Glucagon-like Peptide (GLP)-2 Action in the Murine Central Nervous System Is Enhanced by Elimination of GLP-1 Receptor Signaling
Bibliographic record
Abstract
Glucagon-like peptide-2 (GLP-2) regulates energy homeostasis via effects on nutrient absorption and maintenance of gut mucosal epithelial integrity. The biological actions of GLP-2 in the central nervous system (CNS) remain poorly understood. We studied the sites of endogenous GLP-2 receptor (GLP-2R) expression, the localization of transgenic LacZ expression under the control of the mouse GLP-2R promoter, and the actions of GLP-2 in the murine CNS. GLP-2R expression was detected in multiple extrahypothalamic regions of the mouse and rat CNS, including cell groups in the cerebellum, medulla, amygdala, hippocampus, dentate gyrus, pons, cerebral cortex, and pituitary. A 1.5-kilobase fragment of the mouse GLP-2R promoter directed LacZ expression to the gastrointestinal tract and CNS regions in the mouse that exhibited endogenous GLP-2R expression, including the cerebellum, amygdala, hippocampus, and dentate gyrus. Intracerebroventricular injection of GLP-2 significantly inhibited food intake during dark-phase feeding in wild-type mice. Disruption of glucagon-like peptide-1 receptor (GLP-1R) signaling with the antagonist exendin-(9-39) in wild-type mice or genetically in GLP-1R(-)/- mice significantly potentiated the anorectic actions of GLP-2. These findings illustrate that CNS GLP-2R expression is not restricted to hypothalamic nuclei and demonstrate that the anorectic effects of GLP-2 are transient and modulated by the presence or absence of GLP-1R signaling 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 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 | 0.000 |
| 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".