Statin Therapy Inhibits Remyelination in the Central Nervous System
Bibliographic record
Abstract
Remyelination of lesions in the central nervous system contributes to neural repair following clinical relapses in multiple sclerosis. Remyelination is initiated by recruitment and differentiation of oligodendrocyte progenitor cells (OPCs) into myelinating oligodendrocytes. Simvastatin, a blood-brain barrier-permeable statin in multiple sclerosis clinical trials, has been shown to impact the in vitro processes that have been implicated in remyelination. Animals were fed a cuprizone-supplemented diet for 6 weeks to induce localized demyelination in the corpus callosum; subsequent return to normal diet for 3 weeks stimulated remyelination. Simvastatin was injected intraperitoneally during the period of coincident demyelination and OPC maturation (weeks 4 to 6), throughout the entire period of OPC responses (weeks 4 to 9), or during the remyelination-only phase (weeks 7 to 9). Simvastatin treatment (weeks 4 to 6) caused a decrease in myelin load and both Olig2(strong) and Nkx2.2(strong) OPC numbers. Simvastatin treatment (weeks 4 to 9 and 7 to 9) caused a decrease in myelin load, which was correlated with a reduction in Nkx2.2(strong) OPCs and an increase in Olig2(strong) cells, suggesting that OPCs were maintained in an immature state (Olig2(strong)/Nkx2.2(weak)). NogoA+ oligodendrocyte numbers were decreased during all simvastatin treatment regimens. Our findings suggest that simvastatin inhibits central nervous system remyelination by blocking progenitor differentiation, indicating the need to monitor effects of systemic immunotherapies that can access the central nervous system on brain tissue-repair processes.
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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 | 0.000 |
| 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 | 0.001 |
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".