Interleukin-1α drives the dysfunctional cross-talk of the airway epithelium and lung fibroblasts in COPD
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) has been associated with aberrant epithelial-mesenchymal interactions resulting in inflammatory and remodelling processes. We developed a co-culture model using COPD and control-derived airway epithelial cells (AECs) and lung fibroblasts to understand the mediators that are involved in remodelling and inflammation in COPD.AECs and fibroblasts obtained from COPD and control lung tissue were grown in co-culture with fetal lung fibroblast or human bronchial epithelial cell lines. mRNA and protein expression of inflammatory mediators, pro-fibrotic molecules and extracellular matrix (ECM) proteins were assessed.Co-culture resulted in the release of pro-inflammatory mediators interleukin (IL)-8/CXCL8 and heat shock protein (Hsp70) from lung fibroblasts, and decreased expression of ECM molecules (e.g. collagen, decorin) that was not different between control and COPD-derived primary cells. This pro-inflammatory effect was mediated by epithelial-derived IL-1α and increased upon epithelial exposure to cigarette smoke extract (CSE). When exposed to CSE, COPD-derived AECs elicited a stronger IL-1α response compared with control-derived airway epithelium and this corresponded with a significantly enhanced IL-8 release from lung fibroblasts.We demonstrate that, through IL-1α production, AECs induce a pro-inflammatory lung fibroblast phenotype that is further enhanced with CSE exposure in COPD, suggesting an aberrant epithelial-fibroblast interaction in COPD.
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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".