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Record W2098990121 · doi:10.1093/cvr/cvu148

HDL and cholesterol handling in the brain

2014· review· en· W2098990121 on OpenAlexaff
Cecilia Vitali, Cheryl L. Wellington, Laura Calabresi

Bibliographic record

VenueCardiovascular Research · 2014
Typereview
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCholesterolApolipoprotein BMicrogliaCentral nervous systemLipoproteinApolipoprotein EHigh-density lipoproteinBiologyReverse cholesterol transportEndocrinologyScavenger receptorInternal medicineCell biologyMedicineImmunologyInflammationDisease

Abstract

fetched live from OpenAlex

Cholesterol is an essential component of both the peripheral nervous system and central nervous system (CNS) of mammals. Brain cholesterol is synthesized in situ by astrocytes and oligodendrocytes and is almost completely isolated from other pools of cholesterol in the body, but a small fraction can be taken up from the circulation as 27-hydroxycholesterol, or via the scavenger receptor class B type I. Glial cells synthesize native high-density lipoprotein (HDL)-like particles, which are remodelled by enzymes and lipid transfer proteins, presumably as it occurs in plasma. The major apolipoprotein constituent of HDL in the CNS is apolipoprotein E, which is produced by astrocytes and microglia. Apolipoprotein A-I, the major protein component of plasma HDL, is not synthesized in the CNS, but can enter and become a component of CNS lipoproteins. Low HDL-C levels have been shown to be associated with cognitive impairment and various neurodegenerative diseases. On the contrary, no clear association with brain disorders has been shown in genetic HDL defects, with the exception of Tangier disease. Mutations in a wide variety of lipid handling genes can result in human diseases, often with a neuronal phenotype caused by dysfunctional intracellular lipid trafficking.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.199
GPT teacher head0.455
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations258
Published2014
Admission routes1
Has abstractyes

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