Low field magnetic stimulation promotes myelin repair and cognitive recovery in chronic cuprizone mouse model
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is an inflammatory demyelinating disease featured with neuroinflammation, demyelination, and the loss of oligodendrocytes. Cognitive impairment and depression are common neuropsychiatric symptoms in MS that are poorly managed with the present interventions. OBJECTIVE: This study aimed to investigate the effects of low field magnetic stimulation (LFMS), a novel non-invasive neuromodulation technology, on cognitive impairment and depressive symptoms associated with MS using a mouse model of demyelination. METHODS: C57BL female mice were fed with a 0.2% cuprizone diet for 12 weeks to induce a chronic demyelinating model followed by 4 weeks of cuprizone withdrawal with either sham or LFMS treatment. RESULTS: Improved cognition and depression-like behaviour and restored weight gain were observed in mice with LFMS treatment. Immunohistochemical and immunoblotting data showed enhanced myelin basic protein (MBP) and myelin oligodendrocyte glycoprotein expressions (MOG) in the prefrontal cortex of mice with LFMS treatment, supporting that myelin repair was promoted. LFMS also increased the protein expression of mature oligodendrocyte biomarker glutathione-S-transferase (GST-π). In addition, expression of TGF-β and associated receptors were elevated with LFMS treatment, implicating this pathway in the response. CONCLUSION: Results from the present study revealed LFMS to have neuroprotective effects, suggesting that LFMS has potential therapeutic value for treating cognitive impairment and depression related to demyelination disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".