Role of metallothionein in regulating the abundance of histochemically reactive zinc in rat tissues
Bibliographic record
Abstract
The objectives of this study were (i) to investigate the modulating effects of zinc nutrition on histochemically reactive zinc in the rat intestine and liver and (ii) to assess the relationship between histochemically reactive zinc and metallothionein-bound zinc in these tissues under varying zinc nutrition. Male Wistar rats were fed a zinc-deficient (3 mg zinc/kg), adequate-zinc (30 mg zinc/kg, ad libitum or pair-fed), or zinc-supplemented (155 mg zinc/kg) diet for 2 or 6 weeks. Plasma N-(6-methoxy-8-quinolyl)-para-toluenesulfonamide-reactive zinc reflected dietary zinc intake. Abundance of the intestine histochemically reactive zinc was correlated with dietary zinc intake after 2 weeks of dietary treatment. Dietary zinc intake had no effect on the abundance of the intestine histochemically reactive zinc after 6 weeks of dietary treatment and the hepatic histochemically reactive zinc after both 2 and 6 weeks of dietary treatment. This lack of effect of dietary zinc intake on the abundance of histochemically reactive zinc was associated with a higher level of metallothionein. The molecular-mass distribution profile revealed that N-(6-methoxy-8-quinolyl)-para-toluenesulfonamide-reactive zinc and metallothionein-bound zinc represented two different, but interrelated, pools of zinc. Overall, these results suggested that the abundance of histochemically reactive zinc was homeostatically regulated, which was partially achieved through the regulation of metallothionein levels in rats.
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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 | 0.000 | 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 | 0.000 |
| 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".