Post-Translational Modifications of Nuclear Receptors and Human Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nuclear receptors (NR) impact a myriad of physiological processes including homeostasis, reproduction, development, and metabolism. NRs are regulated by post-translational modifications (PTM) that markedly impact receptor function. Recent studies have identified NR PTMs that are involved in the onset and progression of human diseases, including cancer. The majority of evidence linking NR PTMs with disease has been demonstrated for phosphorylation, acetylation and sumoylation of androgen receptor (AR), estrogen receptor α (ERα), glucocorticoid receptor (GR) and peroxisome proliferator activated receptor γ (PPARγ). Phosphorylation of AR has been associated with hormone refractory prostate cancer and decreased disease-specific survival. AR acetylation and sumoylation increased growth of prostate cancer tumor models. AR phosphorylation reduced the toxicity of the expanded polyglutamine AR in Kennedy's Disease as a consequence of reduced ligand binding. A comprehensive evaluation of ERα phosphorylation in breast cancer revealed several sites associated with better clinical outcome to tamoxifen therapy, whereas other phosphorylation sites were associated with poorer clinical outcome. ERα acetylation and sumoylation may also have predictive value for breast cancer. GR phosphorylation and acetylation impact GR responsiveness to glucocorticoids that are used as anti-inflammatory drugs. PPARγ phosphorylation can regulate the balance between growth and differentiation in adipose tissue that is linked to obesity and insulin resistance. Sumoylation of PPARγ is linked to repression of inflammatory genes important in patients with inflammatory diseases. NR PTMs provide an additional measure of NR function that can be used as both biomarkers of disease progression, and predictive markers for patient response to NR-directed treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it