Immunohistochemical evaluation of mononuclear infiltrates in canine lupoid onychodystrophy
Bibliographic record
Abstract
The purpose of this study was to characterize the immunophenotype of the inflammatory infiltrate in canine lupoid onychodystrophy and to determine if decalcification interferes with immunoreactivity. Claw biopsies of 14 dogs with lupoid onychodystrophy were stained with CD3, BLA36 and HM57 (CD97α), MAC 387, lysozyme and MHC class II using an immunoperoxidase and avidin/biotin technique. Cells infiltrating the claw matrix were counted in two high‐power fields; numbers were expressed as a percentage of the cellular infiltrate. The inflammatory infiltrate consisted predominantly of B and T cells; macrophages were typically only present in small numbers. There was no correlation between the predominant inflammatory cell and clinical parameters. CD3, BLA36, lysozyme and MHC II preserved significant antigenicity during formalin fixation and short decalcification, while staining for CD79A and particularly MAC 387 was less reliable. Prolonged decalcification of 7–14 days abolished immunostaining with all antibodies. Short decalcification periods allow immunostaining of samples with some antibodies (CD3, BLA36, lysozyme, MHC II), but not others (CD79A, MAC387), while prolonged decalcification prohibits immunostaining. The nature of the mononuclear infiltrate in lupoid onychodystrophy is not helpful clinically. This study was funded by the American Academy of Veterinary Dermatology.
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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) | 0.001 | 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".