Liver X Receptor activation regulates genes involved in lipid homeostasis in developing chondrocytes
Bibliographic record
Abstract
Objective: Osteoarthritis (OA) is the most common type of arthritis and causes debilitating symptoms and decreased quality of life. A better understanding of the molecular mechanisms maintaining cartilage health is needed for developing novel therapeutic strategies. Liver X Receptors (LXRs) are nuclear receptors that have been previously shown to protect against OA. To better understand the regulatory mechanisms behind this effect, we systematically examined LXR's effects on growth plate chondrocyte gene expression. Methods: Primary chondrocytes isolated from the long bones of E15.5 mice were treated with the specific LXR agonist, GW3965, and RNA was isolated for Affymetrix microarrays. Bioinformatics analyses were performed using Gene Ontology (GO) and KEGG pathway analysis. Immunohistochemistry was conducted to examine protein localization of LXR and identified targets in GW3965-treated E15.5 tibiae compared to control. Results: LXR activation in primary growth plate chondrocytes resulted in differential regulations of various genes involved in lipid metabolism. This pattern was compared to LXR activation in immature murine articular chondrocytes (IMACs), which revealed similar roles in lipid homeostasis. Immunohistochemical analysis of LXR and its identified targets Abca1 and Srebf1 revealed preferential protein localization to pre-hypertrophic and resting chondrocytes in GW3965-treated tibial growth plates compared to controls. Conclusion: Our findings show for the first time that LXR activation alters expression of lipid metabolism genes in growth plate chondrocytes, in part through activation of molecules responsible for cellular cholesterol efflux. This provides insight into potential mechanisms through which LXR regulates cellular metabolism to alter chondrocyte behavior and phenotype.
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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".