LCAT synthesized by primary astrocytes esterifies cholesterol on glia-derived lipoproteins
Bibliographic record
Abstract
Lipid trafficking in the brain is essential for the maintenance and repair of neuronal membranes, especially after neurotoxic insults. However, brain lipid metabolism is not completely understood. In plasma, LCAT catalyses the esterification of free cholesterol on circulating lipoproteins, a key step in the maturation of HDL. Brain lipoproteins are apolipoprotein E (apoE)-containing, HDL-like particles secreted initially as lipid-poor discs by glial cells. LCAT is synthesized within the brain, suggesting that it may play a key role in the maturation of these lipoproteins. Here we demonstrate that astrocytes are the primary producers of brain LCAT. This LCAT esterifies free cholesterol on nascent apoE-containing lipopoproteins secreted from glia. ApoE is the major LCAT activator in glia-conditioned media (GCM), and both the cholesterol transporter ABCA1 and apoE are required to generate glial LCAT substrate particles. LCAT deficiency leads to the appearance of abnormal approximately 8 nm particles in GCM, and exogenous LCAT restores the lipoprotein particle distribution to the wild-type (WT) pattern. In vivo, complete LCAT deficiency results in a dramatic increase in apoE-HDL and reduced apolipoprotein A-I (apoA-I)-HDL in murine cerebrospinal fluid (CSF). These data show that brain LCAT esterifies cholesterol on glial-derived apoE-lipoproteins, and influences CSF apoE and apoA-I levels.
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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) | 0.000 | 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 | 0.001 |
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".