IL-5 enhances human mast cell survival and interferon responses to viral infection
Bibliographic record
Abstract
BACKGROUND: Mast cells are important sentinel cells in defense against mucosal infection. Exacerbations of allergic asthma and asthma deaths have been associated with respiratory viral infections. Elevated levels of IL-5 have been associated with the pathogenesis of severe atopic diseases, many of which respond to IL-5 blockade. OBJECTIVE: We sought to examine the impact of IL-5 signaling on mast cells infected with respiratory viruses. METHODS: Cord blood-derived human mast cells were treated with IL-5 or left untreated and infected with human coronavirus OC43, respiratory syncytial virus (RSV), or oncolytic reovirus. Mast cell expression of interferons and of interferon-stimulated genes was evaluated. Total RNA sequencing was performed to determine the impact of IL-5 on the transcriptome of human mast cells, and related functional assays were performed. RESULTS: IL-5-treated mast cells produced significantly more type I and III interferons than did controls not treated with IL-5. Mechanistically, IL-5 treatment led to greater expression of the prosurvival factor B-cell lymphoma 2 (BCL2) and endothelial PAS domain protein 1 (EPAS1) and protected mast cells from apoptosis-induced stress. IL-5 blockade was associated with a decrease in EPAS1 expression in the peripheral blood of asthmatic patients, as shown by transcriptomic data from clinical trials of mepolizumab and benralizumab. CONCLUSIONS: IL-5 signaling selectively promotes interferon responses in mast cells and maintains mast cell populations during mucosal viral infection via a novel IL-5/EPAS1 axis.
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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) | 0.000 | 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) | 0.000 | 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".