Effect of injected dexamethasone on relative cytokine mRNA expression in bronchoalveolar lavage fluid in horses with mild asthma
Bibliographic record
Abstract
BACKGROUND: Mild equine asthma is a common inflammatory airway disease of the horse. The primary treatment of mild equine asthma is corticosteroids. The purpose of this study was to investigate the effects of injected dexamethasone on relative IL-1β, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p35, IL-17, IL-23, IFN-γ, Eotaxin-2 and TNF-α mRNA expression in bronchoalveolar lavage (BAL) fluid in healthy Thoroughbred horses (n = 6), and those with mild equine asthma (n = 7). RESULTS: Horses with mild equine asthma had a significantly greater bronchoalveolar lavage mast cell percentage than healthy horses both before and after treatment. Mild equine asthma was associated with a 4.95-fold up-regulation of IL-17 (p = 0.026) and a 2.54-fold down-regulation of IL-10 (p = 0.049) compared to healthy horses. TNF-α was down-regulated in response to dexamethasone treatment in both healthy horses (3.03-fold, p = 0.023) and those with mild equine asthma (1.75-fold, p = 0.023). IL-5 was also down-regulated in horses with mild asthma (2.17-fold, p = 0.048). CONCLUSIONS: Horses with mild equine asthma have a lower concentration of IL-10 in BAL fluid than healthy controls which concurs with human asthmatics. The marked up-regulation of IL-17 in horses with mild asthma suggests these horses had a true tendency of "allergic" airway inflammation in response to environmental allergens. Dexamethasone administration exerted anti-inflammatory effects associated with down-regulation of TNF-α in all horses, and decreased levels of IL-5 mRNA expression in horses with mild equine asthma. The inhibition of the Th-2 response, without any alterations to the airway cytology, indicates that maintained exposure to environmental allergens perpetuates airway 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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".