Conjugated Linoleic Acid Suppresses NF-κB Activation and IL-12 Production in Dendritic Cells through ERK-Mediated IL-10 Induction
Bibliographic record
Abstract
Polyunsaturated fatty acids (PUFA) have been shown to modulate immune responses and have therapeutic effects in inflammatory disorders. However, the influence of PUFA on dendritic cells (DC), key cells of the innate immune system in shaping adaptive immune responses, has not yet been defined. In this study, we examine the effects of the cis-9, trans-11 isomer of conjugated linoleic acid (c9, t11-CLA), a dietary PUFA found in meat and dairy products, on murine DC activation. Treatment of DC with c9, t11-CLA suppressed LPS-induced IL-12, enhanced IL-10R expression, and enhanced IL-10 production at the transcriptional and protein level. The suppression of IL-12 by c9, t11-CLA was found to be IL-10 dependent. We investigated the involvement of the MAPK, ERK, and the transcription factor, NF-kappaB, in this IL-10-mediated effect. c9, t11-CLA enhanced ERK activation after LPS stimulation, and inhibition of ERK resulted in abrogation of IL-10 and recovery of IL-12 production. c9, t11-CLA decreased NF-kappaB:DNA binding after LPS stimulation, which was concomitant with delayed translocation of NF-kappaBp65 into the nucleus and an increase in IkappaBalpha. These effects were reversed by addition of a neutralizing anti-IL-10 Ab. Our findings demonstrate that c9, t11-CLA suppresses IL-12 production by LPS-stimulated DC by ERK mediated IL-10-induction. Furthermore, these IL-10-mediated effects are dependent on inhibition of NF-kappaB activation. This is the first study to demonstrate that c9, t11-CLA can enhance transcription and production of the anti-inflammatory cytokine IL-10, while inhibiting the Th1-promoting cytokine IL-12, and may explain certain of its immunosuppressive properties.
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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 | 0.000 |
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".