The Anti‐Lipolytic Effects of Acute AICAR‐Induced AMPK Activation in Visceral and Subcutaneous Rat Adipose Tissue is Independent of HSL Phosphorylation on Serine 563 and 660 Residues
Bibliographic record
Abstract
AICAR‐induced AMP‐activated protein kinase (AMPK) activation suppresses basal and epinephrine‐stimulated lipolysis in adipocytes. Our goal was to investigate whether the anti‐lipolytic effects of AICAR‐induced AMPK activation are mediated via inhibition of hormone sensitive lipase (HSL). Isolated rat epididymal (Epi), retroperitoneal (Ret), and subcutaneous (Sc) adipocytes were acutely (1h) incubated either in the absence or presence of AICAR (10 – 500μM), under basal and epinephrine (10μM) stimulated conditions. The lipolytic response and the phosphorylation status of HSL on Ser563 and Ser660 were determined. AICAR treatment significantly inhibited basal (77%, 31%, and 80%) and epinephrine stimulated (84%, 68%, and 86%) lipolysis in Epi, Ret, and Sc adipocytes, respectively. HSL phosphorylation on both serine residues was unaffected by AICAR under basal and epinephrine stimulated conditions. Interestingly, pharmacological inhibition of AMPK increased basal and epinephrine‐stimulated lipolysis and also reversed the anti‐lipolytic effect of low (10–100μM) AICAR concentrations. Even though lipolysis was increased by the AMPK inhibitor; HSL phosphorylation was not modified. These data indicate that the anti‐lipolytic effects of AICAR‐induced AMPK activation is independent of HSL phosphorylation, and appears to occur downstream of this enzyme. Funding was provided by NSERC, CIHR and CDA.
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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) | 0.002 | 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".