Eicosapentaenoic Acid and Rosiglitazone Increase Adiponectin in an Additive and PPARγ‐Dependent Manner in Human Adipocytes
Bibliographic record
Abstract
Adiponectin, an anti-inflammatory and insulin-sensitizing protein secreted from adipose tissue, may be modulated by dietary fatty acids, although the mechanism is not fully known. Our objective was to investigate the effect of long-chain n-3 polyunsaturated fatty acids (PUFAs) on adiponectin in cultured human adipocytes, and to elucidate the role of peroxisome proliferator-activated receptor-γ (PPARγ) in this regulation. Isolated human adipocytes were cultured for 48 h with 100 µmol/l eicosapentaenoic acid (C20:5n-3, EPA), docosahexaenoic acid (C22:6n-3, DHA), palmitic acid (C16:0), 100 µmol/l EPA plus 100 µmol/l DHA, or bovine serum albumin (control). Additionally, adipocytes were treated for 48 h with a PPARγ antagonist (BADGE) or agonist (rosiglitazone) in isolation or in conjunction with either EPA or DHA. At 48 h, EPA and DHA increased (P < 0.05) adiponectin secretion by 88 and 47%, respectively, while EPA, but not DHA, also increased (136%, P < 0.001) cellular adiponectin protein. Interestingly, PPARγ antagonism completely abolished the DHA-mediated increase in secreted adiponectin, but only partially attenuated the EPA-mediated response. Thus, EPA's effects on adiponectin do not appear to be entirely PPARγ mediated. Rosiglitazone increased (P < 0.001) the secreted and cellular adiponectin protein (90 and 582%, respectively). Finally, the effects of EPA and rosiglitazone on adiponectin secretion were additive (+230% at 48 h combined, compared to 121 and 124% by EPA or rosiglitazone alone, respectively). Overall, our findings emphasize the therapeutic importance of long-chain n-3 PUFA alone, or in combination with a PPARγ agonist, as a stimulator of adiponectin, a key adipokine involved in obesity and related diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".