Glucagon secretion and signaling in the development of diabetes
Bibliographic record
Abstract
Normal release of glucagon from pancreatic islet α-cells promotes glucose mobilization, which counteracts the hypoglycemic actions of insulin, thereby ensuring glucose homeostasis. In treatment of diabetes aimed at rigorously reducing hyperglycemia to avoid chronic complications, the resulting hypoglycemia triggering glucagon release from α-cells is frequently impaired, with ensuing hypoglycemic complications. This review integrates the physiology of glucagon secretion regulating glucose homeostasis in vivo to single α-cell signaling, and how both become perturbed in diabetes. α-cells within the social milieu of the islet micro-organ are regulated not only by intrinsic signaling events but also by paracrine regulation, particularly by adjacent insulin-secreting β-cells and somatostatin-secreting δ-cells. We discuss the intrinsic α-cell signaling events, including glucose sensing and ion channel regulation leading to glucagon secretion. We then discuss the complex crosstalk between the islet cells and the breakdown of this crosstalk in diabetes contributing to the dysregulated glucagon secretion. Whereas, there are many secretory products released by β- and δ-cells that become deficient or excess in diabetes, we discuss the major ones, including the better known insulin and lesser known somatostatin, which act as putative paracrine on/off switches that very finely regulate α-cell secretory responses in health and diabetes. Of note in several type 1 diabetes (T1D) rodent models, blockade of excess somatostatin actions on α-cell could normalize glucagon secretion sufficient to attain normoglycemia in response to hypoglycemic assaults. There has been slow progress in fully elucidating the pathophysiology of the α-cell in diabetes because of the small number of α-cells within an islet and the islet mass becomes severely reduced and inflamed in diabetes. These limitations are just now being surmounted by new approaches.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".