FGF2 and BMP4 influence on FGFR2 dynamics during the segregation of epiblast and primitive endoderm cells in the pre-implantation mouse embryo
Bibliographic record
Abstract
Abstract Specification of the epiblast (EPI) and primitive endoderm (PE) in the mouse embryo involves FGF signaling through the RAS/MAP kinase pathway. FGFR1 and FGFR2 are thought to mediate this signaling in the inner cell mass (ICM) of the mouse blastocyst. In this study, we verified the dynamics of FGFR2 expression through a green fluorescent protein reporter mouse line (FGFR2-eGFP). We observed that FGFR2-eGFP is present in the late 8-cell stage; however, it is absent or reduced in the ICM of early blastocysts. We then correlated GFP expression with GATA6 and NANOG after immunostaining. We detected that GFP is weakly correlated with GATA6 in early blastocysts, but this correlation quickly increases as the blastocyst develops. The correlation between GFP and NANOG decreases throughout blastocyst development. Treatment with FGF from the morula stage onwards did not affect FGFR2-eGFP presence in the ICM of early blastocysts; however, late blastocysts presented FGFR2-eGFP in all cells of the ICM. BMP treatment positively influenced FGFR2-eGFP expression and reduced the number of NANOG-positive cells in late blastocysts. In conclusion, FGFR2 is not strongly associated with PE precursors in the early blastocyst, but it is highly correlated with PE cells as blastocyst development progresses, consistent with the proposed role for FGF in maintenance rather than initiating the PE lineage.
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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".