Ecsit is required for Bmp signaling and mesoderm formation during mouse embryogenesis
Bibliographic record
Abstract
Bone morphogenetic proteins (Bmps) are members of the transforming growth factor beta (TGFbeta) superfamily that play critical roles during mouse embryogenesis. Signaling by Bmp receptors is mediated mainly by Smad proteins. In this study, we show that a targeted null mutation of Ecsit, encoding a signaling intermediate of the Toll pathway, leads to reduced cell proliferation, altered epiblast patterning, impairment of mesoderm formation, and embryonic lethality at embryonic day 7.5 (E7.5), phenotypes that mimic the Bmp receptor type1a (Bmpr1a) null mutant. In addition, specific Bmp target gene expression is abolished in the absence of Ecsit. Biochemical analysis demonstrates that Ecsit associates constitutively with Smad4 and associates with Smad1 in a Bmp-inducible manner. Together with Smad1 and Smad4, Ecsit binds to the promoter of specific Bmp target genes. Finally, knock-down of Ecsit with Ecsit-specific short hairpin RNA inhibits both Bmp and Toll signaling. Therefore, these results show that Ecsit functions as an essential component in two important signal transduction pathways and establishes a novel role for Ecsit as a cofactor for Smad proteins in the Bmp signaling pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".