Activation of STAT3 in the COPD airway epithelium
Bibliographic record
Abstract
Rationale The mechanisms driving epithelial pathology in COPD are steadily being unveiled, confirming a role for inflammation in the disease. This study explored the interleukin (IL)-6/STAT3 axis, previously reported to link inflammation and epithelial-to-mesenchymal transition, two features of COPD at the airway epithelium level. Methods Bronchoalveolar lavage fluid (BALF) and surgical lung tissue were obtained from nonsmoker controls, smokers and COPD patients. The activation of STAT3 and IL-6 levels were measured in these samples. Primary air–liquid interface (ALI) cultures were carried out from nonsmokers, smokers and COPD patients, and IL-6 release and STAT3 mRNA levels were assessed. BEAS-2B cell cultures were exposed to sputum supernatants from COPD patients versus nonsmokers, with and without a pan-gp130 blocking monoclonal antibody. Finally, primary ALI cultures from nonsmokers were exposed to IL-6 versus vehicle and assessed for epithelial-to-mesenchymal transition and cell differentiation. Results IL-6 and Tyr705-phospho-STAT3 levels were increased in samples from COPD patients compared to controls, both in BALF and in the airway epithelium, as well as in ALI cultures. BEAS-2B cells exposed to COPD sputum supernatants displayed STAT3 activation that was inhibited by the pan-gp130 blocking monoclonal antibody. In addition, stimulation of ALI cultures with IL-6 induced increased vimentin expression and fibronectin release and reduced the expression of apical junctional complexes proteins, indicating epithelial-to-mesenchymal transition. Finally, no impact on airway cell differentiation was observed. Conclusions The IL-6/STAT3 axis is activated in the COPD airway epithelium, presumably contributing to epithelial-to-mesenchymal transition.
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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) | 0.002 | 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".