IL-13 modulates exosome production and miRNAs cargo in bronchial epithelial cells in severe asthma
Bibliographic record
Abstract
<b>Introduction:</b> Asthma is a chronic disease characterized by inflammation and airway remodeling. Both exosomes and miRNAs were shown to participate in asthma physiopathology. Exosomes have been shown to promote inflammation, however, their modulation and miRNAs cargo under type 2 cytokine stimulation remain unclear. <b>Objectives:</b> To evaluate the effect of IL-13 on exosome release by bronchial epithelial cells (BEC) obtained from bronchial biopsies of severe asthmatic subjects compared to healthy controls and packaging of miR-126, -155 and -19a. <b>Methods:</b> BEC from healthy donor and severe asthmatics were stimulated or not with recombinant human IL-13. Exosomes were obtained by serial ultracentrifuges and were quantified using CD63 protein expression by Western Blot. Cellular and exosomes-derived miR-126, -155 and -19a expression were assessed by q-PCR. miR-155 was modulated in BEC with specific miR-155 mimic or inhibitor. <b>Results:</b> BEC from severe asthmatic subjects express more miR-155, -126 and -19a than cells from healthy donors and this feature is increased under IL-13 stimulation. Moreover, BEC from severe asthmatic release more exosome with an increased cargo of miR-155, -126 and -19a than cells from healthy donors. Overexpression of miR-155 in BEC increased IL-13Rα1 gene expression while its inhibition is associated with a reduce IL-13Rα1 expression in both asthmatic and healthy donors. Conclusion In severe asthma, bronchial epithelial cells release more exosomes and these latter contain more miRNAs than bronchial epithelial cells from healthy donors. These features increase under IL-13 stimulation, suggesting a potential role of type 2 cytokine-exosome axis in severe asthma.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".