Mast Cells, FcεRI, and IL-13 Are Required for Development of Airway Hyperresponsiveness after Aerosolized Allergen Exposure in the Absence of Adjuvant
Bibliographic record
Abstract
In certain models of allergic airway disease, mast cells facilitate the development of inflammation and airway hyper-responsiveness (AHR). To define the role of the high affinity IgE receptor (FcepsilonRI) in the development of AHR, mice with a disruption of the alpha subunit of the high affinity IgE receptor (FcepsilonRI(-/-)) were exposed on 10 consecutive days to nebulized OVA. Forty-eight hours after the last nebulization, airway responsiveness was monitored by the contractile response of tracheal smooth muscle to electrical field stimulation (EFS). After the 10-day OVA challenge protocol, wild-type mice demonstrated increased responsiveness to EFS, whereas similarly challenged FcepsilonRI(-/-) mice showed a low response to EFS, similar to nonexposed animals. Further, allergen-challenged FcepsilonRI(-/-) mice showed less airway inflammation, goblet cell hyperplasia, and lower levels of IL-13 in lung homogenates compared with the controls. IL-13-deficient mice failed to develop an increased response to EFS or goblet cell hyperplasia after the 10-day OVA challenge. We transferred bone marrow-derived mast cells from wild-type mice to FcepsilonRI(-/-) mice 1 day before initiating the challenge protocol. After the 10-day OVA challenge, recipient FcepsilonRI(-/-) mice demonstrated EFS-induced responses similar to those of challenged wild-type mice. Transferred mast cells could be detected in tracheal preparations. These results show that FcepsilonRI is important for the development of AHR after an aerosolized allergen sensitization protocol and that this effect is mediated through FcepsilonRI on mast cells and production of IL-13 in the lung.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".