Increase in serum levels of uric acid, an endogenous antioxidant, under treatment with glatiramer acetate for multiple sclerosis
Bibliographic record
Abstract
Free radicals including peroxynitrite are induced in Multiple Sclerosis (MS). Antioxidant and peroxynitrite inhibitor uric acid (UA), suppresses the MS animal model experimental autoimmune encephalomyelitis (EAE). MS patients have lower average serum UA than controls. An inverse relationship exists between MS and gout Glatiramer acetate (GA) suppresses EAE and is beneficial in relapsing MS. We investigated serum UA changes during open-label treatment of relapsing MS with GAA. Ten patients (six females, four males, aged 19 to 39 years, mean age 32 years) completed 6 months of GAA (Copaxone 20 mg s.c daily). Of these, nine completed 12 months. After 6 months on GAA, serum UA (normal, 173359 micromol/ml for women, 258-491 micromol/ml for men) increased in nine and marginally decreased (302 to 300 micromol/ml) in a single patient. Mean UA significantly increased from 240 to 303 micromol/ml (P=0.0014). At 12 months, UA remained significantly higher than at start (P=0.006) decreasing in only one patient. In contrast, we found no significant UA changes after 6 and 12 months of treatment in 21 MS patients treated with interferon beta1-a (Avonex), or in 11 treated with interferon beta1-a (Rebif), or in five placebo-treated controls. Increasing UA, a natural inhibitor of free radicals, may represent a mechanism of action of glatiramer acetate in MS.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".