Panel of Oxidative Stress and Inflammatory Biomarkers in ALS: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Pathophysiological mechanisms that contribute to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS) include oxidative stress and inflammation. We conducted a preliminary study to explore these mechanisms, to discuss their link in ALS, and to determine the feasibility of incorporating this combined analysis into current biomarkers research. METHODS: We enrolled 10 ALS patients and 10 controls. We measured the activities of glutathione peroxidase, glutathione reductase, superoxyde dismutase (SOD), and the levels of serum total antioxidant status (TAS), malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and glutathione status (e.g. glutathione disulfide, GSSG/reduced glutathione, GSH). We analysed the concentrations of homocysteine, several cytokines, vitamins and metals by standard methods used in routine practice. RESULTS: There was a significant decrease in TAS levels (p=0.027) and increase in 8-OHdG (p=0.014) and MDA (p=0.011) levels in ALS patients. We also observed a significantly higher GSSG/GSH ratio (p=0.022), and IL-6 (p=0.0079) and IL-8 (p=0.009) concentrations in ALS patients. Correlations were found between biological and clinical markers (homosysteine vs. clinical status at diagnosis, p=0.02) and between some biological markers such as IL-6 vs. GSSG/GSH (p=0.045) or SOD activity (p=0.017). CONCLUSION: We confirmed the systemic alteration of both the redox and the inflammation status in ALS patients, and we observed a link with some clinical parameters. These promising results encourage us to pursue this study with collection of combined oxidative stress and inflammatory markers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".