Fenretinide Corrects the Imbalance between Omega-6 to Omega-3 Polyunsaturated Fatty Acids and Inhibits Macrophage Inflammatory Mediators via the ERK Pathway
Bibliographic record
Abstract
We previously identified Fragile X-related protein 1 (FXR1) as an RNA-binding protein involved in the post-transcriptional control of TNF and other cytokines in macrophages. Macrophages derived from FXR1-KO mice overexpress several inflammatory cytokines including TNF. Recently, we showed that fenretinide (4HPR) is able to inhibit several inflammatory cytokines in the lungs of cystic fibrosis mice, which also have abnormal immune responses. Therefore, we hypothesized that 4HPR might also be able to downregulate excessive inflammation even in macrophages with ablated FXR1. Indeed, our results demonstrate that 4HPR inhibited the excessive production of inflammatory mediators, including TNF, IL-6, CCL2 and CCL-5 in LPS-stimulated FXR1-KO macrophages, by selectively inhibiting phosphorylation of ERK1/2, which is naturally more phosphorylated in FXR1-KO cells. We also found that LPS stimulation of FXR1-KO macrophages led to significantly higher ratio of arachidonic acid/docosahexaenoic acid than observed in FXR1-WT macrophages. Interestingly, treatment with 4HPR was associated with the normalization of arachidonic acid/docosahexaenoic acid ratio in macrophages, which we found to impact phosphorylation of ERK1/2. Overall, this study shows for the first time that 4HPR modulates inflammatory cytokine expression in macrophages by correcting a phospholipid-bound fatty acid imbalance that impacts the phosphorylation of ERK1/2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.002 |
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 teacher head, 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".