MicroRNA-155-5p Differentially Regulates IL-13Rα1 and IL-13Rα2 Expression and Signaling Driving Abnormal Lung Epithelial Cell Phenotype in Severe Asthma
Bibliographic record
Abstract
Abstract MicroRNA (miR)-155-5p increases in innate and adaptive immune cells in response to IL-13 and is associated with the severity of asthma. However, little is known about its role in airway structural cells. Bronchial epithelial cells (BECs) isolated from healthy donors and patients with severe asthma were stimulated with IL-13. miR-155-5p expression and release were measured by real-time (RT)-PCR in BECs and in their derived exosomes. Modulation of miR-155-5p in BECs was performed using transfection of miR-155-5p inhibitor and mimic. IL-13 receptor α1 (IL-13Rα1), IL-13Rα2, MUC5AC, IL-8, and eotaxin-1 expression was measured by RT-PCR and Western blot analysis. The BEC repair process was assessed by a wound-healing assay. IL-13Rα1 and IL-13Rα2 expression and downstream pathways were evaluated by Western blot analysis. A dual luciferase assay was used to identify miR-155-5p target genes associated with IL-13R signaling. BECs from patients with severe asthma showed increased expression and exosomal release of miR-155-5p at baseline with amplification by IL-13 stimulation. BECs from patients with asthma expressed more IL-13Rα1 and less IL-13Rα2 than those from healthy donors, and IL-13Rα1 but not IL-13Rα2 induced miR-155-5p expression under IL-13 stimulation. miR-155-5p overexpression favored MUC5AC, IL-8, and Eotaxin-1 through the IL-13Rα1/SOCS1/STAT6 pathway while delaying the repair process by downregulating IL-13Rα2/MAPK14/c-Jun/c-fos signaling. The dual luciferase assay confirmed that miR-155-5p modulates both IL-13R pathways by directly targeting SOCS1, c-fos, and MAPK14. miR-155-5p is overexpressed in BECs from patients with severe asthma and regulates IL-13Rα1 and IL-13Rα2 expression and signaling, favoring expression of mucin- and eosinophil-related genes to the detriment of airway repair. These results show that miR-155-5p may contribute to airway epithelial cell dysfunction in patients with severe asthma.
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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 | 0.000 |
| 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".