Epinephrine-mediated regulation of PDK4 mRNA in rat adipose tissue
Bibliographic record
Abstract
Fatty acid reesterification in adipose tissue is dependent on the generation of glycerol 3-phosphate, and, at least in rodent adipose tissue, this appears to occur primarily through glyceroneogenesis. A key enzyme in this process is pyruvate dehydrogenase kinase 4 (PDK4). PDK4 is induced in white adipose tissue by thiazolidinediones (TZDs) and the inhibition or knockdown of PDK4 inhibits TZD-induced increases in glyceroneogenesis. Since TZDs have many unwanted side effects, we were interested in identifying alternative mechanisms that could regulate PDK4 mRNA expression in white adipose tissue. In this regard we hypothesized that exercise, fasting, and epinephrine would increase PDK4 mRNA levels in rat epididymal adipose tissue. We further postulated that the p38 mitogen-activated protein kinase (MAPK) and 5'-AMP-activated protein kinase (AMPK) signaling pathways would control PDK4 mRNA expression in cultured adipose tissue. Exercise, fasting, and in or ex vivo epinephrine treatment increased PDK4 mRNA levels. These perturbations did not increase the expression of PDK1, -2, or -3. Pyruvate dehydrogenase phosphorylation was increased after an overnight fast and 4 h after the cessation of exercise. In cultured adipose tissue, epinephrine increased p38 and AMPK signaling; however, the direct activation of AMPK by AICAR or metformin led to reductions in PDK4 mRNA levels. The p38 inhibitor SB202190 reduced epinephrine-mediated increases in p38 MAPK activation without altering hormone-sensitive lipase or AMPK phosphorylation or attenuating epinephrine-induced increases in lipolysis. Reductions in p38 MAPK signaling were associated with decreases in PDK4 mRNA expression. The inhibition of peroxisome proliferator-activated receptor-γ (PPARγ) also attenuated the induction of PDK4. Our results are the very first to demonstrate an epinephrine-mediated regulation of PDK4 mRNA levels in white adipose tissue and suggest that p38 MAPK and PPARγ could be involved in this pathway.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".