The possible role of oxidative stress marker glutathione in the assessment of cognitive impairment in multiple sclerosis
Bibliographic record
Abstract
Oxidative stress markers have a distinct role in the process of demyelination in multiple sclerosis. This study investigated the potential correlation of markers of oxidative stress (glutathione [GSH], catalase) with the number of demyelinating lesions and the degree of disability, cognitive deficit, and depression in patients with relapsing-remitting multiple sclerosis (RRMS). Sixty subjects meeting the criteria for RRMS (19 men and 41 women), and 66 healthy controls (24 men, 42 women) were included. In this study, GSH significantly negatively correlated with the degree of cognitive impairment. This is the first study of subjects with RRMS that performed the mentioned research of serum GSH levels on the degree of cognitive damage examined by the Montreal Scale of Cognitive Assessment (MoCA) test. The development of cognitive changes, verified by the MoCA test, was statistically significantly influenced by the positive number of magnetic resonance lesions, degree of depression, expanded disability status scale (EDSS), age, and GSH values. Based on these results, it can be concluded that it is necessary to monitor cognitive status early in RRMS patients, especially in those with a larger number of demyelinating lesions and a higher EDSS level and in older subjects. Also, the serum level of GSH is a potential biomarker of disease progression, which could be used more widely in RRMS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".