The clinical response to minocycline in multiple sclerosis is accompanied by beneficial immune changes: a pilot study
Bibliographic record
Abstract
Minocycline has immunomodulatory and neuroprotective activities in vitro and in an animal model of multiple sclerosis (MS). We have previously reported that minocycline decreased gadolinium-enhancing activity over six months in a small trial of patients with active relapsing-remitting MS (RRMS). Here we report the impact of oral minocycline on clinical and magnetic resonance imaging (MRI) outcomes and serum immune molecules in this cohort over 24 months of open-label minocycline treatment. Despite a moderately high pretreatment annualized relapse rate (1.3/year pre-enrolment; 1.2/year during a three-month baseline period) prior to treatment, no relapses occurred between months 6 and 24. Also, despite very active MRI activity pretreatment (19/40 scans had gadolinium-enhancing activity during a three-month run-in), the only patient with gadolinium-enhancing lesions on MRI at 12 and 24 months was on half-dose minocycline. Levels of the p40 subunit of interleukin (IL)-12, which at high levels might antagonize the proinflammatory IL-12 receptor, were elevated over 18 months of treatment, as were levels of soluble vascular cell adhesion molecule-1. The activity of matrix metalloproteinase-9 was decreased by treatment. Thus, clinical and MRI outcomes are supported by systemic immunological changes and call for further investigation of minocycline 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".