Pioglitazone attenuates hepatic inflammation and fibrosis in phosphatidylethanolamine<i>N</i>-methyltransferase-deficient mice
Bibliographic record
Abstract
Phosphatidylethanolamine N-methyltransferase (PEMT) is an important enzyme in hepatic phosphatidylcholine (PC) biosynthesis. Pemt(-/-) mice are protected against high-fat diet (HFD)-induced obesity and insulin resistance; however, these mice develop nonalcoholic fatty liver disease (NAFLD). We hypothesized that peroxisomal proliferator-activated receptor-γ (PPARγ) activation by pioglitazone might stimulate adipocyte proliferation, thereby directing lipids from the liver toward white adipose tissue. Pioglitazone might also act directly on PPARγ in the liver to improve NAFLD. Pemt(+/+) and Pemt(-/-) mice were fed a HFD with or without pioglitazone (20 mg·kg(-1)·day(-1)) for 10 wk. Pemt(-/-) mice were protected from HFD-induced obesity but developed NAFLD. Treatment with pioglitazone caused an increase in body weight gain in Pemt(-/-) mice that was mainly due to increased adiposity. Moreover, pioglitazone improved NAFLD in Pemt(-/-) mice, as indicated by a 35% reduction in liver weight and a 57% decrease in plasma alanine transaminase levels. Livers from HFD-fed Pemt(-/-) mice were steatotic, inflamed, and fibrotic. Hepatic steatosis was still evident in pioglitazone-treated Pemt(-/-) mice; however, treatment with pioglitazone reduced hepatic fibrosis, as evidenced by reduced Sirius red staining and lowered mRNA levels of collagen type Iα1 (Col1a1), tissue inhibitor of metalloproteinases 1 (Timp1), α-smooth muscle actin (Acta2), and transforming growth factor-β (Tgf-β). Similarly, oxidative stress and inflammation were reduced in livers from Pemt(-/-) mice upon treatment with pioglitazone. Together, these data show that activation of PPARγ in HFD-fed Pemt(-/-) mice improved liver function, while these mice were still protected against diet-induced obesity and insulin resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".