Venlafaxine Improves the Cognitive Impairment and Depression-Like Behaviors in a Cuprizone Mouse Model by Alleviating Demyelination and Neuroinflammation in the Brain
Bibliographic record
Abstract
Growing evidence has implicated that myelin deficits and neuroinflammation may be a shared pathophysiology and treatment target for the mood and cognitive symptoms in major depressive disorder and multiple sclerosis. Venlafaxine is a versatile antidepressant for depression, anxiety and neuropathy. Previous studies showed venlafaxine has neuroprotective effects through multiple mechanisms. However, it is unclear whether venlafaxine treatment can alter myelin integrity and inflammation status in the brain. We investigated the effects of venlafaxine in an acute cuprizone mouse model of demyelination. This animal model exhibits cognitive impairment and mood disturbances, brain myelin loss and prominent neuroinflammation. This study was a two by three design with a total of six groups of C57BL/6 mice (n=16 per group). Three groups on regular diet received vehicle (water), venlafaxine 5mg/kg or 20 mg/kg daily for five weeks respectively; other three groups were fed with 0.2% cuprizone and concurrently received vehicle (water), venlafaxine 5mg/kg or 20 mg/kg daily for six weeks respectively. The working memory and depression-like behaviors were assessed using the Y-maze, tail suspension and forced swim tests. Mice brains were harvested after euthanasia and processed for immunohistochemistry of myelin pathology, oligodendrocyte, astrocyte and microglia. A high dose of venlafaxine treatment improved the working memory and depression-like behaviors, mitigated myelin and oligodendrocyte loss. The protective effect may be mediated by reducing microglia-medicated inflammation in the brain. These findings suggest that myelin integrity and neuroinflammation modulation may be part of the mechanisms behind venlafaxine’s therapeutic effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".