| Title |
Multimodal Actions of Neural Stem Cells in a Mouse Model of ALS: A Meta-Analysis
|
|---|---|
| Published in |
Science Translational Medicine, December 2012
|
| DOI | 10.1126/scitranslmed.3004579 |
| Pubmed ID | |
| Authors |
Yang D. Teng, Susanna C. Benn, Steven N. Kalkanis, Jeremy M. Shefner, Renna C. Onario, Bin Cheng, Mahesh B. Lachyankar, Michael Marconi, Jianxue Li, Dou Yu, Inbo Han, Nicholas J. Maragakis, Jeronia Lládo, Kadir Erkmen, D. Eugene Redmond, Richard L. Sidman, Serge Przedborski, Jeffrey D. Rothstein, Robert H. Brown, Evan Y. Snyder |
| Abstract |
Amyotrophic lateral sclerosis (ALS) is a lethal disease characterized by the unremitting degeneration of motor neurons. Multiple processes involving motor neurons and other cell types have been implicated in its pathogenesis. Neural stem cells (NSCs) perform multiple actions within the nervous system to fulfill their functions of organogenesis and homeostasis. We test the hypothesis that transplanted, undifferentiated multipotent migratory NSCs may help to ameliorate an array of pathological mechanisms in the SOD1(G93A) transgenic mouse model of ALS. On the basis of a meta-analysis of 11 independent studies performed by a consortium of ALS investigators, we propose that transplanted NSCs (both mouse and human) can slow both the onset and the progression of clinical signs and prolong survival in ALS mice, particularly if regions sustaining vital functions such as respiration are rendered chimeric. The beneficial effects of transplanted NSCs seem to be mediated by a number of actions including their ability to produce trophic factors, preserve neuromuscular function, and reduce astrogliosis and inflammation. We conclude that the widespread, pleiotropic, modulatory actions exerted by transplanted NSCs may represent an accessible therapeutic application of stem cells for treating ALS and other untreatable degenerative diseases. |
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Demographic breakdown
| Type | Count | As % |
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Mendeley readers
Geographical breakdown
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|---|---|---|
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| Uruguay | 1 | <1% |
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| Unknown | 117 | 94% |
Demographic breakdown
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|---|---|---|
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| Researcher | 22 | 18% |
| Student > Bachelor | 21 | 17% |
| Student > Master | 8 | 6% |
| Professor | 6 | 5% |
| Other | 22 | 18% |
| Unknown | 24 | 19% |
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