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Architectural Trends in the Human Normal and Bicuspid Aortic Valve Leaflet and Its Relevance to Valve Disease

Overview of attention for article published in Annals of Biomedical Engineering, February 2014
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Title
Architectural Trends in the Human Normal and Bicuspid Aortic Valve Leaflet and Its Relevance to Valve Disease
Published in
Annals of Biomedical Engineering, February 2014
DOI 10.1007/s10439-014-0973-0
Pubmed ID
Authors

Ankush Aggarwal, Giovanni Ferrari, Erin Joyce, Michael J. Daniels, Rachana Sainger, Joseph H. Gorman, Robert Gorman, Michael S. Sacks

Abstract

The bicuspid aortic valve (AV) is the most common cardiac congenital anomaly and has been found to be a significant risk factor for developing calcific AV disease. However, the mechanisms of disease development remain unclear. In this study we quantified the structure of human normal and bicuspid leaflets in the early disease stage. From these individual leaflet maps average fiber structure maps were generated using a novel spline based technique. Interestingly, we found statistically different and consistent regional structures between the normal and bicuspid valves. The regularity in the observed microstructure was a surprising finding, especially for the pathological BAV leaflets and is an essential cornerstone of any predictive mathematical models of valve disease. In contrast, we determined that isolated valve interstitial cells from BAV leaflets show the same in vitro calcification pathways as those from the normal AV leaflets. This result suggests the VICs are not intrinsically different when isolated, and that external features, such as abnormal microstructure and altered flow may be the primary contributors in the accelerated calcification experienced by BAV patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 56 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 17%
Professor > Associate Professor 8 14%
Student > Ph. D. Student 7 12%
Student > Master 6 10%
Student > Bachelor 5 9%
Other 11 19%
Unknown 11 19%
Readers by discipline Count As %
Engineering 19 33%
Medicine and Dentistry 13 22%
Agricultural and Biological Sciences 6 10%
Physics and Astronomy 2 3%
Social Sciences 1 2%
Other 2 3%
Unknown 15 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 June 2014.
All research outputs
#21,157,205
of 25,986,827 outputs
Outputs from Annals of Biomedical Engineering
#2
of 2 outputs
Outputs of similar age
#247,265
of 324,984 outputs
Outputs of similar age from Annals of Biomedical Engineering
#7
of 7 outputs
Altmetric has tracked 25,986,827 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2 research outputs from this source. They receive a mean Attention Score of 3.8. This one scored the same or higher as 0 of them.
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We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.