Distinct functions of BMP4 during different stages of mouse ES cell neural commitment
Bibliographic record
Abstract
Bone morphogenetic protein (BMP) signaling plays a crucial role in maintaining the pluripotency of mouse embryonic stem cells (ESCs) and has negative effects on ESC neural differentiation. However, it remains unclear when and how BMP signaling executes those different functions during neural commitment. Here, we show that a BMP4-sensitive window exists during ESC neural differentiation. Cells at this specific period correspond to the egg cylinder stage epiblast and can be maintained as ESC-derived epiblast stem cells (ESD-EpiSCs), which have the same characteristics as EpiSCs derived from mouse embryos. We propose that ESC neural differentiation occurs in two stages: first from ESCs to ESD-EpiSCs and then from ESD-EpiSCs to neural precursor cells (NPCs). We further show that BMP4 inhibits the conversion of ESCs into ESD-EpiSCs during the first stage, and suppresses ESD-EpiSC neural commitment and promotes non-neural lineage differentiation during the second stage. Mechanistic studies show that BMP4 inhibits FGF/ERK activity at the first stage but not at the second stage; and IDs, as important downstream genes of BMP signaling, partially substitute for BMP4 functions at both stages. We conclude that BMP signaling has distinct functions during different stages of ESC neural commitment.
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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 | 0.000 |
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".