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Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra

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http://hdl.handle.net/2183/19916
Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España
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  • INIBIC-RNASA-IMEDIR - Artigos [46]
  • GI-RNASA - Artigos [156]
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Title
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
Author(s)
González-Durruthy, Michael
Monserrat, José M.
Rasulev, Bakhtiyor
Casañola-Martín, Gerardo M.
Barreiro Sorrivas, José María
Paraíso-Medina, Sergio
Maojo, Víctor
González-Díaz, Humberto
Pazos, A.
Munteanu, Cristian-Robert
Date
2017-11-11
Citation
González-Durruthy M, Monserrat JM, Rasulev B, et al. Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra. Nanomaterials (Basel). 2017;7(11):386
Abstract
[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first time and they are based on CNT Raman spectra star graph transform (spectral moments) and perturbation theory. The experimental measures of Jm showed that no tested CNT family can inhibit the oxygen consumption profiles of mitochondria. The best model for the prediction of Jm for other CNTs was provided by random forest using eight features, obtaining test R-squared (R2) of 0.863 and test root-mean-square error (RMSE) of 0.0461. The results demonstrate the capability of encoding CNT information into spectral moments of the Raman star graphs (SG) transform with a potential applicability as predictive tools in nanotechnology and material risk assessments.
Keywords
Carbon nanotubes
Cytotoxicity
Mitochondria oxygen mass flux
Raman spectroscopy
Graph theory
Spectral moments
 
Editor version
http://dx.doi.org/10.3390/nano7110386
Rights
Atribución 3.0 España
ISSN
2079-4991

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