Deficiency of liver adipose triglyceride lipase in mice causes progressive hepatic steatosis
Bibliographic record
Abstract
UNLABELLED: Accumulation of cytoplasmic triacylglycerol (TG) underlies hepatic steatosis, a major cause of cirrhosis. The pathways of cytoplasmic TG metabolism are not well known in hepatocytes, but evidence suggests an important role in lipolysis for adipose triglyceride lipase (ATGL). We created mice with liver-specific inactivation of Pnpla2, the ATGL gene. These ATGLLKO mice had severe progressive periportal macrovesicular and pericentral microvesicular hepatic steatosis (73, 150, and 226 μmol TG/g liver at 4, 8, and 12 months, respectively). However, plasma levels of glucose, TG, and cholesterol were similar to those of controls. Fasting 3-hydroxybutyrate level was normal, but in thin sections of liver, beta oxidation of palmitate was decreased by one-third in ATGLLKO mice compared with controls. Tests of very low-density lipoprotein production, glucose, and insulin tolerance and gluconeogenesis from pyruvate were normal. Plasma alanine aminotransferase levels were elevated in ATGLLKO mice, but histological estimates of inflammation and fibrosis and messenger RNA (mRNA) levels of tumor necrosis factor-α and interleukin-6 were similar to or lower than those in controls. ATGLLKO cholangiocytes also showed cytoplasmic lipid droplets, demonstrating that ATGL is also a major lipase in cholangiocytes. There was a 50-fold reduction of hepatic diacylglycerol acyltransferase 2 mRNA level and a 2.7-fold increase of lipolysosomes in hepatocytes (P < 0.001), suggesting reduced TG synthesis and increased lysosomal degradation of TG as potential compensatory mechanisms. CONCLUSION: Compared with the hepatic steatosis of obesity and diabetes, steatosis in ATGL deficiency is well tolerated metabolically. ATGLLKO mice will be useful for studying the pathophysiology of hepatic steatosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".