EventsMOL2NET'16, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 2nd ed.
Published
This submission belongs to the session 04. NANOBIOMAT-02: Nanotechnology & Materials Science Congress, Jackson & Fargo, USA, 2016. of the event MOL2NET'16, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 2nd ed.
Published date
25 Jan, 2017
Citation
Natalia Sizochenko, Bakhtiyor Rasulev, Jerzy Leszczynski, Nanoparticles mutagenicity: search for matches and potential limitations of Comet assay and Ames test, in Proceedings of MOL2NET'16, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 2nd ed., 15 October–20 October 2022, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-02-03898
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Nanoparticles mutagenicity: search for matches and potential limitations of Comet assay and Ames test

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1. Department of Chemistry and Biochemistry, Interdisciplinary Center for Nanotoxicity (ICN), Jackson State University (JSU), USA
2. Department of Coatings and Polymeric Materials, North Dakota State University , Fargo, North Dakota, United States
Abstract

One of main problems of nanotoxicology is related to difficulty in selection of the most appropriate mutagenicity test. For instance, it is an open question, whether or not Ames test is relevant for nanoparticles. The major principles and mechanisms of action supposed to be different, because Ames test is based on prokaryotic responses, while other available methods are based on eukaryotic cells. Mutagenicity of 28 silica- and metal oxide nanoparticles was evaluated by means of combination of supervised and unsupervised learning techniques. Classification models were developed for mutagenicity of nanoparticles in Ames and Comet tests. Quantitative comparison of results was followed by self-organizing map modeling. Self-organizing maps were employed to find topology of a whole data set on the basis of developed classification models and known endpoints. It was found, that ionic characteristics were responsible for mutagenicity. Data visualization technique was helpful to understand specific interactions between important descriptors in different models. For series of untested NPs mutagenicity/safety were predicted.

Keywords
Nanoparticles
Ames test
Comet
classification
modeling
QSAR
toxicity
mutagenicity
Poster
summary.pdf
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