The Role of Interleukin-1β in Murine Cigarette Smoke–Induced Emphysema and Small Airway Remodeling
Bibliographic record
Abstract
Interleukin-1beta (IL-1beta), a proinflammatory cytokine, is elevated in cigarette smokers. To determine whether IL-1beta plays a role in the pathogenesis of cigarette smoke-induced emphysema and small airway remodeling, IL-1 receptor knockout (IL1RKO), TNF-alpha receptor knockout (TNFRKO), or C57Bl/6 (control) mice were exposed to cigarette smoke acutely or for up to 6 months. With a single acute exposure, smoke elevated IL-1beta in C57Bl/6 mice. IL1RKO mice were protected against acute smoke-mediated increases in lavage inflammatory cells and matrix breakdown. In C57Bl/6 mice, acute smoke-mediated increases in inflammatory cells, serum IL-1beta, and serum TNF-alpha were blocked by z-VAD-fmk, a pan-caspase inhibitor, or z-WEHD-fmk, a caspase-1 (IL-1-converting enzyme, [ICE]) inhibitor. With 6 months of exposure, IL-1beta was no longer increased, but IL-18 was elevated. After 6 months of exposure, IL1RKO mice were 65% protected against emphysema, whereas TNFRKO mice were 83% protected. Both strains were completely protected against small airway remodeling. Lavage desmosine, hydroxyproline, and hyaluronan, matrix breakdown markers, were elevated in C57 but not IL1RKO mice. We conclude that IL-1beta plays a significant role in induction of murine emphysema and small airway remodeling, and is comparable to TNF-alpha in its effects. The protective effects of caspase inhibitors appear to be related to inhibition of ICE and raise the question of whether models that ameliorate emphysema with caspase inhibitors are really blocking IL-1beta (and IL-18) activation rather than blocking apoptosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".