Essential role of the ERK/MAPK pathway in blood-placental barrier formation
Bibliographic record
Abstract
The mammalian genome contains two ERK/MAP kinase kinase genes, Map2k1 and Map2k2, which encode dual-specificity kinases responsible for ERK activation. Loss of Map2k1 function in mouse causes embryonic lethality due to placental defects, whereas Map2k2 mutants have a normal lifespan. The majority of Map2k1(+/-) Map2k2(+/-) embryos die during gestation from the underdevelopment of the placenta labyrinth, demonstrating that both kinases are involved in placenta formation. Map2k1(+/-) Map2k2(+/-) mutants show reduced vascularization of the labyrinth and defective formation of syncytiotrophoblast layer II (SynT-II) leading to the accumulation of multinucleated trophoblast giant cells (MTGs). To define the cell type-specific contribution of the ERK/MAPK pathway to placenta development, we performed deletions of Map2k1 function in different Map2k1 Map2k2 allelic backgrounds. Loss of MAP kinase kinase activity in pericytes or in allantois-derived tissues worsens the MTG phenotype. These results define the contribution of the ERK/MAPK pathway in specific embryonic and extraembryonic cell populations for normal placentation. Our data also indicate that MTGs could result from the aberrant fusion of SynT-I and -II. Using mouse genetics, we demonstrate that the normal development of SynT-I into a thin layer of multinucleated cells depends on the presence of SynT-II. Lastly, the combined mutations of Map2k1 and Map2k2 alter the expression of several genes involved in cell fate specification, cell fusion and cell polarity. Thus, appropriate ERK/MAPK signaling in defined cell types is required for the proper growth, differentiation and morphogenesis of the placenta.
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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".