Direct Differentiation of Human Embryonic Stem Cells into Selective Neurons on Nanoscale Ridge/Groove Pattern Arrays
Human embryonic stem cells (hESCs) are pluripotent cells that have the potential to be used for tissue engineering and regenerative medicine. Biochemical and biological agents are widely used to induce hESC differentiation. However, it would be better if we could induce the differentiation of hESCs without using such agents because these factors are expensive. It is also difficult to determine optimal concentrations of agents for efficient differentiation. Moreover, the mechanism of differentiation induced by these factors is still not fully understood. Using UV-assisted capillary force lithography, we constructed nanoscale ridge/groove pattern arrays with a dimension and alignment that were finely controlled over a large area. Human embryonic stem cells seeded onto the 350-nm ridge/groove pattern arrays differentiated into neuronal lineage after 5 days, in the absence of differentiation-inducing agents. This nanoscale technique could be used for a new neuronal differentiation protocol of hESCs and may also be useful for nanostructured scaffolding for nerve injury repair. In this chapter, we describe this method in detail. This protocol can be used to create nanoscale ridge/groove pattern arrays for effective and rapid directing of the differentiation of hESCs into a neuronal lineage without the use of any differentiation-inducing agents.
- 细胞化学染色分类技术
- Detection of Intracellular/lntranuclear Antigens in Tumor Cells
- Rubidium Efflux as a Tool for the Pharmacological Characterisation of Compounds with BK Channel Opening Properties
- Microencapsulation of Stem Cells to Study Cellular Interactions
- Padlock Probes and Rolling Circle Amplification for Detection of Repeats and Single-Copy Genes in the Single-Cell Comet Assay
- 关于HEK293细胞转染的问题
- HOW TO USE THE COULTER COUNTER TO COUNT CELLS
- Global Analysis of Gene Expression by Differential Display: A Mathematical Model
- 植物体内可溶性糖含量的测定(蒽酮法)
- MTS检测细胞生长