Protein kinase C α modulates liver X receptor α transactivation
Bibliographic record
Abstract
Liver X receptor alpha (LXRalpha), an oxysterol-activated nuclear hormone receptor, regulates the expression of genes involved in lipid and cholesterol homeostasis and inflammation. We show here that transactivation by LXRalpha in monkey kidney COS-1 (Cos-1) cells is decreased by activation of the protein kinase C (PKC) signaling pathway. In transient co-transfection assays, phorbol myristate acetate (PMA) suppressed LXR-dependent transactivation of LXR-responsive reporter genes or the natural promoter of the human ATP-binding cassette (ABC), ABCA1 gene. The decrease in LXR transactivation after PMA treatment was also observed in human embryonic kidney (HEK) 293 and human hepatocellular carcinoma (HepG2) cells. Moreover, endogenous LXR target genes, ABCA1 and sterol response element-binding protein-1c, were also decreased by PMA treatment in HEK293 cells as assessed by real-time PCR. The PMA-mediated decrease of LXR activity was blocked by the PKC inhibitor bisindolylmaleimide and mimicked by constitutively active PKCalpha. Nuclear extracts treated with PMA show no decrease in LXRalpha DNA binding as assessed by mobility shift and chromatin immunoprecipitation assays. Additionally, in vitro kinase assays demonstrate that PKCalpha can phosphorylate LXRalpha. Our findings reveal a mode of regulation of LXRalpha that may be relevant to disease conditions where aberrant PKC signaling is observed, such as diabetes.
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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 | 0.001 |
| 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".