Pilot Study of Minocycline in Relapsing-Remitting Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Current multiple sclerosis (MS) treatment is only partially effective and not all patients respond well. The goal in this study was to evaluate minocycline for its safety, tolerability, and MRI impact as a potential therapy over 36 months after a three month run-in in ten relapsing-remitting (RR) MS patients. METHODS: Clinical assessments were at three month intervals until six months, then at six month intervals. Three Tesla MRI was performed monthly during the run-in and first six months of treatment, then at 12, 24, and 36 months. RESULTS: Treatment was safe and well tolerated. Annualized relapse rate was 1.2 during the run-in and 0.25 during treatment. The proportion of active scans was lower during the first six months of treatment (5.6%, p < 0.001) and during the extension (8.7%, p = 0.002) than during the run-in (47.5%). Consistent with these outcomes, mean T2 lesion volume remained stable over three years and percent brain volume change was reduced during year three (-0.37%) of minocycline treatment. CONCLUSIONS: This trial is limited by small sample and no control group but suggests that minocycline is safe and potentially beneficial in RRMS. This supports further investigation of its efficacy.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".