Development and mechanical characterization of decellularized scaffolds for an active aortic graft
Bibliographic record
Abstract
Decellularized porcine aortas are proposed as scaffolds for revolutionary active aortic grafts. A change in the static and dynamic mechanical properties, associated with the microstructure of elastin and collagen fibers, corresponds to alteration in the cyclic expansion and perfusion, in addition to possible graft damage. Therefore, the present study thoroughly investigates the mechanical response of the decellularized scaffolds of human and porcine origin to static and dynamic mechanical loads. The responses of the native human and porcine aortas are also compared; this is unavailable in the literature. Because the aorta is subjected to pulsatile blood pressure, dynamical responses to cyclic loads and their associated viscoelastic properties are particularly relevant for advanced graft design. In parallel, this study examines the microstructure of the decellularized aorta. The resulting data are compared to the analogous data obtained for the native human and porcine tissues. The results indicate that by using an optimized decellularization protocol - based on sodium dodecyl sulfate (SDS) and DNase - that minimizes mechanical and structural changes of the tissue, layered scaffolds with static and dynamic properties very similar to natural human aortas are obtained. In particular, a decellularized porcine aorta is non-inferior to a decellularized human aorta. STATEMENT OF SIGNIFICANCE: About 55,000 patients undergo abdominal aortic aneurysm repair annually in the USA. The currently implanted grafts present a large mechanical mismatch with the native tissue. This increases the pulsatile nature of the blood flow with negative consequences to the organ perfusion. For this reason, biomimetic and mechanically compatible grafts for aortic repair are urgently needed and they can be obtained through tissue engineering. In this study, scaffolds from porcine and human aortas are obtained from an optimized decellularization protocol. They are accurately compared to the native tissue and present the ideal static and dynamic mechanical properties for developing innovative aortic grafts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".