Elevated serum gamma‐glutamyltransferase activity and immunohistochemistry in two dogs with renal carcinoma
Bibliographic record
Abstract
During a 3-year time period, a 15-year-old male castrated Terrier mix (dog 1) and a 6-year-old female spayed Labrador Retriever (dog 2) presented to the North Carolina State Veterinary Hospital with similar blood work abnormalities and no significant physical examination findings. A CBC, chemistry panel, and urinalysis performed on both dogs were relatively unremarkable, other than a marked increase in serum gamma-glutamyltransferase (GGT) activity. Through imaging, both patients were diagnosed with a renal mass, and histopathology of both masses revealed a carcinoma. Immunohistochemical staining of the renal mass in both dog 1 and dog 2 were intensely positive for GGT. Dog 1 had the affected kidney removed, which normalized the GGT value. Dog 2 was euthanized, and metastasis to the lung was noted upon postmortem examination. There have been limited case studies documenting an elevation in serum GGT in dogs diagnosed with renal carcinoma. While renal carcinoma is uncommon in dogs, it is an important differential to keep in mind when there is a marked increase in serum GGT without accompanying increases in other measured liver enzymes. In addition, serum GGT can serve as a helpful biomarker for disease resolution and recurrence, as surgical removal of the renal mass (dog 1) led to the resolution of the elevated serum GGT. To our knowledge, this is the first report demonstrating IHC staining for GGT in a canine renal carcinoma.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".