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Nanomaterials 2017, 7(11), 386; https://doi.org/10.3390/nano7110386

Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra

1
Institute of Biological Science (ICB), Federal University of Rio Grande, Rio Grande, RS 96270-900, Brazil
2
Department of Coatings and Polymeric Materials, North Dakota State University (NDSU), Fargo, ND 58102, USA
3
Department of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
4
Computer Science School (ETSIINF), Polytechnic University of Madrid (UPM), Calle de losCiruelos, Boadilla del Monte, 28660 Madrid, Spain
5
Biomedical Informatics Group, Artificial Intelligence Department, Polytechnic University of Madrid, Calle de los Ciruelos, Boadilla del Monte, 28660 Madrid, Spain
6
Department of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940 Leioa, Biscay, Spain
7
IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Biscay, Spain
8
INIBIC Institute of Biomedical Research, CHUAC, UDC, 15006 Coruña, Spain
9
RNASA-IMEDIR, Computer Sciences Faculty, University of Coruña, 15071 Coruña, Spain
*
Authors to whom correspondence should be addressed.
Received: 7 October 2017 / Revised: 6 November 2017 / Accepted: 8 November 2017 / Published: 11 November 2017
(This article belongs to the Special Issue Experimental Nanosciences, Computational Chemistry, and Data Analysis)
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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. View Full-Text
Keywords: carbon nanotubes; cytotoxicity; mitochondria oxygen mass flux; Raman spectroscopy; graph theory; spectral moments carbon nanotubes; cytotoxicity; mitochondria oxygen mass flux; Raman spectroscopy; graph theory; spectral moments
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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González-Durruthy, M.; Monserrat, J.M.; Rasulev, B.; Casañola-Martín, G.M.; Barreiro Sorrivas, J.M.; Paraíso-Medina, S.; Maojo, V.; González-Díaz, H.; Pazos, A.; Munteanu, C.R. Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra. Nanomaterials 2017, 7, 386.

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