Impaired insulin-stimulated glucose transport in ATM-deficient mouse skeletal muscle
Bibliographic record
Abstract
There are reports that ataxia telangiectasia mutated (ATM) plays a role in insulin-stimulated Akt phosphorylation, although this is not the case in some cell types. Because Akt plays a key role in insulin signaling, which leads to glucose transport in skeletal muscle, the predominant tissue in insulin-stimulated glucose disposal, we examined whether insulin-stimulated Akt phosphorylation and (or) glucose transport would be decreased in skeletal muscle of mice lacking functional ATM, compared with muscle from wild-type mice. We found that in vitro insulin-stimulated Akt phosphorylation was normal in soleus muscle from mice with 1 nonfunctional allele of ATM (ATM+/-) and from mice with 2 nonfunctional alleles (ATM-/-). However, insulin did not stimulate glucose transport or the phosphorylation of AS160 in ATM-/- soleus. ATM protein level was markedly higher in wild-type extensor digitorum longus (EDL) than in wild-type soleus. In EDL from ATM-/- mice, insulin did not stimulate glucose transport. However, in contrast to findings for soleus, insulin-stimulated Akt phosphorylation was blunted in ATM-/- EDL, concomitant with a tendency for insulin-stimulated phosphatidylinositol 3-kinase activity to be decreased. Together, the findings suggest that ATM plays a role in insulin-stimulated glucose transport at the level of AS160 in muscle comprised of slow and fast oxidative-glycolytic fibers (soleus) and at the level of Akt in muscle containing fast glycolytic fibers (EDL).
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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 | 0.001 |
| 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) | 0.002 | 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".