Effect of chronic exposure to excess dietary copper and dietary selenium supplementation on liver specimens from rats
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of chronic exposure to excess dietary copper (Cu) on liver specimens from rats and the effects of dietary selenium (Se) supplementation in experimental Cu toxicosis. ANIMALS: 60 weanling male Fischer 344 rats. PROCEDURE: Rats were randomly assigned to 4 groups of 15 rats each and fed 1 of the following 4 diets: high Cu (500 microg/g)/adequate Se (0.2 microg/g); high Cu (500 microg/g)/supplemented Se (2 microg/g); adequate Cu (18 microg/g)/adequate Se (0.2 microg/g); or, adequate Cu (18 microg/g)/supplemented Se (2 microg/g). Five rats per group were euthanatized after 3, 6, and 12 months, and liver specimens were obtained for histologic examination, histochemistry, metal analysis by atomic absorption spectrophotometry, measurement of glutathione peroxidase activity, and assessment of lipid peroxidation, using quantification of malondialdehyde (MDA) by the thiobarbituric acid reaction. RESULTS: Hepatic Cu concentration was significantly higher in rats fed high Cu diets (range, 9 to 18 microg/g of tissue [wet weight]), compared with rats receiving adequate Cu diets (4.0 to 5.7 microg/g of tissue). Rats fed high-Cu diets for 3, 6, and 12 months had mild multifocal hepatitis often surrounding necrotic foci. However, an increase in hepatic MDA content, indicative of lipid peroxidation, was not detected in these rats. Development of morphologic changes was not prevented by use of dietary Se supplementation. CONCLUSION AND CLINICAL RELEVANCE: Long-term exposure to excess dietary Cu caused mild hepatic lesions in Fischer 344 rats. Dietary Se supplementation did not prevent hepatic damage in rats with Cu toxicosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".