Tracheobronchial mucus viscoelasticity during environmental challenge in horses with recurrent airway obstruction
Bibliographic record
Abstract
The goal of this study was to compare the rheological properties of mucus from horses with recurrent airway obstruction (RAO) to that from healthy controls during environmental challenge by stabling in stalls with straw as bedding and hay as feed. We determined viscoelasticity (log G* dyn/cm2, at 10 radian/s) and calculated mucociliary clearability index (MCI) and cough clearability index (CCI), which are derivative parameters of G* and the ratio of viscosity and elasticity measured at 1 and 100 radian/s, respectively. We also investigated the solids content of mucus, and cytology of bronchoalveolar lavage fluid (BALF). Samples were obtained before (0 h) and 6, 24 and 48 h after environmental challenge. The central findings were rheological changes in airway mucus, which occurred over time in RAO-affected animals, but not in controls. Mucus rheology was similar in both groups at 0 and 6 h. In RAO-affected horses, mucus viscoelasticity, as measured by log G*, increased from 2.49 +/- 0.18 dyn/cm2 (mean +/- s.e.) at 0 h to 3.05 +/- 0.13 dyn/cm2 at 24 h after environmental challenge, and was accompanied by significant decreases in MCI and CCI. Percent solids of mucus did not differ significantly between the 2 groups, nor over time. Rheological values did not correlate with BALF cytology. We conclude that viscoelastic properties of tracheal mucus samples from RAO horses in remission do not differ from those of normal horses. However, environmental challenge causes clinical signs of small airway disease and a concurrent increase in mucus viscoelasticity only in RAO horses. Therefore, we infer that unfavourable changes in mucus rheology may contribute to stasis and accumulation of mucus in RAO horses in exacerbation, but not in clinical remission.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".