Absence of the Glucagon-Like Peptide-1 Receptor Does Not Affect the Metabolic Phenotype of Mice with Liver-Specific G<sub>s</sub>α Deficiency
Bibliographic record
Abstract
The stimulatory G protein α-subunit (G(s)α) couples hormone and other receptors to the generation of intracellular cAMP. We previously showed that mice with liver-specific G(s)α deficiency [liver-specific G(s)α knockout (LGsKO) mice] had reduced adiposity and improved glucose tolerance associated with increased glucose-stimulated insulin secretion, pancreatic islet hyperplasia, and very high serum glucagon and glucagon-like peptide 1 (GLP-1) levels. Because GLP-1 is known to stimulate insulin secretion and to have effects on energy balance, we mated LGsKO mice with germline GLP-1 receptor (GLP-1R) knockout mice (Glp1r(-/-)) and compared LGsKO to double-knockout (LGs/Glp1r(-/-)) mice to determine the contribution of excess GLP-1R signaling to the LGsKO phenotype. Loss of the GLP-1R failed to reverse most of the metabolic features of LGsKO mice, including reduced fat mass, increased glucose tolerance, and second-phase glucose-stimulated insulin secretion, islet cell hyperplasia, and very high glucagon and GLP-1 levels. However, loss of GLP-1R impaired first-phase insulin secretion in mice with or without liver-specific G(s)α deficiency. Thus, excess GLP-1 action (or at least through GLP-1R) does not contribute to the LGsKO metabolic phenotype, and other unknown factors involved in the cross talk between the liver G(s)α/cAMP pathway and pancreatic islet function need to be further elucidated.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".