Myeloid AMPK signaling restricts fibrosis but is not required for metformin improvements during CDAHFD-induced NASH in mice
Bibliographic record
Abstract
Metabolic programming underpins inflammation and liver macrophage activation in the setting of chronic liver disease. Here, we sought to identify the role of an important metabolic regulator, AMP-activated protein kinase (AMPK), specifically within myeloid cells during the progression of non-alcoholic steatohepatitis (NASH) and whether treatment with metformin, a firstline therapy for diabetes and activator of AMPK could stem disease progression. Male and female Prkaa1 fl/fl /Prkaa2 fl/fl (Flox) control and Flox- LysM -Cre + (MacKO) mice were fed a low-fat control or a choline-deficient, amino acid defined 45% Kcal high-fat diet (CDAHFD) for 8 weeks, where metformin was introduced in the drinking water (50 or 250 mg/kg/day) for the last 4 weeks. Hepatic steatosis and fibrosis were dramatically increased in response to CDAHFD-feeding compared to low-fat control. While myeloid AMPK signaling had no effect on markers of hepatic steatosis or circulating markers, fibrosis as measured by total liver collagen was significantly elevated in livers from MacKO mice, independent of sex. Although treatment with 50 mg/kg/day metformin had no effect on any parameter, intervention with 250 mg/kg/day metformin completely ameliorated hepatic steatosis and fibrosis in both male and female mice. While the protective effect of metformin was associated with lower final body weight, and decreased expression of lipogenic and Col1a1 transcripts, it was independent of myeloid AMPK signaling. These results suggest that endogenous AMPK signaling in myeloid cells, both liver-resident and infiltrating, acts to restrict fibrogenesis during CDAHFD-induced NASH progression but is not the mechanism by which metformin improves markers of NASH.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".