Marginal Zinc Deficiency Promotes Pancreatic Islet Enlargement While Zinc Supplementation Improves the Pancreatic Insulin Response in Zucker Diabetic Fatty Rats
Bibliographic record
Abstract
Zinc deficiency has been associated with the worsening of diabetes while zinc supplementation has been proposed to ameliorate diabetes. This study examined the effects of marginal zinc deficiency (MZD) and zinc supplementation (ZS) on obesity, glycemic control, pancreatic islets, hepatic steatosis and renal function of Zucker diabetic fatty (ZDF) rats. Male ZDF rats were fed an MZD, zinc control (ZC) or ZS diet (4, 30 and 300 mg Zn/kg diet, respectively), and lean Zucker rats were fed a ZC diet for 8 weeks. MZD and ZS did not alter body weight or whole-body composition in ZDF rats. MZD ZDF rats had reduced zinc concentrations in the femur and pancreas, a greater number of enlarged pancreatic islets and a diminished response to an oral glucose load based on a 1.8-fold greater incremental area-under-the-curve (AUC) for glucose compared to ZC ZDF. ZS ZDF rats had elevated serum, femur and pancreatic zinc concentrations, unchanged pancreatic parameters and a 50% reduction in the AUC for insulin compared to ZC ZDF rats, suggesting greater insulin sensitivity. Dietary zinc intake did not alter hepatic steatosis, creatinine clearance, or levels of proteins that contribute to insulin signaling, inflammation or zinc transport in epididymal fat. Potential adverse effects of ZS were suggested by reduced hepatic copper concentrations and elevated serum urea compared to ZC ZDF rats. In summary, ZS improved the pancreatic insulin response but not the glucose handling. In contrast, reduced zinc status in ZDF rats led to impaired glucose tolerance and a compensatory increase in the number and size of pancreatic islets which could lead to β-cell exhaustion.
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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 | 0.001 | 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".