WldS Enhances Insulin Transcription and Secretion via a SIRT1-Dependent Pathway and Improves Glucose Homeostasis
Bibliographic record
Abstract
UNLABELLED: OBJECTIVE Wld(S) (Wallerian degeneration slow), a fusion protein from a spontaneous mutation containing full-length nicotinamide mononucleotide adenylyltransferase 1, has NAD biosynthesis activity and protects axon from degeneration robustly. NAD biosynthesis is also implicated in insulin secretion in β-cells. The aim of this study was to investigate the effect of Wld(S) on β-cells and glucose homeostasis. RESEARCH DESIGN AND METHODS: Using the Wld(S) mice, we measured the expression of Wld(S) in pancreas and analyzed the effect of Wld(S) on glucose homeostasis. The direct effect of Wld(S) on insulin transcription and secretion and the related mechanisms was measured in isolated islets or β-cell lines. Silent information regulator 1 (SIRT1), an NAD-dependent protein deacetylase, is involved in insulin secretion. Thus, Wld(S) mice with SIRT1 deficiency were generated to study whether the SIRT1-dependent pathway is involved. RESULTS: Wld(S) is highly expressed in the pancreas and improves glucose homeostasis. Wld(S) mice are resistant to high-fat diet-induced glucose intolerance and streptozotocin (STZ)-induced hyperglycemia. Wld(S) increases insulin transcription dependent on its NAD biosynthesis activity and enhances insulin secretion. SIRT1 is required for the improved insulin transcription, secretion, and resistance to STZ-induced hyperglycemia caused by Wld(S). Moreover, Wld(S) associates with SIRT1 and increases NAD levels in the pancreas, causing the enhanced SIRT1 activity to downregulate uncoupling protein 2 (UCP2) expression and upregulate ATP levels. CONCLUSIONS: Our results demonstrate that Wld(S) combines an insulinotropic effect with protection against β-cell failure and suggest that enhancing NAD biosynthesis in β-cells to increase SIRT1 activity could be a potential therapeutic approach for diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".