Modulatory effect of simvastatin on redox status, caspase-3 expression, p-protein kinase B (p-Akt), and brain-derived neurotrophic factor (BDNF) in an ethanol-induced neurodegeneration model
Bibliographic record
Abstract
Neurodegenerative diseases are a common cause of morbidity and mortality worldwide, with oxidative stress, inflammation, and protein aggregation representing the main underlying mechanisms that ultimately lead to cell death. Ethanol has shown strong neurodegenerative consequences in experimental animal brains. Statins are a class of lipid-lowering drugs with many pleotropic effects. Therefore, the aim of the present study was to explore the modulatory effect of simvastatin (10 mg·kg–1·day–1) before and after the development of neurodegeneration (for 55 and 25 days, respectively) on redox state, caspase-3 expression, p-protein kinase B (p-Akt), and brain-derived neurotrophic factor (BDNF) in ethanol-induced (15% ethanol solution for 55 days) neurodegeneration. Seventy female Albino Swiss mice were included and randomly divided into five groups: C, control group; E, ethanol group; ES, group treated with simvastatin from the first day of ethanol intake; E + S, group treated with simvastatin after neurodegeneration development; and S, simvastatin group. Administration of simvastatin from the first day improved the biochemical changes, suppressed apoptosis, and induced autophagy and neurogenesis; however, its administration after the development of neurodegeneration resulted in partial improvement. The histopathological findings confirmed the biochemical changes. In conclusion, simvastatin has a neuroprotective effect against the development of ethanol-induced neurodegeneration and its progression.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".