An unexpected link between fatty acid synthase and cholesterol synthesis in proinflammatory macrophage activation
Bibliographic record
Abstract
Different immune activation states require distinct metabolic features and activities in immune cells. For instance, inhibition of fatty acid synthase (FASN), which catalyzes the synthesis of long-chain fatty acids, prevents the proinflammatory response in macrophages; however, the precise role of this enzyme in this response remains poorly defined. Consistent with previous studies, we found here that FASN is essential for lipopolysaccharide-induced, Toll-like receptor (TLR)-mediated macrophage activation. Interestingly, only agents that block FASN upstream of acetoacetyl-CoA synthesis, including the well-characterized FASN inhibitor C75, inhibited TLR4 signaling, while those acting downstream had no effect. We found that acetoacetyl-CoA could overcome C75's inhibitory effect, whereas other FASN metabolites, including palmitate, did not prevent C75-mediated inhibition. This suggested an unexpected role for acetoacetyl-CoA in inflammation that is independent of its role in palmitate synthesis. Our evidence further suggested that acetoacetyl-CoA arising from FASN activity promotes cholesterol production, indicating a surprising link between fatty acid synthesis and cholesterol synthesis. We further demonstrate that this process is required for TLR4 to enter lipid rafts and facilitate TLR4 signaling. In conclusion, we have uncovered an unexpected link between FASN and cholesterol synthesis that appears to be required for TLR signal transduction and proinflammatory macrophage activation.
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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 | 0.000 |
| 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".