The Effect of Pranlukast on Allergen-induced Bone Marrow Eosinophilopoiesis in Subjects with Asthma
Bibliographic record
Abstract
We investigated the mechanisms by which leukotriene receptor antagonists decrease airway eosinophil number. In a randomized, double-blind crossover study, we examined the effects of 2 weeks of treatment with pranlukast 300 mg twice a day or placebo on allergen-induced changes in airway eosinophil number and bone marrow eosinophil progenitors in 15 subjects with mild asthma. Pranlukast treatment for 2 weeks decreased mean sputum eosinophil count from 0.15 x 10(6)/g (5.3% of cells) before treatment to 0.02 x 10(6)/g (0.7% of cells) after treatment (p < 0.05), whereas placebo did not. Pranlukast also decreased the eosinophil count (5.6% at 7 hours and 7.5% at 24 hours) (p < 0.05) after allergen inhalation compared with placebo (13.8% at 7 hours and 15.3% at 24 hours). There was a similar trend for sputum cells immunostaining for EG2, eotaxin, interleukin-5, and regulated upon activation, normal T cell expressed and secreted. Pranlukast also significantly attenuated the allergen-induced increase in the number of bone marrow eosinophil/basophil cfu (mean 0.3) at 24 hours compared with placebo (mean 6.2). The proportion of CD34(+) cells expressing the eotaxin receptor CC chemokine receptor 3, 24 hours after allergen inhalation, was also reduced by pranlukast. We conclude that, the cysteinyl leukotriene receptor antagonist, pranlukast, attenuates allergen-induced increase in airway eosinophils by decreasing bone marrow eosinophilopoiesis and airway chemotactic and eosinophilopoietic cytokines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".