A New Construction Technique for Tissue-Engineered Heart Valves Using the Self-Assembly Method
Bibliographic record
Abstract
Tissue engineering appears as a promising option to create new heart valve substitutes able to overcome the serious drawbacks encountered with mechanical substitutes or tissue valves. The objective of this article is to present the construction method of a new entirely biological stentless aortic valve using the self-assembly method and also a first assessment of its behavior in a bioreactor when exposed to a pulsatile flow. A thick tissue was created by stacking several fibroblast sheets produced with the self-assembly technique. Different sets of custom-made templates were designed to confer to the thick tissue a three-dimensional (3D) shape similar to that of a native aortic valve. The construction of the valve was divided in two sequential steps. The first step was the installation of the thick tissue in a flat preshaping template followed by a 4-week maturation period. The second step was the actual cylindrical 3D forming of the valve. The microscopic tissue structure was assessed using histological cross sections stained with Masson's Trichrome and Picrosirius Red. The thick tissue remained uniformly populated with cells throughout the construction steps and the dense extracellular matrix presented corrugated fibers of collagen. This first prototype of tissue-engineered heart valve was installed in a bioreactor to assess its capacity to sustain a light pulsatile flow at a frequency of 0.5 Hz. Under the light pulsed flow, it was observed that the leaflets opened and closed according to the flow variations. This study demonstrates that the self-assembly method is a viable option for the construction of complex 3D shapes, such as heart valves, with an entirely biological material.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".