Notch1 Is Pan-Endothelial at the Onset of Flow and Regulated by Flow
Bibliographic record
Abstract
Arteriovenous differentiation is a key event during vascular development and hemodynamic forces play an important role. Arteriovenous gene expression is present before the onset of flow, however it remains plastic and flow can alter arteriovenous identity. Notch signaling is especially important in the genetic determination of arteriovenous identity. Nevertheless, the effect of the onset of circulation on Notch expression and signaling has not been studied. The aim of this study is therefore to investigate the interaction of Notch1 signaling and hemodynamic forces during early vascular development. We find that the onset of Notch1 expression coincides with the onset of flow, and that expression is pan-endothelial at the onset of circulation in mouse embryos and only becomes arterial-specific after remodeling has occurred. When we ablate flow in the early embryo, endothelial cells fail to express Notch1. We show that low and disturbed flow patterns upregulate Notch1 expression in endothelial cells in vitro, but that higher shear stress levels do not (≥10 dynes/cm2). Using siRNA, we knocked down Notch1 to investigate the role of Notch1 in mechanotransduction. When we applied shear stress levels similar to those found in embryonic arteries, we found an upregulation of Klf2, Dll1, Dll4, Jag1, Hey1, Nrp1 and CoupTFII but that only Dll4, Hey1, Nrp1 and EphB4 required Notch1 for flow-induced expression. Our results therefore indicate that Notch1 can modulate mechanotransduction but is not a critical mediator of the process since many genes mechanotransduce normally in the absence of Notch1, including genes involved in arteriovenous differentiation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".