Bleomycin promotes cellular senescence and activation of the cGAS-STING pathway without direct effect on fibrosis in an idiopathic pulmonary fibrosis model
Bibliographic record
Abstract
Bleomycin is an effective anticancer agent that causes drug-induced interstitial pneumonia (IP). Medical history is a risk factor for adverse effects, particularly a history of IP and age-related fibrosis. Anti-cancer drugs for lung cancer with idiopathic pulmonary fibrosis (IPF) often aggravate pulmonary fibrosis. Thus, we examined the pathological effects of bleomycin, an anticancer drug, in precision-cut lung slices (PCLS) of lungs with usual interstitial pneumonia (UIP). We found that the lungs of mice with induced UIP (iUIP), which exhibit a pathology similar to that of IPF, underwent accelerated senescence. Treatment of iUIP PCLS with bleomycin reduced the nuclear membrane component lamin B1 and nuclear DNA with γH2AX leaked into the cytoplasm. This perinuclear DNA may activate NF-κB through the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway. As a result, the unresolved DNA damage associated with the failure of DNA repair and senescence progression is more advanced in these cells. However, Col1a1 and Acta2 expression was not induced in either bleomycin-treated normal or iUIP PCLS, suggesting that there was no direct fibrotic effect on the lungs. We concluded that lungs with iUIP exhibited accelerated senescence following bleomycin treatment, leading to cell death.
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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) | 0.000 | 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".