The effects of marginal zinc deficiency and zinc supplementation on diabetes and the immune system in Zucker diabetic fatty rats
Bibliographic record
Abstract
Many of the symptoms of zinc deficiency and diabetes are the same, and are related to increased inflammation. Zinc supplementation may improve immunity and glycemic control, and reduce inflammation. The purpose of this study was to determine if marginal zinc deficiency (MZD) worsens and zinc supplementation (ZS) improves diabetes and immune parameters in Zucker diabetic fatty (ZDF) rats. Male ZDF rats were fed MZD (4 mg Zn/kg diet), zinc control ([ZC], 30 mg Zn/kg diet), or ZS (300 mg Zn/kg diet) diet, and lean ZDF rats fed ZC diet for 8 weeks. Parameters of diabetes, inflammation, and immune cell proportions and function were assessed. Results showed that MZD may exacerbate diabetes but had little effect on the immune parameters, while ZS had little effect on diabetes but may worsen immune function. Overall, it is the balance between zinc deficiency and toxicity that is necessary for optimal health improvements.
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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 | 0.001 | 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 | 0.001 |
| 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".