Berberine ameliorates high-fat diet-induced metabolic disorders through promoting gut Akkermansia and modulating bile acid metabolism
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Coptidis Rhizoma, the rhizome of Coptis chinensis Franch., has long been employed in the treatment of diabetes. Its active component, berberine, has been utilized in clinical practice; however, the underlying mechanisms of its protective effects remain to be fully elucidated. METHODS: Metabolomics and lipidomics analyzed plasma metabolite and lipid changes in mice fed a high-fat diet and treated with 25 mg/kg/day berberine for three months. Metagenomics and microbiota transplantation identified gut microbiota responding to berberine. Co-administration of berberine and Akkermansia was studied for metabolic effects, analyzing plasma and fecal metabolomics. RESULTS: Berberine reduced triglycerides and cholesterol, showing metabolic protective effects. Metagenomics identified Akkermansia as key to berberine's benefits, validated by microbiota transplantation. Berberine enhanced Akkermansia growth, preserving intestinal mucus and tight junctions. It promotes the conversion of cholesterol to bile acids by inhibiting adenosine 5 '-monophosphate -activated protein kinase (AMPK), which promotes the expression of cholesterol 7-alpha hydroxylase (CYP7A1). Co-administration of berberine and Akkermansia amplified these effects. Potential metabolites, including linoleic acid and N-acetylputrescine, contributed to the observed benefits. CONCLUSION: Berberine, through Akkermansia, maintains intestinal integrity and reduces cholesterol, highlighting its potential as a therapeutic agent for metabolic disorders. Combining berberine with Akkermansia enhances its efficacy against hyperlipidemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it