Mechanical Strain-Induced RhoA Activation Requires NADPH Oxidase-Mediated ROS Generation in Caveolae
Bibliographic record
Abstract
Increased intraglomerular pressure leads to kidney fibrosis, and can be modeled by exposing glomerular mesangial cells (MC) to mechanical strain. We previously showed that RhoA mediates strain-induced matrix production. Here we investigate whether reactive oxygen species (ROS) are required for RhoA activation. Maximal RhoA activation (1 min) was inhibited by ROS scavenge or NADPH oxidase inhibition. Strain activated NADPH oxidase, with Rac1, p47(phox), and p67(phox) membrane translocation, and Rac1 activation, observed within 30 sec. Epidermal growth factor receptor (EGFR) inhibition blocked RhoA and Rac1 activation, p67(phox) membrane translocation, and ROS generation. However, EGFR activation was unaffected by ROS inhibitors, placing it upstream of ROS generation. We previously showed, using chemical disruption, that caveolae mediate strain-induced EGFR and RhoA activation. In MC from caveolin-1 knockout mice, which lack caveolae, RhoA and Rac1 activation, p67(phox) membrane translocation, and ROS generation were absent. These were rescued by caveolin-1 re-expression. ROS generation, Rac1 activation, and p67(phox) membrane translocation were also prevented by Src inhibition. They were absent in MC stably infected with caveolin-1 Y14A, a mutant resistant to Src phosphorylation. In MC, caveolae are thus important mediators of strain-induced ROS generation through NADPH oxidase, mediating a signaling cascade which results in RhoA activation.
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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".