Heaves, an asthma‐like disease of horses
Bibliographic record
Abstract
Animal models have been developed to investigate specific components of asthmatic airway inflammation, hyper-responsiveness or remodelling. However, all of these aspects are rarely observed in the same animal. Heaves is a naturally occurring disease of horses that combines these features. It is characterized by stable dust-induced inflammation, bronchospasm and remodelling. The evaluation of horses during well-controlled natural antigen exposure and avoidance in experimental settings allows the study of disease mechanisms in the asymptomatic and symptomatic stages, an approach rarely feasible in humans. Also, the disease can be followed over several years to observe the cumulative effect of repeated episodes of clinical exacerbation or to evaluate long-term treatment, contrasting most murine asthma models. This model has shown complex gene and environment interactions, the involvement of both innate and adaptive responses to inflammation, and the contribution of bronchospasm and tissue remodelling to airway obstruction, all occurring in a natural setting. Similarities with the human asthmatic airways are well described and the model is currently being used to evaluate airway remodelling and its reversibility in ways that are not possible in people for ethical reasons. Tools including antibodies, recombinant proteins or gene arrays, as well as methods for sampling tissues and assessing lung function in the horse are constantly evolving to facilitate the study of this animal model. Research perspectives that can be relevant to asthma include the role of neutrophils in airway inflammation and their response to corticosteroids, systemic response to pulmonary inflammation, and maintaining athletic capacities with early intervention.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".