Nobiletin ameliorates high fat-induced disruptions in rhythmic glucagon-like peptide-1 secretion
Bibliographic record
Abstract
The incretin hormone glucagon-like peptide-1 (GLP-1) is secreted by the intestinal L cell in response to nutrient intake. However, GLP-1 secretion also follows a circadian rhythm which is disrupted by the saturated fatty acid palmitate in vitro and high-fat diet (HFD) feeding in vivo. The flavonoid nobiletin is a clock enhancer which improves metabolic homeostasis. Therefore, the aim of this study was to elucidate whether and how nobiletin mitigates the negative effects of palmitate and HFD-feeding on rhythmic GLP-1 release. Pre-treatment of murine GLUTag L cells with palmitate dampened the GLP-1 secretory response at the normal peak of secretion, while nobiletin co-treatment restored GLP-1 secretion and upregulated the 'metabolic pathway' transcriptome. Mice fed a HFD also lost their GLP-1 secretory rhythm in association with markedly increased GLP-1 levels and upregulation of L cell transcriptional pathways related to 'sensing' and 'transducing' cellular stimuli at the normal peak of GLP-1 release. Nobiletin co-administration reduced GLP-1 levels to more physiological levels and upregulated L cell 'oxidative metabolism' transcriptional pathways. Furthermore, nobiletin improved colonic microbial 16S rRNA gene diversity and reduced the levels of Proteobacteria in HFD-fed mice. Collectively, this study establishes that nobiletin improves the normal rhythm in GLP-1 secretion following fat-induced disruption.
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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 | 0.001 |
| 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".