Endobronchial ultrasonography detects subepithelial remodeling in large airways of asthmatic horses
Bibliographic record
Abstract
Heaves is a naturally-occurring asthma-like disease of horses. Increased smooth muscle (ASM) and extracellular matrix (ECM) mass have been detected in airways of asthmatic man and horses. Assessment of ASM and ECM remodeling in vivo is still problematic, as endobronchial biopsies often provide incomplete sampling of the bronchial wall. Endobronchial ultrasonography (EBUS) allows non-invasive evaluation of large airway structures in man and in isolated equine lungs, as we have already shown ex vivo .We now hypothesize that in vivo EBUS can differentiate horses with heaves from controls based on the thickness of ASM and ECM layer. EBUS was performed in 4 horses with heaves and 3 controls under sedation using a 30 MHz radial probe. Horses were then humanely euthanized for reasons other than respiratory conditions. Ten randomly chosen cartilaginous bronchi were harvested at necropsy from the lungs of all animals and processed for histology. Internal airway perimeter (Pi), thickness of the epithelium (L1), combined ECM and ASM layers (L2) and L2 area were measured on EBUS images. The equivalent structures were measured on histological sections. A significant increase in L2 thickness and normalized L2 area (A L2 /Pi 2 ) were detected in central airways of horses with heaves compared to controls (p<0.05). Results were confirmed histologically as ASM mass and ECM components were increased in the large airways of heaves-affected horses compared to controls (p<0.05). Therefore, EBUS allows in vivo evaluation of bronchial remodeling affecting large airway submucosal structures in horses and could be used to monitor airway remodeling non-invasively in interventional studies in this species.
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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) | 0.000 | 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 | 0.001 | 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".