Loss of carnitine palmitoyltransferase 1a reduces docosahexaenoic acid-containing phospholipids and drives sexually dimorphic liver disease in mice
Bibliographic record
Abstract
BACKGROUND AND AIMS: Genome and epigenome wide association studies identified variants in carnitine palmitoyltransferase 1a (CPT1a) that associate with lipid traits. The goal of this study was to determine the role of liver-specific CPT1a on hepatic lipid metabolism. APPROACH AND RESULTS: Male and female liver-specific knockout (LKO) and littermate controls were placed on a low-fat or high-fat diet (60% kcal fat) for 15 weeks. Mice were necropsied after a 16 h fast, and tissues were collected for lipidomics, matrix-assisted laser desorption ionization mass spectrometry imaging, kinome analysis, RNA-sequencing, and protein expression by immunoblotting. Female LKO mice had increased serum alanine aminotransferase levels which were associated with greater deposition of hepatic lipids, while male mice were not affected by CPT1a deletion relative to male control mice. Mice with CPT1a deletion had reductions in DHA-containing phospholipids at the expense of monounsaturated fatty acids (MUFA)-containing phospholipids in whole liver and at the level of the lipid droplet (LD). Male and female LKO mice increased RNA levels of genes involved in LD lipolysis (Plin2, Cidec, G0S2) and in polyunsaturated fatty acid metabolism (Elovl5, Fads1, Elovl2), while only female LKO mice increased genes involved in inflammation (Ly6d, Mmp12, Cxcl2). Kinase profiling showed decreased protein kinase A activity, which coincided with increased PLIN2, PLIN5, and G0S2 protein levels and decreased triglyceride hydrolysis in LKO mice. CONCLUSIONS: Liver-specific deletion of CPT1a promotes sexually dimorphic steatotic liver disease (SLD) in mice, and here we have identified new mechanisms by which females are protected from HFD-induced liver injury.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".