Relative effects of VEGF‐A and VEGF‐C on endothelial cell proliferation, migration and PAF synthesis: Role of neuropilin‐1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vascular endothelial growth factor (VEGF-A) is an inducer of endothelial cell (EC) proliferation, migration, and synthesis of inflammatory agents such as platelet-activating factor (PAF). Recently, neuropilin-1 (NRP-1) has been described as a coreceptor of KDR which potentiates VEGF-A activity. However, the role of NRP-1 in numerous VEGF-A activities remains unclear. To assess the contribution of NRP-1 to VEGF-A mediated EC proliferation, migration, and PAF synthesis, we used porcine aortic EC (PAEC) recombinantly expressing Flt-1, NRP-1, KDR or KDR and NRP-1. Cells were stimulated with VEGF-A, which binds to Flt-1, KDR and NRP-1, and VEGF-C, which binds to KDR only. VEGF-A was 12.4-fold more potent than VEGF-C in inducing KDR phosphorylation in PAEC-KDR. VEGF-A and VEGF-C showed similar potency to mediate PAEC-KDR proliferation, migration, and PAF synthesis. On PAEC-KDR/NRP-1, VEGF-A was 28.6-fold more potent than VEGF-C in inducing KDR phosphorylation and PAEC-KDR/NRP-1 proliferation (1.3-fold), migration (1.7-fold), and PAF synthesis (4.6-fold). These results suggest that cooperative binding of VEGF-A to KDR and NRP-1 enhances KDR phosphorylation and its biological activities. Similar results were obtained with bovine aortic EC that endogenously express both KDR and NRP-1 receptors. In contrast, stimulation of PAEC-Flt-1 and PAEC-NRP-1 with VEGF-A or VEGF-C did not induce proliferation, migration, or PAF synthesis. In conclusion, the presence of NRP-1 on EC preferentially increases KDR activation by VEGF-A as well as KDR-mediated biological activities, and may elicit novel intracellular events. On the other hand, VEGF-A and VEGF-C have equipotent biological activities on EC in absence of NRP-1.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it