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.

用于解决环境过程中混合物暴露问题的综合工具和模型 与紧急情况相关的污染事件 总体方案描述 与气候变化相关的灾害加上经济活动以及已经增加的脆弱性 弱势社区的灾难性化学污染事件的风险显着增加 与天气相关或人为紧急情况造成的化学品暴露的复杂性及其潜力。 不利的健康影响，需要快速、全面地评估暴露的潜在危害 复杂的混合物，保护弱势群体和生命阶段的必要性需要新颖的 该中心由一支经验丰富的科学家团队组成。 来自生物医学、地球科学、数据科学和工程学科，他们有一个共同的目标：开发、 应用并翻译一套全面的工具和模型，以帮助急救人员、受影响的人员 社区和政府机构在描述和减轻人类健康后果时 这些将适用于现有的受污染废物场和 项目 1 将为灾害相关的污染事件开发新颖的分析和计算策略。 项目 2 将开发新工具来快速表征儿科特征。 环境灾难后接触有害挥发性有机化合物会带来呼吸系统健康风险。 项目3将开发并使用胎儿-母体界面组织芯片模型来快速评估早产 项目4将继续开发定量的体外预测方法。 项目 5 对复杂混合物以及个体内和个体间的毒性差异进行了评估。 超级基金修复任务通过使用实验和计算工程来开发优化 用于有毒混合物的多组分吸附剂。灾难研究响应（DR2）核心将是一个集中化的。 灾害发生前、发生期间和发生后的环境采样和评估资源 A 数据管理。 Analysis Core将开发计算和统计工具，用于分析和整合“大数据” 环境健康风险和地理空间科学核心将为该中心提供数据和服务 描述灾害期间人类健康风险和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者合作，解决健康问题 可能受到环境紧急事件相关污染事件影响的民众的担忧。 我们将继续对学生和博士后研究员进行跨学科方法的培训 将研究成果转化为地方、州、国家和地区的决策和应急响应。 国际利益相关者涉及技术转让和定期推广。最后，管理。 该计划包括与德克萨斯农工大学管理部门和 NIEHS 资助的密切合作 转化环境健康研究中心，并由代表的顾问监督 学术界、联邦和州机构、工业界和非政府组织。

项目成果

Hurricane Recovery and Ecological Resilience: Measuring the Impacts of Wetland Alteration Post Hurricane Ike on the Upper TX Coast.

• DOI: 10.1007/s00267-017-0943-z
• 发表时间: 2017-12
• 期刊: Environmental management
• 影响因子: 3.5
• 作者: Reja MY;Brody SD;Highfield WE;Newman GD
• 通讯作者: Newman GD

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

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

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