Oxysterol Activators of Liver X Receptor and 9-cis-Retinoic Acid Promote Sequential Steps in the Synthesis and Secretion of Tumor Necrosis Factor-α from Human Monocytes
Bibliographic record
Abstract
Liver X receptor alpha (LXRalpha), is a nuclear hormone receptor that is activated by oxysterols and plays a crucial role in regulating cholesterol and lipid metabolism in liver and cholesterol efflux from lipid-loaded macrophages. Here we show that treatment of human peripheral blood monocytes or monocytic THP-1 cells with the LXR ligand 22(R)-hydroxycholesterol (22(R)-HC), in combination with 9-cis-retinoic acid (9cRA), a ligand for the LXR heterodimerization partner retinoid X receptor (RXR), results in the specific induction of the potent pro-apoptotic and pro-inflammatory cytokine tumor necrosis factor-alpha (TNF-alpha). Promoter analysis, inhibitor studies, and order-of-addition experiments demonstrated that TNF-alpha induction by 22(R)-HC and 9cRA occurs by a novel two-step process. The initial step involves 22(R)-HC-dependent induction of TNF-alpha mRNA, and intracellular accumulation of TNF-alpha protein, mediated by binding of LXRalpha/RXRalpha to an LXR response element at position -879 of the TNF-alpha promoter. Subsequent cell release of TNF-alpha protein occurs via a separable 9cRA-dependent, LXRalpha-independent step that requires de novo transcription and protein synthesis. Our findings reveal a potentially new dimension of the physiological role of LXRalpha and identify a unique multistep pathway of TNF-alpha production that may be of consequence to the normal function of LXR in monocyte/macrophages and in disease conditions such as atherosclerosis.
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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) | 0.002 | 0.001 |
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".