Effects of atorvastatin on the regeneration of pancreatic β-cells after streptozotocin treatment in the neonatal rodent
Bibliographic record
Abstract
To investigate the role of statins in beta-cell regeneration a model of streptozotocin (STZ)-induced beta-cell injury was used in the neonatal rat. We hypothesized that beta-cell growth and regeneration would increase following treatment with atorvastatin and that this would be associated with intraislet vasculogenesis. Pregnant Wistar rats were gavaged with 20 or 40 mg/kg atorvastatin for 21 days commencing on gestation day 15. Atorvastatin was detected in the circulation of the offspring. On postnatal day 4, the pups were given either a control or STZ (70 mg/kg ip) injection. beta-Cell mass had partially recovered by postnatal day 44 following STZ treatment, and atorvastatin (20 mg/kg) significantly increased beta-cell mass in both STZ-treated and control animals. An increase in the numbers of small islets at postnatal day 44 was seen in STZ-treated animals following atorvastatin, suggestive of neogenesis, and glucose tolerance was improved. Treatment with atorvastatin caused an increase in the numbers of intraislet endothelial cells at postnatal day 14 and the percentage of endothelial cells undergoing DNA synthesis, suggesting that angiogenesis had preceded the increase in beta-cell mass. The results indicate that functional beta-cell mass was expanded with atorvastatin in both control and STZ-treated neonatal rats and suggests a novel effect of a statin in promoting islet plasticity.
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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) | 0.001 | 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".