Deficient Cholesterol Esterification in Plasma of apoc2 Knockout Zebrafish and Familial Chylomicronemia Patients
Bibliographic record
Abstract
Hypertriglyceridemia is an independent risk factor for cardiovascular disease. Apolipoprotein C-II (APOC2) is an obligatory cofactor for lipoprotein lipase (LPL), the major enzyme catalyzing plasma triglyceride hydrolysis. We have created an apoc2 knockout zebrafish model, which mimics the familial chylomicronemia syndrome (FCS) in human patients with a defect in the APOC2 or LPL gene. In this study, we measured plasma levels of free cholesterol (FC) and cholesterol esters (CE) and found that apoc2 mutant zebrafish have a significantly higher FC to CE ratio (FC/CE), when compared to the wild type. Feeding apoc2 mutant zebrafish a low-fat diet reduced triglyceride levels but not the FC/CE ratio. In situ hybridization and qPCR results demonstrated that the hepatic expression of lecithin-cholesterol acyltransferase (lcat), the enzyme responsible for esterifying plasma FC to CE, and of apolipoprotein A-I, a major protein component of HDL, were dramatically decreased in apoc2 mutants. Furthermore, the FC/CE ratio was significantly increased in the whole plasma and in a chylomicron-depleted fraction of human FCS patients. The FCS plasma LCAT activity was significantly lower than that of healthy controls. In summary, this study, using a zebrafish model and human patient samples, reports for the first time the defect in plasma cholesterol esterification associated with LPL deficiency.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".