Adipocyte Lipolysis-stimulated Interleukin-6 Production Requires Sphingosine Kinase 1 Activity
Bibliographic record
Abstract
Adipocyte lipolysis can increase the production of inflammatory cytokines such as interleukin-6 (IL-6) that promote insulin resistance. However, the mechanisms that link lipolysis with inflammation remain elusive. Acute activation of β3-adrenergic receptors (ADRB3) triggers lipolysis and up-regulates production of IL-6 in adipocytes, and both of these effects are blocked by pharmacological inhibition of hormone-sensitive lipase. We report that stimulation of ADRB3 induces expression of sphingosine kinase 1 (SphK1) and increases sphingosine 1-phosphate production in adipocytes in a manner that also depends on hormone-sensitive lipase activity. Mechanistically, we found that adipose lipolysis-induced SphK1 up-regulation is mediated by the c-Jun N-terminal kinase (JNK)/activating protein-1 signaling pathway. Inhibition of SphK1 by sphingosine kinase inhibitor 2 diminished the ADRB3-induced IL-6 production both in vitro and in vivo. Induction of IL-6 by ADRB3 activation was suppressed by siRNA knockdown of Sphk1 in cultured adipocytes and was severely attenuated in Sphk1 null mice. Conversely, ectopic expression of SphK1 increased IL-6 expression in adipocytes. Collectively, these data demonstrate that SphK1 is a critical mediator in lipolysis-triggered inflammation in adipocytes.
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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".