RXR acts as a coregulator in the regulation of genes of the hypothalamo-pituitary axis by thyroid hormone receptors
Bibliographic record
Abstract
Thyroid hormone receptors (TRs) often modulate transcriptional activity of target genes by heterodimerization with the 9-cis retinoic acid receptor (RXR). On positive thyroid response elements (TREs), RXR favors binding of the TR-RXR complex to DNA and stimulates transcription. RXR action on negative TREs is unclear. Furthermore, the single half-site configuration of many negative TREs does not favor the binding of a classic TR-RXR heterodimer. In a comparative study using CV-1 cells (relatively RXR- and TR-deficient) and JEG-3 cells (relatively TR-deficient), we demonstrate the importance of RXR in the negative transcriptional regulation of genes of the hypothalamo-pituitary axis by tri-iodothyronine. While RXR has variable effects on ligand-independent activation produced by TRs, it was required for efficient ligand-dependent repression of the TRH gene for TRalpha1 and TRbeta1 and of the TSH genes by all TRs. Using different RXR constructs we also observed the importance of the C-terminus of RXR but not of the N-terminus nor the DNA-binding domain, in the potentiation of negative regulation. We thus suggest that, with regard to negative regulation of the TRH and TSH genes by thyroid hormones, RXR behaves more like a cofactor than a classic heterodimerization partner.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".