Characterization of the Inflammatory Infiltrate in Canine Chronic Hepatitis
Bibliographic record
Abstract
Canine chronic hepatitis (CCH) is a progressive inflammatory disease of unknown etiology. To characterize the inflammatory infiltrate, 16 dogs with CCH were selected and classified into three groups based on the stage of fibrosis, as evaluated with Masson's trichrome stain. The inflammatory infiltrate in each liver section was immunohistochemically characterized and evaluated using CD3, lysozyme, lamba and kappa light chain, and alpha-smooth muscle actin antibodies. Numerous breeds were affected, and middle-aged females predominated in this select group. Necroinflammatory activity progressively increased and then waned as the hepatitis progressed to cirrhosis. CD3+ lymphocytes were the most numerous lymphoid cells in dogs with CCH. Degenerate hepatocytes were occasionally surrounded by CD3+ lymphocytes. Necrosis was positively correlated with the number of CD3+ lymphocytes. The lamba and kappa light chain-positive cell infiltrate was variable but generally mild. A positive correlation between the lambda and kappa light chain-positive cells and the portal alpha-smooth muscle actin was found. The number of alpha-smooth muscle actin-positive cells (myofibroblasts) in portal triads and fibrous septa was positively correlated with the stage of fibrosis. In contrast, no correlation was found between the number of lysozyme-positive cells (Kupffer cells) and the stage of fibrosis. These results further support the idea of an immune-mediated process in CCH and suggest that periductular myofibroblasts play an important role in canine liver fibrogenesis.
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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".