Single-cell RNA sequencing identifies CXADR as a fate determinant of the placental exchange surface
Bibliographic record
Abstract
The placenta is the critical interface between mother and fetus, and consequently, placental dysfunction underlies many pregnancy complications. Placental formation requires an adequate expansion of trophoblast stem and progenitor cells followed by finely tuned lineage specification events. Here, using single-cell RNA sequencing of mouse trophoblast stem cells during the earliest phases of differentiation, we identify gatekeepers of the stem cell state, notably Nicol1, and uncover unsuspected trajectories of cell lineage diversification as well as regulators of lineage entry points. We show that junctional zone precursors and precursors of one of the two syncytial layers of the mouse placental labyrinth, the Syncytiotrophoblast-I lineage, initially share similar trajectories. Importantly, our functional analysis of one such lineage precursor marker, CXADR, demonstrates that this cell surface protein regulates the differentiation dynamics between the two syncytial layers of the mouse labyrinth, ensuring the correct establishment of the placental exchange surface. Deciphering the mechanisms underlying trophoblast lineage specification will inform our understanding of human pregnancy in health and disease.
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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".