High cholesterol triggers white matter alterations and cognitive deficits in a mouse model of cerebrovascular disease: benefits of simvastatin
Bibliographic record
Abstract
Transgenic mice overexpressing transforming growth factor-β1 (TGF mice) display impaired cerebrovascular reactivity, cerebral hypoperfusion and neurovascular uncoupling, but no overt cognitive deficits until old age. Cardiovascular diseases are a major risk factor for vascular cognitive impairment and dementia (VCID). We investigated the impact of a high cholesterol diet (HCD) on cerebrovascular and cognitive function in adult (6 months) and aged (12 months) TGF mice, together with the potential benefit of simvastatin (SV), an anti-cholesterol drug with pleiotropic effects, in adult mice. HCD increased blood, but not brain, cholesterol levels in treated mice, which SV did not reduce. In WT mice, HCD induced small, albeit significant, impairment in endothelium-dependent dilatory function. In TGF mice, HCD worsened the established brain vessel dilatory dysfunction in an age-dependent manner and increased the number of string vessels in the white matter (WM), alterations respectively normalized and significantly countered by SV. HCD triggered cognitive decline only in TGF mice at both ages, a deficit prevented by SV. Concurrently, HCD upregulated galectin-3 immunoreactivity in WM microglial cells, a response significantly reduced in SV-treated TGF mice. Grey matter astrogliosis and microgliosis were not affected by HCD or SV. In the subventricular zone of adult HCD-treated TGF mice, SV promoted oligogenesis and migration of oligodendrocyte progenitor cells. The results demonstrate that an underlying cerebrovascular pathology increases vulnerability to cognitive failure when combined to another risk factor for dementia, and that WM alterations are associated with this loss of function. The results further indicate that myelin repair mechanisms, as triggered by SV, may bear promise in preventing or delaying cognitive decline related to VCID.
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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 | 0.000 | 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".