Endoscopic Evaluation of Angiogenesis in the Large Airways of Horses with Heaves Using Narrow Band Imaging
Bibliographic record
Abstract
BACKGROUND: Heaves is a severe debilitating condition of horses, characterized by lower airway inflammation and permanent structural changes of the bronchial wall. Chronic inflammation promotes the formation of new vessels, a phenomenon known as angiogenesis. Narrow band imaging (NBI) endoscopy is a noninvasive technique that enhances the visualization of submucosal vessels, and commonly is employed for the study of angiogenesis in human patients. OBJECTIVES: Using NBI, we aimed to determine whether or not the central airways of horses with heaves undergo angiogenesis. ANIMALS: Horses with heaves during exacerbation of the disease (n = 5) and healthy controls (n = 6). METHODS: A library of NBI images was established from previously recorded videoendoscopies. Images were acquired by an operator blinded to horse ID. Images were obtained from 3 sites: 130 from the trachea (14 ± 9.3 [mean ± SD] images per horse with heaves and 10 ± 5.4 from controls; P = .45), 58 from the carina (5.4 ± 3.2 from horses with heaves and 5.2 ± 2.8 fromn controls; P > .99) and 167 from the intermediate bronchi (17.8 ± 6.7 from horses with heaves and 13 ± 5.6 from controls; P = .17). Using dedicated stereology software (NewCAST, Visiopharm; Denmark), the volume density of superficial and deep vessels was calculated blindly by point counting at each site for all horses. RESULTS: In the trachea, the volume density of superficial vessels was increased in horses with heaves compared to controls (P = .02). No difference was found between groups for the volume density of both superficial and deep vessels at the carina or intermediate bronchi. CONCLUSION AND CLINICAL RELEVANCE: NBI imaging of the airways was easily performed in standing sedated horses.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".