Effect of aminoguanidine on sciatic functional index, oxidative stress, and rate of apoptosis in an experimental rat model of ischemia–reperfusion injury
Bibliographic record
Abstract
This study was conducted to investigate the potential protective effects of aminoguanidine (AG) on sciatic functional index (SFI), oxidative stress status, and apoptosis index using a rat model of experimental sciatic nerve ischemia-reperfusion injury (I/R). Treatment groups received 150 mg AG/kg body mass, 24 h after the induction of ischemia. After reperfusion for 2, 4, 7, 14, and 28 days, we evaluated measured SFI, plasma antioxidant enzymes, total antioxidant capacity (TAC), malondialdehyde (MDA), and index of apoptosis. SFI was significantly improved on the 7th and 14th day of reperfusion in the AG-treated groups. AG treatment resulted in the significant reduction of MDA levels on the 7th and 14th day of reperfusion. TAC was only increased after 7 days of reperfusion compared with the untreated group. SOD activity was decreased in both the untreated and AG-treated groups by comparison with the control, but did not show a significant change. GPx activity decreased only after 7 days of reperfusion. The maximal rate of apoptosis occurred on the 7th day of reperfusion. Treatment with AG significantly reduced this enhancement. AG exhibits positive effects against sciatic nerve I/R injury, possibly in part because of the protective effects of AG against apoptosis and I/R-induced oxidative stress.
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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 | 0.000 |
| 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".