Liver X Receptors as potential therapeutic targets in atherosclerosis
Bibliographic record
Abstract
PURPOSE: Atherosclerosis is the primary independent risk factor of cardiovascular disease, and Liver X Receptors (LXRalpha and LXRbeta) activation may play an anti-atherosclerosis effect. In this article, we summarize the current state of knowledge of roles of LXRs in physiology and homeostasis as well as the links between LXR action and atherosclerosis, and discuss the potential therapeutic effects of LXR agonists. SOURCE: A MEDLINE database search was performed to identify relevant articles using the keywords "liver X receptors", "LXRs", and "atherosclerosis". Additional papers were identified by a manual research of the references from the key articles. PRINCIPLE FINDINGS: Both LXR isoforms promote reverse cholesterol transport (RCT) and have anti-inflammatory activity. LXRalpha is the predominant receptor in the liver regulating triglyceride synthesis. The antiatherosclerotic ability of LXRs makes them attractive targets for drugs for the treatment of cardiovascular disease. However, LXR activation induces lipogenesis and hypertriglyceridemia. The first-generation synthetic ligands of LXR increase hepatic lipogenesis and plasma triglyceride levels. New LXR ligands need to be designed without undesirable side effects. CONCLUSION: LXR beta-selective agonists and LXR modulators, which act as agonists in macrophages and induce cholesterol efflux while as antagonists of lipogenesis in the liver, are two critical and attractive approaches to treat atherosclerosis and cardiovascular diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".