Tumour necrosis factor-related apoptosis inducing ligand promotes the development of experimental chronic obstructive pulmonary disease (MUC1P.905)
Bibliographic record
Abstract
Abstract Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide and causes significant healthcare and economic burden. Cigarette smoking is a major risk factor. There is a lack of effective treatments for COPD due to the poor understanding of the underlining mechanisms. Tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) is implicated in respiratory diseases such as asthma and pulmonary fibrosis. However, the role of TRAIL in the pathogenesis of COPD is unknown. In this study, TRAIL mRNA expression and/or protein levels in the lung (airway and parenchyma) and serum were increased in a mouse model of cigarette smoke-induced experimental COPD. Genetic deletion of TRAIL significantly reduced cigarette smoke-induced pulmonary inflammation, expression of key pro-inflammatory mediators, emphysema-like alveolar enlargement and improved lung function in experimental COPD. Interestingly, genetic deletion of TRAIL led to spontaneous small airway remodelling characterized by increased airway epithelial cell thickness and collagen deposition. Importantly, antibody-mediated neutralization of TRAIL reduced cigarette smoke-induced pulmonary inflammation, emphysema-like alveolar enlargement and small airway remodelling. Our study is the first to show that TRAIL plays an important role in the pathogenesis of COPD and provides further evidence for TRAIL being a pivotal inflammatory cytokine in respiratory diseases.
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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) | 0.003 | 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".