Title |
iPS cell technologies: significance and applications to CNS regeneration and disease
|
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Published in |
Molecular Brain, March 2014
|
DOI | 10.1186/1756-6606-7-22 |
Pubmed ID | |
Authors |
Hideyuki Okano, Shinya Yamanaka |
Abstract |
In 2006, we demonstrated that mature somatic cells can be reprogrammed to a pluripotent state by gene transfer, generating induced pluripotent stem (iPS) cells. Since that time, there has been an enormous increase in interest regarding the application of iPS cell technologies to medical science, in particular for regenerative medicine and human disease modeling. In this review article, we outline the current status of applications of iPS technology to cell therapies (particularly for spinal cord injury), as well as neurological disease-specific iPS cell research (particularly for Parkinson's disease and Alzheimer's disease). Finally, future directions of iPS cell research are discussed including a) development of an accurate assay system for disease-associated phenotypes, b) demonstration of causative relationships between genotypes and phenotypes by genome editing, c) application to sporadic and common diseases, and d) application to preemptive medicine. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 2 | 14% |
United Kingdom | 2 | 14% |
Japan | 2 | 14% |
Unknown | 8 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 57% |
Scientists | 4 | 29% |
Science communicators (journalists, bloggers, editors) | 2 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | <1% |
United Kingdom | 3 | <1% |
Poland | 2 | <1% |
Japan | 2 | <1% |
Germany | 1 | <1% |
Unknown | 389 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 80 | 20% |
Student > Bachelor | 61 | 15% |
Student > Master | 51 | 13% |
Researcher | 48 | 12% |
Student > Doctoral Student | 21 | 5% |
Other | 53 | 13% |
Unknown | 87 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 107 | 27% |
Biochemistry, Genetics and Molecular Biology | 68 | 17% |
Medicine and Dentistry | 39 | 10% |
Neuroscience | 38 | 9% |
Engineering | 13 | 3% |
Other | 37 | 9% |
Unknown | 99 | 25% |