Ligand-Dependent Corepressor (LCoR) Is a Rexinoid-Inhibited Peroxisome Proliferator-Activated Receptor <i>γ</i> –Retinoid X Receptor <i>α</i> Coactivator
Bibliographic record
Abstract
The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) is an essential regulator of placental development. To gain deeper insights into placental PPARγ signaling, we dissected its regulation of the Muc1 promoter. We find that, unlike prototypic target activation by heterodimeric receptors, which is either stimulated by or refractory to retinoid X receptor (RXR) ligands (rexinoids), the induction of Muc1 by liganded PPARγ requires RXRα but is inhibited by rexinoids. We demonstrate that this inhibition is mediated by the activation function 2 (AF2) domain of RXRα and that Muc1 activation entails altered AF2 structures of both PPARγ and RXRα. This unique regulation of Muc1 reflects specific coactivation of PPARγ-RXRα heterodimers by the transcription cofactor ligand-dependent corepressor (LCoR), corroborated by significant downregulation of Muc1 in Lcor-null placentas. LCoR interacts with PPARγ and RXRα in a synergistic fashion via adjacent noncanonical protein motifs, and the AF2 domain of ligand-bound RXRα inhibits this interaction. We further identify the transcription factor Krüppel-like factor 6 (KLF6) as a critical regulator of placental development and a component of Muc1 regulation in cooperation with PPARγ, RXRα, and LCoR. Combined, these studies reveal new principles and players in nuclear receptor function in general and placental PPARγ signaling in particular.
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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) | 0.001 | 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".