Late-breaking abstract: Effects of a dual CysLT1/2 antagonist, ONO-6950, on allergen-induced airway responses in subjects with mild allergic asthma
Bibliographic record
Abstract
Background: The cysteinyl leukotrienes (CysLTs) play a key role in the pathophysiology of asthma. In addition to functioning as potent bronchoconstrictors, CysLTs contribute to airway inflammation through eosinophil and neutrophil chemotaxis, plasma exudation and mucus secretion. Aim: To test the activity of the dual CysLT1/2 antagonist, ONO-6950, against allergen-induced airway responses. Methods: Subjects with documented allergen-induced early (EAR) and late (LAR) asthmatic responses were randomized in a 3-way crossover study to receive ONO -6950 (200 mg) or montelukast (10 mg) or placebo q.d. on Days 1-8 of the 3 treatment periods. Allergen was inhaled on Day 7 and forced expiratory volume in 1 second (FEV 1 ) was measured for 7 hours following challenge. Sputum eosinophils, and airway hyperresponsiveness were measured before and after allergen challenge. The primary outcome was the effect of ONO-6950 versus placebo on the EAR and LAR. Results: Twenty-five non-smoking subjects with mild allergic asthma were enrolled and 20 subjects completed all 3 treatment periods per protocol. ONO-6950 was well tolerated. Compared to placebo, ONO-6950 significantly attenuated the maximum % fall in FEV 1 and area under the %FEV 1 /time curve during the early and late asthmatic responses (p<0.05), and allergen-induced sputum eosinophils. There were no significant differences between ONO-6950 and montelukast. Conclusions: Attenuation of EAR, LAR, and airway inflammation is consistent with CysLT1 blockade. Whether dual CysLT1/2 antagonism offers additional benefit for treatment of asthma requires further study. Funded by ONO Pharmaceutical Co., Ltd., and AllerGen NCE Inc.
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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) | 0.003 | 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".