R-spondin1 Deficiency Enhances β-Cell Neogenesis in a Murine Model of Diabetes
Bibliographic record
Abstract
OBJECTIVE: The cWnt activator, R-spondin1 (Rspo1), regulates β-cell growth, function, and neogenesis, although its role in conditions such as streptozotocin (STZ)-induced diabetes is unknown. We hypothesized that Rspo1 deficiency enhances β-cell neogenesis in STZ-induced diabetes. METHODS: Wild-type (Rspo1) and knockout (Rspo1) mice were injected with STZ (40 mg/kg) for 5 days, followed by analysis of oral glucose and insulin tolerance, and were killed on day 6 (acute; 9-11 mice) or 32 (chronic; 11-16 mice). Immunohistochemistry was performed for β-cell apoptosis, proliferation, neogenesis, and markers of β-cell maturity. RESULTS: There was no difference in oral glucose handling between STZ-induced Rspo1 and Rspo1 mice, although Rspo1 mice demonstrated increased insulin sensitivity. β-cell mass, islet number, and islet size distribution did not differ between STZ-induced Rspo1 and Rspo1 mice, but Rspo1 animals had reduced β-cell apoptosis and increased numbers of insulin-positive ductal cells, indicating β-cell neogenesis. Furthermore, the increased β-cell regeneration observed in the Rspo1 animals was associated with a more differentiated/mature β-cell phenotype as assessed by increased immunopositivity for Nkx6.1, MafA, and GLUT2. CONCLUSIONS: These findings indicate that Rspo1 is a negative regulator of β-cell neogenesis, development, and survival in the face of STZ-induced diabetes, providing a therapeutic target for the enhancement of β-cell mass.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".