Effect of captopril and the bradykinin–PKC pathway on ROS production in type 1 diabetic rats
Bibliographic record
Abstract
The aim of this study was to investigate the possible effects of captopril as a promoter in modulating the oxidant-antioxidant balance in rats with type 1 diabetes, and the influence of protein kinase C (PKC) pathways in the production of reactive oxygen species (ROS) induced by bradykinin in type 1 diabetic rats. This study evaluated the redox status in both the cardiac tissue and at the cellular level (neutrophils). Two concentrations of captopril were utilized: (i) 5 mg·(kg body mass)(-1), which was considered a therapeutic dose; and (ii) 10 mg·(kg body mass)(-1). Body mass, plasma glucose, and serum insulin were evaluated. To investigate the redox status of the cardiac tissue, we analyzed lipid peroxidation, concentration of carbonylated protein, catalase activity, and the concentration of glutathione. For a more accurate assessment of the possible antioxidant effect of captopril, we also analyzed ROS in neutrophils (in vivo), and ROS production induced by bradykinin and the influence of the PKC pathway in this production (in vitro). Our data show that the hearts of diabetic animals have increased oxidative damage, exemplified by the increased concentration of carbonylated protein and thiobarbituric acid reactive substances (TBARS). However, animals treated with captopril at both concentrations showed lower concentrations of carbonylated protein compared with untreated diabetic animals. We found an increase of catalase activity in the heart of diabetic rats, which was reversed by captopril treatment at both of the dosages tested. Our data showed that captopril was able to reduce ROS production in the neutrophils of diabetic rats at a dose of 10 mg captopril·(kg body mass)(-1). However, the antioxidant effect of captopril is independent of bradykinin. Diabetes induces oxidative stress, and these results suggest that captopril has an antioxidant effect and can modulate the production of ROS in circulating neutrophils.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".