Gluco-incretins control insulin secretion at multiple levels as revealed in mice lacking GLP-1 and GIP receptors
Bibliographic record
Abstract
The role of the gluco-incretin hormones GIP and GLP-1 in the control of beta cell function was studied by analyzing mice with inactivation of each of these hormone receptor genes, or both. Our results demonstrate that glucose intolerance was additively increased during oral glucose absorption when both receptors were inactivated. After intraperitoneal injections, glucose intolerance was more severe in double- as compared to single-receptor KO mice, and euglycemic clamps revealed normal insulin sensitivity, suggesting a defect in insulin secretion. When assessed in vivo or in perfused pancreas, insulin secretion showed a lack of first phase in Glp-1R(-/-) but not in Gipr(-/-) mice. In perifusion experiments, however, first-phase insulin secretion was present in both types of islets. In double-KO islets, kinetics of insulin secretion was normal, but its amplitude was reduced by about 50% because of a defect distal to plasma membrane depolarization. Thus, gluco-incretin hormones control insulin secretion (a) by an acute insulinotropic effect on beta cells after oral glucose absorption (b) through the regulation, by GLP-1, of in vivo first-phase insulin secretion, probably by an action on extra-islet glucose sensors, and (c) by preserving the function of the secretory pathway, as evidenced by a beta cell autonomous secretion defect when both receptors are inactivated.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".