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iPCS Cell Modeling of Inherited Cardiac Arrhythmias

Overview of attention for article published in Current Treatment Options in Cardiovascular Medicine, July 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

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1 Wikipedia page

Citations

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47 Mendeley
Title
iPCS Cell Modeling of Inherited Cardiac Arrhythmias
Published in
Current Treatment Options in Cardiovascular Medicine, July 2014
DOI 10.1007/s11936-014-0331-4
Pubmed ID
Authors

Rami Shinnawi, Lior Gepstein

Abstract

The study of inherited cardiac disorders is hampered by the lack of suitable in vitro human cardiac disease models and relevant functional assays. A potential solution to this cell-sourcing challenge may be the recently described human induced pluripotent stem cell (hiPSC) technology. Pioneering studies were successful in establishing patient-specific, hiPSC-derived cardiomyocyte models of the most common inherited cardiac arrhythmogenic disorders, such as the different long QT syndrome subtypes (types 1, 2, 3, 8), overlap syndrome LQTS3/Brugada syndrome, catecholaminergic polymorphic ventricular tachycardia (CPVT) types 1 and 2, and arrhythmogenic right ventricular cardiomyopathy (ARVC). These studies initially demonstrated the ability of the generated hiPSC models to recapitulate the disease processes in the culture dish. More recently, such studies were also able to provide new mechanistic insights into the disease processes, as well as to derive a unique drug-screening platform to test existing and novel therapeutic treatment options in an environment resembling the human physiological milieu. Moreover, initial evidence suggests that such models can help to optimize drug treatment in a personalized manner in the future. Nevertheless, several hurdles still exist for using hiPSC-based models for the aforementioned tasks, such as the hiPSC-derived cardiomyocytes' relatively immature phenotype, and also the resulting cell heterogeneity. Extensive research work is ongoing to address these challenges, as well as to add new opportunities for the field by utilizing recent advances in gene editing technologies. Here, we discuss the significant findings that hiPSC-based models have provided for each of the inherited cardiac arrhythmia syndromes so far, and the current challenges that this technique is facing.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Netherlands 2 4%
Unknown 43 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 26%
Researcher 8 17%
Student > Bachelor 4 9%
Other 4 9%
Student > Master 3 6%
Other 6 13%
Unknown 10 21%
Readers by discipline Count As %
Medicine and Dentistry 12 26%
Biochemistry, Genetics and Molecular Biology 9 19%
Agricultural and Biological Sciences 7 15%
Engineering 3 6%
Chemical Engineering 1 2%
Other 3 6%
Unknown 12 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 September 2014.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Current Treatment Options in Cardiovascular Medicine
#149
of 410 outputs
Outputs of similar age
#73,181
of 228,379 outputs
Outputs of similar age from Current Treatment Options in Cardiovascular Medicine
#1
of 4 outputs
Altmetric has tracked 22,783,848 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 410 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 228,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
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 all of them