Cytokines promote lipolysis in 3T3-L1 adipocytes through induction of NADPH oxidase 3 expression and superoxide production
Bibliographic record
Abstract
NADPH oxidase (NOX) enzymes are one of the major superoxide-generating systems in cells. NOX-generated superoxide has been suggested to promote insulin resistance in the liver. However, the role of NOX enzymes in mediating metabolic dysfunction in other insulin target tissues remains unclear. Here, we show that NOX3 expression is induced in differentiated 3T3-L1 adipocytes upon treatment with proinflammatory cytokines. Superoxide production increased concurrently with NOX3 protein expression in cytokine-treated adipocytes, which was inhibited by the NOX inhibitor diphenyleneiodonium (DPI). Treatment of adipocytes with cytokines increased lipolysis and decreased PPARγ activity. Interestingly, treatment with DPI blunted lipolysis activation by cytokines but failed to restore PPARγ activity. siRNA-mediated NOX3 downregulation also prevented cytokine-induced superoxide generation and lipolysis. In line with increasing lipolysis, cytokines increased the phosphorylation of hormone-sensitive lipase (HSL), which was reversed by treatment with DPI and silencing of NOX3 expression. We conclude that NOX3 is a cytokine-inducible superoxide-generating enzyme in adipocytes, which promotes lipolysis through increasing phosphorylation of HSL. This suggests a key role for NOX3-mediated superoxide production in the increased adipocyte lipolysis in inflammatory settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.002 |
| 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".