Effect of Long-Term Fluticasone Treatment on Immune Function in Horses with Heaves
Bibliographic record
Abstract
BACKGROUND: Corticosteroids currently are the most effective pharmacological treatment available to control heaves in horses. Systemically administered corticosteroids have been shown to alter immune response in horses, humans, and other species. Aerosolized administration theoretically minimizes systemic adverse effects, but the effect of inhaled corticosteroids on immune function has not been evaluated in horses. OBJECTIVES: To evaluate the effects of prolonged administration of inhaled fluticasone on the immune system of heaves-affected horses. ANIMALS: Heaves-affected horses were treated with inhaled fluticasone (n = 5) for 11 months or received environmental modifications only (n = 5). METHODS: Prospective analysis. Clinical parameters and CBC, lymphocyte subpopulations and function, and circulating neutrophil gene expression were sequentially measured. Primary and anamnestic immune responses also were evaluated by measuring antigen-specific antibodies in response to vaccination with bovine viral antigen and tetanus toxoid, respectively. RESULTS: No clinical adverse effects were observed and no differences in immune function were detected between treated and untreated horses. CONCLUSIONS AND CLINICAL IMPORTANCE: The treatment of heaves-affected horses with inhaled fluticasone at therapeutic dosages for 11 months has no significant detectable effect on innate and adaptive (both humoral and cell-mediated) immune parameters studied. These results suggest that prolonged administration of fluticasone would not compromise the systemic immune response to pathogens nor vaccination in adult horses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".