Potential role of hepatic lipase in the accrual of docosahexaenoic acid (DHA) in the brain
Bibliographic record
Abstract
DHA is an essential fatty acid that is required for the normal development and function of the brain. Because of its inability to synthesize adequate amounts of DHA from the precursors, the brain has to acquire DHA through the blood brain barrier (BBB). Recent studies demonstrated the presence of a transporter at the BBB that specifically transports DHA into the brain in the form of lysophosphatidylcholine (LPC‐DHA). However, the mechanism by which LPC‐DHA is generated in the plasma is not known. Our previous studies showed that there are three different enzymes in plasma‐ lecithin cholesterol acyltransferase (LCAT), endothelial lipase (EL), and hepatic lipase (HL), which can generate LPC‐DHA from sn‐2 DHA PC of lipoproteins. In this study we determined the potential roles of these enzymes in the delivery of DHA to the brain by examining the brain DHA levels in the mice genetically deficient in each of these enzymes. The results show that the brain DHA levels of LCAT‐deficient mice (16.3%) or EL‐deficient mice (15.2%) were not significantly lower than those of their littermates. However, the concentration of brain DHA was significantly lower in HL knockout (KO) mice (13.5%) compared to their littermates (17.1%) (p<0.002). The DHA levels were also lower in the plasma but not in the liver, or heart of HL KO mice. Furthermore, the concentration of LPC‐DHA was significantly decreased in the plasma of HL KO mice. These results suggest that HL may be important for the supply of DHA to the brain by generating LPC‐DHA either in the plasma itself, or in the liver, followed by its secretion into plasma. Support or Funding Information Supported by NIH R01 HL 68685 (PVS)
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".