Adrenergic Regulation of AMP-activated Protein Kinase in Brown Adipose Tissue in Vivo
Bibliographic record
Abstract
AMP-activated protein kinase (AMPK), an evolutionarily conserved serine-threonine kinase that senses cellular energy status, is activated by stress and neurohumoral stimuli. We investigated the mechanisms by which adrenergic signaling alters AMPK activation in vivo. Brown adipose tissue (BAT) is highly enriched in sympathetic innervation, which is critical for regulation of energy homeostasis. We performed unilateral denervation of BAT in wild type (WT) mice to abolish neural input. Six days post-denervation, UCP-1 protein levels and AMPK α2 protein and activity were reduced by 45%. In β(1,2,3)-adrenergic receptor knock-out mice, unilateral denervation led to a 25-45% decrease in AMPK activity, protein expression, and Thr(172) phosphorylation. In contrast, acute α- or β-adrenergic blockade in WT mice resulted in increased AMPK α Thr(172) phosphorylation and AMPK α1 and α2 activity in BAT. But short term blockade of α-adrenergic signaling in β(1,2,3)-adrenergic receptor knock-out mice resulted in decreased AMPK activity in BAT, which strongly correlated with enhanced phosphorylation of AMPK on Ser(485/491), a site associated with inhibition of AMPK activity. Both PKA and AKT inhibitors attenuated AMPK Ser(485/491) phosphorylation resulting from α-adrenergic blockade and prevented decreases in AMPK activity. In vitro mechanistic studies in BAT explants showed that the effects of α-adrenergic blockade appeared to be secondary to inhibition of oxygen consumption. In conclusion, adrenergic pathways regulate AMPK activity in vivo acutely via alterations in Thr(172) phosphorylation and chronically through changes in the α catalytic subunit protein levels. Furthermore, AMPK α Ser(485/491) phosphorylation may be a novel mechanism to inhibit AMPK activity in vivo and alter its biological effects.
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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 | 0.001 |
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".