Relationship between the bacterial ocular surface microbiota and outcomes for cats with feline herpesvirus type 1 ocular surface disease
Bibliographic record
Abstract
OBJECTIVE: Feline herpesvirus 1 (FHV-1) causes ocular surface disease in domestic cats. The purpose of this study was to assess the relationship between bacterial ocular surface microbiota and outcomes for cats with FHV-1 ocular surface disease. ANIMALS STUDIED: Twenty-two shelter-housed cats with confirmed FHV-1 ocular surface disease. PROCEDURES: Animals were grouped according to FHV-1 shedding and ocular clinical scores following intervention: worsened outcome (WorOut, n = 11) or improved outcome (ImpOut, n = 11). Scoring and conjunctival sampling were completed on Days 1 and 8 of twice daily antiviral treatment. Bacterial DNA was extracted and submitted for 16S rRNA gene sequencing. Real-time polymerase chain reaction was performed for selected bacterial species. Overall DNA concentration between groups was assessed. RESULTS: Bacterial microbiota relative abundance composition was significantly different between ImpOut and WorOut groups (weighted UniFrac p = .006). Alpha diversity was significantly higher in the ImpOut group compared with the WorOut group (Shannon p = .042, Simpson's p = .022, Pielou's p = .037). Differences in the relative abundance of various phyla and species were detected between groups. Total DNA concentration was higher in the WorOut group compared with the ImpOut group (p = .04). Feline GAPDH (p = .001) and Bilophila wadsworthia (p = .024) copy number was significantly higher in the ImpOut group compared with the WorOut group. CONCLUSIONS: The results highlight the important relationship between the bacterial ocular surface microbiota and FHV-1 infection outcomes in cats treated with antiviral medications. Low bacterial species diversity, higher overall DNA (presumed predominantly bacterial) load, and certain bacterial phyla/species were associated with poor outcomes for cats with FHV-1 ocular disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".