Dysregulation of cholesterol balance in the brain: contribution to neurodegenerative diseases
Bibliographic record
Abstract
Dysregulation of cholesterol homeostasis in the brain is increasingly being linked to chronic neurodegenerative disorders, including Alzheimer's disease (AD), Huntington's disease (HD), Parkinson's disease (PD), Niemann-Pick type C (NPC) disease and Smith-Lemli Opitz syndrome (SLOS). However, the molecular mechanisms underlying the correlation between altered cholesterol metabolism and the neurological deficits are, for the most part, not clear. NPC disease and SLOS are caused by mutations in genes involved in the biosynthesis or intracellular trafficking of cholesterol, respectively. However, the types of neurological impairments, and the areas of the brain that are most affected, differ between these diseases. Some, but not all, studies indicate that high levels of plasma cholesterol correlate with increased risk of developing AD. Moreover, inheritance of the E4 isoform of apolipoprotein E (APOE), a cholesterol-carrying protein, markedly increases the risk of developing AD. Whether or not treatment of AD with statins is beneficial remains controversial, and any benefit of statin treatment might be due to anti-inflammatory properties of the drug. Cholesterol balance is also altered in HD and PD, although no causal link between dysregulated cholesterol homeostasis and neurodegeneration has been established. Some important considerations for treatment of neurodegenerative diseases are the impermeability of the blood-brain barrier to many therapeutic agents and difficulties in reversing brain damage that has already occurred. This article focuses on how cholesterol balance in the brain is altered in several neurodegenerative diseases, and discusses some commonalities and differences among the diseases.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".