Human recombinant activated protein C-coated stent for the prevention of restenosis in porcine coronary arteries
Bibliographic record
Abstract
Activated protein C (APC), an endogenous protein, inhibits inflammation and thrombosis and interrupts the coagulation cascade. Here, we investigated the effect of human recombinant APC on the development of neointimal hyperplasia in porcine coronary arteries. Yukon Choice bare metal stents were coated with 2.6 µg APC/mm(2). Under general anesthesia, APC-coated and bare stents were implanted in the left anterior descending and circumflex coronary arteries of 10 domestic pigs. During the 4-week follow-up, animals were treated with dual antiplatelet therapy and neointimal hyperplasia was evaluated via histology. Scanning electron microscopy indicated successful but unequal coating of stents with APC; nearly complete drug release occurred within 4 h. Enzyme-linked immunosorbent assay revealed that intracoronary stent implantation rapidly increased the levels of monocyte chemoattractant protein-1, an effect that was inhibited by APC release from the coated stent. Fibrin deposition and adventitial inflammation were significantly decreased 1 month after implanting APC-coated stents versus bare stents, paralleled by significantly smaller neointimal area (0.98 ± 0.92 vs. 1.44 ± 0.91 mm(2), P = 0.028), higher lumen area (3.47 ± 0.94 vs. 3.06 ± 0.91 mm(2), P = 0.046), and lower stenosis area (22.2 ± 21.2% vs. 32.1 ± 20.1%, P = 0.034). Endothelialization was complete with APC-coated but not bare (90%) stents. P-selectin immunostaining revealed significantly fewer activated endothelial cells in the neointima in the APC group (4.6 ± 1.9 vs. 11.6 ± 4.1%, P < 0.001). Thus, short exposure of coronary arteries to APC reduced inflammatory responses, neointimal proliferation, and in-stent restenosis, offering a promising therapy to improve clinical outcomes of coronary stenting. However, coating stents with APC for prolonged, controlled drug release remains technically challenging.
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 | 0.000 | 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".