Peptide‐coated vascular grafts: An <i>in vivo</i> study in sheep
Bibliographic record
Abstract
The data on function and patency of prosthetic vascular grafts in various clinical settings are limited. The purpose of this in vivo study was to compare the function and patency of P15-coated expanded polytetrafluoroethylene (ePTFE) vascular grafts to uncoated ePTFE grafts in sheep. The P15 cell-binding peptide was covalently immobilized onto the surface of ePTFE grafts by a novel atmospheric plasma coating method. We evaluated the amount of neointimal tissue ingrowth present at the arterial and venous sides of the anastomoses and the degree of endothelial cell resurfacing of the luminal surface of the graft. Four P15-coated grafts and two control grafts were implanted as arteriovenous grafts between the femoral artery and vein and the carotid artery and jugular vein in two sheep (n = 6). One animal was euthanized after 14 days and the other after 28 days. The study showed the intimal ingrowth was significantly less. The average intimal thickness of P15-coated grafts (658 microm) was approximately two and a half times less than that of uncoated samples (1657 microm). The newly formed endothelial cell lining was thicker and its coverage was more uniform for P15-coated grafts compared to the uncoated controls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".