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个项目摘要 有证据表明，接触超级基金化学物质会导致不良妊娠结局（APO），包括 早产（PTB）。波多黎各（PR）中PTB和婴儿死亡率的发生率是美国所有州中最高的 领土。 PR中有18个超级基金地点，饮用水污染的证据很广泛。而且， 极端天气事件（飓风，流量）可能导致超级基金化学物质的暴露率升高。保护 中心将东北大学的研究人员聚集在一起，佐治亚大学波多黎各大学， 密歇根大学为了对关系和机制提供急需的理解 接触可疑化学物质会导致APO，并开发新方法以降低PR及其他地区的风险。 为此，保护使用源结构结构，整合流行病学，毒理学，命运和运输， 以及修复研究，统一的采样基础架构，集中式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，Protect已建立了有关环境条件和产前的详细且广泛的数据集 怀孕母亲的状况（暴露，社会经济和健康数据 - 每次参与2400多个数据点 - iipant），产生了从2000多个准妈妈及其子女组成的同类中收集的丰富数据集。保护 数据管理和分析核心（DMAC）在整个中心中心管理数据，同时提供两个分析 支持评估定量和定性数据。 DMAC为此提供了一组全面的数据字典 数据集并开发了用于正确处理敏感数据的协议。 保护数据库有可能帮助解锁可以将环境因素与早产联系起来的关系 出生结果。该数据集旨在利用强大的AI/ML工具集来帮助识别和建立这些关系。 但是，在我们开始利用这些强大的工具之前，必须克服特殊的挑战才能准备数据。这些 挑战包括我们数据集中缺少数据的程度以及我们数据中的继承类不平衡。这个项目将 解决这些问题的问题，并利用通过举行一系列探索的黑客马拉松发展的反馈和经验 这些数据集。结果应该是生产一套准备AI/ML工具的数据集，并提供多个数据集 新的开源工具集解决数据中的失误和失​​衡。