Experimental Demyelination and Remyelination of Murine Spinal Cord by Focal Injection of Lysolecithin
Bibliographic record
Abstract
Multiple sclerosis is an inflammatory demyelinating disease of the central nervous system characterized by plaque formation containing lost oligodendrocytes, myelin, axons, and neurons. Remyelination is an endogenous repair mechanism whereby new myelin is produced subsequent to proliferation, recruitment, and differentiation of oligodendrocyte precursor cells into myelin-forming oligodendrocytes, and is necessary to protect axons from further damage. Currently, all therapeutics for the treatment of multiple sclerosis target the aberrant immune component of the disease, which reduce inflammatory relapses but do not prevent progression to irreversible neurological decline. It is therefore imperative that remyelination-promoting strategies be developed which may delay disease progression and perhaps reverse neurological symptoms. Several animal models of demyelination exist, including experimental autoimmune encephalomyelitis and curprizone; however, there are limitations in their use for studying remyelination. A more robust approach is the focal injection of toxins into the central nervous system, including the detergent lysolecithin into the spinal cord white matter of rodents. In this protocol, we demonstrate that the surgical procedure involved in injecting lysolecithin into the ventral white matter of mice is fast, cost-effective, and requires no additional materials than those commercially available. This procedure is important not only for studying the normal events involved in the remyelination process, but also as a pre-clinical tool for screening candidate remyelination-promoting therapeutics.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".