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Surface-Related Features Responsible for Cytotoxic Behavior of MXenes Layered Materials Predicted with Machine Learning Approach

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cris.lastimport.scopus2024-02-12T19:47:07Z
dc.abstract.enTo speed up the implementation of the two-dimensional materials in the development of potential biomedical applications, the toxicological aspects toward human health need to be addressed. Due to time-consuming and expensive analysis, only part of the continuously expanding family of 2D materials can be tested in vitro. The machine learning methods can be used—by extracting new insights from available biological data sets, and provide further guidance for experimental studies. This study identifies the most relevant highly surface-specific features that might be responsible for cytotoxic behavior of 2D materials, especially MXenes. In particular, two factors, namely, the presence of transition metal oxides and lithium atoms on the surface, are identified as cytotoxicity-generating features. The developed machine learning model succeeds in predicting toxicity for other 2D MXenes, previously not tested in vitro, and hence, is able to complement the existing knowledge coming from in vitro studies. Thus, we claim that it might be one of the solutions for reducing the number of toxicological studies needed, and allows for minimizing failures in future biological applications.
dc.affiliationUniwersytet Warszawski
dc.contributor.authorJastrzębska, Agnieszka M.
dc.contributor.authorMarchwiany, Maciej E.
dc.contributor.authorPopielska, Magdalena
dc.contributor.authorPopielski, Mariusz
dc.contributor.authorMajewski, Jacek
dc.contributor.authorJastrzębska, Agnieszka
dc.date.accessioned2024-01-26T09:25:03Z
dc.date.available2024-01-26T09:25:03Z
dc.date.copyright2020-07-10
dc.date.issued2020
dc.description.accesstimeAT_PUBLICATION
dc.description.financeŚrodki finansowe przyznane na realizację projektu w zakresie badań naukowych lub prac rozwojowych
dc.description.number14
dc.description.versionFINAL_PUBLISHED
dc.description.volume13
dc.identifier.doi10.3390/MA13143083
dc.identifier.issn1996-1944
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/121174
dc.identifier.weblinkhttps://www.mdpi.com/1996-1944/13/14/3083/pdf
dc.languageeng
dc.pbn.affiliationphysical sciences
dc.relation.ispartofMaterials
dc.relation.pages1-17
dc.rightsCC-BY
dc.sciencecloudnosend
dc.subject.enmachine learning
dc.subject.enMXenes
dc.subject.encytotoxicity
dc.subject.envan der Waals layered materials
dc.titleSurface-Related Features Responsible for Cytotoxic Behavior of MXenes Layered Materials Predicted with Machine Learning Approach
dc.typeJournalArticle
dspace.entity.typePublication