Lung exposure to lipopolysaccharide causes atherosclerotic plaque destabilisation
Bibliographic record
Abstract
Epidemiological studies have implicated lung inflammation as a risk factor for acute cardiovascular events, but the underlying mechanisms linking lung injury with cardiovascular events are largely unknown.Our objective was to develop a novel murine model of acute atheromatous plaque rupture related to lung inflammation and to investigate the role of neutrophils in this process.Lipopolysaccharide (LPS; 3 mg·kg(-1)) or saline (control) was instilled directly into the lungs of male apolipoprotein E-null C57BL/6J mice following 8 weeks of a Western-type diet. 24 h later, atheromas in the right brachiocephalic trunk were assessed for stability ex vivo using high-resolution optical projection tomography and histology. 68% of LPS-exposed mice developed vulnerable plaques, characterised by intraplaque haemorrhage and thrombus, versus 12% of saline-exposed mice (p=0.0004). Plaque instability was detectable as early as 8 h post-intratracheal LPS instillation, but not with intraperitoneal instillation. Depletion of circulating neutrophils attenuated plaque rupture.We have established a novel plaque rupture model related to lung injury induced by intratracheal exposure to LPS. In this model, neutrophils play an important role in both lung inflammation and plaque rupture. This model could be useful for screening therapeutic targets to prevent acute vascular events related to lung inflammation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".