A critical role for endoglin in the emergence of blood during embryonic development
Bibliographic record
Abstract
Much remains unknown about the signals that induce early mesoderm to initiate hematopoietic differentiation. Here, we show that endoglin (Eng), a receptor for the TGFβ superfamily, identifies all cells with hematopoietic fate in the early embryo. These arise in an Eng(+)Flk1(+) mesodermal precursor population at embryonic day 7.5 (E7.5), a cell fraction also endowed with endothelial potential. In Eng-knockout embryos, hematopoietic colony activity and numbers of CD71(+)Ter119(+) erythroid progenitors were severely reduced. This coincided with severely reduced expression of embryonic globin and key bone morphogenic protein (BMP) target genes, including the hematopoietic regulators Scl, Gata1, Gata2, and Msx-1. To interrogate molecular pathways active in the earliest hematopoietic progenitors, we applied transcriptional profiling to sorted cells from E7.5 embryos. Eng(+)Flk-1(+) progenitors coexpressed TGFβ and BMP receptors and target genes. Furthermore, Eng(+)Flk-1(+) cells presented high levels of phospho-SMAD1/5, indicating active TGFβ and/or BMP signaling. Remarkably, under hematopoietic serum-free culture conditions, hematopoietic outgrowth of Eng-expressing cells was dependent on the TGFβ superfamily ligands BMP4, BMP2, or TGF-β1. These data demonstrate that the E(+)F(+) fraction at E7.5 represents mesodermal cells competent to respond to TGFβ1, BMP4, or BMP2, shaping their hematopoietic development, and that Eng acts as a critical regulator in this process by modulating TGF/BMP signaling.
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 | 0.000 | 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".