Comprehensive tools and models for addressing exposure to mixtures during environmental emergency-related contamination events

用于解决环境紧急事件相关污染事件期间混合物暴露问题的综合工具和模型

• 批准号: 10707432
• 负责人: Ivan Rusyn
• 金额: $ 181.56万
• 依托单位: TEXAS A&M UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707432
• 关键词: Academia; Acute; Address; Air Pollutants; Analytical Chemistry; Area; Attention; Basic Science; Benchmarking; Big Data; Chemical Exposure; Chemicals; Chemistry; Childhood; Communities; Complex; Complex Mixtures; Computer Models; Coupled; Data; Data Analyses; Data Engineering; Data Science; Decision Making; Development; Disasters; Discipline; Dose; Economics; Education; Emergency Situation; Emergency response; Engineering; Environmental Health; Environmental Impact; Evaluation; Event; Experimental Models; Exposure to; Faculty; First Aid; Funding; Geographic Distribution; Geoscience; Goals; Government Agencies; Hazardous Chemicals; Hazardous Substances; Hazardous Waste Sites; Health; Health Hazards; Human; In Vitro; Individual; Industry; Infrastructure; International; Intervention; Lead; Life; Methods; Modeling; Modernization; National Institute of Environmental Health Sciences; Nongovernmental Organizations; North Carolina; Pathway interactions; Population; Population Growth; Postdoctoral Fellow; Predisposition; Pregnancy; Premature Birth; Prevention; Program Description; Public Health; Quantitative Evaluations; Readiness; Recovery; Reproducibility; Research; Resources; Risk; Risk Assessment; Sampling; Science; Scientist; Services; Site; Soil; Students; Superfund; Techniques; Technology Transfer; Testing; Texas; Time; Tissue Microarray; Toxic effect; Training; Translating; Translational Research; Universities; University adminstration; Vulnerable Populations; Water; Weather; Work; adverse outcome; air sampling; anthropogenesis; biomedical scientist; climate change; community engagement; community organizations; cost; data analysis pipeline; data management; disaster resilience; experience; first responder; hazard; inter-individual variation; interdisciplinary approach; land use; multidisciplinary; neighborhood disadvantage; next generation; novel; novel strategies; outreach; programs; promote resilience; rapid detection; rapid technique; remediation; respiratory health; response; skills; socioeconomic disparity; student training; support tools; tool; volatile organic compound; wasting

Comprehensive tools and models for addressing exposure to mixtures during environmental emergency-related contamination events Overall Program Description Climate change-associated disasters coupled with economic activity and the enhanced vulnerability of already disadvantaged communities markedly increase risks from catastrophic chemical contamination events resulting from weather-related or anthropogenic emergencies. The complexities of chemical exposures and their potential adverse health impacts, the need to rapidly and comprehensively evaluate the potential hazards of exposures to complex mixtures, and the necessity of protecting vulnerable populations and life-stages call for novel approaches in the Superfund Research Program. This Center consists of a team of well-established scientists from biomedical, geosciences, data science, and engineering disciplines who share a common goal: to develop, apply, and translate a comprehensive set of tools and models that will aid first responders, impacted communities, and government agencies in characterizing and mitigating the human health consequences of exposure to hazardous mixtures. These will be applicable for both existing contaminated waste sites and disaster-related contamination events. Project 1 will develop novel analytical and computational strategies for exposure assessment of complex mixtures. Project 2 will develop novel tools to rapidly characterize pediatric respiratory health risks from exposure to hazardous volatile organic compounds after environmental disasters. Project 3 will develop and use feto-maternal interface tissue chip models for rapid assessment of preterm birth risks of hazardous substances. Project 4 will continue development of predictive in vitro methods for quantitative evaluation of the complex mixtures and intra- and inter-individual variability in toxicity. Project 5 is responsive to the Superfund remediation mandate by using experimental and computational engineering to develop optimized multi-component sorbents for toxic mixtures. A Disaster Research Response (DR2) Core will be a centralized resource for environmental sampling and assessment before, during, and after disasters. A Data Management and Analysis Core will develop computational and statistical tools for analysis and integration of “big data” in environmental health. A Risk and Geospatial Science Core will provide the Center with data and services for characterizing human health risks and the geographic distribution of hazardous substances during disasters. The Center will engage with community organizations and public health practitioners in Texas to address health concerns of the populations that may be impacted by environmental emergency-related contamination events. We will continue training students and postdoctoral fellows in inter-disciplinary approaches across our scientific areas, decision making and emergency response. The research translation to local, state, national and international stakeholders involves both technology transfer and regular outreach. Finally, the management of this program includes close partnerships with the Texas A&M University administration and the NIEHS-funded Center for Translational Environmental Health Research, and is overseen by the advisors representing academia, federal and state agencies, industry and a non-governmental organization.

