Relationship between Platelets and Neutrophil Adhesion and Neointimal Growth after Repeated Arterial Wall Injury Induced by Angioplasty in Pigs
Bibliographic record
Abstract
Platelet and neutrophil interactions with injured vascular wall may contribute to restenosis. Their importance was mainly examined following balloon injury of intact arteries. However, dilation of diseased arteries is clinically more relevant and may elicit different responses. We investigated the relationship between platelets and neutrophil adhesion, neointima formation and P-selectin expression on damaged arteries after repeated balloon injury. In an acute single-injury model, 8 pigs were subjected to bilateral carotid angioplasty and sacrificed 1 h later. In a chronic model, 19 pigs were subjected to similar procedures and allowed to recover for 4 weeks; then 18 arteries were redilated at the same previously injured sites (double injury) while the remaining arteries were not redilated and used to investigate the extent and the adhesive properties of the neointima. After single injury, (51)Cr-platelet adhesion (x10(6)/cm(2)) increased significantly from 3.8 +/- 0.6 to 45.9 +/- 6.5 (p < 0.05) on mildly and deeply injured segments, respectively, and were statistically similar after double injury. After single injury, (111)In-neutrophil adhesion (x10(3)/cm(2)) increased from 226.6 +/- 45.5 to 512.5 +/- 70.3 (p < 0.05) on mildly and deeply injured segments, and were significantly higher (p < 0.05) after double injury (mild: 1,289.1 +/- 227.9 and deep: 2,411.8 +/- 333.9). As well, the neo-endothelium expresses P-selectin at 4 weeks and platelet and neutrophil adhesion was directly related to neointimal growth. These results, which indicate ongoing proinflammatory processes 1 month post-angioplasty, suggest that neutrophils may participate in the progression of restenosis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".