 diabetes in Northern Chile. Environ Res 167:248-254 |
| Rothman, Nathaniel; Zhang, Luoping; Smith, Martyn T et al. (2018) Formaldehyde, Hematotoxicity, and Chromosomal Changes-Response. Cancer Epidemiol Biomarkers Prev 27:120-121 |
| Yik-Sham Chung, Clive; Timblin, Greg A; Saijo, Kaoru et al. (2018) Versatile Histochemical Approach to Detection of Hydrogen Peroxide in Cells and Tissues Based on Puromycin Staining. J Am Chem Soc 140:6109-6121 |
| Rappaport, Stephen M (2018) Redefining environmental exposure for disease etiology. NPJ Syst Biol Appl 4:30 |
| Tachachartvanich, Phum; Sangsuwan, Rapeepat; Ruiz, Heather S et al. (2018) Assessment of the Endocrine-Disrupting Effects of Trichloroethylene and Its Metabolites Using in Vitro and in Silico Approaches. Environ Sci Technol 52:1542-1550 |
| Guyton, Kathryn Z; Rieswijk, Linda; Wang, Amy et al. (2018) Key Characteristics Approach to Carcinogenic Hazard Identification. Chem Res Toxicol : |
| Roh, Taehyun; Steinmaus, Craig; Marshall, Guillermo et al. (2018) Age at Exposure to Arsenic in Water and Mortality 30-40 Years After Exposure Cessation. Am J Epidemiol 187:2297-2305 |
| Daniels, Sarah I; Chambers, John C; Sanchez, Sylvia S et al. (2018) Elevated Levels of Organochlorine Pesticides in South Asian Immigrants Are Associated With an Increased Risk of Diabetes. J Endocr Soc 2:832-841 |
| Guyton, Kathryn Z; Rusyn, Ivan; Chiu, Weihsueh A et al. (2018) Application of the key characteristics of carcinogens in cancer hazard identification. Carcinogenesis 39:614-622 |
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