Activation of Peroxisome Proliferator–Activated Receptor Gamma and Retinoid X Receptor Results in Net Depletion of Cellular Cholesteryl Esters in Macrophages Exposed to Oxidized Lipoproteins
Bibliographic record
Abstract
OBJECTIVE: Peroxisome proliferator-activated receptor gamma (PPARgamma), a ligand-activated transcription factor, has pleiotropic effects, including regulation of macrophage differentiation and lipid homeostasis. The PPARgamma ligands, thiazolidinediones (TZDs), attenuate atherosclerosis in mice by uncertain mechanisms. The objective of this study was to determine whether activation of PPARgamma or its obligate heterodimer, retinoid X receptor (RXR), modulates macrophage foam cell formation induced by oxidized (ox) lipoproteins. METHODS AND RESULTS: Incubation of THP-1 macrophages with oxHTG-VLDL, oxREM, or oxLDL increased cellular cholesteryl ester over 6-fold. Preincubation with the TZD, ciglitazone, the RXR-specific ligand, 9-cis retinoic acid (9cRA) or the combination reduced CE mass accumulation by up to 65%. Ciglitazone and 9cRA increased CD36 mRNA (up to 4-fold); however, uptake of [125I]oxLDL was only modestly enhanced (up to 1.8-fold) becaues of a concomitant PPARgamma:RXR-induced decrease in SRAI/II activity (up to 40%). This suggested that PPARgamma:RXR activation inhibited cholesteryl ester accumulation by enhancing cholesterol efflux. Ciglitazone and 9cRA were found to increase the expression of ATP-binding cassette proteins A1 and G1, resulting in enhanced cholesterol efflux to lipoprotein-deficient serum, apoAI and HDL3. CONCLUSIONS: PPARgamma and/or RXR activation inhibit foam cell formation through enhanced cholesterol efflux despite increased oxLDL uptake. These observations explain the reduced atherosclerosis in TZD-treated mice and may extend the therapeutic implications of these ligands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".