Intraislet SLIT–ROBO signaling is required for beta-cell survival and potentiates insulin secretion
Bibliographic record
Abstract
We previously cataloged putative autocrine/paracrine signaling loops in pancreatic islets, including factors best known for their roles in axon guidance. Emerging evidence points to nonneuronal roles for these factors, including the Slit-Roundabout receptor (Robo) family, in cell growth, migration, and survival. We found SLIT1 and SLIT3 in both beta cells and alpha cells, whereas SLIT2 was predominantly expressed in beta cells. ROBO1 and ROBO2 receptors were detected in beta and alpha cells. Remarkably, even modest knockdown of Slit production resulted in significant beta-cell death, demonstrating a critical autocrine/paracrine survival role for this pathway. Indeed, recombinant SLIT1, SLIT2, and SLIT3 decreased serum deprivation, cytokine, and thapsigargin-induced cell death under hyperglycemic conditions. SLIT treatment also induced a gradual release of endoplasmic reticulum luminal Ca(2+), suggesting a unique molecular mechanism capable of protecting beta cells from endoplasmic reticulum stress-induced apoptosis. SLIT treatment was also associated with rapid actin remodeling. SLITs potentiated glucose-stimulated insulin secretion and increased the frequency of glucose-induced Ca(2+) oscillations. These observations point to unexpected roles for local Slit secretion in the survival and function of pancreatic beta cells. Because diabetes results from a deficiency in functional beta-cell mass, these studies may contribute to therapeutic approaches for improving beta-cell survival and function.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".