Reduced Nephrin Tyrosine Phosphorylation Enhances Insulin Secretion and Increases Glucose Tolerance With Age
Bibliographic record
Abstract
BACKGROUND: Nephrin is a transmembrane protein with well-established signaling roles in kidney podocytes, and a smaller set of secretory functions in pancreatic β cells are implicated in diabetes. Nephrin signaling is mediated in part through its 3 cytoplasmic YDxV motifs, which can be tyrosine phosphorylated by high glucose and β cell injuries. Although in vitro studies demonstrate these phosphorylated motifs can regulate β cell vesicle trafficking and insulin release, in vivo evidence of their role in this cell type remains to be determined. METHODS: To further explore the role of nephrin YDxV phosphorylation in β cells, we used a mouse line with tyrosine to phenylalanine substitutions at each YDxV motif (nephrin-Y3F) to inhibit phosphorylation. We assessed islet function via primary islet glucose-stimulated insulin secretion assays and oral glucose tolerance tests. RESULTS: Nephrin-Y3F mice successfully developed pancreatic endocrine and exocrine tissues with minimal structural differences. Unexpectedly, male and female nephrin-Y3F mice showed elevated insulin secretion, with a stronger increase observed in male mice. At 8 months of age, no differences in glucose tolerance were observed between wild-type (WT) and nephrin-Y3F mice. However, aged nephrin-Y3F mice (16 months of age) demonstrated more rapid glucose clearance compared to WT controls. CONCLUSION: Taken together, loss of nephrin YDxV phosphorylation does not alter baseline islet function. Instead, our data suggest a mechanism linking impaired nephrin YDxV phosphorylation to improved islet secretory ability with age. Targeting nephrin phosphorylation could provide novel therapeutic opportunities to improve β cell function.
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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) | 0.000 | 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) | 0.002 | 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".