Macrophage Metalloelastase Mediates Acute Cigarette Smoke–induced Inflammation via Tumor Necrosis Factor-α Release
Bibliographic record
Abstract
The cells and proteases that mediate cigarette smoke-induced emphysema are controversial, with evidence favoring either neutrophils and neutrophil-derived serine proteases or macrophages and macrophage-derived metalloproteases as the important effectors. We recently reported that both macrophage metalloelastase (MMP-12) and neutrophils are required for acute cigarette smoke-induced connective tissue breakdown, the precursor of emphysema. Here we show how these disparate observations can be linked. Both wild-type (MMP-12 +/+) mice and mice lacking MMP-12 (MMP-12 -/-) demonstrated rapid increases in whole-lung nuclear factor-kappaB activation and gene expression of proinflammatory cytokines after cigarette smoke exposure, indicating that a lack of MMP-12 does not produce a global failure to upregulate inflammatory mediators. However, only MMP-12 +/+ mice demonstrated increased whole-lung tumor necrosis factor-alpha (TNF-alpha) protein or release of TNF-alpha from cultured alveolar macrophages exposed to smoke in vitro. Levels of whole-lung E-selectin, an endothelial activation marker, were increased in only MMP-12 +/+ mice. These findings suggest that, acutely, MMP-12 mediates smoke-induced inflammation by releasing TNF-alpha from macrophages, with subsequent endothelial activation, neutrophil influx, and proteolytic matrix breakdown caused by neutrophil-derived proteases. TNF-alpha release may be a general mechanism whereby metalloproteases drive cigarette smoke-induced inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".