Docosahexaenoic Acid Decreases Pro-Inflammatory Mediators in an In Vitro Murine Adipocyte Macrophage Co-Culture Model
Bibliographic record
Abstract
Paracrine interactions between adipocytes and macrophages contribute to chronic inflammation in obese adipose tissue. Dietary strategies to mitigate such inflammation include long-chain polyunsaturated fatty acids, docosahexaenoic (DHA) and eicosapentaenoic (EPA) acids, which act through PPARγ-dependent and independent pathways. We utilized an in vitro co-culture model designed to mimic the ratio of macrophages:adipocytes in obese adipose tissue, whereby murine 3T3-L1 adipocytes were cultured with RAW 264.7 macrophages in direct contact, or separated by a trans-well membrane (contact-independent mechanism), with 125 µM of albumin-complexed DHA, EPA, palmitic acid (PA), or albumin alone (control). Thus, we studied the effect of physical cell contact versus the presence of soluble factors, with or without a PPARγ antagonist (T0070907) in order to elucidate putative mechanisms. After 12 hr, DHA was the most anti-inflammatory, decreasing MCP1 and IL-6 secretion in the contact system (-57%, -63%, respectively, p ≤ 0.05) with similar effects in the trans-well system. The trans-well system allowed for isolation of cell types for inflammatory mediator analysis. DHA decreased mRNA expression (p<0.05) of Mcp1 (-7.1 fold) and increased expression of the negative regulator, Mcp1-IP (+1.5 fold). In macrophages, DHA decreased mRNA expression of pro-inflammatory M1 polarization markers (p ≤ 0.05), Nos2 (iNOS; -7 fold), Tnfα (-4.2 fold) and Nfκb (-2.3 fold), while increasing anti-inflammatory Tgfβ1 (+1.7 fold). Interestingly, the PPARγ antagonist co-administered with DHA or EPA in co-culture reduced (p ≤ 0.05) adiponectin cellular protein, without modulating other cytokines (protein or mRNA). Overall, our findings suggest that DHA may lessen the degree of MCP1 and IL-6 secreted from adipocytes, and may reduce the degree of M1 polarization of macrophages recruited to adipose tissue, thereby decreasing the intensity of pro-inflammatory cross-talk between adipocytes and macrophages in obese 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".