Lysosomal acid lipase regulates VLDL synthesis and insulin sensitivity in mice
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Lysosomal acid lipase (LAL) hydrolyses cholesteryl esters and triacylglycerols (TG) within lysosomes to mobilise NEFA and cholesterol. Since LAL-deficient (Lal (-/-) ) mice suffer from progressive loss of adipose tissue and severe accumulation of lipids in hepatic lysosomes, we hypothesised that LAL deficiency triggers alternative energy pathway(s). METHODS: We studied metabolic adaptations in Lal (-/-) mice. RESULTS: Despite loss of adipose tissue, Lal (-/-) mice show enhanced glucose clearance during insulin and glucose tolerance tests and have increased uptake of [(3)H]2-deoxy-D-glucose into skeletal muscle compared with wild-type mice. In agreement, fasted Lal (-/-) mice exhibit reduced glucose and glycogen levels in skeletal muscle. We observed 84% decreased plasma leptin levels and significantly reduced hepatic ATP, glucose, glycogen and glutamine concentrations in fed Lal (-/-) mice. Markedly reduced hepatic acyl-CoA concentrations decrease the expression of peroxisome proliferator-activated receptor α (PPARα) target genes. However, treatment of Lal (-/-) mice with the PPARα agonist fenofibrate further decreased plasma TG (and hepatic glucose and glycogen) concentrations in Lal (-/-) mice. Depletion of hepatic nuclear factor 4α and forkhead box protein a2 in fasted Lal (-/-) mice might be responsible for reduced expression of microsomal TG transfer protein, defective VLDL synthesis and drastically reduced plasma TG levels. CONCLUSIONS/INTERPRETATION: Our findings indicate that neither activation nor inactivation of PPARα per se but rather the availability of hepatic acyl-CoA concentrations regulates VLDL synthesis and subsequent metabolic adaptations in Lal (-/-) mice. We conclude that decreased plasma VLDL production enhances glucose uptake into skeletal muscle to compensate for the lack of energy supply.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".