An EPAC1/PDE1C-Signaling Axis Regulates Formation of Leading-Edge Protrusion in Polarized Human Arterial Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Pharmacological activation of protein kinase A (PKA) reduces migration of arterial smooth muscle cells (ASMCs), including those isolated from human arteries (HASMCs). However, when individual migration-associated cellular events, including the polarization of cells in the direction of movement or rearrangements of the actin cytoskeleton, are studied in isolation, these individual events can be either promoted or inhibited in response to PKA activation. While pharmacological inhibition or deficiency of exchange protein activated by cAMP-1 (EPAC1) reduces the overall migration of ASMCs, the impact of EPAC1 inhibition or deficiency, or of its activation, on individual migration-related events has not been investigated. Herein, we report that EPAC1 facilitates the formation of leading-edge protrusions (LEPs) in HASMCs, a critical early event in the cell polarization that underpins their migration. Thus, RNAi-mediated silencing, or the selective pharmacological inhibition, of EPAC1 decreased the formation of LEPs by these cells. Furthermore, we show that the ability of EPAC1 to promote LEP formation by migrating HASMCs is regulated by a phosphodiesterase 1C (PDE1C)-regulated "pool" of intracellular HASMC cAMP but not by those regulated by the more abundant PDE3 or PDE4 activities. Overall, our data are consistent with a role for EPAC1 in regulating the formation of LEPs by polarized HASMCs and show that PDE1C-mediated cAMP hydrolysis controls this localized event.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".