Prolonged AICAR-induced AMP-kinase activation promotes energy dissipation in white adipocytes: novel mechanisms integrating HSL and ATGL
Bibliographic record
Abstract
This study was designed to investigate the effects of prolonged activation of AMP-activated protein kinase (AMPK) on lipid partitioning and the potential molecular mechanisms involved in these processes in white adipose tissue (WAT). Rat epididymal adipocytes were incubated with 5'-aminoimidasole-4-carboxamide-1-beta-d-ribofuranoside (AICAR;0.5 mM) for 15 h. Also, epididymal adipocytes were isolated 15 h after AICAR was injected (i.p. 0.7 g/kg body weight) in rats. Adipocytes were utilized for various metabolic assays and for determination of gene expression and protein content. Time-dependent in vivo plasma NEFA concentrations were determined. AICAR treatment significantly increased AMPK activation, inhibited lipogenesis, and increased FA oxidation. This was accompanied by upregulation of peroxisome proliferator-activated receptor (PPAR)alpha, PPARdelta, and PPARgamma-coactivator-1alpha (PGC-1alpha) mRNA levels. Lipolysis was first suppressed, but then increased, both in vitro and in vivo, with prolonged AICAR treatment. Exposure to AICAR increased adipose triglyceride lipase (ATGL) content and FA release, despite inhibition of basal and epinephrine-stimulated hormone-sensitive lipase (HSL) activity. Here, we provide evidence that prolonged AICAR-induced AMPK activation can remodel adipocyte metabolism by upregulating pathways that favor energy dissipation versus lipid storage in WAT. Additionally, we show novel time-dependent effects of AICAR-induced AMPK activation on lipolysis, which involves antagonistic modulation of HSL and ATGL.
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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".