The Glucagon-like Peptide-2 Receptor Mediates Direct Inhibition of Cellular Apoptosis via a cAMP-dependent Protein Kinase-independent Pathway
Bibliographic record
Abstract
Glucagon and the glucagon-like peptides regulate metabolic functions via signaling through a glucagon receptor subfamily of G protein-coupled receptors. Activation of glucagon-like peptide-2 receptor (GLP-2R) signaling maintains the integrity of the intestinal epithelial mucosa via regulation of crypt cell proliferation. Because GLP-2 decreases mortality and reduces intestinal apoptosis in rodents after experimental injury, we examined whether GLP-2R signaling directly modifies the cellular response to external injury. We show here that activation of GLP-2R signaling inhibits cycloheximide-induced apoptosis in baby hamster kidney fibroblasts expressing a transfected GLP-2 receptor. GLP-2 reduced DNA fragmentation and improved cell survival, in association with reduced activation of caspase-3 and decreased poly(ADP-ribose) polymerase cleavage and reduced caspase-8 and caspase-9-like activities. Both GLP-2 and forskolin reduced mitochondrial cytochrome c release and decreased the cycloheximide-induced cleavage of caspase-3 in the presence or absence of the PKA inhibitor H-89. Similarly, GLP-2 increased cell survival following cycloheximide in the presence of the kinase inhibitors PD98054 and LY294002. These findings provide evidence that signaling through G protein-coupled receptors of the glucagon superfamily is directly linked to regulation of apoptosis and suggest the existence of a cAMP-dependent protein kinase-, phosphatidylinositol 3-kinase-, and mitogen-activated protein kinase-independent pathway coupling GLP-2R signaling to caspase inhibition and cell survival.
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) | 0.000 | 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 | 0.001 |
| 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".