Correlation of Lipid Peroxidation and Glutathione Levels with severity of Systemic Lupus Erythematosus: a Pilot study from Single Center
Bibliographic record
Abstract
PURPOSE: Systemic Lupus Erythematosus (SLE) is a multifactoral chronic autoimmune disease with unidentified etiology. Imbalance of oxidative status is one possible cause of active disease. Plasma malondialdehyde (MDA) and plasma glutathione (GSH) level have been used as a determinate of oxidative status. Limited data has examined these 2 parameters by severity of SLE. METHODS: We determined whether there was an association between plasma MDA and plasma GSH level with the severity of SLE. Forty four SLE patients (2 Men and 42 Women) and twenty healthy volunteers (3 Men, 17 women) participated in this study. SLE participants were classified by the severity of disease (mild, moderate or severe). The plasma MDA and plasma Glutathione levels were measured. The correlation of plasma MDA and plasma GSH levels with the severity of SLE disease were determined. RESULTS: Plasma MDA levels with different severity of SLE (mild, moderate, and severe of SLE patients) were not significantly different from those of the control group (p=1.0). Plasma GSH levels were significantly lower in the moderate and severe SLE groups than the control group (p=0.001). In addition, a significant correlation between plasma GSH and severity of SLE was observed. (Pearson correlation coefficient = -0.428, p<0.001). The relationship could be described by the equation GSH level (microM) = (-7.624) SLEDAI score +545.90. CONCLUSION: A significant correlation between plasma GSH and SLE severity exists that may aid evaluation of the disease severity and usefulness of the treatment of SLE.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".