Inhibition of neuronal cholesterol biosynthesis with lovastatin leads to impaired synaptic vesicle release even in the presence of lipoproteins or geranylgeraniol
Bibliographic record
Abstract
Cholesterol is highly enriched in the brain, and plays a key role in synapse formation and function. The brain does not derive cholesterol from the circulation; instead, the majority of cholesterol is made in glia and secreted in form of lipoproteins. Neurons can synthesize cholesterol, but the extent of neuronal cholesterol biosynthesis in the adult brain is unknown. Cholesterol biosynthesis inhibitors of the statin family are widely used to lower circulating cholesterol and cardiovascular risk. Lipophilic statins can cross the blood brain barrier and inhibit brain cholesterol biosynthesis with possible consequences for synaptic cholesterol homeostasis. We have investigated the effects of lovastatin on synapse maturation and synaptic vesicle release. Treatment of primary hippocampal neurons with low levels of lovastatin for one week reduced synapse density and impaired synaptic vesicle release. Neither lipoproteins nor geranylgeraniol fully counteracted the lovastatin-induced decrease of synaptic vesicle exocytosis, even when cholesterol depletion was prevented. In contrast, restoration of neuronal cholesterol synthesis with mevalonate prevented defects in vesicle exocytosis without fully normalizing neuronal cholesterol content. These results raise the possibility that chronic exposure of neurons to lipophilic statins may affect synaptic transmission, and indicate that hippocampal neurons need a certain level of endogenous cholesterol biosynthesis.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".