The 3D reconstructed skin micronucleus assay using imaging flow cytometry and deep learning: A proof-of-principle investigation.
Artificial Intelligence
Automation, Laboratory
/ instrumentation
Deep Learning
False Positive Reactions
Feasibility Studies
Flow Cytometry
/ instrumentation
Humans
Image Processing, Computer-Assisted
/ instrumentation
Micronucleus Tests
/ instrumentation
Mitomycin
/ toxicity
Models, Biological
Mutagenicity Tests
/ instrumentation
Predictive Value of Tests
Proof of Concept Study
Skin
/ diagnostic imaging
Skin, Artificial
Software
Tissue Scaffolds
Genotoxicity
Human skin model
ImageStream
Journal
Mutation research. Genetic toxicology and environmental mutagenesis
ISSN: 1879-3592
Titre abrégé: Mutat Res Genet Toxicol Environ Mutagen
Pays: Netherlands
ID NLM: 101632149
Informations de publication
Date de publication:
May 2021
May 2021
Historique:
received:
25
09
2020
revised:
13
01
2021
accepted:
18
01
2021
entrez:
18
4
2021
pubmed:
19
4
2021
medline:
20
5
2021
Statut:
ppublish
Résumé
The reconstructed skin micronucleus (RSMN) assay was developed in 2006, as an in vitro alternative for genotoxicity evaluation of dermally applied chemicals or products. In the years since, significant progress has been made in the optimization of the assay, including publication of a standard protocol and extensive validation. However, the diverse morphology of skin cells makes cell preparation and scoring of micronuclei (MN) tedious and subjective, thus requiring a high level of technical expertise for evaluation. This ultimately has a negative impact on throughput and the assay would benefit by the development of an automated method which could reduce scoring subjectivity while also improving the robustness of the assay by increasing the number of cells that can be scored. Imaging flow cytometry (IFC) with the ImageStream
Identifiants
pubmed: 33865536
pii: S1383-5718(21)00005-X
doi: 10.1016/j.mrgentox.2021.503314
pii:
doi:
Substances chimiques
Mitomycin
50SG953SK6
Types de publication
Evaluation Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
503314Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.