Development of a reinforced porcine elastin composite vascular scaffold
Bibliographic record
Abstract
Elastin, a principal structural component of native arteries, has distinct biological and mechanical advantages when used as a biomaterial; however, its low ultimate tensile strength has limited its use as an arterial conduit. We have developed a scaffold, consisting of a purified elastin tubular conduit strengthened with fibrin bonded layers of acellular small intestinal submucosa (aSIS) for potential use as a small diameter vascular graft. The addition of aSIS increased the ultimate tensile strength of the elastin conduits nine-fold. Burst pressures for the elastin composite vascular scaffold (1,396 +/- 309 mmHg) were significantly higher than pure elastin conduits (162 +/- 36 mmHg) and comparable to native saphenous veins. The average suture pullout strength of the elastin composite vascular scaffolds was 14.612 +/- 3.677 N, significantly higher than the pure elastin conduit (0.402 +/- 0.098 N), but comparable to native porcine carotid arteries (13.994 +/- 4.344 N). Cyclic circumferential strain testing indicated that the composite scaffolds were capable of withstanding physiological loading conditions for at least 83 h. Implantation of the elastin composites as carotid interposition grafts in swine demonstrated its superiority to clinically acceptable ePTFE with significantly longer average patency times of 5.23 h compared to 4.15 h. We have developed a biologically based elastin scaffold with suitable mechanical properties and low thrombogenicity for in vivo implantation, and with the potential for cellular repopulation and host integration reestablishing an appropriate elastic artery.
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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) | 0.000 | 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 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".