Disrupted and Elevated Circadian Secretion of Glucagon-Like Peptide-1 in a Murine Model of Type 2 Diabetes
Bibliographic record
Abstract
Metabolism and circadian rhythms are intimately linked, with circadian glucagon-like peptide-1 (GLP-1) secretion by the intestinal L-cell entraining rhythmic insulin release. GLP-1 secretion has been explored in the context of obesogenic diets, but never in a rodent model of type 2 diabetes (T2D). There is also considerable disagreement regarding GLP-1 levels in human T2D. Furthermore, recent evidence has demonstrated decreased expression of the β-cell exocytotic protein secretagogin (SCGN) in T2D. To extend these findings to the L-cell, we administered oral glucose tolerance tests at 6 time points in 4-hour intervals to the high-fat diet/streptozotocin (HFD-STZ) mouse model of T2D. This revealed a 10-fold increase in peak GLP-1 secretion with a phase shift of the peak from the normal feeding period into the fasting-phase. This was accompanied by impairments in the rhythms of glucose, glucagon, mucosal clock genes (Arntl and Cry2), and Scgn. Immunostaining revealed that L-cell GLP-1 intensity was increased in the HFD-STZ model, as was the proportion of L-cells that expressed SCGN; however, this was not found in L-cells from humans with T2D, which exhibited decreased GLP-1 staining but maintained their SCGN expression. Gcg expression in isolated L-cells was increased along with pathways relating to GLP-1 secretion and electron transport chain activity in the HFD-STZ condition. Further investigation into the mechanisms responsible for this increase in GLP-1 secretion may give insights into therapies directed toward upregulating endogenous GLP-1 secretion.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".