Nitric Oxide Inhibits Stretch-Induced MAPK Activation in Mesangial Cells Through RhoA Inactivation
Bibliographic record
Abstract
Glomerular capillary hypertension is an important determinant of glomerulosclerosis in rats with subtotal renal ablation. Dietary supplementation with L-arginine increases renal nitric oxide (NO) production and limits glomerular injury in this model, and early benefits are seen without altered glomerular capillary pressure. In an in vitro model of hemodynamically mediated signaling, the authors have reported that subjecting MC to cyclic stretch/relaxation activates the mitogen-activated protein kinase p42/44 (Erk) cascade and that NO and cyclic GMP abrogate stretch-induced Erk activation by inducing actin cytoskeletal disassembly. The actin cytoskeleton is regulated by the Rho family of GTPases, including RhoA; therefore, the authors examined the role of RhoA in stretch-induced Erk activation and as an NO target. In primary rat MC subjected to cyclic mechanical strain, RhoA activity was maximally increased (2.4-fold) after 1 min of stretch, and Erk activation temporally followed. The Rho-kinase inhibitor Y-27632 attenuated Erk activation in a dose-dependent manner and prevented stretch-induced actin stress fiber formation. The NO donors S-nitroso-N-acetylpenicillamine and cGMP both inhibited stretch-induced RhoA and Erk activation and stress fiber formation. Infection of MC with the RhoA mutant RhoA-Ala188, which is resistant to NO-dependent phosphorylation, abrogated the effects of NO and cGMP on stretch-induced Erk activation and stress fiber formation. The authors conclude that the early activation of RhoA is essential for stretch-induced actin stress fiber formation and Erk activation in MC, events which are prevented by NO and cGMP through their action on RhoA. Inhibition of RhoA may thus be a new approach to the prevention of hemodynamically mediated glomerular injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".