| Title |
Muse cells and induced pluripotent stem cell: implication of the elite model
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, April 2012
|
| DOI | 10.1007/s00018-012-0994-5 |
| Pubmed ID | |
| Authors |
Masaaki Kitada, Shohei Wakao, Mari Dezawa |
| Abstract |
Induced pluripotent stem (iPS) cells have attracted a great deal attention as a new pluripotent stem cell type that can be generated from somatic cells, such as fibroblasts, by introducing the transcription factors Oct3/4, Sox2, Klf4, and c-Myc. The mechanism of generation, however, is not fully understood. Two mechanistic theories have been proposed; the stochastic model purports that every cell type has the potential to be reprogrammed to become an iPS cell and the elite model proposes that iPS cell generation occurs only from a subset of cells. Some reports have provided theoretical support for the stochastic model, but a recent publication demonstrated findings that support the elite model, and thus the mechanism of iPS cell generation remains under debate. To enhance our understanding of iPS cells, it is necessary to clarify the properties of the original cell source, i.e., the components of the original populations and the potential of each population to become iPS cells. In this review, we discuss the two theories and their implications in iPS cell research. |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Mexico | 1 | 1% |
| Jordan | 1 | 1% |
| Portugal | 1 | 1% |
| Unknown | 66 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 20% |
| Student > Ph. D. Student | 11 | 16% |
| Professor > Associate Professor | 9 | 13% |
| Student > Master | 8 | 11% |
| Other | 5 | 7% |
| Other | 13 | 19% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 36% |
| Medicine and Dentistry | 15 | 21% |
| Biochemistry, Genetics and Molecular Biology | 9 | 13% |
| Economics, Econometrics and Finance | 3 | 4% |
| Computer Science | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 12 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 July 2020.
All research outputs
#2,460,988
of 23,794,258 outputs
Outputs from Cellular and Molecular Life Sciences
#332
of 4,151 outputs
Outputs of similar age
#15,569
of 165,323 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#4
of 48 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 165,323 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.