Molecular mechanisms underlying AMPK‐induced inhibition of glucose uptake in primary rat adipocytes
Bibliographic record
Abstract
This study investigated the molecular mechanisms by which AMP‐kinase (AMPK) activation inhibits basal and insulin‐stimulated glucose uptake in primary adipocytes. Rat epididymal adipocytes were exposed to AICAR for 1h. Subsequently, glucose uptake and the phosphorylation states of AMPK, ACC, Akt, and the Akt substrate of 160kDa (AS160) were determined in primary adipocytes either expressing LacZ (control) or a kinase dead AMPKα1 mutant (KD‐AMPKα1). AICAR increased AMPK and ACC phopshorylation, without affecting basal and insulin‐stimulated Akt phosphorylation. However, AMPK activation suppressed AS160 phosphorylation by 80% and 50% and glucose uptake by 35% and 50% under basal and insulin‐stimulated conditions, respectively. Expression of the KD‐AMPKα1 mutant fully prevented the suppression of AS160 phosphorylation as well as the inhibitory effect of AICAR‐induced AMPK activation on basal and insulin‐stimulated glucose uptake. This study provides novel evidence that suppression of AS160 phosphorylation by AICAR‐induced AMPK activation leads to inhibition of basal and insulin‐stimulated glucose uptake in primary rat adipocytes. Disruption of AMPKα1 signaling fully prevented these effects, indicating that insulin‐signaling steps that are common to white adipose tissue and skeletal muscle regulation of glucose uptake are distinctly affected by AMPK activation in these tissues.
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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 | 0.001 |
| 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".