The Neuronal Ca2+ Sensor Protein Visinin-like Protein-1 Is Expressed in Pancreatic Islets and Regulates Insulin Secretion
Bibliographic record
Abstract
Visinin-like protein-1 (VILIP-1) is a member of the neuronal Ca2+ sensor protein family that modulates Ca2+-dependent cell signaling events. VILIP-1, which is expressed primarily in the brain, increases cAMP formation in neural cells by modulating adenylyl cyclase, but its functional role in other tissues remains largely unknown. In this study, we demonstrate that VILIP-1 is expressed in murine pancreatic islets and beta-cells. To gain insight into the functions of VILIP-1 in beta-cells, we used both overexpression and small interfering RNA knockdown strategies. Overexpression of VILIP-1 in the MIN6 beta-cell line or isolated mouse islets had no effect on basal insulin secretion but significantly increased glucose-stimulated insulin secretion. cAMP accumulation was elevated in VILIP-1-overexpressing cells, and the protein kinase A inhibitor H-89 attenuated increased glucose-stimulated insulin secretion. Overexpression of VILIP-1 in isolated mouse beta-cells increased cAMP content accompanied by increased cAMP-responsive element-binding protein gene expression and enhanced exocytosis as detected by cell capacitance measurements. Conversely, VILIP-1 knockdown by small interfering RNA caused a reduction in cAMP accumulation and produced a dramatic increase in preproinsulin mRNA, basal insulin secretion, and total cellular insulin content. The increase in preproinsulin mRNA in these cells was attributed to enhanced insulin gene transcription. Taken together, we have shown that VILIP-1 is expressed in pancreatic beta-cells and modulates insulin secretion. Increased VILIP-1 enhanced insulin secretion in a cAMP-associated manner. Down-regulation of VILIP-1 was accompanied by decreased cAMP accumulation but increased insulin gene transcription.
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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 | 0.001 |
| 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".