Combining metformin therapy with caloric restriction for the management of type 2 diabetes and nonalcoholic fatty liver disease in obese rats
Bibliographic record
Abstract
Weight loss is recommended for patients with nonalcoholic fatty liver disease (NAFLD), while metformin may lower liver enzymes in type 2 diabetics. Yet, the efficacy of the combination of weight loss and metformin in the treatment of NAFLD is unclear. We assessed the effects of metformin, caloric restriction, and their combination on NAFLD in diabetic Otsuka Long-Evans Tokushima Fatty (OLETF) rats. Male OLETF rats (age 20 weeks; n = 6-8 per group) were fed ad libitum (AL), given metformin (300 mg·kg(-1)·day(-1); Met), calorically restricted (70% of AL; CR), or calorically restricted and given metformin (CR+Met) for 12 weeks. Met lowered adiposity compared with AL but not to the same magnitude as CR or CR+Met (p < 0.05). Although only CR improved fasting insulin and glucose, the combination of CR+Met was needed to improve post-challenge glucose tolerance. All treatments lowered hepatic triglycerides, but further improvements were observed in the CR groups (p < 0.05, Met vs. CR or CR+Met) and a further reduction in serum alanine aminotransferases was observed in CR+Met rats. CR lowered markers of hepatic de novo lipogenesis (fatty acid synthase, acetyl-CoA carboxylase (ACC), and stearoyl-CoA desaturase-1 (SCD-1)) and increased hepatic mitochondrial activity (palmitate oxidation and β-hydroxyacyl CoA dehydrogenase (β-HAD) activity). Changes were enhanced in the CR+Met group for ACC, SCD-1, β-HAD, and the mitophagy marker BNIP3. Met decreased total hepatic mTOR content and inhibited mTOR complex 1, which may have contributed to Met-induced reductions in de novo lipogenesis. These findings in the OLETF rat suggest that the combination of caloric restriction and metformin may provide a more optimal approach than either treatment alone in the management of type 2 diabetes and NAFLD.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".