Cell and molecular regulation of the mouse blastocyst
Bibliographic record
Abstract
Animals use diverse strategies to specify tissue lineages during development. A common strategy is to partition maternally supplied and localized lineage determinants into progenitor cells. The mouse embryo appears to use a different, more regulative strategy to specify the first three lineages: the epiblast (EPI: future embryo), the trophectoderm (TE: future placenta), and the primitive endoderm (PE: future yolk sac). These lineages are specified during two successive differentiation steps leading to formation of the blastocyst. Here, we review classic and contemporary models of early lineage specification in the mouse, and describe recent efforts to understand the molecular regulation of these events. We describe evidence that trophectoderm differentiation bears resemblance to the process of epithelialization and describe the importance of apical/basal protein complexes in regulating this process. Next, we present a revised model of PE specification, and describe evidence that PE cells in the inner cell mass sort out to occupy their ultimate position on the surface of the EPI. Finally, we describe factors that reinforce these lineages and three distinct stem cell types that can be isolated from them. Together, these mechanisms guide the differentiation of the first lineages of the mouse and thereby set up tissues that will be important for the first steps of embryonic body patterning.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".