Mast Cell-Deficient KitW-sh Mice Develop House Dust Mite-Induced Lung Inflammation despite Impaired Eosinophil Recruitment
Bibliographic record
Abstract
BACKGROUND: Mast cells are implicated in allergic and innate immune responses in asthma, although their role in models using an allergen relevant for human disease is incompletely understood. House dust mite (HDM) allergy is common in asthma patients. Our aim was to investigate the role of mast cells in HDM-induced allergic lung inflammation. METHODS: Wild-type (Wt) and mast cell-deficient Kit(w-sh) mice on a C57BL/6 background were repetitively exposed to HDM via the airways. RESULTS: HDM challenge resulted in a rise in tryptase activity in bronchoalveolar lavage fluid (BALF) of Wt mice, indicative of mast cell activation. Kit(w-sh) mice showed a strongly attenuated HDM- induced recruitment of eosinophils in BALF and lung tissue, accompanied by reduced pulmonary levels of the eosinophil chemoattractant eotaxin. Remarkably, Kit(w-sh) mice demonstrated an unaltered capacity to develop lung pathology and increased mucus production in response to HDM. The increased plasma IgE in response to HDM in Wt mice was absent in Kit(w-sh) mice. CONCLUSION: These data contrast with previous reports on the role of mast cells in models using ovalbumin as allergen in that C57BL/6 Kit(w-sh) mice display a selective impairment of eosinophil recruitment without differences in other features of allergic inflammation.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".