Effects of a cysteinyl leukotriene receptor antagonist on eosinophil recruitment in experimental allergic rhinitis
Bibliographic record
Abstract
The cysteinyl leukotrienes (cysLTs) are potent lipid mediators in allergic disease, acting through a receptor (cysLT1-R) which can be targeted in rhinitis and asthma. We investigated the effects of cysLT1-R antagonism in experimental allergic rhinitis, focusing on bone marrow eosinophil progenitor responses. BALB/c mice were sensitized, then given daily intranasal ovalbumin for 2 weeks, with montelukast sodium (5 mg/kg or 2.5 mg/kg) or placebo by gavage. Bone marrow eosinophil/basophil colonies were enumerated, and colony cells were morphologically assessed as indices of eosinophil differentiation and maturation. Montelukast treatment resulted in a significant decrease of eosinophils in the nasal mucosa, and in either bone marrow interleukin (IL)-5-, but not IL-3-, or granulocyte-macrophage colony-stimulating factor-responsive eosinophil/basophil colony-forming units, and IL-5-stimulated eosinophil maturation. These results indicate that cysLT1-R antagonism in vivo limits both IL-5-responsive eosinophilopoiesis, acting at several stages of eosinophil differentiation and maturation. The anti-allergic effects of cysLT1-R antagonists are consistent with the concept that cysLTs and IL-5 act together in the recruitment of eosinophils and eosinophil progenitors from the marrow during upper airway 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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".