Role of Endogenous Glucagon-Like Peptide-1 in Islet Regeneration After Partial Pancreatectomy
Bibliographic record
Abstract
A reduction in beta-cell mass is an important causative factor in type 1 and type 2 diabetes. Glucagon-like peptide-1 (GLP-1) and the long-acting agonist exendin 4 (Ex-4) expand beta-cell mass by stimulating neogenesis and proliferation. In the partial pancreatectomy (Ppx) model, exogenous Ex-4 promotes islet regeneration, leading to sustained improvement in glucose tolerance. In this study, we investigate the potential role of endogenous GLP-1 in islet growth. We examined beta-cell mass regeneration after 70% Ppx in mice receiving the GLP-1 antagonist Ex9-39 and in GLP-1R(-/-) mice. In Ex9-39-treated sham-operated mice, persistent fasting hyperglycemia was observed, but beta-cell mass was not diminished. In pancreatectomized mice, persistent glucose intolerance was noted, but this was not further exacerbated by Ex9-39. Accordingly, beta-cell mass recovery of Ppx mice was not impaired by Ex9-39. In contrast, GLP-1R(-/-) CD1 mice showed worse glucose intolerance after Ppx compared with wild-type CD1 Ppx mice, and this correlated with a significant defect in beta-cell mass regeneration. The recovery of beta-cell mass differed markedly in the BALB/c and CD1 control mice, indicating a significant role of genetic background in the regulation of beta-cell mass. These studies point to a role for endogenous GLP-1 in beta-cell regeneration after Ppx in mice.
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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) | 0.001 | 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".