Liver-Specific Disruption of the Murine Glucagon Receptor Produces α-Cell Hyperplasia
Bibliographic record
Abstract
Glucagon is a critical regulator of glucose homeostasis; however, mechanisms regulating glucagon action and α-cell function and number are incompletely understood. To elucidate the role of the hepatic glucagon receptor (Gcgr) in glucagon action, we generated mice with hepatocyte-specific deletion of the glucagon receptor. Gcgr(Hep)(-/-) mice exhibited reductions in fasting blood glucose and improvements in insulin sensitivity and glucose tolerance compared with wild-type controls, similar in magnitude to changes observed in Gcgr(-/-) mice. Despite preservation of islet Gcgr signaling, Gcgr(Hep)(-/-) mice developed hyperglucagonemia and α-cell hyperplasia. To investigate mechanisms by which signaling through the Gcgr regulates α-cell mass, wild-type islets were transplanted into Gcgr(-/-) or Gcgr(Hep)(-/-) mice. Wild-type islets beneath the renal capsule of Gcgr(-/-) or Gcgr(Hep)(-/-) mice exhibited an increased rate of α-cell proliferation and expansion of α-cell area, consistent with changes exhibited by endogenous α-cells in Gcgr(-/-) and Gcgr(Hep)(-/-) pancreata. These results suggest that a circulating factor generated after disruption of hepatic Gcgr signaling can increase α-cell proliferation independent of direct pancreatic input. Identification of novel factors regulating α-cell proliferation and mass may facilitate the generation and expansion of α-cells for transdifferentiation into β-cells and the treatment of diabetes.
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 | 0.001 | 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) | 0.002 | 0.001 |
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".