Role of the actin cytoskeleton in angiotensin II signaling in human vascular smooth muscle cells
Bibliographic record
Abstract
Angiotensin II (Ang II) regulates vascular smooth muscle cell (VSMC) function by activating signaling cascades that promote vasoconstriction, growth, and inflammation. Subcellular mechanisms coordinating these processes are unclear. In the present study we questioned the role of the actin cytoskeleton in Ang II-mediated signaling through mitogen-activated protein (MAP) kinases and reactive oxygen species (ROS) in VSMCs. Human VSMCs were studied. Cells were exposed to Ang II (10−7 mol/L) in the absence and presence of cytochalasin B (10−6 mol/L, 60 minute), which disrupts the actin cytoskeleton. Phosphorylation of p38MAP kinase, JNK and ERK1/2 was assessed by immunoblotting. ROS generation was measured using the fluoroprobe CM-H2DCFDA (4 mmol/L). Interaction between the cytoskeleton and NADPH oxidase was determined by evaluating the presence of p47phox in the Triton X-100 insoluble membrane fraction. Ang II significantly increased phosphorylation of p38MAP kinase, JNK and ERK1/2 (2–3-fold above control, p<0.05). Cytochalasin B pretreatment attenuated p38MAP kinase and JNK effects (p<0.05) without altering ERK1/2 phosphorylation. ROS formation, which was increased in Ang II-stimulated cells, was significantly reduced by cytochalasin B (p<0.01). p47phox, critically involved in NADPH oxidase activation, co-localized with the actin cytoskeleton in Ang II-stimulated cells. Our data demonstrate that Ang II-mediated ROS formation and activation of p38MAP kinase and JNK, but not ERK1/2, involves the actin-cytoskeleton in VSMCs. In addition, Ang II promotes interaction between actin and p47phox. These data indicate that the cytoskeleton is involved in differential MAP kinase signaling and ROS generation by Ang II in VSMCs. Together these studies suggest that the cytoskeleton may be a central point of cross-talk in growth- and redox-signaling pathways by Ang II, which may be important in the regulation of VSMC function.
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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".