The Development and Application of Tools to Study the Multiscale Biomechanics of the Aortic Valve
Bibliographic record
Abstract
Calcific aortic valve disease (CAVD) is one of the most common causes of cardiovascular disease in North America. Mechanical factors have been closely linked to the pathogenesis of CAVD and may contribute to the disease by actively regulating the mechanobiology of valve interstitial cells (VICs). Mechanical forces affect VIC function through interactions between the VIC and the extracellular matrix (ECM). Studies have shown that the transfer of mechanical stimulus during cell-ECM interaction depends on the local material properties at hierarchical length scales encompassing tissue, cell and cytoskeleton. In this thesis, biomechanical tools were developed and applied to investigate hierarchical cell-ECM interactions, using VICs and valve tissue as a model system. Four topics of critical importance to understanding VIC-ECM interactions were studied: focal biomechanical material properties of aortic valve tissue; viscoelastic properties of VICs; transduction of mechanical deformation from the ECM to the cytoskeletal network; and the impact of altered cell-ECM interactions on VIC survival. To measure focal valve tissue properties, a micropipette aspiration (MA) method was implemented and validated. It was found that nonlinear elastic properties of the top layer of a multilayered biomaterial can be estimated by MA by using a pipette with a diameter smaller than the top layer thickness. Using this approach, it was shown that the effective stiffness of the fibrosa layer is greater than that of the ventricularis layer in intact aortic valve leaflets (p<0.01). To characterize the viscoelastic properties of VICs, an inverse FE method of single cell MA was developed and compared with the analytical half-space model. It was found that inherent differences in the half-space and FE models of single cell MA yield different cell viscoelastic material parameters. However, under particular experimental conditions, the parameters estimated by the half-space model are statistically indistinguishable from those predicted by the FE model. To study strain transduction from the ECM to cytoskeleton, an improved texture correlation algorithm and a uniaxial tension release device were developed. It was found that substrate strain fully transfers to the cytoskeletal network via focal adhesions in live VICs under large strain tension release. To study the effects of cell-ECM interactions on VIC survival, two mechanical stimulus systems that can simulate the separate effects of cell contraction and cell monolayer detachment were developed. It was found that cell sheet detachment and disrupted cell-ECM signaling is likely responsible for the apoptosis of VICs grown in culture on thin collagen matrices, leading to calcification. The studies presented in this thesis refine existing biomechanical tools and provide new experimental and analytical tools with which to study cell-ECM interactions. Their application resulted in an improved understanding of hierarchical valve biomechanics, mechanotransduction, and mechanobiology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".