Histological and genotypical characterization of feline cutaneous mycobacteriosis: a retrospective study of formalin‐fixed paraffin‐embedded tissues
Bibliographic record
Abstract
Twenty-nine cases presumptively diagnosed as feline cutaneous mycobacteriosis were evaluated microscopically with haematoxylin and eosin and modified Fite's stained sections using archived formalin-fixed paraffin-embedded tissue specimens. Lesions were characterized histologically as feline leprosy (7 cases lepromatous and 16 cases tuberculoid) or atypical mycobacteriosis (3 cases); three cases did not fit these criteria and were classified as 'miscellaneous'. Actinomycetales-specific polymerase chain reaction (PCR) of variable regions 1, 2 and 3 of the 16S ribosomal RNA (rRNA) gene and subsequent sequence analysis of the amplicons were performed to identify the species of mycobacteria associated with each case. Together, this study identified 10 different Actinomycetales organisms with greater than 98% nucleotide sequence identity to named species, nine were of the genus Mycobacterium and eight were associated with feline leprosy (both lepromatous and tuberculoid). Based on this study, we conclude that feline cutaneous mycobacteriosis should be considered as a syndrome with varied clinical and histological presentations associated with a variety of different Mycobacterium species, organisms other than Mycobacterium sp. may be associated with feline cutaneous mycobacteriosis lesions, and molecular diagnostic techniques can be an important tool for identifying agents associated with lesions of feline cutaneous mycobacteriosis.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".