Elevated IL-17A in very severe COPD is localized to mast cells and correlates with lung function decline
Bibliographic record
Abstract
Escalation and progression of chronic obstructive pulmonary disease (COPD) is poorly understood. Interleukin (IL)-17A plays a complex role in immunity and is increased in peripheral lung tissue of mild/moderate COPD and in the bronchial mucosa of severe COPD, suggesting a potential role in pathogenesis. The expression of IL-17A has, however, not been determined in very severe COPD. We hypothesized that the expression of IL-17A is increased in peripheral lung tissue of very severe COPD, and is associated with lung function decline. Automated immunodetection of IL-17A and cell specific markers was performed in lung tissue specimens collected from patients with GOLD stage I-IV COPD, as well as from smoking and never-smoking controls. Expression of immunoreactivity was quantified using digital image analysis. Increased expression of IL-17A was observed in COPD compared to smoking and never-smoking controls, and expression of IL-17A correlated with lung function decline. Further analysis revealed that IL-17A was only significantly elevated in severe-very severe COPD (GOLD III/IV), compared to asymptomatic never-smokers as well as current smokers. While small a proportion of CD3+ T cells expressed IL-17A in very severe COPD, the majority of IL-17A+ cells were identified as tryptase+ mast cells. The increased expression of IL-17A in the peripheral lung of patients with advanced COPD correlates with lung function decline and is suggestive of a potential role in disease progression. Furthermore, IL-17A was foremost localized to mast cells underscoring a role of this cell type in the immunopathology of 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".