Preventive effect of α‐lipoic acid and ebselen on rat intestine against ischemia/reperfusion injury
Bibliographic record
Abstract
Purpose: Reactive oxygen species (ROS) and reactive nitrogen species(RNS) generated during reperfusion of the tissue are characteristic of ischemia and reperfusion (I/R) injury. The present study was designed to evaluate whether a‐Lipoic Acid (a‐LA) and Ebselen have protective effect in intestinal I/R injury. Methods: Fourty Sprague‐Dawley rats were divided into five groups equally: Group‐1 Sham‐operated; Group‐2 I/R; Group‐3 I/R+a‐LA; Group‐4 I/R+Ebselen; Group‐5 I/R+a‐LA+Ebselen. Intestinal ischemia for 45 min and reperfusion for 3 days were carried out. Ileal specimens were obtained to determine the tissue levels of Malondialdehide (MDA), Protein Carbonyl (PC) content, Superoxide dismutase (SOD) and Glutation Peroxidase (GPx) and histologic changes. Results: There was a statistically significant decrease in SOD and GPx levels, with an increase in MDA and PC content and intestinal mucosal injury in intestinal I/R group (p<0.05). a‐LA and Ebselen led to a significantly increase in SOD and GPx level, with a decrease in MDA and PC content and intestinal injury when compared with I/R group, (p<0.05). Although shortness of villous and epithelial lifting was seen in the rats subject to I/R, there was slightly injury in mucosa in treatment groups. Conclusion: a‐LA and Ebselen played significant protective role in attenuating I/R injury of the intestine by scavenging ROS and RNS.
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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 | 0.000 | 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".