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Human induced pluripotent stem cell for modeling cardiovascular diseases

Overview of attention for article published in Regenerative Medicine Research, January 2014
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Mentioned by

twitter
3 tweeters
facebook
1 Facebook page

Citations

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17 Dimensions

Readers on

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38 Mendeley
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Title
Human induced pluripotent stem cell for modeling cardiovascular diseases
Published in
Regenerative Medicine Research, January 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.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 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 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Ph. D. Student 7 18%
Student > Bachelor 6 16%
Student > Master 6 16%
Professor 3 8%
Other 4 11%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 34%
Biochemistry, Genetics and Molecular Biology 8 21%
Medicine and Dentistry 5 13%
Engineering 4 11%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 3 8%
Unknown 3 8%

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
#4,646,990
of 9,053,319 outputs
Outputs from Regenerative Medicine Research
#9
of 19 outputs
Outputs of similar age
#132,927
of 266,592 outputs
Outputs of similar age from Regenerative Medicine Research
#1
of 2 outputs
Altmetric has tracked 9,053,319 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 19 research outputs from this source. They receive a mean Attention Score of 2.0. This one scored the same or higher as 10 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 266,592 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them