Topography of the respiratory, oral, and guttural pouch bacterial and fungal microbiotas in horses
Bibliographic record
Abstract
BACKGROUND: The lower respiratory tract microbiota of the horse is different in states of health and disease, but the bacterial and fungal composition of the healthy respiratory tract of the horse has not been studied in detail. HYPOTHESIS: The respiratory tract environment contains distinct niche microbiotas, which decrease in species richness at more distal sampling locations. OBJECTIVE: Characterize the bacterial and fungal microbiotas along the upper and lower respiratory tract of the horse. ANIMALS: Healthy Argentinian Thoroughbred horses (n = 11) from the same client-owned herd. METHODS: Prospective cross-sectional study. Eleven upper and lower respiratory tract anatomical locations (bilateral nasal, bilateral deep nasal, nasopharynx, floor of mouth, oropharynx, arytenoids, proximal and distal trachea, guttural pouch) were sampled using a combination of swabs, protected specimen brushes, and saline washes. Total DNA was extracted from each sample and negative control, and the 16S rRNA gene (V4) and ITS2 region were sequenced. Community composition, alpha-diversity, and beta-diversity were compared among sampling locations. RESULTS: Fungal species richness and diversity were highest in the nostrils. More spatial heterogeneity was found in bacterial composition than in fungal communities. The pharyngeal microbiota was most similar to the distal tracheal bacterial and fungal microbiota in healthy horses and therefore may serve as the primary source of bacteria and fungi to the lower respiratory tract. CONCLUSIONS AND CLINICAL IMPORTANCE: The pharynx is an important location that should be targeted in respiratory microbiota research in horses. Future studies that investigate whether biomarkers of respiratory disease can be reliably detected in nasopharyngeal swab samples are warranted.
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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 | 0.001 | 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".