The effects of montelukast on tissue inflammatory and bone marrow responses in murine experimental allergic rhinitis: interaction with interleukin‐5 deficiency
Bibliographic record
Abstract
The cysteinyl leukotrienes (cysLTs) are potent lipid mediators in allergic disease, acting through the receptors, cysLT1R and cysLTR2, and are produced by eosinophils derived from eosinophil/basophil (Eo/B) bone marrow (BM) progenitors. We have demonstrated the suppressive effects of either interleukin-5 (IL-5) deficiency or montelukast on eosinophil recruitment in murine allergic rhinitis, but neither of them fully abrogated the symptoms caused by residual inflammation and cytokine redundancy in eliciting BM Eo/B responses. We hypothesized that IL-5 deficiency and montelukast act synergistically to suppress tissue inflammatory and BM responses. Our objective was to investigate the effects of the cysLT1R antagonist, montelukast, on in vivo tissue inflammatory and BM responses in murine experimental allergic rhinitis with or without IL-5 deficiency. Three groups of age-matched BALB/c mice with or without IL-5 deficiency were tested: controls (ovalbumin sensitization and challenge, placebo treatment) and two montelukast-treated groups (2.5 mg/kg or 5 mg/kg). Nasal symptoms, BM and nasal mucosal eosinophils, basophils, and BM Eo/B colony-forming units (CFU) were evaluated. Montelukast decreased nasal symptoms in a dose-dependent manner, and significantly decreased the number of eosinophils in both BM and nasal tissue in IL-5-replete mice compared to controls. In IL-5-deficient mice, in which eosinophilia was absent, montelukast significantly decreased both nasal symptoms and basophils in BM and nasal mucosal tissue, and lowered IL-5-responsive Eo/B-CFU ex vivo, compared to controls. The addition of cysLT1R blockade to IL-5 deficiency more fully attenuates symptoms and upper airway inflammation than either factor alone, providing evidence of systemic, BM mechanisms in allergic rhinitis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".