Bronchial brush cytology, endobronchial biopsy, and SALSA immunohistochemistry in severe equine asthma
Bibliographic record
Abstract
Horses with severe equine asthma (SEA), also known as heaves and recurrent airway obstruction, have persistent neutrophilic inflammation of the lower airways. Cytologic evaluation of bronchoalveolar lavage (BAL) fluid is commonly used to confirm the clinical diagnosis of SEA. However, the utility of microscopic assessment of bronchial brushings, endobronchial biopsies, and immunohistochemical detection of disease-associated biomarkers for the diagnosis of SEA remain poorly characterized. Salivary scavenger and agglutinin (SALSA) has anti-inflammatory properties and downregulated gene expression in SEA; therefore, it was investigated as a tissue biomarker for airway and systemic inflammation. Six asthmatic and 6 non-asthmatic horses were exposed to an inhaled challenge. Before and after challenge, samples of BAL fluid, bronchial brushing, and endobronchial biopsy were collected. Location of SALSA in biopsies was determined, and immunohistochemical label intensity was computed using image analysis software. Serum amyloid A (SAA) was measured to assess systemic inflammation. After challenge, neutrophil proportions were significantly higher in asthmatic versus non-asthmatic horses in BAL fluid (least squares means, 95% confidence interval: 80.9%, 57.2% to 93.1%, vs 3.6%, 1.1% to 10.7%) and in brush cytology slides (39.5%, 7.7% to 83.6%, vs 0.2%, 0% to 2.3%), illustrating the potential of brush cytology as an alternate modality to BAL for assessing intraluminal inflammation. Bronchial histopathologic findings and intensity of SALSA immunolabeling in surface and glandular epithelium were similar in asthmatic and non-asthmatic horses, indicating limited changes in bronchial tissue from the inhaled challenge. Increases in SAA indicated systemic inflammation, but SALSA immunolabeling did not change significantly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".