Sam68 promotes hepatic gluconeogenesis via CRTC2
Bibliographic record
Abstract
Abstract Hepatic gluconeogenesis is essential for glucose homeostasis and also a therapeutic target for type 2 diabetes, but its mechanism is incompletely understood. Here, we report that Sam68, an RNA-binding adaptor protein and Src kinase substrate, is a novel regulator of hepatic gluconeogenesis. Both global and hepatic deletions of Sam68 significantly reduce blood glucose levels and the glucagon-induced expression of gluconeogenic genes. Protein, but not mRNA, levels of CRTC2, a crucial transcriptional regulator of gluconeogenesis, are >50% lower in Sam68-deficient hepatocytes than in wild-type hepatocytes. Sam68 interacts with CRTC2 and reduces CRTC2 ubiquitination. However, truncated mutants of Sam68 that lack the C- (Sam68ΔC) or N-terminal (Sam68ΔN) domains fails to bind CRTC2 or to stabilize CRTC2 protein, respectively, and transgenic Sam68ΔN mice recapitulate the blood-glucose and gluconeogenesis profile of Sam68-deficient mice. Hepatic Sam68 expression is also upregulated in patients with diabetes and in two diabetic mouse models, while hepatocyte-specific Sam68 deficiencies alleviate diabetic hyperglycemia and improves insulin sensitivity in mice. Thus, our results identify a role for Sam68 in hepatic gluconeogenesis, and Sam68 may represent a therapeutic target for diabetes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".