Characterization of Lung Hyperresponsiveness, Inflammation, and Alveolar Macrophage Mediator Production in Allergy Resistant and Susceptible Rats
Bibliographic record
Abstract
To better understand asthma pathogenesis, we characterized airway responsiveness, lung inflammation, and mediator production of alveolar macrophages (AM) after allergen sensitization and challenge in two strains of rats showing different susceptibilities in developing airway allergic reactions. Airway responsiveness to acethylcholine was measured 24 h after ovalbumin (OVA) challenge, whereas bronchoalveolar lavages were performed 5 min, 8 h, and 24 h after challenge. Brown Norway rats showed airway hyperresponsiveness after challenge, whereas lung resistance remained unchanged in Sprague-Dawley rats. Interestingly, Sprague-Dawley rats developed a neutrophilic inflammation, whereas both neutrophils and eosinophils were increased in Brown Norway rats. AM mediator production varied with time with a lower tumor necrosis factor (TNF) and interleukin (IL)-10 release at 8 h after challenge. OVA challenge stimulated spontaneous TNF and IL-10 release by AM isolated 24 h after challenge in both strains of rats, although AM from Brown Norway rats released significantly more IL-10 and TNF. Furthermore, nitric oxide production was increased only in OVA-challenged (24 h) Brown Norway rats. Our results suggest that AM may participate to the expansion of Th2 inflammation in Brown Norway rats and that differences in AM mediator production may explain, in part, distinct allergic susceptibilities in these two strains of rats.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".