Abstract 327: ETS Factors Regulate the VEGF-Dependent, Arterial-Specific Expression of Dll4
Bibliographic record
Abstract
Development of the vascular system begins with vasculogenesis, followed by the specification of endothelial cells into arterial and venous fates. Establishing and maintaining these separate fates is critical for the proper functioning of circulatory networks in the embryo as well as the mature adult. In fact, the congenital condition, Arteriovenous Malformation (AVM), arises due to defects during arterial-venous (AV) specification of endothelial cells, resulting in abnormal AV shunts that may burst leading to vascular lesions and stroke. To date, the molecular processes that control early AV specification remain incompletely understood. In the mouse, Delta-like 4 (Dll4) is a critical mediator of AV identity as loss of only one copy of Dll4 produces AV specification defects and embryonic lethality. Although previous studies have shown that Dll4 is the first Notch ligand expressed in the arterial endothelium and that its expression is induced by Vascular endothelial growth factor, the transcriptional pathways that direct its arterial-specific expression are unknown. Here we report the identification of an arterial-specific enhancer of the Dll4 gene. We show through deletion analyses as well as gain-of-function and loss-of-function studies that Vegf signaling activates ETS factors in the arterial endothelium to drive expression of Dll4. Surprisingly, Notch signaling is not required for the initiation of Dll4 expression but rather functions as a maintenance factor in the arterial endothelium. These studies provide novel mechanistic insight into the transcriptional program that mediates arterial specification and may provide insight into the underlying defects that occur during the development of AVMs.
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) | 0.006 | 0.002 |
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".