Effect of combining rosiglitazone with either metformin or insulin on β-cell mass and function in an animal model of Type 2 diabetes characterized by reduced β-cell mass at birth
Bibliographic record
Abstract
BACKGROUND: Interventions that preserve or increase β-cell mass may also prevent Type 2 diabetes. Rosiglitazone alone, as well as in combination with metformin, prevents diabetes in people with high, yet non-diabetic glucose levels. These effects may be mediated through changes in β-cell mass. In the present study, the effect of combining rosiglitazone with metformin and/or insulin on β-cell mass and glucose levels was examined in a rat model of Type 2 diabetes. METHODS: Diabetes-prone pups were randomized to receive rosiglitazone alone or in combination with metformin and/or insulin starting at 4 weeks of age. β-Cell mass and glucose homeostasis were examined in adulthood. RESULTS: Rosiglitazone treatment reduced insulin resistance and partially restored β-cell mass in animals with reduced β-cell mass at birth. The addition of metformin to rosiglitazone decreased insulin resistance and reduced weight gain, but had no additional effect on β-cell mass. Conversely, the addition of insulin had no additional effect on these outcomes. Although the combination of rosiglitazone and metformin did not affect β-cell mass at 26 weeks of age, it did result in reduced body weight and insulin resistance. CONCLUSION: The results of the present study suggest that the addition of metformin to rosiglitazone improves the metabolic profile through an effect on insulin resistance and not β-cell mass.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".