Association of Dietary Copper and Zinc Levels with Hepatic Copper and Zinc Concentration in Labrador Retrievers
Bibliographic record
Abstract
BACKGROUND: Copper-associated hepatitis is an inherited disease in the Labrador Retriever. Apart from genetic factors, dietary intake of copper and zinc are suspected to play a role in the pathogenesis. OBJECTIVES: To investigate whether dietary copper and zinc levels of commercially available dry diets are associated with hepatic copper and zinc concentrations in Labrador Retrievers. ANIMALS: Fifty-five Labrador Retrievers that were fed a single brand and type of commercial dry food for at least 1 year. Of these, 44 dogs were family members of Labrador Retrievers with copper-associated hepatitis. METHODS: Liver biopsies, blood samples, and diet samples were obtained. Liver specimens were scored histologically and copper and zinc concentrations were quantified. Dietary concentrations of copper and zinc were measured. The association between dietary intake of copper and zinc and hepatic copper and zinc concentrations was investigated by linear regression analysis. RESULTS: High dietary copper and low dietary zinc levels were significantly associated with high hepatic copper levels. No association between dietary intake and hepatic zinc was present. CONCLUSIONS AND CLINICAL RELEVANCE: Dietary copper and zinc at current levels in commercially available dry dog food can influence hepatic copper and can be a risk factor for the development of copper-associated hepatitis in Labrador Retrievers with a genetic susceptibility to copper.
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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 | 0.001 |
| 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".