High glucose-induced RhoA activation requires caveolae and PKCβ1-mediated ROS generation
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Bibliographic record
Abstract
Glomerular matrix accumulation is a hallmark of diabetic nephropathy. We previously showed that RhoA activation by high glucose in mesangial cells (MC) leads to matrix upregulation (Peng F, Wu D, Gao B, Ingram AJ, Zhang B, Chorneyko K, McKenzie R, Krepinsky JC. Diabetes 57: 1683-1692, 2008). Here, we study the mechanism whereby RhoA is activated. In primary rat MC, RhoA activation required glucose entry and metabolism. Broad PKC inhibitors (PMA, bisindolylmaleimide, Gö6976), as well as specific PKCβ blockade with an inhibitor and small interfering RNA (siRNA), prevented RhoA activation by glucose. PKCβ inhibition also abrogated reactive oxygen species (ROS) generation by glucose. The ROS scavenger N-acetylcysteine (NAC) or NADPH oxidase inhibitors apocynin and DPI prevented glucose-induced RhoA activation. RhoA and some PKC isoforms localize to caveolae. Chemical disruption of these microdomains prevented RhoA and PKCβ1 activation by glucose. In caveolin-1 knockout cells, glucose did not induce RhoA and PKCβ1 activation; these responses were rescued by caveolin-1 reexpression. Furthermore, glucose-induced ROS generation was significantly attenuated by chemical disruption of caveolae and in knockout cells. Downstream of RhoA signaling, activator protein-1 (AP-1) activation was also inhibited by disrupting caveolae, was absent in caveolin-1 knockout MC and rescued by caveolin-1 reexpression. Finally, transforming growth factor (TGF)-β1 upregulation, mediated by AP-1, was prevented by RhoA signaling inhibition and by disruption or absence of caveolae. In conclusion, RhoA activation by glucose is dependent on PKCβ1-induced ROS generation, most likely through NADPH oxidase. The activation of PKCβ1 and its downstream effects, including upregulation of TGF-β1, requires caveolae. These microdomains are thus important mediators of the profibrogenic process associated with diabetic nephropathy.
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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) | 0.001 | 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 it