Nitric Oxide‐Mediated Growth Inhibition of an Endothelialized Tissue Engineered Aortic Valve
Bibliographic record
Abstract
The tissue engineering (TE) of aortic valves may provide an alternative to the use of non‐viable bioprosthetic replacements. Endothelialization of a TE construct is necessary to establish a non‐thrombogenic surface and has been shown to inhibit the proliferation of vascular smooth muscle cells within the construct. Previously it has been shown that nitric oxide (NO) production by endothelial cells may be responsible for this growth inhibition. To test this hypothesis, cells scaffold constructs (CSCs) were produced consisting of radial artery cells seeded onto small intestine submucosa. After one week in culture, an analog inhibitor of nitric oxide synthase, L‐iminoethyl‐L‐orthinine (L‐NIO, 100 μM) was added to either CSCs or endothelialiazed CSCs (ECSCs). Constructs were cultured for an additional week, followed by fixation and tissue thickness analysis by confocal microscopy. ECSC and CSC control groups were cultured for two weeks in the absence of L‐NIO. The presence of an endothelium (ECSCs) significantly inhibited growth of the construct, however, in the presence of L‐NIO, growth of the construct continued in a manner similar to CSCs (75.6μ m vs 55.3μm). Results suggest that the production of NO by the endothelium may be responsible for growth inhibition of the ECSCs providing a valuable tool for controlling TE valve construct thickness in vitro . Funding provided by 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".