| Title |
Biophysical Characteristics Reveal Neural Stem Cell Differentiation Potential
|
|---|---|
| Published in |
PLOS ONE, September 2011
|
| DOI | 10.1371/journal.pone.0025458 |
| Pubmed ID | |
| Authors |
Fatima H. Labeed, Jente Lu, Hayley J. Mulhall, Steve A. Marchenko, Kai F. Hoettges, Laura C. Estrada, Abraham P. Lee, Michael P. Hughes, Lisa A. Flanagan |
| Abstract |
Distinguishing human neural stem/progenitor cell (huNSPC) populations that will predominantly generate neurons from those that produce glia is currently hampered by a lack of sufficient cell type-specific surface markers predictive of fate potential. This limits investigation of lineage-biased progenitors and their potential use as therapeutic agents. A live-cell biophysical and label-free measure of fate potential would solve this problem by obviating the need for specific cell surface markers. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 25% |
| United States | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 1 | 25% |
| Unknown | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Portugal | 1 | 1% |
| Peru | 1 | 1% |
| Unknown | 74 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 31% |
| Student > Master | 12 | 16% |
| Researcher | 8 | 10% |
| Professor > Associate Professor | 8 | 10% |
| Student > Bachelor | 7 | 9% |
| Other | 10 | 13% |
| Unknown | 8 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 23 | 30% |
| Agricultural and Biological Sciences | 19 | 25% |
| Physics and Astronomy | 5 | 6% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Medicine and Dentistry | 4 | 5% |
| Other | 10 | 13% |
| Unknown | 12 | 16% |