AMPK activation by SC4 inhibits noradrenaline-induced lipolysis and insulin-stimulated lipogenesis in white adipose tissue
Bibliographic record
Abstract
The effects of small-molecule AMP-activated protein kinase (AMPK) activators in rat epididymal adipocytes were compared. SC4 was the most effective and submaximal doses of SC4 and 5-amino-4-imidazolecarboxamide (AICA) riboside were combined to study the effects of AMPK activation in white adipose tissue (WAT). Incubation of rat adipocytes with SC4 + AICA riboside inhibited noradrenaline-induced lipolysis and decreased hormone-sensitive lipase (HSL) Ser563 phosphorylation, without affecting HSL Ser565 phosphorylation. Preincubation of fat pads from wild-type (WT) mice with SC4 + AICA riboside inhibited insulin-stimulated lipogenesis from glucose or acetate and these effects were lost in AMPKα1 knockout (KO) mice, indicating AMPKα1 dependency. Moreover, in fat pads from acetyl-CoA carboxylase (ACC)1/2 S79A/S212A double knockin versus WT mice, the effect of SC4 + AICA riboside to inhibit insulin-stimulated lipogenesis from acetate was lost, pinpointing ACC as the main AMPK target. Treatment with SC4 + AICA riboside decreased insulin-stimulated glucose uptake, an effect that was still observed in fat pads from AMPKα1 KO versus WT mice, suggesting the effect was partly AMPKα1-independent. SC4 + AICA riboside treatment had no effect on the insulin-induced increase in palmitate esterification nor on sn-glycerol-3-phosphate-O-acyltransferase activity. Therefore in WAT, AMPK activation inhibits noradrenaline-induced lipolysis and suppresses insulin-stimulated lipogenesis primarily by inactivating ACC and by inhibiting glucose uptake.
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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) | 0.001 | 0.001 |
| 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".