Voluntary running exercise prevents β-cell failure in susceptible islets of the Zucker diabetic fatty rat
Bibliographic record
Abstract
Physical activity improves glycemic control in type 2 diabetes (T2D), but its contribution to preserving β-cell function is uncertain. We evaluated the role of physical activity on β-cell secretory function and glycerolipid/fatty acid (GL/FA) cycling in male Zucker diabetic fatty (ZDF) rats. Six-week-old ZDF rats engaged in voluntary running for 6 wk (ZDF-A). Inactive Zucker lean and ZDF (ZDF-I) rats served as controls. ZDF-I rats displayed progressive hyperglycemia with β-cell failure evidenced by falling insulinemia and reduced insulin secretion to oral glucose. Isolated ZDF-I rat islets showed reduced glucose-stimulated insulin secretion expressed per islet and per islet protein. They were also characterized by loss of the glucose regulation of fatty acid oxidation and GL/FA cycling, reduced mRNA expression of key β-cell genes, and severe reduction of insulin stores. Physical activity prevented diabetes in ZDF rats through sustaining β-cell compensation to insulin resistance shown in vivo and in vitro. Surprisingly, ZDF-A islets had persistent defects in fatty acid oxidation, GL/FA cycling, and β-cell gene expression. ZDF-A islets, however, had preserved islet insulin mRNA and insulin stores compared with ZDF-I rats. Physical activity did not prevent hyperphagia, dyslipidemia, or obesity in ZDF rats. In conclusion, islets of ZDF rats have a susceptibility to failure that is possibly due to altered β-cell fatty acid metabolism. Depletion of pancreatic islet insulin stores is a major contributor to islet failure in this T2D model, preventable by physical activity.
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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".