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Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry

BACKGROUND: To solve current issues using big data, solve current issues related to the semiconductor and electronics industry, I tried to establish the data for each toxicity mechanism for adverse outcome pathway (AOP) for the exposure. OBJECTIVE: I planned to increase the efficiency of human hazar...

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Autor principal: Rim, Kyung-Taek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097676/
https://www.ncbi.nlm.nih.gov/pubmed/33968152
http://dx.doi.org/10.1007/s13273-021-00139-4
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author Rim, Kyung-Taek
author_facet Rim, Kyung-Taek
author_sort Rim, Kyung-Taek
collection PubMed
description BACKGROUND: To solve current issues using big data, solve current issues related to the semiconductor and electronics industry, I tried to establish the data for each toxicity mechanism for adverse outcome pathway (AOP) for the exposure. OBJECTIVE: I planned to increase the efficiency of human hazard assessment by searching, analyzing, and linking test data on the relationship between key events occurred at each level, which are the biological targets of chemicals in semiconductor manufacturing. RESULTS: It was found that 48 kinds of chemicals had 11 AOPs, while 103 chemicals had multiple AOPs, and 26 had case evidence. As a result of AOP analysis, it was found that a total of 320 chemicals had 42 AOPs, and 190 major chemicals corresponded to 11 AOPs. It was found necessary to develop a complex AOP and secure an (inhalation or dermal) exposure scenario for combined exposure at work. As a comparative search (41 out of 190 chemicals) of biomarkers specific to occupational diseases, 12 biomarkers were found to be related to breast cancer. The AOPs for 50 specific chemicals were presented, together with occupational disease-specific AOPs and key events relationship from 50 chemicals, and taxonomic classification for each AOP analysis could be found. With a comparative search, 41 out of 190 chemicals were associated with specific biomarkers for occupational diseases, and 12 mRNA or protein biomarkers were found to be related to breast cancer by cross-validation with the attached Table 24 of the Enforcement Regulations of the OSHAct and the CTD. CONCLUSION: The mechanism of occupational diseases caused by chemicals was presented, together with pathological preventions. I believe that a strategy is needed to expand the target organization for each chemical by linking with activities, such as work environment measurement, and cooperating with screening items and methods suitable for toxic chemicals, like AOP tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13273-021-00139-4.
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spelling pubmed-80976762021-05-05 Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry Rim, Kyung-Taek Mol Cell Toxicol Original Article BACKGROUND: To solve current issues using big data, solve current issues related to the semiconductor and electronics industry, I tried to establish the data for each toxicity mechanism for adverse outcome pathway (AOP) for the exposure. OBJECTIVE: I planned to increase the efficiency of human hazard assessment by searching, analyzing, and linking test data on the relationship between key events occurred at each level, which are the biological targets of chemicals in semiconductor manufacturing. RESULTS: It was found that 48 kinds of chemicals had 11 AOPs, while 103 chemicals had multiple AOPs, and 26 had case evidence. As a result of AOP analysis, it was found that a total of 320 chemicals had 42 AOPs, and 190 major chemicals corresponded to 11 AOPs. It was found necessary to develop a complex AOP and secure an (inhalation or dermal) exposure scenario for combined exposure at work. As a comparative search (41 out of 190 chemicals) of biomarkers specific to occupational diseases, 12 biomarkers were found to be related to breast cancer. The AOPs for 50 specific chemicals were presented, together with occupational disease-specific AOPs and key events relationship from 50 chemicals, and taxonomic classification for each AOP analysis could be found. With a comparative search, 41 out of 190 chemicals were associated with specific biomarkers for occupational diseases, and 12 mRNA or protein biomarkers were found to be related to breast cancer by cross-validation with the attached Table 24 of the Enforcement Regulations of the OSHAct and the CTD. CONCLUSION: The mechanism of occupational diseases caused by chemicals was presented, together with pathological preventions. I believe that a strategy is needed to expand the target organization for each chemical by linking with activities, such as work environment measurement, and cooperating with screening items and methods suitable for toxic chemicals, like AOP tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13273-021-00139-4. Springer Singapore 2021-05-05 2021 /pmc/articles/PMC8097676/ /pubmed/33968152 http://dx.doi.org/10.1007/s13273-021-00139-4 Text en © The Korean Society of Toxicogenomics and Toxicoproteomics 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Rim, Kyung-Taek
Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title_full Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title_fullStr Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title_full_unstemmed Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title_short Application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
title_sort application of the adverse outcome pathway framework to predict the toxicity of chemicals in the semiconductor manufacturing industry
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097676/
https://www.ncbi.nlm.nih.gov/pubmed/33968152
http://dx.doi.org/10.1007/s13273-021-00139-4
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