EPAC1 controls vascular endothelial cell permeability and the adaptation of these cells to differential fluid shear stress
Bibliographic record
Abstract
The permeability of a monolayer of vascular endothelial cells (VECs) to the paracellular transit of macromolecules is largely dependent on their ability to form vascular endothelial cadherin (VEcad)‐based contacts between neighbouring VECs and on the strength of the linkages between these VECad‐based structures and the actin cytoskeleton. We reported previously that cAMP‐elevating agents reduce VEC permeability largely through an exchange protein activated by cAMP‐1 (EPAC1)‐mediated strengthening of these inter‐VEC adhesions. Specifically, we showed that integration of EPAC1 into VECad‐based macromolecular signaling complexes allowed localized EPAC1‐dependent activation of Rap‐1 at regions of VEC intercellular contacts and reduced permeability. Since high VEC permeability occur in vivo in areas of the vasculature that experience low fluid shear‐stresses and these areas are more likely to develop atherosclerotic lesions, we studied the impact of EPAC1 activation on VEC permeability under conditions of high or low laminar shear stress. Our results indicated that while VECs aligned poorly when subjected to low fluid shear‐stresses, EPAC1 activators markedly promoted alignment under these conditions.
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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) | 0.001 | 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".