Zeta-Potential Read-Across Model Utilizing Nanodescriptors Extracted via the NanoXtract Image Analysis Tool Available on the Enalos Nanoinformatics Cloud Platform.
image nanodescriptors
nanoinformatics
read-across
zeta potential
Journal
Small (Weinheim an der Bergstrasse, Germany)
ISSN: 1613-6829
Titre abrégé: Small
Pays: Germany
ID NLM: 101235338
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
received:
13
11
2019
revised:
07
02
2020
pubmed:
17
3
2020
medline:
17
3
2020
entrez:
17
3
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32174008
doi: 10.1002/smll.201906588
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1906588Informations de copyright
© 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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