SSTR2 is the functionally dominant somatostatin receptor in human pancreatic β- and α-cells
Bibliographic record
Abstract
Somatostatin-14 (SST) inhibits insulin and glucagon secretion by activating G protein-coupled somatostatin receptors (SSTRs), of which five isoforms exist (SSTR1-5). In mice, the effects on pancreatic β-cells are mediated by SSTR5, whereas α-cells express SSTR2. In both cell types, SSTR activation results in membrane hyperpolarization and suppression of exocytosis. Here, we examined the mechanisms by which SST inhibits secretion from human β- and α-cells and the SSTR isoforms mediating these effects. Quantitative PCR revealed high expression of SSTR2, with lower levels of SSTR1, SSTR3, and SSTR5, in human islets. Immunohistochemistry showed expression of SSTR2 in both β- and α-cells. SST application hyperpolarized human β-cells and inhibited action potential firing. The membrane hyperpolarization was unaffected by tolbutamide but antagonized by tertiapin-Q, a blocker of G protein-gated inwardly rectifying K⁺ channels (GIRK). The effect of SST was mimicked by an SSTR2-selective agonist, whereas a SSTR5 agonist was marginally effective. SST strongly (>70%) reduced depolarization-evoked exocytosis in both β- and α-cells. A slightly weaker inhibition was observed in both cell types after SSTR2 activation. SSTR3- and SSTR1-selective agonists moderately reduced the exocytotic responses in β- and α-cells, respectively, whereas SSTR4- and SSTR5-specific agonists were ineffective. SST also reduced voltage-gated P/Q-type Ca²⁺ currents in β-cells, but normalization of Ca²⁺ influx to control levels by prolonged depolarizations only partially restored exocytosis. We conclude that SST inhibits secretion from both human β- and α-cells by activating GIRK and suppressing electrical activity, reducing P/Q-type Ca²⁺ currents, and directly inhibiting exocytosis. These effects are mediated predominantly by SSTR2 in both cell types.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".