Fibroblast growth factor 21 and dietary interventions: what we know and what we need to know next
Bibliographic record
Abstract
Dietary interventions include the change of dietary styles, such as fasting and dietary or nutrient restrictions; or the addition of plant-derived compounds (such as polyphenols known as curcumin, resveratrol, or anthocyanin, or other nutraceuticals) into the diet. During the past a few decades, large number of studies have demonstrated therapeutic activities of these dietary interventions on metabolic and other diseases in human subjects or various animal models. Mechanisms underlying those versatile therapeutic activities, however, remain largely unclear. Interestingly, recent studies have shown that fibroblast growth factor 21 (FGF21), a liver-derived hormone or hepatokine, mediates metabolic beneficial effects of certain dietary polyphenols as well as protein restriction. Here I have briefly summarized functions of FGF21, highlighted related dietary interventions, and presented literature discussions on role of FGF21 in mediating function of dietary polyphenol intervention and protein restriction. This is followed by presenting my perspective view, with the involvement of gut microbiota. It is anticipated that further breakthroughs in this field in the near future will facilitate conceptual merge of classical medicine and modern medicine.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".