Journal
ADVANCED MATERIALS
Volume 30, Issue 17, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.201705684
Keywords
disease modeling; neuron regeneration; neuronal degenerative; neuronal differentiation; neuronal trans-differentiation
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Funding
- National Natural Science Foundation of China [81570760, 31771283, 31771644, 11402176]
- National Key Research and Development Program of China [2017YFA0103900, 2017YFA0103902, 2016YFA0102200, 2017YFA0104100, 2017YFA0103904]
- One Thousand Youth Talents Program of China
- Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [A11323]
- Shanghai Rising-Star Program [15QA1403600]
- Natural Science Foundation of Shanghai [16ZR1439500, 15ZR1434000]
- Start-up Research Fund of Tongji University
- Shanghai East Hospital
- Fundamental Research Funds for the Central Universities of Tongji University
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Neuron regeneration from pluripotent stem cells (PSCs) differentiation or somatic cells trans-differentiation is a promising approach for cell replacement in neurodegenerative diseases and provides a powerful tool for investigating neural development, modeling neurological diseases, and uncovering the mechanisms that underlie diseases. Advancing the materials that are applied in neural differentiation and trans-differentiation promotes the safety, efficiency, and efficacy of neuron regeneration. In the neural differentiation process, matrix materials, either natural or synthetic, not only provide a structural and biochemical support for the monolayer or three-dimensional (3D) cultured cells but also assist in cell adhesion and cell-to-cell communication. They play important roles in directing the differentiation of PSCs into neural cells and modeling neurological diseases. For the trans-differentiation of neural cells, several materials have been used to make the conversion feasible for future therapy. Here, the most current applications of materials for neural differentiation for PSCs, neuronal trans-differentiation, and neurological disease modeling is summarized and discussed.
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