AMPK Activation and Lipid Homeostasis Regulation in MASLD: Investigating the Hepatoprotective and Anti‐Inflammatory Effects of Meta‐Capridin Medium‐Chain Triglycerides
Bibliographic record
Abstract
Metabolic dysfunction–associated steatotic liver disease (MASLD) is characterized by hepatic lipid accumulation, mitochondrial dysfunction, and chronic inflammation. Disruptions in fatty acid oxidation and ketogenesis contribute to disease progression, highlighting the potential of dietary interventions that enhance hepatic metabolic adaptation. This study investigates the effects of a medium‐chain triglyceride supplement, meta‐Capridin (m‐CAP), on hepatic ketogenesis, mitochondrial function, and inflammatory responses in a MASLD rat model. Male Wistar rats were assigned to preventive and therapeutic groups and fed a normal diet, a high‐fat diet (HFD), or a HFD supplemented with m‐CAP. Key metabolic markers, including β‐hydroxybutyrate, mitochondrial enzyme activity, peroxisome proliferator‐activated receptor alpha (PPAR‐α), AMP‐activated protein kinase (AMPK), and LXR, were assessed alongside inflammatory cytokines and NLRP3 inflammasome activation. Results showed that m‐CAP enhanced hepatic ketogenesis, increased AMPK phosphorylation, and upregulated PPAR‐α, improving mitochondrial function. Additionally, it suppressed NLRP3 activation and proinflammatory cytokines, particularly in the therapeutic phase. These findings suggest that m‐CAP promotes hepatic ketogenesis and modulates inflammation, supporting its potential as a functional food‐based strategy for MASLD prevention and treatment.
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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) | 0.001 | 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".