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Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling

We report the synthesis and characterization of graphene functionalized with iron (Fe(3+)) oxide (G-Fe(3)O(4)) nanohybrids for radio-frequency magnetic hyperthermia application. We adopted the wet chemical procedure, using various contents of Fe(3)O(4) (magnetite) from 0–100% for making two-dimensio...

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Autores principales: Dar, M. S., Akram, Khush Bakhat, Sohail, Ayesha, Arif, Fatima, Zabihi, Fatemeh, Yang, Shengyuan, Munir, Shamsa, Zhu, Meifang, Abid, M., Nauman, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034160/
https://www.ncbi.nlm.nih.gov/pubmed/35478795
http://dx.doi.org/10.1039/d1ra03428f
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author Dar, M. S.
Akram, Khush Bakhat
Sohail, Ayesha
Arif, Fatima
Zabihi, Fatemeh
Yang, Shengyuan
Munir, Shamsa
Zhu, Meifang
Abid, M.
Nauman, Muhammad
author_facet Dar, M. S.
Akram, Khush Bakhat
Sohail, Ayesha
Arif, Fatima
Zabihi, Fatemeh
Yang, Shengyuan
Munir, Shamsa
Zhu, Meifang
Abid, M.
Nauman, Muhammad
author_sort Dar, M. S.
collection PubMed
description We report the synthesis and characterization of graphene functionalized with iron (Fe(3+)) oxide (G-Fe(3)O(4)) nanohybrids for radio-frequency magnetic hyperthermia application. We adopted the wet chemical procedure, using various contents of Fe(3)O(4) (magnetite) from 0–100% for making two-dimensional graphene–Fe(3)O(4) nanohybrids. The homogeneous dispersal of Fe(3)O(4) nanoparticles decorated on the graphene surface combined with their biocompatibility and high thermal conductivity make them an excellent material for magnetic hyperthermia. The morphological and magnetic properties of the nanohybrids were studied using scanning electron microscopy (SEM) and a vibrating sample magnetometer (VSM), respectively. The smart magnetic platforms were exposed to an alternating current (AC) magnetic field of 633 kHz and of strength 9.1 mT for studying their hyperthermic performance. The localized antitumor effects were investigated with artificial neural network modeling. A neural net time-series model was developed for the assessment of the best nanohybrid composition to serve the purpose with an accuracy close to 100%. Six Nonlinear Autoregressive with External Input (NARX) models were obtained, one for each of the components. The assessment of the accuracy of the predicted results has been done on the basis of Mean Squared Error (MSE). The highest Mean Squared Error value was obtained for the nanohybrid containing 45% magnetite and 55% graphene (F(45)G(55)) in the training phase i.e., 0.44703, which is where the model achieved optimal results after 71 epochs. The F(45)G(55) nanohybrid was found to be the best for hyperthermia applications in low dosage with the highest specific absorption rate (SAR) and mean squared error values.
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spelling pubmed-90341602022-04-26 Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling Dar, M. S. Akram, Khush Bakhat Sohail, Ayesha Arif, Fatima Zabihi, Fatemeh Yang, Shengyuan Munir, Shamsa Zhu, Meifang Abid, M. Nauman, Muhammad RSC Adv Chemistry We report the synthesis and characterization of graphene functionalized with iron (Fe(3+)) oxide (G-Fe(3)O(4)) nanohybrids for radio-frequency magnetic hyperthermia application. We adopted the wet chemical procedure, using various contents of Fe(3)O(4) (magnetite) from 0–100% for making two-dimensional graphene–Fe(3)O(4) nanohybrids. The homogeneous dispersal of Fe(3)O(4) nanoparticles decorated on the graphene surface combined with their biocompatibility and high thermal conductivity make them an excellent material for magnetic hyperthermia. The morphological and magnetic properties of the nanohybrids were studied using scanning electron microscopy (SEM) and a vibrating sample magnetometer (VSM), respectively. The smart magnetic platforms were exposed to an alternating current (AC) magnetic field of 633 kHz and of strength 9.1 mT for studying their hyperthermic performance. The localized antitumor effects were investigated with artificial neural network modeling. A neural net time-series model was developed for the assessment of the best nanohybrid composition to serve the purpose with an accuracy close to 100%. Six Nonlinear Autoregressive with External Input (NARX) models were obtained, one for each of the components. The assessment of the accuracy of the predicted results has been done on the basis of Mean Squared Error (MSE). The highest Mean Squared Error value was obtained for the nanohybrid containing 45% magnetite and 55% graphene (F(45)G(55)) in the training phase i.e., 0.44703, which is where the model achieved optimal results after 71 epochs. The F(45)G(55) nanohybrid was found to be the best for hyperthermia applications in low dosage with the highest specific absorption rate (SAR) and mean squared error values. The Royal Society of Chemistry 2021-06-18 /pmc/articles/PMC9034160/ /pubmed/35478795 http://dx.doi.org/10.1039/d1ra03428f Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by/3.0/
spellingShingle Chemistry
Dar, M. S.
Akram, Khush Bakhat
Sohail, Ayesha
Arif, Fatima
Zabihi, Fatemeh
Yang, Shengyuan
Munir, Shamsa
Zhu, Meifang
Abid, M.
Nauman, Muhammad
Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title_full Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title_fullStr Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title_full_unstemmed Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title_short Heat induction in two-dimensional graphene–Fe(3)O(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
title_sort heat induction in two-dimensional graphene–fe(3)o(4) nanohybrids for magnetic hyperthermia applications with artificial neural network modeling
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034160/
https://www.ncbi.nlm.nih.gov/pubmed/35478795
http://dx.doi.org/10.1039/d1ra03428f
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