Glucose-regulated Glucagon Secretion Requires Insulin Receptor Expression in Pancreatic α-Cells
Bibliographic record
Abstract
The insulin receptor (IR) and its signaling appear to be essential for insulin secretion from pancreatic beta-cells. However, much less is known about the role of the IR in alpha-cells. To assess the role of the IR in glucagon and insulin secretion, we engineered adeno-viruses for high efficiency small interference RNA (siRNA)-IR expression in isolated mouse pancreatic islets and lentiviruses for siRNA-IR expression in pancreatic alpha- and beta-cell lines (alpha-TC6 and MIN6) with specific, long term stable IR knockdown. Western blot analysis showed that these strategies resulted in 60-80% reduction of IR protein in islets and alpha- and beta-cell lines. Cell growth was reduced by 35-50% in alpha-TC and MIN6 cells stably expressing siRNA-IR, respectively. Importantly, glucagon secretion, in response to glucose (25 to 2.8 mm), was completely abolished in islets expressing siRNA-IR, whereas secretion increased 1.7-fold in islets expressing control siRNA. In contrast, there was no difference in glucose-stimulated insulin secretion when comparing siRNA-IR and siRNA control, with both groups showing a 1.7-fold increase. Islet glucagon and insulin content were also unaffected by IR knockdown. To further explore the role of the IR, siRNA-IR was stably expressed in pancreatic cell lines, which dramatically suppressed glucose-regulated glucagon secretion in alpha-TC6 cells (3.4-fold) but did not affect GSIS in MIN6 cells. Defects in siRNA-IR-expressing alpha-cells were associated with an alteration in the activity of Akt and p70S6K where insulin-induced phosphorylation of protein kinase B/AKt was greatly reduced while p70S6K activation was enhanced, suggesting that the related pathways play important roles in alpha cell function. This study provides direct evidence that appropriate expression of the IR in alpha-cells is required for glucose-dependent glucagon secretion.
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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 | 0.000 |
| 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 | 0.001 |
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".