Dermatitis caused by autochthonous <i>Cercopithifilaria bainae</i> from a dog in Florida, <scp>USA</scp>: clinical, histological and parasitological diagnosis and treatment
Bibliographic record
Abstract
BACKGROUND: Cercopithifilaria bainae is a tick-vectored filarioid nematode associated with erythematous dermatitis in dogs. It has not been reported previously in the United States. HYPOTHESIS/OBJECTIVE: To describe clinical, histological and parasitological diagnosis and treatment of C. bainae in a dog. ANIMALS: An 11-month-old golden retriever/standard poodle mixed breed dog from Florida (USA). METHODS AND MATERIALS: The dog had no travel history within or outside the United States, was presented with a one month history of annular erythematous plaques on the head and ulcers on the medial canthi. Lesions were unresponsive to antibiotic treatment. RESULTS: Histopathological evaluation of skin biopsies revealed an eosinophilic to lymphohistiocytic perivascular dermatitis with multiple microgranulomas and rare 5-10 μm diameter microfilariae within microgranulomas. Microfilarial morphology was consistent with C. bainae. PCR and sequencing of 18S rRNA and mitochondrial cytochrome oxidase subunit I genes confirmed the nematodes as C. bainae. The dog was treated with a commercial spot-on containing imidacloprid and moxidectin, and clinical resolution occurred. CONCLUSIONS AND CLINICAL IMPORTANCE: To the best of the authors' knowledge, this is the first report of C. bainae in a dog in the United States and the first description of dermatological lesions caused primarily by C. bainae.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".