Decoding Oxidative Stress and Antioxidative Parameters in Patients with Spinal Cord Injury
Bibliographic record
Abstract
Introduction:In this study we evaluated the connivance of oxidative and antioxidative parameters in the pathogenesis of spinal cord injury (SCI). Although the etiology and pathogenesis of SCI remain to be fully understood, it has been suggested that reactive oxygen species (ROS) and oxidative stress may play a significant role in the pathophysiology of SCI. Furthermore, there is little information available in scientific literature about oxidative and antioxidative parameters in SCI patients. Methods:Oxidative stress was determined by measuring the levels of Lipid Peroxides (LPO) and Protein carbonyl in plasma and antioxidative parameters like Glutathione Reductase (GR), catalase and Glutathione peroxidase (GPx) in lysate in 40 SCI patients and 40 healthy subjects without SCI. However, pain was measured by McGill pain questionnaire. Results: Concentrations of catalase (p<0.01), GR (p<0.01) and GPx (p<0.01) were significantly lower in patients with SCI than in controls, and levels of oxidative stress parameters, LPO (p<0.01), Protein carbonyl (p<0.01) were significantly higher in patients than in controls. A significant positive correlation was found between LPO and pain score among SCI patients group. Furthermore, a significant positive correlation was also found between Protein carbonyl and pain score among SCI patients group than in control group. Conclusion: The present results indicate that SCI patients are exposed to oxidative stress and this escalated oxidative stress may play a role in the etiopathogenesis of the disease. Moreover, our results also show that increased oxidative stress parameters are more strongly amalgamated with pain in SCI patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".