Nuclear Hormone Receptor Coregulator: Role in Hormone Action, Metabolism, Growth, and Development
Bibliographic record
Abstract
Nuclear hormone receptor coregulator (NRC) (also referred to as activating signal cointegrator-2, thyroid hormone receptor-binding protein, peroxisome proliferator activating receptor-interacting protein, and 250-kDa receptor associated protein) belongs to a growing class of nuclear cofactors widely known as coregulators or coactivators that are necessary for transcriptional activation of target genes. The NRC gene is also amplified and overexpressed in breast, colon, and lung cancers. NRC is a 2063-amino acid protein that harbors a potent N-terminal activation domain (AD1) and a second more centrally located activation domain (AD2) that is rich in Glu and Pro. Near AD2 is a receptor-interacting domain containing an LxxLL motif (LxxLL-1), which interacts with a wide variety of ligand-bound nuclear hormone receptors with high affinity. A second LxxLL motif (LxxLL-2) located in the C-terminal region of NRC is more restricted in its nuclear hormone receptor specificity. The intrinsic activation potential of NRC is regulated by a C-terminal serine, threonine, leucine-regulatory domain. The potential role of NRC as a cointegrator is suggested by its ability to enhance transcriptional activation of a wide variety of transcription factors and from its in vivo association with a number of known transcriptional regulators including CBP/p300. Recent studies in mice indicate that deletion of both NRC alleles leads to embryonic lethality resulting from general growth retardation coupled with developmental defects in the heart, liver, brain, and placenta. NRC(-/-) mouse embryo fibroblasts spontaneously undergo apoptosis, indicating the importance of NRC as a prosurvival and antiapoptotic gene. Studies with 129S6 NRC(+/-) mice indicate that NRC is a pleiotropic regulator that is involved in growth, development, reproduction, metabolism, and wound healing.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".