Remodeling of lipid landscape in high fat fed very-long chain acyl-CoA dehydrogenase null mice favors pro-arrhythmic polyunsaturated fatty acids and their downstream metabolites
Bibliographic record
Abstract
Very-long chain acyl-CoA dehydrogenase (VLCAD) catalyzes the initial step of mitochondrial long chain (LC) fatty acid β-oxidation (FAO). Inherited VLCAD deficiency (VLCADD) predisposes to neonatal arrhythmias whose pathophysiology is still not understood. We hypothesized that VLCADD results in global disruption of cardiac complex lipid homeostasis, which may set conditions predisposing to arrhythmia. To test this, we assessed the cardiac lipidome and related molecular markers in seven-month-old VLCAD−/− mice, which mimic to some extent the human cardiac phenotype. Mice were sacrificed in the fed or fasted state after receiving for two weeks a chow or a high-fat diet (HFD), the latter condition being known to worsen symptoms in human VLCADD. Compared to their littermate counterparts, HFD/fasted VLCAD−/− mouse hearts displayed the following lipid alterations: (1) Lower LC, but higher VLC-acylcarnitines accumulation, (2) higher levels of arachidonic acid (AA) and lower docosahexaenoic acid (DHA) contents in glycerophospholipids (GPLs), as well as (3) corresponding changes in pro-arrhythmogenic AA-derived isoprostanes and thromboxane B2 (higher), and anti-arrythmogenic DHA-derived neuroprostanes (lower). These changes were associated with remodeling in the expression of gene or protein markers of (1) GPLs remodeling: higher calcium-dependent phospholipase A2 and lysophosphatidylcholine-acyltransferase 2, (2) calcium handling perturbations, and (3) endoplasmic reticulum stress. Altogether, these results highlight global lipid dyshomeostasis beyond FAO in VLCAD−/− mouse hearts, which may set conditions predisposing the hearts to calcium mishandling and endoplasmic reticulum stress and thereby may contribute to the pathogenesis of arrhythmias in VLCADD in mice as well as in humans.
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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 | 0.000 | 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".