<i>Aspergillus fumigatus</i>Induces Immunoglobulin E–Independent Mast Cell Degranulation
Bibliographic record
Abstract
BACKGROUND: Pulmonary colonization by Aspergillus fumigatus in chronic lung disease is associated with progressive decline in lung function even in the absence of specific allergic response. We hypothesized that A. fumigatus contributes to this decline by inducing pulmonary mast cell degranulation even in the absence of antigen-specific immunoglobulin E (IgE). Therefore, we investigated whether A. fumigatus can induce mast cell degranulation independently of IgE. METHODS: We studied the interactions of Aspergillus species with mast cells in the absence of IgE in vitro with use of scanning electron microscopy. The extent of mast cell degranulation was quantified by measuring the release of beta-hexosaminidase. RESULTS: Mature A. fumigatus hyphae induced mast cell degranulation in the absence of IgE. Hyphae of Aspergillus flavus, Aspergillus niger, and Aspergillus nidulans induced much less mast cell degranulation. Mast cell degranulation required direct contact with mature A. fumigatus hyphae, and was not induced by conidia or immature hyphae. Killed hyphae induced significant degranulation, whereas live hyphae from mutants deficient in the fungal development regulators StuA and MedA induced very little degranulation. CONCLUSIONS: Factors expressed on the surface of mature A. fumigatus hyphae that are controlled by StuA and MedA induce mast cell degranulation in the absence of IgE.
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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".