Selective tethering of mural cell phosphodiesterase 4D variants allows spatial resolution of cAMP‐mediated events required for adhesion and migration
Bibliographic record
Abstract
Mural cells can inhibit vascular lesion progression and stabilize angiogenic vascular tubes during tissue repair or they can act maladaptively and promote atherosclerotic lesion progression and arterial stenosis; effects dependent on binding to selected extracellular matrix (ECM) proteins and on choosing between chemotactic gradients. Although cAMP, acting via protein kinase A (PKA) or exchange protein activated by cAMP (EPAC), impacts mural cell adhesion or migration, a consensus has emerged that individual actions occur within discrete “compartments” populated by cAMP‐signaling complexes (cAMP‐signalosomes). Previously we showed that PKA in leading edge structures in migrating mural cells was in a cAMP‐signalosome also populated by one (PDE4D8) of the five PDE4D variants in these cells. Displacing PDE4D8 from these structures activated PKA, inhibited actin assembly and inhibited migration. Here we report on the subcellular targeting of the five mural cell PDE4D variant, identify their interacting protein partner(s), and assess their impact on mural cell adhesion/migration. Our data show that each PDE4D variant impacts mural cell cAMP‐signaling and selectively control specific cellular functions.
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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".