Analysis of the otic mycobiota in dogs with otitis externa compared to healthy individuals
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Otitis externa is a common multifactorial disease with a prevalence in dogs as high as 10-20%. In humans, the diversity of the cutaneous mycobiota appears to increase in diseased states, whereas one canine study identified a decrease in diversity of the cutaneous mycobiota in atopic dogs compared to healthy individuals. HYPOTHESIS/OBJECTIVES: To describe the otic mycobiota in dogs with otitis externa compared to healthy dogs. ANIMALS: Samples were collected from six dogs with clinical and cytological evidence of otitis externa and five clinically normal dogs. METHODS AND MATERIALS: Swabs were collected from the ears of six dogs with fungal otitis externa. DNA from each sample was isolated and Illumina sequencing was performed targeting the internal transcribed spacer region. Sequences were processed using the bioinformatics software MOTHUR. RESULTS: Fungi from ten different phyla were identified. The mycobiota of all affected ears was dominated by the genera Malassezia, which accounted for 55.7-98.4% of sequences (median 96.8%). Affected ears had significantly decreased observed richness, estimated richness and inverse Simpson's diversity index compared to controls (P = 0.008). Linear discriminant analysis effect size (LEfSe) analysis identified 42 operational taxonomic units (OTUs) that were differentially abundant (P < 0.05). Three OTUs were over-represented in the affected ears, including M. pachydermatis, whereas 39 OTUs were over-represented in healthy ears. CONCLUSIONS: Reduced fungal richness and diversity was present in affected ears, with markedly higher relative abundances of Malassezia. The otic fungal mycobiota is much more complex than has been identified with culture-based studies.
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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 | 0.001 |
| 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 it