综合工具和模型，以解决环境中的混合物暴露 紧急污染事件 总体程序描述 气候变化相关的灾难以及经济活动以及已经增强的脆弱性 处境不利的社区显着增加了导致灾难性化学污染事件的风险 来自与天气有关的或人为的紧急情况。化学暴露及其潜力的复杂性 不利的健康影响，需要快速，全面评估暴露的潜在危害 复杂的混合物，必要的保护脆弱的人群和生命阶段需要新颖 超级基金研究计划的方法。该中心由一组成熟的科学家组成 来自生物医学，地球科学，数据科学和工程学科，共有共同的目标：发展，发展 应用并翻译一套全面的工具和模型，这些工具和模型将有助于急救人员 社区和政府机构在表征和减轻人类健康后果的影响 暴露于危险混合物中。这些适用于现有的被污染的废物站点和 与灾难有关的污染事件。项目1将制定新颖的分析和计算策略 复杂混合物的暴露评估。项目2将开发新颖的工具来快速描述小儿 环境灾难后暴露于危险挥发性有机化合物中的呼吸健康风险。 项目3将开发和使用Feto-Matnal界面组织芯片模型，以快速评估早产 有危险物质的风险。项目4将继续开发定量预测性体外方法 评估复合物混合物以及毒性内和个体间变异性的评估。项目5对 通过使用实验和计算工程来开发优化的超级基金补救任务 用于有毒混合物的多组分吸附剂。灾难研究反应（DR2）核心将是集中的 灾难之前，期间和之后的环境抽样和评估资源。数据管理 分析核心将开发用于分析和集成“大数据”的计算和统计工具 环境健康。风险和地理空间科学核心将为中心提供数据和服务 表征人类健康风险和灾难中有害物质的地理分布。 该中心将与德克萨斯州的社区组织和公共卫生从业人员互动以解决健康 可能会受到环境紧急污染事件影响的人群的关注。 我们将继续培训学生和博士后研究员，以跨学科的方法进行我们的科学培训 区域，决策和紧急响应。研究转化为地方，州，国家和 国际利益相关者涉及技术转移和定期推广。最后，管理 该计划包括与德克萨斯A＆M大学管理和NIEHS资助的密切合作伙伴关系 转化环境健康研究中心，由代表的顾问监督 学术界，联邦和州机构，工业以及非政府组织。

项目成果

Risk Characterization and Probabilistic Concentration-Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays.

• DOI: 10.1289/ehp7600
• 发表时间: 2021-01
• 期刊: Environmental health perspectives
• 影响因子: 10.4
• 作者: Hsieh NH;Chen Z;Rusyn I;Chiu WA
• 通讯作者: Chiu WA

Integrating a Resilience Scorecard and Landscape Performance into a Geodesign Process.

将弹性记分卡和景观性能整合到地理设计过程中。

• DOI: 10.1080/01426397.2019.1569219
• 发表时间: 2020
• 期刊: Landscape research
• 影响因子: 1.8
• 作者: Newman,Galen;Malecha,Matthew;Yu,Siyu;Qiao,Zixu;Horney,Jennifer;Lee,Jaekyung;Kim,You-Jung;Lee,RyunJ;Berke,Philip
• 通讯作者: Berke,Philip

Quantitative In Vitro-to-In Vivo Extrapolation for Mixtures: A Case Study of Superfund Priority List Pesticides.

混合物的体外到体内定量外推：超级基金优先清单农药的案例研究。

• DOI: 10.1093/toxsci/kfab076
• 发表时间: 2021
• 期刊: Toxicological sciences : an official journal of the Society of Toxicology
• 作者: Valdiviezo,Alan;Luo,Yu-Syuan;Chen,Zunwei;Chiu,WeihsuehA;Rusyn,Ivan
• 通讯作者: Rusyn,Ivan

Binary Classification of the Endocrine Disrupting Chemicals by Artificial Neural Networks.

通过人工神经网络对内分泌干扰化学品进行二元分类。

• DOI: 10.1016/b978-0-443-15274-0.50418-2
• 发表时间: 2023
• 期刊: ESCAPE. European Symposium on Computer Aided Process Engineering
• 作者: Aghayev,Zahir;Walker,GeorgeF;Iseri,Funda;Ali,Moustafa;Szafran,AdamT;Stossi,Fabio;Mancini,MichaelA;Pistikopoulos,EfstratiosN;Beykal,Burcu
• 通讯作者: Beykal,Burcu

Resilience through Regeneration: The economics of repurposing vacant land with green infrastructure.

• DOI: 10.15302/j-laf-20180602
• 发表时间: 2019
• 期刊: Landscape architecture frontiers
• 影响因子: 0.7
• 作者: Galen D. Newman;L. Dongying;Zhu Rui;Ren Dingding