Th17 cytokines induce pro-fibrotic cytokines release from human eosinophils
Bibliographic record
Abstract
BACKGROUND: Subepithelial fibrosis is one of the most critical structural changes affecting bronchial airway function during asthma. Eosinophils have been shown to contribute to the production of pro-fibrotic cytokines, TGF-β and IL-11, however, the mechanism regulating this process is not fully understood. OBJECTIVE: In this report, we investigated whether cytokines associated with inflammation during asthma may induce eosinophils to produce pro-fibrotic cytokines. METHODS: Eosinophils were isolated from peripheral blood of 10 asthmatics and 10 normal control subjects. Eosinophils were stimulated with Th1, Th2 and Th17 cytokines and the production of TGF-β and IL-11 was determined using real time PCR and ELISA assays. RESULTS: The basal expression levels of eosinophil derived TGF-β and IL-11 cytokines were comparable between asthmatic and healthy individuals. Stimulating eosinophils with Th1 and Th2 cytokines did not induce expression of pro-fibrotic cytokines. However, stimulating eosinophils with Th17 cytokines resulted in the enhancement of TGF-β and IL-11 expression in asthmatic but not healthy individuals. This effect of IL-17 on eosinophils was dependent on p38 MAPK activation as inhibiting the phosphorylation of p38 MAPK, but not other kinases, inhibited IL-17 induced pro-fibrotic cytokine release. CONCLUSIONS: Th17 cytokines might contribute to airway fibrosis during asthma by enhancing production of eosinophil derived pro-fibrotic cytokines. Preventing the release of pro-fibrotic cytokines by blocking the effect of Th17 cytokines on eosinophils may prove to be beneficial in controlling fibrosis for disorders with IL-17 driven inflammation such as allergic and autoimmune diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".