Oxidized Low-Density Lipoprotein Loading of Macrophages Downregulates TLR-Induced Proinflammatory Responses in a Gene-Specific and Temporal Manner through Transcriptional Control
Bibliographic record
Abstract
Abstract Hypercholesterolemia is a key risk factor for atherosclerosis and leads to the uptake of native and oxidized low-density lipoprotein (oxLDL) by macrophages (Mϕs) and foam cell formation. Inflammatory processes accompany Mϕ foam cell formation in the artery wall, yet the relationship between Mϕ lipid loading and their response to inflammatory stimuli remains elusive. We investigated proinflammatory gene expression in thioglycollate-elicited peritoneal Mϕs, bone marrow–derived Mϕs and dendritic cells, and RAW264.7 cells. Loading with oxLDL did not induce peritoneal Mϕ apoptosis or modulate basal-level expression of proinflammatory genes. Upon stimulation of TLR4, the rapid induction of IFN-β was inhibited in cells loaded with oxLDL, whereas the induction of other proinflammatory genes by TLR4 (LPS), TLR3 (polyriboinosinic-polyribocytidylic acid), TLR2 (Pam3CSK4), and TLR9 (CpG) remained comparable within the first 2 h. Subsequently, the expression of a subset of proinflammatory genes (e.g., IL-1β, IL-6, CCL5) was reduced in oxLDL-loaded cells at the level of transcription. This phenomenon was partially dependent on NF erythroid 2–related factor 2 (NRF2) but not on nuclear liver X receptors α and β (LXRα,β), peroxisome proliferator-activated receptor-γ (PPARγ), and activating transcription factor 3 (ATF3). LPS-induced NF-κB reporter activity and intracellular signaling by NF-κB and MAPK pathways were comparable in oxLDL-loaded Mϕs, yet the binding of p65/RelA (the prototypic NF-κB family member) was reduced at IL-6 and CCL5 promoters. This study revealed that oxLDL loading of Mϕs negatively regulates transcription at late stages of TLR-induced proinflammatory gene expression and implicates epigenetic mechanisms such as histone deacetylase activity.
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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 | 0.001 | 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) | 0.000 | 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 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".