Combined treatments with metformin and phosphodiesterase inhibitors alleviate nonalcoholic fatty liver disease in high-fat diet fed rats: a comparative study
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) is an excessive accumulation of fats in the liver resulting in hepatic inflammation and fibrous tissue formation along with insulin resistance. This study was designed to investigate the possible protective effects of metformin alone and in combination with different phosphodiesterase inhibitors (PDEIs). Rats were fed a high-fat diet (HFD) for 16 weeks to induce NAFLD. Starting from week 12, rats received metformin alone or in combination with pentoxifylline, cilostazol, or sildenafil. HFD administration resulted in hepatic steatosis and inflammation in rats. In addition, liver index, body composition index, activities of liver enzymes, and serum lipids deviated from normal. Further, significant elevations were recorded compared to control in terms of serum glucose, insulin, and HOMA-IR (homeostasis model assessment index for insulin resistance), oxidative stress parameters, hepatic TNF-α and NF-κB gene expression, and iNOS protein expression. Rats treated with metformin showed a significant improvement in the aforementioned parameters. However, the addition of pentoxifylline to metformin treatment synergized its action and produced a fortified effect against HFD-induced NAFLD better than other PDEIs. Data from this study indicated that combined treatment of metformin and pentoxifylline had the most remarkable ameliorated effects against HFD-induced NAFLD; further clinical investigations are needed to approve PDEIs for NAFLD treatment.
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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) | 0.002 | 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 | 0.000 |
| 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".