β Cell tone is defined by proglucagon peptides through cAMP signaling
Bibliographic record
Abstract
Paracrine interactions between pancreatic islet cells have been proposed as a mechanism to regulate hormone secretion and glucose homeostasis. Here, we demonstrate the importance of proglucagon-derived peptides (PGDPs) for α to β cell communication and control of insulin secretion. Signaling through this system occurs through both the glucagon-like peptide receptor (Glp1r) and glucagon receptor (Gcgr). Loss of PGDPs, or blockade of their receptors, decreases insulin secretion in response to both metabolic and nonmetabolic stimulation of mouse and human islets. This effect is due to reduced β cell cAMP and affects the quantity but not dynamics of insulin release, indicating that PGDPs dictate the magnitude of insulin output in an isolated islet. In healthy mice, additional factors that stimulate cAMP can compensate for loss of PGDP signaling; however, input from α cells is essential to maintain glucose tolerance during the metabolic stress induced by high-fat feeding. These findings demonstrate an essential role for α cell regulation of β cells, raising the possibility that abnormal paracrine signaling contributes to impaired insulin secretion in diabetes. Moreover, these findings support reconsideration of the role for α cells in postprandial glucose control.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".