Bibliographic record
Abstract
PURPOSE OF REVIEW: This article evaluates recent experimental and human evidence regarding the involvement of lipids, lipoproteins, and apolipoproteins in neurodegenerative diseases, and reviews the current literature of the effects of cholesterol-lowering treatment on cognition. RECENT FINDINGS: Plasma levels of traditional lipids and lipoproteins are not consistently associated with risk of dementia even though low plasma levels of apolipoprotein E, through unknown mechanisms, robustly predict future dementia. Experimental evidence suggests neuroprotective roles of several brain and cerebrospinal fluid apolipoproteins. Whether plasma levels of apolipoprotein E, or any other apolipoprotein with possible central nervous system and/or blood-brain barrier functions (apolipoproteins J, A-I, A-II, A-IV, D, C-I, and C-III) may become accessible biomarker components that improve risk prediction for dementia together with genetic risk variants and cardiovascular risk factors remains to be determined. SUMMARY: Apolipoproteins with well established functions in peripheral lipid metabolism may play important roles for brain vascular health and Alzheimer's disease pathophysiology. Experimental work on lipids, lipoproteins, and apolipoproteins in the central nervous system together with robust prospective human studies will help to substantiate the drug target potential of these lipid components.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".