Exercise Increases Apelin Expression In White Adipose Tissue
Bibliographic record
Abstract
PURPOSE: Apelin is a recently identified adipokine whose expression is controlled at least in part by PGC-1 alpha. Apelin has been shown to increase uncoupling protein 3 expression in skeletal muscle and to lead to increases in resting metabolic rate. To date the effects of exercise on PGC-1 alpha and apelin expression in white adipose tissue have not been determined. Within this context the purpose of the present investigation was to test the hypothesis that an acute bout of exercise would increase PGC-1 alpha and apelin expression in rat abdominal adipose tissue. A secondary aim of this study was to determine if epinephrine mediates exercise induced increases in these genes METHODS: To address these specific aims we used a rat model of swim exercise in combination with ex vivo adipose tissue organ culture and measured changes in gene expression in epididymal adipose tissue by RT-PCR. RESULTS: Immediately following 2 hours of swim exercise PGC-1 alpha and apelin expression were increased 4 fold in epididymal adipose tissue. The increase in PGC-1 alpha was associated with a ∼45% increase in apelin expression. Ex vivo epinephrine treatment for 2, 4, 6 or 12 hours led to increases in PGC-1 alpha and apelin expression. To assess if beta adrenergic signaling could mediate the effects of exercise on the induction of PGC-1 and apelin, rats were treated with saline or the beta blocker propranolol and exercised for 2 hours by swimming. The immediate post exercise increase in PGC-1 alpha was partially reduced by beta blockade while exercise induced increases in apelin were completely attenuated. CONCLUSIONS: This is the first study to demonstrate that exercise causes increases in PGC-1 alpha and apelin expression in white adipose tissue. Moreover, the current results are consistent with the hypothesis that beta adrenergic agonists mediate a portion of the exercise induced increases in PGC-1 alpha and apelin expression in white adipose tissue.
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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 | 0.000 |
| 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".