Sildenafil decreased cardiac cell apoptosis in diabetic mice: reduction of oxidative stress as a possible mechanism
Bibliographic record
Abstract
Oxidative stress plays a dominant role in the pathogenesis of cardiac cell apoptosis in diabetic patients. Sildenafil has been demonstrated to have antioxidant effects. In this study, the effects of sildenafil on diabetes-induced cardiac cell apoptosis and the antioxidant status of diabetic mouse hearts were investigated. Diabetic mice showed lower body weight gains and heart weights compared with control mice, and sildenafil treatment did not increase these parameters in diabetic mice. Although apoptotic rates, caspase-3 enzyme activity, and malondialdehyde levels were significantly higher in diabetic mouse hearts than in controls, they were reduced in diabetic mice after sildenafil treatment. At the end of the first week, we observed no significant differences in antioxidant enzyme activities (CAT, GSH-Px, and SOD) in diabetic and control groups, whereas at the end of the second week of sildenafil treatment, antioxidant enzyme activities were higher in the diabetic group. In conclusion, our study indicated that sildenafil was beneficial to hearts of diabetic mice by reducing cardiac cell apoptosis, partially because of its antioxidant effects in the heart.
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".