Suppressed smooth muscle proliferation and inflammatory cell invasion after arterial injury in elafin-overexpressing mice
Bibliographic record
Abstract
Elastases degrade the extracellular matrix, releasing growth factors and chemotactic peptides, inducing glycoproteins such as tenascin, and thereby promoting vascular cell proliferation and migration. Administration of serine elastase inhibitors reduces experimentally induced vascular disease. The ability to mount an intrinsic anti-elastase response may, therefore, protect against intimal/medial thickening after vascular injury. To investigate this, we showed that wire-induced endothelial denudation of the carotid artery is associated with transient elevation in elastase activity and confirmed that this is abolished in transgenic mice overexpressing the serine elastase inhibitor, elafin, targeted to the cardiovascular system. Ten days after injury, nontransgenic littermates show vessel enlargement, intimal thickening, increased medial area and cellularity, and 2-fold increase in tenascin. Injured vessels in transgenic mice become enlarged but are otherwise similar to sham-operated controls. Injury-induced vessel wall thickening, which is observed only in nontransgenic mice, is related to foci of neutrophils and macrophages, in addition to smooth muscle cells that fail to stain for alpha-actin and are likely dedifferentiated. Our study therefore suggests that a major determinant of the vascular response to injury is the early transient induction of serine elastase activity, which leads to cellular proliferation and inflammatory cell migration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".