Qiao, Shupei, Liu, Yi, Han, Fengtong, Guo, Mian, Hou, Xiaolu, Ye, Kangruo, Deng, Shuai, Shen, Yijun, Zhao, Yufang, Wei, Haiying, Song, Bing ORCID: https://orcid.org/0000-0001-9356-2333, Yao, Lifen and Tian, Weiming 2018. An intelligent neural stem cell delivery system for neurodegenerative diseases treatment. Advanced Healthcare Materials 7 (12) , 1800080. 10.1002/adhm.201800080 |
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Abstract
Transplanted stem cells constitute a new therapeutic strategy for the treatment of neurological disorders. Emerging evidence indicates that a negative microenvironment, particularly one characterized by the acute inflammation/immune response caused by physical injuries or transplanted stem cells, severely impacts the survival of transplanted stem cells. In this study, to avoid the influence of the increased inflammation following physical injuries, an intelligent, double‐layer, alginate hydrogel system is designed. This system fosters the matrix metalloproeinases (MMP) secreted by transplanted stem cell reactions with MMP peptide grafted on the inner layer and destroys the structure of the inner hydrogel layer during the inflammatory storm. Meanwhile, the optimum concentration of the arginine‐glycine‐aspartate (RGD) peptide is also immobilized to the inner hydrogels to obtain more stem cells before arriving to the outer hydrogel layer. It is found that blocking Cripto‐1, which promotes embryonic stem cell differentiation to dopamine neurons, also accelerates this process in neural stem cells. More interesting is the fact that neural stem cell differentiation can be conducted in astrocyte‐differentiation medium without other treatments. In addition, the system can be adjusted according to the different parameters of transplanted stem cells and can expand on the clinical application of stem cells in the treatment of this neurological disorder.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Dentistry |
Publisher: | Wiley: 12 months |
ISSN: | 2192-2640 |
Date of First Compliant Deposit: | 31 October 2018 |
Last Modified: | 26 Nov 2024 13:00 |
URI: | https://orca.cardiff.ac.uk/id/eprint/116045 |
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