Liver Histopathology and Liver and Serum Alanine Aminotransferase and Alkaline Phosphatase Activities in Epileptic Dogs Receiving Phenobarbital
Bibliographic record
Abstract
Phenobarbital (PB) therapy is frequently associated with elevated serum alanine aminotransferase (ALT) and alkaline phosphatase (AP) activities in dogs without clinical signs of liver disease. The goal of this study was to determine if increased serum ALT and AP activities in clinically healthy PB-treated epileptic dogs are due to hepatic enzyme induction or to subclinical liver injury. Liver biopsies were obtained from 12 PB-treated dogs without clinical signs of liver disease but with elevated serum ALT and/or AP activities or both. Liver biopsies were obtained from eight healthy control dogs not receiving PB. Biopsies were evaluated histopathologically (all dogs) and liver homogenates were assayed for ALT (all dogs) and AP (six treated dogs, all controls) activities. As a positive control, liver cytochrome P4502B, an enzyme known to be induced by PB, was measured by benzyloxyresorufin-O-dealkylase activity and immunoblotting (five treated dogs, all controls). Serum AP isoenzyme analyses were performed. Results showed that ALT and AP activities in liver homogenates were not increased in treated dogs compared with controls, whereas the positive control for induction, CYP2B, was dramatically increased in treated dogs. Histopathological examination of liver biopsies revealed more severe and frequent abnormalities in treated dogs compared to controls, but similar types of abnormalities were found in both groups. Serum AP isoenzyme analyses in treated dogs demonstrated increased corticosteroid-induced and liver isoenzyme activities compared to controls. Results do not support induction of ALT or AP in the liver as the cause of elevated serum activities of these enzymes due to PB.
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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 | 0.001 |
| 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".