确定环境疾病与环境因素之间关系的毒理学研究系统综述

Yujin Ka, Kyunghee Ji
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摘要

背景:众所周知,环境疾病的发生与长期暴露于有毒化学物质有关,包括水媒污染物、空气/室内污染物、石棉、加湿器消毒剂中的成分等。目的:在本研究中,我们回顾了与韩国环境卫生法定义的环境疾病和有毒化学品相关的毒理学研究。并提出了今后环境疾病防治所必需的毒理学研究方向。方法:通过PubMed和Web of Science对以往环境疾病相关研究趋势进行调查。详细回顾了与加湿器消毒剂有关的毒理学研究。我们确定了与诱发环境疾病相关的不良结果通路(AOPs),并提出了一种化学筛选系统,该系统使用AOP、化学毒性大数据和深度学习模型来选择诱发环境疾病的化学物质。结果:对化学品毒性的研究每年都在增加,但在揭示接触化学品与环境疾病发生之间的明确因果关系方面存在局限性。有必要开发各种与疾病发生相关的暴露和效应生物标志物,并进行毒性动力学研究。一种使用AOP和化学毒性大数据的新型化学筛选系统可能有助于选择导致环境疾病的化学物质。结论:从毒理学的角度来看,开发与环境疾病相关的AOP和基于深度学习的化学筛选系统将有助于提前预防环境疾病。
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A Systematic Review of Toxicological Studies to Identify the Association between Environmental Diseases and Environmental Factors
ABSTRACT Background: The occurrence of environmental disease is known to be associated with chronic exposure to toxic chemicals, including waterborne contaminants, air/indoor pollutants, asbestos, ingredients in humidifier disinfectants, etc. Objectives: In this study, we reviewed toxicological studies related to environmental disease as defined by the Environmental Health Act in Korea and toxic chemicals. We also suggested a direction for future toxicological research necessary for the prevention and management of environmental disease. Methods: Trends in previous studies related to environmental disease were investigated through PubMed and Web of Science. A detailed review was provided on toxicological studies related to the humidifier disinfectants. We identified adverse outcome pathways (AOPs) that can be linked to the induction of environmental diseases, and proposed a chemical screening system that uses AOP, chemical toxicity big data, and deep learning models to select chemicals that induce environmental disease. Results: Research on chemical toxicity is increasing every year, but there is a limitation to revealing a clear causal relationship between exposure to chemicals and the occurrence of environmental disease. It is necessary to develop various exposure- and effect-biomarkers related to disease occurrence and to conduct toxicokinetic studies. A novel chemical screening system that uses AOP and chemical toxicity big data could be useful for selecting chemicals that cause environmental diseases. Conclusions: From a toxicological point of view, developing AOP related to environmental diseases and a deep learning-based chemical screening system will contribute to the prevention of environmental diseases in advance.
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