The emerging role of ethanolamine phosphate phospholyase in regulating hepatic phosphatidylethanolamine and plasma lipoprotein metabolism in mice
Bibliographic record
Abstract
Abstract Ethanolamine phosphate phospholyase (ETNPPL) is an enzyme that irreversibly degrades phospho‐ethanolamine (p‐ETN), an intermediate in the Kennedy pathway of phosphatidylethanolamine (PE) biosynthesis. PE is the second most abundant phospholipid in mammalian membranes. Disturbance of hepatic phospholipid homeostasis has been linked to the development of metabolic dysfunction‐associated steatotic liver disease (MASLD). We generated whole‐body Etnppl knockout mice to investigate the impact of genetic deletion of Etnppl on hepatic lipid metabolism. Primary hepatocytes isolated from Etnppl −/− mice showed increased conversion of [3H]ethanolamine to [ 3 H]p‐ETN and [ 3 H]PE compared to Etnppl +/+ mice. Male and female Etnppl +/+ and Etnppl −/− mice were fed either a chow or a western‐type diet (WTD). Irrespective of diet, Etnppl −/− mice had elevated fasting levels of total plasma cholesterol, triglyceride (TG) and apolipoprotein B100 (VLDL particles). Interestingly, hepatic TG secretion was unchanged between groups. Although hepatic lipids (phosphatidylcholine (PC), PE, TG, and cholesterol) were not different between mice, RNA sequencing analysis showed downregulation in genes related to cholesterol biosynthesis in Etnppl −/− mice. Furthermore, hepatic low‐density lipoprotein receptor‐related protein1 (LRP1) protein level was lower in female Etnppl −/− mice, which may indicate reduced uptake of remnant VLDL particles from circulation. Hepatic PE levels were only increased in WTD‐fed female Etnppl −/− mice, not chow diet‐fed mice. However, hepatic lipid accumulation and metabolic dysfunction‐associated steatohepatitis (MASH) development were unchanged between Etnppl +/+ and Etnppl −/− mice. To conclude, ETNPPL has a role in regulating plasma lipoprotein metabolism independent of hepatic TG 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".