IL-22 contributes to TGF-β1-mediated epithelial-mesenchymal transition in asthmatic bronchial epithelial cells
Bibliographic record
Abstract
BACKGROUND: Allergic asthma is characterized by airway inflammation in response to antigen exposure, leading to airway remodeling and lung dysfunction. Epithelial-mesenchymal transition (EMT) may play a role in airway remodeling through the acquisition of a mesenchymal phenotype in airway epithelial cells. TGF-β1 is known to promote EMT; however, other cytokines expressed in severe asthma with extensive remodeling, such as IL-22, may also contribute to this process. In this study, we evaluated the contribution of IL-22 to EMT in primary bronchial epithelial cells from healthy and asthmatic subjects. METHODS: Primary bronchial epithelial cells were isolated from healthy subjects, mild asthmatics and severe asthmatics (n=5 patients per group). The mRNA and protein expression of epithelial and mesenchymal cell markers and EMT-associated transcription factors was evaluated following stimulation with TGF-β1, IL-22 and TGF-β1+IL-22. RESULTS: Primary bronchial epithelial cells stimulated with TGF-β1 underwent EMT, demonstrated by decreased expression of epithelial markers (E-cadherin and MUC5AC) and increased expression of mesenchymal markers (N-cadherin and vimentin) and EMT-associated transcription factors. IL-22 alone had no effect on epithelial or mesenchymal gene expression. However, IL-22+TGF-β1 promoted the expression of some EMT transcription factors (Snail1 and Zeb1) and led to a more profound cadherin shift, but only in cells obtained from severe asthmatics. CONCLUSION: The impact of IL-22 on airway epithelial cells depends on the cytokine milieu and the clinical phenotype of the patient. Further studies are required to determine the molecular mechanism of IL-22 and TGF-β1 cooperativity in driving EMT in primary human bronchial epithelial cells.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 | 0.006 |
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".