Both Protein Kinase A and Exchange Protein Activated by cAMP Coordinate Adhesion of Human Vascular Endothelial Cells
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Bibliographic record
Abstract
cAMP regulates integrin-dependent adhesions of vascular endothelial cells (VECs) to extracellular matrix proteins, their vascular endothelial cadherin-dependent intercellular adhesions, and their proliferation and migration in response to growth and chemotactic factors. Previously, we reported that cAMP-elevating agents differentially inhibited migration of human VECs isolated from large vascular structures (macro-VECs, human aortic endothelial cells [HAECs]) or small vascular structures (micro-VECs, human microvascular endothelial cells [HMVECs]) and that cAMP hydrolysis by phosphodiesterase (PDE)3 and PDE4 enzymes was important in coordinating this difference. Here we report that 2 cAMP-effector enzymes, namely protein kinase (PK)A and exchange protein activated by cAMP (EPAC), each regulate extracellular matrix protein-based adhesions of both macro- and micro-VECs. Of interest and potential therapeutic importance, we report that although specific pharmacological activation of EPAC markedly stimulated adhesion of micro-VECs to extracellular matrix proteins when PKA was inhibited, this treatment only modestly promoted adhesion of macro-VECs. Consistent with an important role for cAMP PDEs in this difference, PDE3 or PDE4 inhibitors promoted EPAC-dependent adhesions in micro-VECs when PKA was inhibited but not in macro-VECs. At a molecular level, we identify multiple, nonoverlapping, PKA- or EPAC-based signaling protein complexes in both macro- and micro-VECs and demonstrate that each of these complexes contains either PDE3B or PDE4D but not both of these PDEs. Taken together, our data support the concept that adhesion of macro- and micro-VECs is differentially regulated by cAMP and that these differences are coordinated through selective actions of cAMP at multiple nonoverlapping signaling complexes that contain PKA or EPAC and distinct PDE variants.
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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 | 0.001 | 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