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Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform.

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Title: Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform.
Authors: Papadiamantis, Anastasios G.1,2 (AUTHOR) E.ValsamiJones@bham.ac.uk, Jänes, Jaak3 (AUTHOR) jaak.janes@ut.ee, Voyiatzis, Evangelos1 (AUTHOR) Voyiatzis@novamechanics.com, Sikk, Lauri3 (AUTHOR) laurisikk@gmail.com, Burk, Jaanus3 (AUTHOR) jaanus.burk@ut.ee, Burk, Peeter3 (AUTHOR) peeter.burk@ut.ee, Tsoumanis, Andreas1 (AUTHOR) tsoumanis@novamechanics.com, Ha, My Kieu4 (AUTHOR) hakieumy12@gmail.com, Yoon, Tae Hyun4,5 (AUTHOR) taeyoon@hanyang.ac.kr, Valsami-Jones, Eugenia2 (AUTHOR) i.lynch@bham.ac.uk, Lynch, Iseult2 (AUTHOR), Melagraki, Georgia6 (AUTHOR) georgiamelagraki@gmail.com, Tämm, Kaido3 (AUTHOR) karu@ut.ee, Afantitis, Antreas1 (AUTHOR) karu@ut.ee
Source: Nanomaterials (2079-4991). Oct2020, Vol. 10 Issue 10, p2017. 1p.
Subjects: Metal nanoparticles, Lactate dehydrogenase, Conduction bands, Adenosine triphosphate, Exposure dose, Metallic oxides, Cell membranes
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). [ABSTRACT FROM AUTHOR]
Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform.
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  Data: <searchLink fieldCode="AR" term="%22Papadiamantis%2C+Anastasios+G%2E%22">Papadiamantis, Anastasios G.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> E.ValsamiJones@bham.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Jänes%2C+Jaak%22">Jänes, Jaak</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> jaak.janes@ut.ee</i><br /><searchLink fieldCode="AR" term="%22Voyiatzis%2C+Evangelos%22">Voyiatzis, Evangelos</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> Voyiatzis@novamechanics.com</i><br /><searchLink fieldCode="AR" term="%22Sikk%2C+Lauri%22">Sikk, Lauri</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> laurisikk@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Burk%2C+Jaanus%22">Burk, Jaanus</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> jaanus.burk@ut.ee</i><br /><searchLink fieldCode="AR" term="%22Burk%2C+Peeter%22">Burk, Peeter</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> peeter.burk@ut.ee</i><br /><searchLink fieldCode="AR" term="%22Tsoumanis%2C+Andreas%22">Tsoumanis, Andreas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> tsoumanis@novamechanics.com</i><br /><searchLink fieldCode="AR" term="%22Ha%2C+My+Kieu%22">Ha, My Kieu</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> hakieumy12@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Yoon%2C+Tae+Hyun%22">Yoon, Tae Hyun</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<i> taeyoon@hanyang.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Valsami-Jones%2C+Eugenia%22">Valsami-Jones, Eugenia</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> i.lynch@bham.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Lynch%2C+Iseult%22">Lynch, Iseult</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Melagraki%2C+Georgia%22">Melagraki, Georgia</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> georgiamelagraki@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Tämm%2C+Kaido%22">Tämm, Kaido</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> karu@ut.ee</i><br /><searchLink fieldCode="AR" term="%22Afantitis%2C+Antreas%22">Afantitis, Antreas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> karu@ut.ee</i>
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  Data: <searchLink fieldCode="JN" term="%22Nanomaterials+%282079-4991%29%22">Nanomaterials (2079-4991)</searchLink>. Oct2020, Vol. 10 Issue 10, p2017. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Metal+nanoparticles%22">Metal nanoparticles</searchLink><br /><searchLink fieldCode="DE" term="%22Lactate+dehydrogenase%22">Lactate dehydrogenase</searchLink><br /><searchLink fieldCode="DE" term="%22Conduction+bands%22">Conduction bands</searchLink><br /><searchLink fieldCode="DE" term="%22Adenosine+triphosphate%22">Adenosine triphosphate</searchLink><br /><searchLink fieldCode="DE" term="%22Exposure+dose%22">Exposure dose</searchLink><br /><searchLink fieldCode="DE" term="%22Metallic+oxides%22">Metallic oxides</searchLink><br /><searchLink fieldCode="DE" term="%22Cell+membranes%22">Cell membranes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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). [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/nano10102017
    Languages:
      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: 2017
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      – SubjectFull: Metal nanoparticles
        Type: general
      – SubjectFull: Lactate dehydrogenase
        Type: general
      – SubjectFull: Conduction bands
        Type: general
      – SubjectFull: Adenosine triphosphate
        Type: general
      – SubjectFull: Exposure dose
        Type: general
      – SubjectFull: Metallic oxides
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      – SubjectFull: Cell membranes
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      – TitleFull: Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform.
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              Text: Oct2020
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