Differentiation of human neural stem cells into neural networks on graphene nanogrids

被引:155
作者
Akhavan, Omid [1 ,2 ]
Ghaderi, Elham [1 ]
机构
[1] Sharif Univ Technol, Dept Phys, Tehran, Iran
[2] Sharif Univ Technol, Inst Nanosci & Nanotechnol, Tehran, Iran
关键词
OSTEOGENIC DIFFERENTIATION; PHOTOCATALYTIC REDUCTION; FIELD STIMULATION; CARBON NANOTUBES; RAMAN-SPECTRA; IN-VITRO; OXIDE; NANOPARTICLES; BACTERIA; NEURONS;
D O I
10.1039/c3tb21085e
中图分类号
TB3 [工程材料学]; R318.08 [生物材料学];
学科分类号
0805 ; 080501 ; 080502 ;
摘要
Graphene nanogrids (crossed graphene nanoribbons synthesized by the oxidative unzipping of multi-walled carbon nanotubes) on a SiO2 matrix containing TiO2 nanoparticles (NPs) were applied as a photocatalytic stimulator in the accelerated differentiation of human neural stem cells (hNSCs) into two-dimensional neural networks. The hydrophilic graphene nanogrids exhibited patterned proliferations of hNSCs (consistent with patterns of the nanogrids), in contrast with the usual random growths occurring on quartz substrates. The number of cell nuclei differentiated on reduced graphene oxide nanoribbon (rGONR) grid/TiO2 NPs/SiO2 increased similar to 5.9 and 26.8 fold compared to the number of cells on quartz substrates, after three weeks of differentiation, in the dark and under photo stimulation, respectively. The stimulation, originated by the injection of photoexcited electrons from the TiO2 NPs into the cells on the nanogrids, also resulted in changing the number of differentiated neurons and glial cells in the patterned neural network by factors of similar to 1.8 and 0.17, respectively. A higher differentiation on the rGONR grids than rGO sheets was assigned to the physical stress induced by the surface topographic features of the nanogrids. The current-voltage properties of the neural networks differentiated on the electrically disconnected rGONR grids demonstrated effective cell-to-cell and cell-to-rGONR couplings after three weeks of the stimulated differentiation.
引用
收藏
页码:6291 / 6301
页数:11
相关论文
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