The failure of selenium supplementation to prevent copper-induced liver damage in Fischer 344 rats.
Bibliographic record
Abstract
This study evaluates the ability of selenium (Se) supplementation to prevent experimental copper (Cu)-induced hepatocellular damage. Weanling male Fischer 344 rats were randomly assigned to groups of 15, 3 groups (A,B,C) were fed Cu-loaded diets (containing 2000 microg/g copper, added as CuSO4) and different levels of Se (added as Na2SeO3 x 5H2O) as follows: A) Cu-loaded/Se adequate diet (0.4 microg/g Se, fed basis); B) Cu-loaded/Se-supplemented diet (2 microg/g Se); and C) Cu-loaded/Se-deficient diet (< 0.2 microg/g). Three additional groups (D,E,F) were fed diets containing adequate levels of Cu (14 microg/g Cu, fed basis) and different levels of Se as follows: D) Cu-adequate/Se-adequate diet; E) Cu-adequate/Se-supplemented diet (2 microg/g Se); and F) Cu-adequate/Se-deficient (< 0.2 microg/g) diet. After 4, 8, and 12 weeks on the experimental diets, liver samples were processed for histology, histochemistry, metal analysis, glutathione peroxidase (GSH-Px) measurement, and quantification of malondialdehyde (MDA). Morphologic changes characteristic of Cu-associated hepatitis, without an increase in hepatic MDA levels, were seen in all Cu-loaded rats in each sampling. Similar changes occurred in rats fed Se-adequate, Se-supplemented and Se-deficient diets. This study demonstrates that Fischer 344 rats fed 2000 microg/g Cu develop morphologic changes due to Cu toxicity without evidence of lipid peroxidation. Furthermore, Se supplementation does not result in protection against Cu-induced liver injury.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".