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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Human induced pluripotent stem cell for modeling cardiovascular diseases
|
|---|---|
| Published in |
Regenerative Medicine Research, February 2014
|
| DOI | 10.1186/2050-490x-2-4 |
| Pubmed ID | |
| Authors |
Ping Liang, Jie Du |
| Abstract |
The invention of the induced pluripotent stem cell (iPSC) technology allows patient-specific, mature somatic cells to be converted into an unlimited supply of pluripotent stem cells (PSCs). These iPSCs can then in turn be differentiated into any cell type including neurons, cardiac cells, pancreatic cells, liver cells, blood cells or enterocytes. Although cardiovascular disease (CVD) is a leading cause of death in the world, the limited cell derivation and cell number in cardiac tissue makes it difficult to study the CVDs using the existing cardiac cell model. By differentiating the patient-specific iPSCs into cardiomyocytes, scientists can generate iPSC-based 'disease in a dish' models and use them to better understand disease mechanism. Here we review the current progress in using iPSC-derived cardiomyocytes to model human CVDs. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 5% |
| Germany | 1 | 2% |
| Unknown | 38 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 20% |
| Student > Ph. D. Student | 7 | 17% |
| Student > Bachelor | 6 | 15% |
| Student > Master | 6 | 15% |
| Professor | 3 | 7% |
| Other | 5 | 12% |
| Unknown | 6 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 32% |
| Biochemistry, Genetics and Molecular Biology | 8 | 20% |
| Medicine and Dentistry | 5 | 12% |
| Engineering | 4 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 5 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 February 2017.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from Regenerative Medicine Research
#16
of 25 outputs
Outputs of similar age
#196,325
of 322,641 outputs
Outputs of similar age from Regenerative Medicine Research
#2
of 4 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25 research outputs from this source. They receive a mean Attention Score of 2.3. This one scored the same or higher as 9 of them.
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 322,641 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.