Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) - Admin Supplement

波多黎各探索污染威胁测试站 (PROTECT) - 管理补充

• 批准号: 10411854
• 负责人: Akram N Alshawabkeh
• 金额: --
• 依托单位: NORTHEASTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10411854
• 关键词: Address; Chemicals; Child; Data; Data Analytics; Data Management Resources; Data Set; Databases; Development; Environmental Exposure; Environmental Risk Factor; Epidemiology; Event; Exposure to; Feedback; Floods; Geographic state; Head; Health; Hurricane; Individual; Infant Mortality; Infrastructure; Methodology; Methods; Michigan; National Institute of Environmental Health Sciences; Outcome; Participant; Pregnant Women; Premature Birth; Premature Infant; Production; Protocols documentation; Puerto Rico; Research Personnel; Risk; Sampling; Series; Source; Structure; Toxicology; Universities; adverse birth outcomes; adverse pregnancy outcome; cohort; contaminated drinking water; data dictionary; data dissemination; data management; data repository; demographics; experience; extreme weather; hackathon; health data; indexing; open source; prenatal; remediation; socioeconomics; superfund chemical; superfund site; tool

1 Project Summary Evidence suggests that exposure to Superfund chemicals contributes to adverse pregnancy outcomes (APOs), including preterm birth (PTB). Rates of PTB and infant mortality in Puerto Rico (PR) are among the highest of all US states and territories. There are 18 Superfund sites in PR, and evidence of contamination of the drinking water is extensive. Moreover, extreme weather events (hurricanes, flooding) may result in elevated exposures to Superfund chemicals. The PROTECT center has brought together researchers from Northeastern University, the University of Puerto Rico, University of Georgia, and the University of Michigan to provide much needed understanding of the relationship and the mechanisms by which exposure to suspect chemicals contribute to APOs, and to develop new methods to reduce risk of exposure in PR and beyond. To do this, PROTECT uses a source-to-outcome structure, integrating epidemiological, toxicological, fate and transport, and remediation studies, a unified sampling infrastructure, a centralized indexed data repository, and a sophisticated data management system. Since its inception in 2010, PROTECT has built detailed and extensive datasets on environmental conditions and prenatal conditions of pregnant mothers (exposure, socioeconomic and health data–close to more than 2400 data points per partic- ipant), yielding a rich dataset collected from a cohort of over 2000 expectant mothers and their children. The PROTECT Data Management and Analytics Core (DMAC) manages data centrally for the entire Center, while providing both analytics support to evaluate quantitative and qualitative data. The DMAC provides a comprehensive set of Data Dictionaries for this dataset and developed protocols for proper handling of sensitive data. The PROTECT database has the potential to help unlock the relationships that can tie environmental factors to preterm birth outcomes. The dataset is primed to leverage powerful AI/ML toolsets to help identify and establish these relationships. But before we can start leveraging these powerful tools, specific challenges must be overcome to prepare the data. These challenges include the degree of missing data in our dataset, and the inherent class imbalance in our data. This project will address these issues head on, and utilize feedback and experience developed through hold a series of hackathons that explore these datasets. The result should be the production of a suite of datasets ready for AI/ML tools, and the delivery a number of new open source toolsets to addressing missingness and imbalance in data.

1项目概要 有证据表明，接触超级基金化学品会导致不良妊娠结局，包括 早产（PTB）。波多黎各（PR）的PTB和婴儿死亡率是美国所有州中最高的， 领土PR有18个超级基金站点，饮用水污染的证据广泛。此外，委员会认为， 极端天气事件（飓风、暴雨）可能导致超级基金化学品暴露量增加。受保护 该中心汇集了来自东北大学、波多黎各大学、格鲁吉亚大学 和密歇根大学提供急需的关系和机制的理解， 暴露于可疑化学品会导致APO，并开发新的方法来降低PR及其他地区的暴露风险。 为了做到这一点，可持续发展技术采用了一种从源头到结果的结构，将流行病学、毒理学、归宿和运输结合在一起， 和补救研究，统一的艾德采样基础设施，集中的索引数据存储库，以及复杂的数据 管理系统. 自2010年成立以来，CRTT已经建立了详细而广泛的环境条件和产前数据集， 怀孕母亲的状况（接触、社会经济和健康数据-接近每个人2400多个数据点， ipant），从2000多名孕妇及其子女的队列中收集了丰富的数据集。受保护 数据管理和分析核心（DMAC）集中管理整个中心的数据，同时提供分析 支持评估定量和定性数据。DMAC为此提供了一套全面的数据字典 数据集，并制定了适当处理敏感数据的协议。 BACT数据库有可能帮助解开环境因素与早产之间的关系 出生结果。该数据集准备利用强大的AI/ML工具集来帮助识别和建立这些关系。 但在我们开始利用这些强大的工具之前，必须克服特定的挑战来准备数据。这些 挑战包括数据集中缺失数据的程度，以及数据中固有的类不平衡。该项目将 正面解决这些问题，并利用通过举办一系列黑客马拉松获得的反馈和经验， 这些数据集。其结果应该是为AI/ML工具准备一套数据集的生产，以及交付一些 新的开源工具集，以解决数据的缺失和不平衡。