Dar M S, Akram Khush Bakhat, Sohail Ayesha, Arif Fatima, Zabihi Fatemeh, Yang Shengyuan, Munir Shamsa, Zhu Meifang, Abid M, Nauman Muhammad
State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, International Joint Laboratory for Advanced Fiber and Low-dimension Materials, College of Materials Science and Engineering, Donghua University Shanghai 201620 P. R. China
Centre for Advanced Electronics and Photovoltaic Engineering (CAEPE), International Islamic University Islamabad Pakistan
RSC Adv. 2021 Jun 18;11(35):21702-21715. doi: 10.1039/d1ra03428f. eCollection 2021 Jun 15.
We report the synthesis and characterization of graphene functionalized with iron (Fe) oxide (G-FeO) nanohybrids for radio-frequency magnetic hyperthermia application. We adopted the wet chemical procedure, using various contents of FeO (magnetite) from 0-100% for making two-dimensional graphene-FeO nanohybrids. The homogeneous dispersal of FeO 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 (FG) in the training phase , 0.44703, which is where the model achieved optimal results after 71 epochs. The FG 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.
我们报道了用于射频磁热疗的氧化铁（FeO）功能化石墨烯（G-FeO）纳米杂化物的合成与表征。我们采用湿化学方法，使用0 - 100%的不同含量的FeO（磁铁矿）来制备二维石墨烯-FeO纳米杂化物。装饰在石墨烯表面的FeO纳米颗粒均匀分散，结合其生物相容性和高导热性，使其成为磁热疗的优异材料。分别使用扫描电子显微镜（SEM）和振动样品磁强计（VSM）研究了纳米杂化物的形态和磁性。将智能磁性平台暴露于633 kHz、强度为9.1 mT的交变电流（AC）磁场中，以研究其热疗性能。通过人工神经网络建模研究局部抗肿瘤作用。开发了一个神经网络时间序列模型，用于评估最适合该目的的纳米杂化物组成，准确率接近100%。获得了六个带有外部输入的非线性自回归（NARX）模型，每个组分一个。基于均方误差（MSE）对预测结果的准确性进行了评估。在训练阶段，含45%磁铁矿和55%石墨烯的纳米杂化物（FG）获得了最高的均方误差值，为0.44703，该模型在71个轮次后在此处取得了最佳结果。发现FG纳米杂化物在低剂量下用于热疗应用效果最佳，具有最高的比吸收率（SAR）和均方误差值。
