The citrus flavonoid nobiletin confers protection from metabolic dysregulation in high-fat-fed mice independent of AMPK
Bibliographic record
Abstract
Obesity, dyslipidemia, and insulin resistance, the increasingly common metabolic syndrome, are risk factors for CVD and type 2 diabetes that warrant novel therapeutic interventions. The flavonoid nobiletin displays potent lipid-lowering and insulin-sensitizing properties in mice with metabolic dysfunction. However, the mechanisms by which nobiletin mediates metabolic protection are not clearly established. The central role of AMP-activated protein kinase (AMPK) as an energy sensor suggests that AMPK is a target of nobiletin. We tested the hypothesis that metabolic protection by nobiletin required phosphorylation of AMPK and acetyl-CoA carboxylase (ACC) in mouse hepatocytes, in mice deficient in hepatic AMPK ( Ampkβ1 −/− ), in mice incapable of inhibitory phosphorylation of ACC ( AccDKI ), and in mice with adipocyte-specific AMPK deficiency ( iβ1β2AKO ). We fed mice a high-fat/high-cholesterol diet with or without nobiletin. Nobiletin increased phosphorylation of AMPK and ACC in primary mouse hepatocytes, which was associated with increased FA oxidation and attenuated FA synthesis. Despite loss of ACC phosphorylation in Ampkβ1 −/− hepatocytes, nobiletin suppressed FA synthesis and enhanced FA oxidation. Acute injection of nobiletin into mice did not increase phosphorylation of either AMPK or ACC in liver. In mice fed a high-fat diet, nobiletin robustly prevented obesity, hepatic steatosis, dyslipidemia, and insulin resistance, and it improved energy expenditure in Ampkβ1 −/− , AccDKI , and iβ1β2AKO mice to the same extent as in WT controls. Thus, the beneficial metabolic effects of nobiletin in vivo are conferred independently of hepatic or adipocyte AMPK activation. These studies further underscore the therapeutic potential of nobiletin and begin to clarify possible mechanisms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".