Novel Mechanism of Aortic Aneurysm Development in Mice Associated With Smoking and Leukocytes
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to evaluate potential mechanisms promoting abdominal aortic aneurysm development with tobacco smoke (TS) exposure. METHODS AND RESULTS: Experiments used the elastase perfusion model of abdominal aortic aneurysms with smoke-free controls. The effect of TS exposure was evaluated in C57/Bl6 mice, after broad-spectrum matrix metalloproteinase inhibition with doxycycline and in mice deficient in matrix metalloproteinase-9, matrix metalloproteinase-12, Cathepsin-S, and Neutrophil Elastase. Preparations of washed marrow, spleen, and peripheral blood leukocytes were transferred to smoke-free mice from 6-week TS-exposed mice or smoke-free mice. All mice were euthanized 14 days after elastase perfusion, and the percentage of change in aortic diameter (%Δ aortic diameter) was calculated. Electron microscopy of aortic tissue from animals exposed to TS without elastase exposure did not demonstrate any ultrastructural changes. Neither doxycycline nor any specific elastase deficiency was effective at preventing an increase in %Δ aortic diameter in TS-exposed animals. Smoke exposure for 6 weeks increased the %Δ aortic diameter after a smoke-free interval of up to 6 weeks before elastase perfusion. Leukocyte preparations from TS-exposed mice localized to abdominal aortic aneurysms and increased the %Δ aortic diameter in smoke-free mice. CONCLUSIONS: The effect of TS on the development of abdominal aortic aneurysms is not dependent on the activity of elastolytic enzymes and persists for long periods despite cessation of TS. Alterations in leukocyte response to aortic injury appear to mediate this effect.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".