Hepatocyte-Specific Ptpn6 Deletion Promotes Hepatic Lipid Accretion, but Reduces NAFLD in Diet-Induced Obesity: Potential Role of Pparγ
Bibliographic record
Abstract
UNLABELLED: Hepatocyte-specific Shp1 knockout mice (Ptpn6(H-KO)) are protected from hepatic insulin resistance evoked by high-fat diet (HFD) feeding for 8 weeks. Unexpectedly, we report herein that Ptpn6(H-KO) mice fed an HFD for up to 16 weeks are still protected from insulin resistance, but are more prone to hepatic steatosis, as compared with their HFD-fed Ptpn6(f/f) counterparts. The livers from HFD-fed Ptpn6(H-KO) mice displayed 1) augmented lipogenesis, marked by increased expression of several hepatic genes involved in fatty acid biosynthesis, 2) elevated postprandial fatty acid uptake, and 3) significantly reduced lipid export with enhanced degradation of apolipoprotein B (ApoB). Despite more extensive hepatic steatosis, the inflammatory profile of the HFD-fed Ptpn6(H-KO) liver was similar (8 weeks) or even improved (16 weeks) as compared to their HFD-fed Ptpn6(f/f) littermates, along with reduced hepatocellular damage as revealed by serum levels of hepatic enzymes. Interestingly, comparative microarray analysis revealed a significant up-regulation of peroxisome proliferator-activated receptor gamma (PPARγ) gene expression, confirmed by quantitative polymerase chain reaction. Elevated PPARγ nuclear activity also was observed and found to be directly regulated by Shp1 in a cell-autonomous manner. CONCLUSION: These findings highlight a novel role for hepatocyte Shp1 in the regulation of PPARγ and hepatic lipid metabolism. Shp1 deficiency prevents the development of severe hepatic inflammation and hepatocellular damage in steatotic livers, presenting hepatocyte Shp1 as a potential novel mediator of nonalcoholic fatty liver diseases in obesity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".