Folic acid supplementation during high-fat diet feeding restores AMPK activation via an AMP-LKB1-dependent mechanism
Bibliographic record
Abstract
AMPK is an endogenous energy sensor that regulates lipid and carbohydrate metabolism. Nonalcoholic fatty liver disease (NAFLD) is regarded as a hepatic manifestation of metabolic syndrome with impaired lipid and glucose metabolism and increased oxidative stress. Our recent study showed that folic acid supplementation attenuated hepatic oxidative stress and lipid accumulation in high-fat diet-fed mice. The aim of the present study was to investigate the effect of folic acid on hepatic AMPK during high-fat diet feeding and the mechanisms involved. Male C57BL/6J mice were fed a control diet (10% kcal fat), a high-fat diet (60% kcal fat), or a high-fat diet supplemented with folic acid (26 mg/kg diet) for 5 wk. Mice fed a high-fat diet exhibited hyperglycemia, hepatic cholesterol accumulation, and reduced hepatic AMPK phosphorylation. Folic acid supplementation restored AMPK phosphorylation (activation) and reduced blood glucose and hepatic cholesterol levels. Activation of AMPK by folic acid was mediated through an elevation of its allosteric activator AMP and activation of its upstream kinase, namely, liver kinase B1 (LKB1) in the liver. Consistent with in vivo findings, 5-methyltetrahydrofolate (bioactive form of folate) restored phosphorylation (activation) of both AMPK and LKB1 in palmitic acid-treated HepG2 cells. Activation of AMPK by folic acid might be responsible for AMPK-dependent phosphorylation of HMG-CoA reductase, leading to reduced hepatic cholesterol synthesis during high-fat diet feeding. These results suggest that folic acid supplementation may improve cholesterol and glucose metabolism by restoration of AMPK activation in the liver.
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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) | 0.000 | 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 | 0.001 | 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".