Immunohistochemical investigation of canine episcleritis
Bibliographic record
Abstract
OBJECTIVES: To identify macrophages, B cells and T cells in archived canine episcleral biopsies and to correlate these findings with the clinical presentation and therapeutic outcome. PROCEDURES: Archived formalin-fixed biopsies were immunohistochemically labeled for CD18, CD79a, and CD3 to identify macrophages, B cells and T cells, respectively. Slides were digitally photographed and positive cells were manually counted. Signalment, duration of illness, affected eye(s), treatment, and therapeutic outcome were reviewed for each dog. Dogs were divided into groups based on clinical presentation (unilateral episcleritis, bilateral episcleritis or nodular granulomatous episclerokeratitis (NGE). RESULTS: Twenty-four cases were evaluated. There were 19 episcleritis (13 unilateral, six bilateral) and five NGE cases. The mean age for clinical manifestations of unilateral episcleritis was 6.8 years, bilateral episcleritis was 8.7 years, and NGE was 3.8 years. The Cocker Spaniel was over-represented in the episcleritis groups. All NGE cases were Collies. Approximately 50% of the unilateral episcleritis cases resolved and did not require long-term therapy. Almost all cases of bilateral episcleritis and NGE required continuous medical therapy to maintain remission. There was a significantly higher percentage of B lymphocytes in biopsies from lesions that required ongoing medical therapy to maintain lesion remission than in the lesions that resolved, and for which medications were discontinued (P = 0.0471). CONCLUSIONS: The prognosis for resolution of NGE and bilateral episcleritis without long-term medical therapy is poor. There is a significant difference in the inflammatory cell population in episcleritis that resolved with medical therapy vs. episcleritis that required ongoing medical therapy.
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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 | 0.001 | 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) | 0.002 | 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".