IL-13 modulates exosome production and miRNAs cargo in bronchial epithelial cells in severe asthma
Bibliographic record
Abstract
Introduction: Asthma is a chronic disease characterized by a prevailing type 2 inflammation and associated with airway remodeling. Exosomes emerged as regulators of cell-cell paracrine communication that transport DNA, lipids and miRNA. Both exosomes and miRNAs were recently shown to participate in asthma physiopathology. In asthmatics, exosomes have been shown to promote inflammation, however, their role in airway remodeling, their modulation and miRNAs cargo under type 2 cytokine stimulation remain unclear in asthma. Objectives: To evaluate the effect of IL-13 on exosome release by bronchial epithelial cells of severe asthmatic subjects compared to healthy controls and packaging of miR-126, -155 and -19a that are involved in cell proliferation and mucus production. Methods: Bronchial epithelial cells (BEC) from healthy donor and severe asthmatics were stimulated or not with recombinant human IL-13. Exosomes were obtained by serial ultracentrifuges. Cells were then harvested and BEC-derived exosomes were quantified using CD63 protein expression by Western Blot. Cellular and exosomes-derived miR-126, -155 and -19a expression was assessed by q-PCR. Results: BEC from severe asthma produce more exosomes than cells from healthy donors. IL-13 stimulation increased exosomes production in BEC from severe asthma compared to BEC from controls. At baseline, BEC from severe asthma express and release in their exosomes more miR-155, -126 and -19a than controls and this effect is increased by IL-13 stimulation. Conclusion: We show that IL-13 increases BEC-derived exosome release and modifies their miRNAs cargo indicating a potential role of type 2 cytokine-exosome axis in 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".