Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform

Research output: Contribution to journalArticlepeer-review

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Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform. / Papadiamantis, Anastasios G; Jänes, Jaak; Voyiatzis, Evangelos; Sikk, Lauri; Burk, Jaanus; Burk, Peeter; Tsoumanis, Andreas; Ha, My Kieu; Yoon, Tae Hyun; Valsami-Jones, Eugenia; Lynch, Iseult; Melagraki, Georgia; Tämm, Kaido; Afantitis, Antreas.

In: Nanomaterials, Vol. 10, No. 10, 2017, 13.10.2020, p. 1-19.

Research output: Contribution to journalArticlepeer-review

Harvard

Papadiamantis, AG, Jänes, J, Voyiatzis, E, Sikk, L, Burk, J, Burk, P, Tsoumanis, A, Ha, MK, Yoon, TH, Valsami-Jones, E, Lynch, I, Melagraki, G, Tämm, K & Afantitis, A 2020, 'Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform', Nanomaterials, vol. 10, no. 10, 2017, pp. 1-19. https://doi.org/10.3390/nano10102017

APA

Papadiamantis, A. G., Jänes, J., Voyiatzis, E., Sikk, L., Burk, J., Burk, P., Tsoumanis, A., Ha, M. K., Yoon, T. H., Valsami-Jones, E., Lynch, I., Melagraki, G., Tämm, K., & Afantitis, A. (2020). Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform. Nanomaterials, 10(10), 1-19. [2017]. https://doi.org/10.3390/nano10102017

Vancouver

Author

Papadiamantis, Anastasios G ; Jänes, Jaak ; Voyiatzis, Evangelos ; Sikk, Lauri ; Burk, Jaanus ; Burk, Peeter ; Tsoumanis, Andreas ; Ha, My Kieu ; Yoon, Tae Hyun ; Valsami-Jones, Eugenia ; Lynch, Iseult ; Melagraki, Georgia ; Tämm, Kaido ; Afantitis, Antreas. / Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform. In: Nanomaterials. 2020 ; Vol. 10, No. 10. pp. 1-19.

Bibtex

@article{4e1b3bbca3064602812dfd1c823579b6,
title = "Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform",
abstract = "A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).",
keywords = "Atomistic descriptors, Computational descriptors, Cytotoxicity, In silico modelling, Isalos analytics platform, Machine learning, Metal oxide nanoparticles",
author = "Papadiamantis, {Anastasios G} and Jaak J{\"a}nes and Evangelos Voyiatzis and Lauri Sikk and Jaanus Burk and Peeter Burk and Andreas Tsoumanis and Ha, {My Kieu} and Yoon, {Tae Hyun} and Eugenia Valsami-Jones and Iseult Lynch and Georgia Melagraki and Kaido T{\"a}mm and Antreas Afantitis",
year = "2020",
month = oct,
day = "13",
doi = "10.3390/nano10102017",
language = "English",
volume = "10",
pages = "1--19",
journal = "Nanomaterials",
issn = "2079-4991",
publisher = "MDPI",
number = "10",

}

RIS

TY - JOUR

T1 - Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform

AU - Papadiamantis, Anastasios G

AU - Jänes, Jaak

AU - Voyiatzis, Evangelos

AU - Sikk, Lauri

AU - Burk, Jaanus

AU - Burk, Peeter

AU - Tsoumanis, Andreas

AU - Ha, My Kieu

AU - Yoon, Tae Hyun

AU - Valsami-Jones, Eugenia

AU - Lynch, Iseult

AU - Melagraki, Georgia

AU - Tämm, Kaido

AU - Afantitis, Antreas

PY - 2020/10/13

Y1 - 2020/10/13

N2 - A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).

AB - A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).

KW - Atomistic descriptors

KW - Computational descriptors

KW - Cytotoxicity

KW - In silico modelling

KW - Isalos analytics platform

KW - Machine learning

KW - Metal oxide nanoparticles

UR - http://www.scopus.com/inward/record.url?scp=85092522232&partnerID=8YFLogxK

U2 - 10.3390/nano10102017

DO - 10.3390/nano10102017

M3 - Article

C2 - 33066094

VL - 10

SP - 1

EP - 19

JO - Nanomaterials

JF - Nanomaterials

SN - 2079-4991

IS - 10

M1 - 2017

ER -