Palmitoleate Reverses High Fat-induced Proinflammatory Macrophage Polarization via AMP-activated Protein Kinase (AMPK)
Bibliographic record
Abstract
A rise in tissue-embedded macrophages displaying "M1-like" proinflammatory polarization is a hallmark of metabolic inflammation during a high fat diet or obesity. Here we show that bone marrow-derived macrophages (BMDM) from high fat-fed mice retain a memory of their dietary environment in vivo (displaying the elevated proinflammatory genes Cxcl1, Il6, Tnf, Nos2) despite 7-day differentiation and proliferation ex vivo. Notably, 6-h incubation with palmitoleate (PO) reversed the proinflammatory gene expression and cytokine secretion seen in BMDM from high fat-fed mice. BMDM from low fat-fed mice exposed to palmitate (PA) for 18 h ex vivo also showed elevated expression of proinflammatory genes (Cxcl1, Il6, Tnf, Nos2, and Il12b) associated with M1 polarization. Conversely, PO treatment increased anti-inflammatory genes (Mrc1, Tgfb1, Il10, Mgl2) and oxidative metabolism, characteristic of M2 macrophages. Therefore, saturated and unsaturated fatty acids bring about opposite macrophage polarization states. Coincubation of BMDM with both fatty acids counteracted the PA-induced Nos2 expression in a PO dose-dependent fashion. PO also prevented PA-induced IκBα degradation, RelA nuclear translocation, NO production, and cytokine secretion. Mechanistically, PO exerted its anti-inflammatory function through AMP-activated protein kinase as AMP kinase knockout or inhibition by Compound C offset the PO-dependent prevention of PA-induced inflammation. These results demonstrate a nutritional memory of BMDM ex vivo, highlight the plasticity of BMDM polarization in response to saturated and unsaturated fatty acids, and identify the potential to reverse diet- and saturated fat-induced M1-like polarization by administering palmitoleate. These findings could have applicability to reverse obesity-linked inflammation in metabolically relevant tissues.
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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".