Regulation of hepatic cholesterol biosynthesis by berberine during hyperhomocysteinemia
Bibliographic record
Abstract
Hyperhomocysteinemia, an elevation of blood homocysteine levels, is a metabolic disorder associated with dysfunction of multiple organs. We previously demonstrated that hyperhomocysteinemia stimulated hepatic 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase leading to hepatic lipid accumulation and liver injury. The liver plays an important role in cholesterol biosynthesis and overall homeostasis. HMG-CoA reductase catalyzes the rate-limiting step in cholesterol biosynthesis. Hepatic HMG-CoA reductase is a major target for lowering cholesterol levels in patients with hypercholesterolemia. The aim of the present study was to examine the effect of berberine, a plant-derived alkaloid, on hepatic cholesterol biosynthesis in hyperhomocysteinemic rats and to identify the underlying mechanism. Hyperhomocysteinemia was induced in Sprague-Dawley rats by feeding a high-methionine diet for 4 wk. HMG-CoA reductase activity was markedly elevated in the liver of hyperhomocysteinemic rats, which was accompanied by hepatic lipid accumulation. Activation of HMG-CoA reductase was caused by an increase in its gene expression and a reduction in its phosphorylation (an inactive form of the enzyme). Treatment of hyperhomocysteinemic rats with berberine for 5 days inhibited HMG-CoA reductase activity and reduced hepatic cholesterol content. Such an inhibitory effect was mediated by increased phosphorylation of HMG-CoA reductase. Berberine treatment also improved liver function. These results suggest that berberine regulates hepatic cholesterol biosynthesis via increased phosphorylation of HMG-CoA reductase. Berberine may be therapeutically useful for the management of cholesterol homeostasis.
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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 | 0.000 | 0.000 |
| 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".