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A novel approach for a toxicity prediction model of environmental pollutants
A novel approach for a toxicity prediction model of environmental pollutants
環境汚染物質の毒性予測のための新規アプローチ
Hosoya, Junichi
There are myriad environmental pollutants on the earth, and a large amount of new environmental pollutants may be produced in future. The identification of newly emerging pollutants predicted from limited information is important in human health risk management. From the viewpoints of cost and ethics, development of two effective approaches, instead of the conventional animal experiment, is expected. One is toxicogenomics, representing the DNA microarray analysis; and the other is in silico approaches based on the quantitative structure-activity relationship (QSAR). Toxicogenomics has been widely used for sensitively and quickly elucidating the molecular and cellular actions of chemicals and other environmental stressors resulting in biological damage. QSAR is a potential tool for predicting the activity and properties of chemicals, including their physicochemical attributes, health effects, ecotoxicity, and biological activity. In this study, I attempted to develop new and efficient toxicity prediction models for the myriad environmental pollutants including those in automobile emissions. Toward this goal, I tried to combine toxicogenomics with QSAR. 64 chemicals/particulates detected in automobile emissions were selected; and the DNA microarray method was used to examine their effect on gene expression in human lung cells. The results showed that the expression of various genes was altered in cells exposed to PAHs, nitroarenes or quinones. Furthermore, these 64 chemicals/particulates were divided into some groups reflecting the physicochemical characteristics of these compounds by using hierarchical clustering analysis of the gene expression data. Then, IL-8, as a well-known proinflammatory cytokine involved in allergic inflammation induced by automobile emissions, was selected to develop an in silico prediction model by utilizing the QSAR for IL-8 gene expression. Furthermore, I validated the prediction model according to known data from previous reports. As a result, this prediction model showed high accuracy in predicting up-regulation of the IL-8 gene. These results suggest that the prediction model using QSAR based on the gene expression from toxicogenomics may have great potential in predictive toxicology of environmental pollutants.
新潟大学大学院自然科学研究科
平成24年3月23日
新大院博(理)甲第348号
新大院博(理)甲第348号
新潟大学
2012-03-23
eng
thesis
http://hdl.handle.net/10191/20787
https://niigata-u.repo.nii.ac.jp/records/5305
1
48
13101甲第3647号
博士(理学)
2012-03-23
新潟大学
https://niigata-u.repo.nii.ac.jp/record/5305/files/D_S_R_K348.pdf
application/pdf
4.2 MB
2019-08-05