Retinoic acid regulates Sox2 expression during neuronal and glial differentiation in mouse P19 cells
Bibliographic record
Abstract
Retinoic acid (RA) is a small lipophilic molecule that plays important roles in embryonic development by regulating cell proliferation, signaling and differentiation. There is compelling evidence that RA signaling controls the expression of a number of transcription factors in a spatio-temporal manner during these processes. In particular, Sox2, a transcription factor known for its involvement in stem cell fate commitment and neurogenesis may serve as a target of RA. In this study, we have used mouse embryonic carcinoma (EC) P19 cells to examine the effect of RA on Sox2 expression during neuronal and glial differentiation. Undifferentiated P19 cells express abundant levels of Sox2 during proliferation, a fact further supported by Sox2-DNA interaction throughout various stages of mitosis. In the presence of RA, P19 cells form embryonic bodies (EB) and differentiate into neurons and astrocytes in a chronological order similar to that of cell differentiation in the brain. RT-PCR, western blot and immunocytochemistry analyses show that the level of Sox2 is significantly reduced in P19 cells, as they differentiate into neurons, whereas P19 astrocytes maintain Sox2 expression. These results show that Sox2 is differentially expressed during neurogenesis and gliogenesis, suggesting its distinct functions throughout these processes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".