Tissue Engineering the Aortic Valve Spongiosa Using Matrigel‐Cell‐Scaffold‐Composites (MCSCs)
Bibliographic record
Abstract
The middle layer of the aortic valve, termed the spongiosa, consists mainly of glycosaminoglycans (GAGs). Its function is to serve as a shock absorber and resist compression forces between the two outer layers of the valve, and is therefore a necessary component of the bioengineered valve. MCSCs were created by seeding radial artery cells (RACs; 2×10 6 /ml) mixed with endothelial growth media and Matrigel onto small intestinal submucosa, and incubated at 37°C for 0, 1, 2 or 3 weeks. Composites were stained with Alcian Blue for GAGs and immunohistochemistry was used to detect the core protein decorin. Thickness of constructs and cell proliferation were quantified, and gelatin zymography was performed to test for extracellular matrix remodeling. Constructs stayed intact for a minimum of three weeks and stained positively for GAGs and decorin. As culture time increased, MCSC thickness increased. Cell density was stable across all culture times. Zymography revealed the presence of both latent and active matrix metalloproteinase 2. In summary, these composites have shown they are capable of producing GAGs, along with one of their associated core proteins, can lay down new matrix, maintain a constant rate of proliferation, and are likely to be engaging in matrix remodeling. These findings support the use of Matrigel and RACs in our bioengineering efforts. This research is funded by The Heart and Stroke Foundation of Ontario.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".