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 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 | 0.001 | 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 | 0.000 | 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 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".