Elimination of glucagon-like peptide 1R signaling does not modify weight gain and islet adaptation in mice with combined disruption of leptin and GLP-1 action.
Bibliographic record
Abstract
Leptin and glucagon-like peptide 1 (GLP-1) exhibit opposing actions in the endocrine pancreas. GLP-1 stimulates insulin biosynthesis, secretion, and islet growth, whereas leptin inhibits glucose-dependent insulin secretion and insulin gene transcription. In contrast, GLP-1 and leptin actions overlap in the central nervous system, where leptin has been shown to activate GLP-1 circuits that inhibit food intake. To determine the physiological importance of GLP-1 receptor (GLP-1R)-leptin interactions, we studied islet function and feeding behavior in ob/ob:GLP-1R(-/-) mice. Although GLP-1R actions are thought to be essential for glucose-dependent insulin secretion, the levels of fasting glucose, glycemic excursion after glucose loading, glucose-stimulated insulin, and pancreatic insulin RNA content were similar in ob/ob:GLP-1R(+/+) versus ob/ob:GLP-1R(-/-) mice. Despite evidence linking GLP-1R signaling to the regulation of islet neogenesis and proliferation, ob/ob:GLP-1R(-/-) mice exhibited significantly increased islet numbers and area and an increase in the number of large islets compared with GLP-1R(+/+) or (-/-) mice (P < -0.01 to 0.05). Similarly, growth rates and both shortand long-term control of food intake were comparable in ob/ob:GLP-1R(+/+) versus ob/ob:GLP-1R4(-/-) mice. Furthermore, leptin produced a similar inhibition of food intake in GLP-1R(-/-), ob/ob:GLP-1R(+/+), and ob/ob:GLP1R4(-/-) mice. These findings illustrate that although leptin and GLP-1 actions overlap in the brain and endocrine pancreas, disruption of GLP-1 signaling does not modify the response to leptin or the phenotype of leptin deficiency in the ob/ob mouse, as assessed by long-term control of body weight or the adaptive beta-cell response to insulin resistance in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".