Biophysical properties of alveolar surfactant in drever dogs with hunting associated pulmonary edema
Bibliographic record
Abstract
BACKGROUND: A syndrome of acute non-cardiogenic pulmonary edema associated with hunting is prevalent in the drever breed, but etiology of this syndrome is currently unknown. Alveolar surfactant has a critical role in preventing alveolar collapse and edema formation. The aim of this study was to investigate, whether the predisposition to hunting associated pulmonary edema in drever dogs is associated with impaired biophysical properties of alveolar surfactant. Seven privately owned drever dogs with recurrent hunting associated pulmonary edema and seven healthy control dogs of other breeds were included in the study. All affected dogs underwent thorough clinical examinations including echocardiography, laryngeal evaluation, bronchoscopy, and bronchoalveolar lavage (BAL) as well as head, neck and thoracic computed tomography imaging to rule out other cardiorespiratory diseases potentially causing the clinical signs. Alveolar surfactant was isolated from frozen, cell-free supernatants of BAL fluid and biophysical analysis of the samples was completed using a constrained sessile drop surfactometer. Statistical comparisons over consecutive compression expansion cycles were performed using repeated measures ANOVA and comparisons of single values between groups were analyzed using T-test. RESULTS: There were no significant differences between groups in any of the biophysical outcomes of surfactant analysis. The critical function of surfactant, reducing the surface tension to low values upon compression, was similar between healthy dogs and affected drevers. CONCLUSIONS: The etiology of hunting associated pulmonary edema in drever dogs is not due to an underlying surfactant dysfunction.
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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 | 0.000 | 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".