Implication of retinoic acid receptor selective signaling in myogenic differentiation
Bibliographic record
Abstract
Signaling molecules are important for committing individual cells into tissue-specific lineages during early vertebrate development. Retinoic acid (RA) is an important vertebrate morphogen, in that its concentration gradient is essential for correct patterning of the vertebrate embryo. RA signaling is mediated through the activation of retinoic acid receptors (RARs), which function as ligand-dependent transcription factors. In this study, we examined the molecular mechanisms of RAR-selective signaling in myogenic differentiation. We found that just like natural ligand RA, a RAR-selective ligand is an effective enhancer in the commitment of skeletal muscle lineage at the early stage of myogenic differentiation. Interestingly, the kinetics and molecular basis of the RAR-selective ligand in myogenic differentiation are similar to that of natural ligand RA. Also similar to natural ligand RA, the RAR-selective ligand enhances myogenic differentiation through β-catenin signaling pathway while inhibiting cardiac differentiation. Furthermore, while low concentrations of natural ligand RA or RAR-selective ligand regulate myogenic differentiation through RAR function and coactivator recruitment, high concentrations are critical to the expression of a model RA-responsive gene. Thus our data suggests that RAR-mediated gene regulation may be highly context-dependent, affected by locus-specific interaction or local chromatin environment.
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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".