<i>N</i>-acetylcysteine attenuates PKCβ<sub>2</sub>overexpression and myocardial hypertrophy in streptozotocin-induced diabetic rats
Bibliographic record
Abstract
OBJECTIVE: Oxidative stress-mediated activation of protein kinase C (PKC) beta(2) in the myocardium has been implicated in the development of cardiomyopathy. Overexpression of PKCbeta(2) is associated with increased expression of connective tissue growth factor (CTGF) in myocardium, resulting in myocardial hypertrophy. We hypothesized that chronic treatment with the antioxidant N-acetylcysteine (NAC) would normalize oxidative stress-mediated overexpression of myocardial PKCbeta(2) and CTGF and attenuate the development of myocardial hypertrophy. METHODS: Control and streptozotocin-induced diabetic rats were treated with NAC in drinking water for 8 weeks. At termination rats were surgically prepared for hemodynamic measurement, subsequent to which their hearts were removed to evaluate cardiac performance and histological and biochemical changes. Further, the role of PKCbeta(2) in hyperglycemia-induced cardiomyocyte hypertrophy was tested in cultured neonatal cardiomyocytes. RESULTS: Myocardial hypertrophy, characterized by an increased ratio of ventricle weight to body weight and cardiomyocyte cross-sectional area was found to be higher in untreated diabetic rats. Further, in myocardium, increased levels of 15-F(2t)-isoprostane were accompanied by an increased expression of membrane-bound PKCbeta(2) and CTGF. N-acetylcysteine treatment not only attenuated these changes but also prevented hyperglycemia-induced hypertrophy in cultured neonatal rat cardiomyocytes. CONCLUSIONS: The results suggest that PKCbeta(2) overexpression represents a mechanism causing hyperglycemia-mediated myocardial hypertrophy, which can be prevented by the antioxidant N-acetylcysteine.
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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) | 0.001 | 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 | 0.001 |
| 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".