Selective Inhibition of Protein Kinase C β2 Attenuates Inducible Nitric Oxide Synthase–Mediated Cardiovascular Abnormalities in Streptozotocin-Induced Diabetic Rats
Bibliographic record
Abstract
OBJECTIVE: Impaired cardiovascular function in diabetes is partially attributed to pathological overexpression of inducible nitric oxide synthase (iNOS) in cardiovascular tissues. We examined whether the hyperglycemia-induced increased expression of iNOS is protein kinase C-beta(2) (PKCbeta(2)) dependent and whether selective inhibition of PKCbeta reduces iNOS expression and corrects abnormal hemodynamic function in streptozotocin (STZ)-induced diabetic rats. RESEARCH DESIGN AND METHODS: Cardiomyocytes and aortic vascular smooth muscle cells (VSMC) from nondiabetic rats were cultured in low (5.5 mmol/l) or high (25 mmol/l) glucose or mannitol (19.5 mmol/l mannitol + 5.5 mmol/l glucose) conditions in the presence of a selective PKCbeta inhibitor, LY333531 (20 nmol/l). Further, the in vivo effects of PKCbeta inhibition on iNOS-mediated cardiovascular abnormalities were tested in STZ-induced diabetic rats. RESULTS: Exposure of cardiomyocytes to high glucose activated PKCbeta(2) and increased iNOS expression that was prevented by LY333531. Similarly, treatment of VSMC with LY333531 prevented high glucose-induced activation of nuclear factor kappaB, extracellular signal-related kinase, and iNOS overexpression. Suppression of PKCbeta(2) expression by small interference RNA decreased high-glucose-induced nuclear factor kappaB and extracellular signal-related kinase activation and iNOS expression in VSMC. Administration of LY333531 (1 mg/kg/day) decreased iNOS expression and formation of peroxynitrite in the heart and superior mesenteric arteries and corrected the cardiovascular abnormalities in STZ-induced diabetic rats, an action that was also observed with a selective iNOS inhibitor, L-NIL. CONCLUSIONS: Collectively, these results suggest that inhibition of PKCbeta(2) may be a useful approach for correcting abnormal hemodynamics in diabetes by preventing iNOS mediated nitrosative stress.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".