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Asymmetric Cell–Matrix and Biomechanical Abnormalities in Elastin Insufficiency Induced Aortopathy

Overview of attention for article published in Annals of Biomedical Engineering, August 2014
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Title
Asymmetric Cell–Matrix and Biomechanical Abnormalities in Elastin Insufficiency Induced Aortopathy
Published in
Annals of Biomedical Engineering, August 2014
DOI 10.1007/s10439-014-1072-y
Pubmed ID
Authors

Varun K. Krishnamurthy, Ashlie N. Evans, Janaka P. Wansapura, Hanna Osinska, Kelsey E. Maddy, Stefanie V. Biechler, Daria A. Narmoneva, Richard L. Goodwin, Robert B. Hinton

Abstract

Aortopathy is characterized by vascular smooth muscle cell (VSMC) abnormalities and elastic fiber fragmentation. Elastin insufficient (Eln (±)) mice demonstrate latent aortopathy similar to human disease. We hypothesized that aortopathy manifests primarily in the aorto-pulmonary septal (APS) side of the thoracic aorta due to asymmetric cardiac neural crest (CNC) distribution. Anatomic (aortic root vs. ascending aorta) and molecular (APS vs. non-APS) regions of proximal aorta tissue were examined in adult and aged wild type (WT) and mutant (Eln (±)) mice. CNC, VSMCs, elastic fiber architecture, proteoglycan expression, morphometrics and biomechanical properties were examined using histology, 3D reconstruction, micropipette aspiration and in vivo magnetic resonance imaging (MRI). In the APS side of Eln (±) aorta, Sonic Hedgehog (SHH) is decreased while SM22 is increased. Elastic fiber architecture abnormalities are present in the Eln (±) aortic root and APS ascending aorta, and biglycan is increased in the aortic root while aggrecan is increased in the APS aorta. The Eln (±) ascending aorta is stiffer than the aortic root, the APS side is thicker and stiffer than the non-APS side, and significant differences in the individual aortic root sinuses are observed. Asymmetric structure-function abnormalities implicate regional CNC dysregulation in the development and progression of aortopathy.

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Geographical breakdown

Country Count As %
Italy 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 10%
Professor > Associate Professor 2 10%
Researcher 2 10%
Student > Ph. D. Student 1 5%
Lecturer > Senior Lecturer 1 5%
Other 2 10%
Unknown 11 52%
Readers by discipline Count As %
Medicine and Dentistry 3 14%
Engineering 3 14%
Psychology 1 5%
Neuroscience 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Other 0 0%
Unknown 12 57%