Simvastatin Restored Vascular Reactivity, Endothelial Function and Reduced String Vessel Pathology in a Mouse Model of Cerebrovascular Disease
Bibliographic record
Abstract
Cerebrovascular dysfunction seen in Alzheimer's disease (AD) and vascular dementia (VaD) is multifaceted and not limited to the amyloid-β (Aβ) pathology. It encompasses structural alterations in the vessel wall, degenerating capillaries (string vessels), vascular fibrosis and calcification, features recapitulated in transgenic mice that overexpress transforming growth factor-β1 (TGF mice). We recently found that simvastatin rescued Aβ-mediated cerebrovascular and cognitive deficits in a transgenic mouse model of AD. However, whether simvastatin can counteract Aβ-independent deficits remains unknown. Here, we evaluated the effects of simvastatin in aged TGF mice on cerebrovascular reactivity and structure, and on cognitive performance. Simvastatin restored baseline levels of nitric oxide (NO), NO-, and KATP channel-mediated dilations and endothelin-1-induced contractions. Simvastatin significantly reduced vasculopathy with arteriogenic remodeling and string vessel pathology in TGF mice. In contrast, simvastatin did not lessen gliosis, and the cerebrovascular levels of pro-fibrotic proteins and calcification markers remained elevated after treatment. The TGF mice displayed subtle cognitive decline that was not affected by simvastatin. Our results show potent benefits of simvastatin on endothelial- and smooth muscle cell-mediated vasomotor responses, endothelial NO synthesis and in preserving capillary integrity. We conclude that simvastatin could be indicated in the treatment of cerebrovascular dysfunction associated with VaD and AD.
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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) | 0.001 | 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".