Increased PTEN mRNA Expression And Phosphorylation In The Myocardium Of Streptozotocin‐Induced Diabetic Rats: Effects of N‐Acetylcysteine
Bibliographic record
Abstract
PTEN (phosphatase and tensin homologue deleted on chromosome ten) negatively regulates cell survival mediated by the phosphatidylinositol 3‐kinase (PI3K)‐Akt pathway. Recently, PTEN has been described as a critical negative regulator in insulin signaling, potentially involved in insulin resistance, Type 2 diabetes and related cardiac complications. High glucose has been shown to downregulate PTEN expression ( Diabetes 2006; 55 :‐2125), possibly through reactive oxygen species‐mediated inactivation of PTEN. We, therefore, hypothesized that PTEN will be downregulated in the myocardium of Type 1 diabetic rats which may contribute to the development of myocardial hypertrophy ( FASEB J 2005; 19 :). Control and streptozotozin‐induced diabetic rats were treated (CT, DT) or untreated (C, D) with antioxidant N‐acetylcysteine (NAC) in the drinking water for 8 weeks. Myocardial total PTEN protein was decreased by about 70% in D rats, accompanied by 2.4‐fold increase of the PI3K p85 protein compared to C. PI3K p85 protein was significantly reduced in DT rats, while total PTEN protein was unchanged compared to D. However, real‐time PCR identified a significant increase of PTEN mRNA in D rat hearts compared to C, which was prevented by NAC. Further study revealed that PTEN protein expression was decreased in the cytosol, but not in the membrane fraction in D rat hearts relative to C hearts, suggestive of increased membrane translocation. Increased PTEN phosphorylation in the myocardial membrane fraction in D rats was normalized by NAC. Contrary to our hypothesis, the results show that PTEN mRNA is upregulated and activated in the myocardium of Type 1 diabetic rats, which might be followed by accelerated degradation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".