Activation of the GTPase ARF6 regulates invasion of human vascular smooth muscle cells by stimulating MMP14 activity
Bibliographic record
Abstract
Hormones and growth factors stimulate vascular smooth muscle cells (VSMC) invasive capacities during the progression of atherosclerosis. The GTPase ARF6 is an important regulator of migration and proliferation of various cell types, but whether this small G protein can be activated by a variety of stimuli to promote invasion of VSMC remains unknown. Here, we aimed to define whether Platelet-derived growth factor (PDGF), a mitogenic stimulant of vascular tissues, and Angiotensin II (Ang II), a potent vasoactive peptide, can result in the activation of ARF6 in a human model of aortic SMC (HASMC). We demonstrate that these two stimuli can promote loading of GTP on this ARF isoform. Knockdown of ARF6 reduced the ability of both PDGF and Ang II to promote invasion suggesting that this GTPase regulates key molecular mechanisms mediating degradation of the extracellular matrix and migration. We report that PDGF-BB-mediated stimulation of ARF6 results in the activation of the MAPK/ERK1/2, PI3K/AKT and PAK pathways essential for invasion of HASMC. However, Ang II-mediated stimulation of ARF6 only promotes signaling through the MAPK/ERK1/2 and PAK pathways. These ARF6-mediated events lead to activation of MMP14, a membrane-bound collagenase upregulated in atherosclerosis. Moreover, ARF6 depletion decreases the release of MMP2 in the extracellular milieu. Altogether, our findings demonstrate that the GTPase ARF6 acts as a molecular switch to regulate specific signaling pathways that coordinate invasiveness of HASMC.
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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".