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Zeta-Potential Read-Across Model Utilizing Nanodescriptors Extracted via the NanoXtract Image Analysis Tool Available on the Enalos Nanoinformatics Cloud Platform.
Varsou, Dimitra-Danai; Afantitis, Antreas; Tsoumanis, Andreas; Papadiamantis, Anastasios; Valsami-Jones, Eugenia; Lynch, Iseult; Melagraki, Georgia.
Afiliação
  • Varsou DD; Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus.
  • Afantitis A; School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece.
  • Tsoumanis A; Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus.
  • Papadiamantis A; Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus.
  • Valsami-Jones E; School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK.
  • Lynch I; School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK.
  • Melagraki G; School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK.
Small ; 16(21): e1906588, 2020 05.
Article em En | MEDLINE | ID: mdl-32174008
Zeta potential is one of the most critical properties of nanomaterials (NMs) which provides an estimation of the surface charge, and therefore electrostatic stability in medium and, in practical terms, influences the NM's tendency to form agglomerates and to interact with cellular membranes. This paper describes a robust and accurate read-across model to predict NM zeta potential utilizing as the input data a set of image descriptors derived from transmission electron microscopy (TEM) images of the NMs. The image descriptors are calculated using NanoXtract (http://enaloscloud.novamechanics.com/EnalosWebApps/NanoXtract/), a unique online tool that generates 18 image descriptors from the TEM images, which can then be explored by modeling to identify those most predictive of NM behavior and biological effects. NM TEM images are used to develop a model for prediction of zeta potential based on grouping of the NMs according to their nearest neighbors. The model provides interesting insights regarding the most important similarity features between NMs-in addition to core composition the main elongation emerged, which links to key drivers of NM toxicity such as aspect ratio. Both the NanoXtract image analysis tool and the validated model for zeta potential (http://enaloscloud.novamechanics.com/EnalosWebApps/ZetaPotential/) are freely available online through the Enalos Nanoinformatics platform.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Small Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chipre

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Small Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chipre