↓ Skip to main content

Mechanisms of Smooth Muscle Cell Differentiation Are Distinctly Altered in Thoracic Aortic Aneurysms Associated with Bicuspid or Tricuspid Aortic Valves

Overview of attention for article published in Frontiers in Physiology, July 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
40 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Mechanisms of Smooth Muscle Cell Differentiation Are Distinctly Altered in Thoracic Aortic Aneurysms Associated with Bicuspid or Tricuspid Aortic Valves
Published in
Frontiers in Physiology, July 2017
DOI 10.3389/fphys.2017.00536
Pubmed ID
Authors

Elena Ignatieva, Daria Kostina, Olga Irtyuga, Vladimir Uspensky, Alexey Golovkin, Natalia Gavriliuk, Olga Moiseeva, Anna Kostareva, Anna Malashicheva

Abstract

Cellular and molecular mechanisms of thoracic aortic aneurysm are not clear and therapeutic approaches are mostly absent. Thoracic aortic aneurysm is associated with defective differentiation of smooth muscle cells (SMC) of aortic wall. Bicuspid aortic valve (BAV) comparing to tricuspid aortic valve (TAV) significantly predisposes to a risk of thoracic aortic aneurysms. It has been suggested recently that BAV-associated aortopathies represent a separate pathology comparing to TAV-associated dilations. The only proven candidate gene that has been associated with BAV remains NOTCH1. In this study we tested the hypothesis that Notch-dependent and related TGF-β and BMP differentiation pathways are differently altered in aortic SMC of BAV- vs. TAV-associated aortic aneurysms. SMC were isolated from aortic tissues of the patients with BAV- or TAV-associated aortic aneurysms and from healthy donors used as controls. Gene expression was verified by qPCR and Western blotting. For TGF-β induced differentiation SMC were treated with the medium containing TGF-β1. To induce proosteogenic signaling we cultured SMC in the presence of specific osteogenic factors. Notch-dependent differentiation was induced via lentiviral transduction of SMC with activated Notch1 domain. MYOCD expression, a master gene of SMC differentiation, was down regulated in SMC of both BAV and TAV patients. Discriminant analysis of gene expression patterns included a set of contractile genes specific for SMC, Notch-related genes and proosteogenic genes and revealed that control cells form a separate cluster from both BAV and TAV group, while BAV- and TAV-derived SMC are partially distinct with some overlapping. In differentiation experiments TGF-β caused similar patterns of target gene expression for BAV- and TAV derived cells while the induction was higher in the diseased cells than in control ones. Osteogenic induction caused significant change in RUNX2 expression exclusively in BAV group. Notch activation induced significant ACTA2 expression also exclusively in BAV group. We show that Notch acts synergistically with proosteogenic factors to induce ACTA2 transcription and osteogenic differentiation. In conclusion we have found differences in responsiveness of SMC to Notch and to proosteogenic induction between BAV- and TAV-associated aortic aneurysms.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Student > Master 8 20%
Student > Bachelor 3 8%
Professor 3 8%
Professor > Associate Professor 3 8%
Other 6 15%
Unknown 8 20%
Readers by discipline Count As %
Medicine and Dentistry 12 30%
Biochemistry, Genetics and Molecular Biology 8 20%
Engineering 3 8%
Agricultural and Biological Sciences 1 3%
Chemistry 1 3%
Other 1 3%
Unknown 14 35%
Attention Score in Context

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 02 August 2017.
All research outputs
#14,357,979
of 22,992,311 outputs
Outputs from Frontiers in Physiology
#5,321
of 13,752 outputs
Outputs of similar age
#176,995
of 316,999 outputs
Outputs of similar age from Frontiers in Physiology
#126
of 277 outputs
Altmetric has tracked 22,992,311 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,752 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 58% of its peers.
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 316,999 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 277 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.