Data Management and Analysis Core The Iowa Superfund Research Program (ISRP) tackles a highly complex issue that requires a well-integrated thematic approach. The Data Management and Analysis Core (DMAC) will provide the expertise, tools, and workflow optimization to support and maximize ISRP research results and impact. The DMAC and project leaders will develop tailored Priority Analysis Plans with rigorous Quality Assurance to assure accuracy, precision, representativeness, comparability, and reproducibility using appropriate statistical and analytical methods. As a result, ISRP projects will make high-impact discoveries, publish in high-quality journals, and provide timely scientific guidance to stakeholders regarding PCBs in the environment and their effect on human health. DMAC will have five Specific Aims: 1) develop, maintain, and automate data management, data-sharing, and quality assurance infrastructure for full reproducibility, transparency, and rigor in all ISRP studies; 2) support ISRP projects and cores with embedded expert biostatical contributions, services, and guidance; 3) develop novel statistical methods and associated software for data analytic challenges that impact all ISRP projects, cores, and affiliated sciences; 4) support the Research Experience and Training Coordination Core by providing guidance, resources, events, and instruction on data science and informatics to trainees and investigators; and 5) provide the data management and analytical foundations for research integration across the ISRP. Activities proposed under DMAC Specific Aim 3 address SRP mandates 2 and 3, which call for novel statistical methods and tools to support detection and risk assessment. Activities under Specific Aim 5 address SRP mandates 1, 2, and 4 by integrating data and methods from across the ISRP into cost-effective solutions and strategies to comprehensively assess and reduce population-scale PCB risks to human health. Through DMAC, the ISRP is charting new territory at the University of Iowa (UI). This work represents a unique opportunity to align existing resources to support interdisciplinary research. With the help of our UI partners, the DMAC will be an early adopter of proven enabling approaches and technologies for data management, data-sharing, reproducible research workflows, and informatics investigation and training. DMAC will lead the application of biostatistics and informatics to support and optimize ISRP research. We will provide expert staff, platforms, policies, and research support for all ISRP projects and cores throughout the research process, including training and methods to maximize research outcomes, applied solutions, replicable products, and sound evidence-based decision support. DMAC?s activities will enhance full ISRP integration and catalyze effective development, refinement, application, and sharing of innovative solutions generated by ISRP interdisciplinary and transdisciplinary PCB research. DMAC?s centralized services, platforms, and policies, along with innovative new methods, will yield economies of scale in effort and cost for data management, processing, sharing, analysis, and training.

Public Health Relevance

Data Management and Analysis Core The Data Management and Analysis Core (DMAC) is a proposed new core designed to support the specific data management and analysis needs of Iowa Superfund Research Program (ISRP) projects and cores. DMAC?s primary objective will be to apply biostatistics, informatics, and data management to support and optimize the ISRP scientific research process, training, and methods to maximize research outcomes, applied solutions, replicable products, and sound evidence-based decision support. DMAC will provide expert staff, infrastructure, services, software, and research support and synthesis in order to achieve these goals.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Hazardous Substances Basic Research Grants Program (NIEHS) (P42)
Project #
2P42ES013661-15
Application #
9839859
Study Section
Special Emphasis Panel (ZES1)
Project Start
Project End
2025-01-31
Budget Start
2020-04-01
Budget End
2021-03-31
Support Year
15
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Iowa
Department
Type
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Parker, Victoria S; Squirewell, Edwin J; Lehmler, Hans-Joachim et al. (2018) Hydroxylated and sulfated metabolites of commonly occurring airborne polychlorinated biphenyls inhibit human steroid sulfotransferases SULT1E1 and SULT2A1. Environ Toxicol Pharmacol 58:196-201
Mattes, Timothy E; Ewald, Jessica M; Liang, Yi et al. (2018) PCB dechlorination hotspots and reductive dehalogenase genes in sediments from a contaminated wastewater lagoon. Environ Sci Pollut Res Int 25:16376-16388
Uwimana, Eric; Ruiz, Patricia; Li, Xueshu et al. (2018) HUMAN CYP2A6, CYP2B6 AND CYP2E1 ATROPSELECTIVELY METABOLIZE POLYCHLORINATED BIPHENYLS TO HYDROXYLATED METABOLITES. Environ Sci Technol :
Rodriguez, Eric A; Vanle, Brigitte C; Doorn, Jonathan A et al. (2018) Hydroxylated and sulfated metabolites of commonly observed airborne polychlorinated biphenyls display selective uptake and toxicity in N27, SH-SY5Y, and HepG2 cells. Environ Toxicol Pharmacol 62:69-78
Hou, Xingwang; Yu, Miao; Liu, Aifeng et al. (2018) Biotransformation of tetrabromobisphenol A dimethyl ether back to tetrabromobisphenol A in whole pumpkin plants. Environ Pollut 241:331-338
Xiao, Xin; Chen, Baoliang; Chen, Zaiming et al. (2018) Insight into Multiple and Multilevel Structures of Biochars and Their Potential Environmental Applications: A Critical Review. Environ Sci Technol 52:5027-5047
Herkert, Nicholas J; Jahnke, Jacob C; Hornbuckle, Keri C (2018) Emissions of Tetrachlorobiphenyls (PCBs 47, 51, and 68) from Polymer Resin on Kitchen Cabinets as a Non-Aroclor Source to Residential Air. Environ Sci Technol 52:5154-5160
P?n?íková, Kate?ina; Svržková, Lucie; Strapá?ová, Simona et al. (2018) In vitro profiling of toxic effects of prominent environmental lower-chlorinated PCB congeners linked with endocrine disruption and tumor promotion. Environ Pollut 237:473-486
P?n?íková, Kate?ina; Brenerová, Petra; Svržková, Lucie et al. (2018) Atropisomers of 2,2',3,3',6,6'-hexachlorobiphenyl (PCB 136) exhibit stereoselective effects on activation of nuclear receptors in vitro. Environ Sci Pollut Res Int 25:16411-16419
Robertson, Larry W; Weber, Roland; Nakano, Takeshi et al. (2018) PCBs risk evaluation, environmental protection, and management: 50-year research and counting for elimination by 2028. Environ Sci Pollut Res Int 25:16269-16276

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