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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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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%