Role of Leptin in the Regulation of Glucagon-Like Peptide-1 Secretion
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1), released from intestinal endocrine L cells, is a potent insulinotropic hormone. GLP-1 secretion is diminished in obese patients. Because obesity is linked to abnormal leptin signaling, we hypothesized that leptin may modulate GLP-1 secretion. Leptin significantly stimulated GLP-1 secretion (by up to 250% of control) from fetal rat intestinal cells, a mouse L cell line (GLUTag), and a human L cell line (NCI-H716) in a dose-dependent manner (P < 0.05-0.001). The long form of the leptin receptor was shown to be expressed, and leptin induced the phosphorylation of STAT3 in the three cell types. The leptin receptor was also expressed by rodent and human intestinal L cells, and leptin (1 mg/kg i.p.) significantly stimulated GLP-1 secretion in rats and ob/ob mice. To determine the effect of leptin resistance on GLP-1 secretion, C57BL/6 mice were fed a high-fat (45%) or low-fat (10%) diet for 8 weeks. Mice on the high-fat diet became obese; developed glucose intolerance, hyperinsulinemia, and hyperleptinemia; and were leptin resistant. Mice on the high-fat diet also had twofold lower basal plasma GLP-1 and a diminished GLP-1 response to oral glucose, by 28.5 +/- 5.0% (P < 0.05). These results show for the first time that leptin stimulates GLP-1 secretion from rodent and human intestinal L cells, and they suggest that leptin resistance may account for the decreased levels of GLP-1 found in obese humans.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".