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利用摩擦纳米发电机激发神经元细胞的计算建模研究。

A computational modelling study of excitation of neuronal cells with triboelectric nanogenerators.

机构信息

Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Institute for Nanoscience and Nanotechnology (INST), Sharif University of Technology, Tehran, Iran.

出版信息

Sci Rep. 2022 Aug 4;12(1):13411. doi: 10.1038/s41598-022-17050-0.

Abstract

Neurological disorders and nerve injuries, such as spinal cord injury, stroke, and multiple sclerosis can result in the loss of muscle function. Electrical stimulation of the neuronal cells is the currently available clinical treatment in this regard. As an effective energy harvester, the triboelectric nanogenerators (TENG) can be used for self-powered neural/muscle stimulations because the output of the TENG provides stimulation pulses for nerves. In the present study, using a computational modelling approach, the effect of surface micropatterns on the electric field distribution, induced voltage and capacitance of the TENG structures have been investigated. By incorporating the effect of the TENG inside the mathematical model of neuron's electrical behavior (cable equation with Hodgkin-Huxley model), its impact on the electrical behavior of the neurons has been studied. The results show that the TENG operates differently with various surface modifications. The performance of the TENG in excitation of neurons depends on the contact and release speed of its electrodes accordingly.

摘要

神经紊乱和神经损伤,如脊髓损伤、中风和多发性硬化症,可能导致肌肉功能丧失。神经元细胞的电刺激是目前这方面的临床治疗方法。作为一种有效的能量收集器,摩擦纳米发电机(TENG)可用于自供电神经/肌肉刺激,因为 TENG 的输出为神经提供刺激脉冲。在本研究中,使用计算建模方法,研究了表面微图案对 TENG 结构的电场分布、感应电压和电容的影响。通过将 TENG 的效果纳入神经元电行为的数学模型(具有 Hodgkin-Huxley 模型的电缆方程)中,研究了它对神经元电行为的影响。结果表明,TENG 在不同的表面改性下表现不同。TENG 激发神经元的性能取决于其电极的接触和释放速度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818c/9352766/8cb990c6fc3b/41598_2022_17050_Fig1_HTML.jpg

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