Hepatic fibroblast growth factor 21 is required for curcumin or resveratrol in exerting their metabolic beneficial effect in male mice
Bibliographic record
Abstract
Our mechanistic understanding on metabolic beneficial effects of dietary polyphenols has been hampered for decades due to the lack of functional receptors for those compounds and their extremely low plasma concentrations. Recent studies by our team and others suggest that those dietary polyphenols target gut microbiome, and gut-liver axis and that hepatic fibroblast factor 21 (FGF21) serves as a common target for various dietary interventions. Utilizing liver-specific FGF21 null mice ( lFgf21 -/- ), we are asking a straightforward question: Is hepatic FGF21 required for curcumin or resveratrol, two typical dietary polyphenols, in exerting their metabolic beneficial effect in obesogenic diet-induced obesity mouse models. On low-fat diet feeding, no appreciable defect on glucose disposal was observed in male or female lFgf21 -/- mice, while fat tolerance was moderately impaired in male but not in female lFgf21 -/- mice, associated with elevated random and fasting serum triglyceride (TG) levels, and reduced hepatic expression of Ehhadh and Ppargc1a , which encodes the two downstream effectors of FGF21. On high-fat-high-fructose (HFHF) diet challenge, Fgf21 fl/fl but not lFgf21 -/- mice exhibited response to curcumin intervention on reducing fasting serum TG, and on improving fat tolerance. Resveratrol intervention also affected FGF21 expression or its downstream effectors. Metabolic beneficial effects of resveratrol intervention observed in HFHF diet-challenged Fgf21 fl/fl mice were either absent or attenuated in lFgf21 -/- mice. We conclude that hepatic FGF21 is required for curcumin or resveratrol in exerting their major metabolic beneficial effect. The recognition that FGF21 as the common target of dietary intervention, demonstrated in current as well as previous investigations, brings us a novel angle in understanding metabolic disease treatment and prevention. It remains to be further explored how various dietary interventions regulate FGF21 expression and function, via certain common or unique gut-liver or gut-brain-liver axis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".