Signal transduction in melanoma transendothelial migration using a tissue‐engineered human blood vessel
Bibliographic record
Abstract
Transendothelial migration involves major modifications in cell‐cell contact, consequent morphological changes and cytoskeletal reorganization. In this context, GTPases are key modulators in signal transduction leading to cellular modifications. Rap1, a member of the GTPase Ras Family, is implicated in the stability of endothelial adherent junctions. Rap1 is also implicated in integrin‐mediated adhesion of leukocytes to the endothelium, and participate in cadherin‐modulated adhesion. Those mechanisms are poorly understood, so further study is needed to elucidate the steps inherent to this process. We used a tissue‐engineered human blood vessel to analyze the role of Rap1 in the modulation of endothelial junctions. In endothelial cells monocultures, we observed that melanomas increased activated Rap1 and activated Extracellular Signal‐Regulated Kinase (Erk). We further analyzed the distribution of Zonula Occludens‐1 (ZO‐1) in endothelial tight junctions, and we observed a translocation to the nucleus when endothelial cells are stimulated with forskolin, a potent cAMP activator. We have to correlate those activations both with Rap1 signalling pathway and endothelial junctions remodelling. In the future, we will transpose those results using our 3D tissue‐engineered human blood vessels. Financial support is provided by the Canadian Institutes of Health Research.
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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 | 0.000 |
| 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".