Impaired Phosphatidylcholine Biosynthesis Reduces Atherosclerosis and Prevents Lipotoxic Cardiac Dysfunction in ApoE <sup>−/−</sup> Mice
Bibliographic record
Abstract
RATIONALE: Phosphatidylcholine (PC) is the predominant phospholipid component of circulating lipoproteins. The majority of PC is formed by the choline pathway. However, approximately one-third of hepatic PC can also be synthesized by phosphatidylethanolamine N-methyltransferase (PEMT). PEMT is required for normal secretion of very-low-density lipoproteins from the liver. We hypothesized that lack of PEMT would attenuate atherosclerosis and improve myocardial function. OBJECTIVE: Investigate the contribution of PEMT to atherosclerotic lesion formation and cardiac function in mice that lack apolipoprotein E. METHODS AND RESULTS: Mice deficient in apolipoprotein E (Pemt(+/+)/Apoe(-/-)) and mice lacking both PEMT and apoE (Pemt(-/-)/Apoe(-/-)) were fed a chow diet for 1 year. The atherogenic lipoprotein profile of plasma of Apoe(-/-) mice was significantly improved by PEMT deficiency, with lower levels of triacylglycerol (45%) and cholesterol (≈25%) in the very-low-density lipoprotein and low-density/intermediate-density lipoprotein fractions, respectively (P < 0.05). Atherosclerotic lesion area was reduced by ≈30%, and aortic cholesteryl ester and cholesterol content were also reduced by ≈40% by PEMT deficiency (P < 0.05). By in vivo echocardiography, we detected a ≈50% improvement in systolic function in the Pemt(-/-)/Apoe(-/-) compared with Pemt(+/+)/Apoe(-/-) mice (P < 0.05). This was accompanied by a significant reduction in cardiac triacylglycerol (34%) in mice lacking PEMT. CONCLUSIONS: These results indicate that treatment strategies aimed at inhibition of PEMT might prevent the accumulation of cardiac triacylglycerol that predisposes individuals to compromised cardiac function.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".