Integrative metabolism in MASLD and MASH: Pathophysiology and emerging mechanisms
Bibliographic record
Abstract
The liver acts as a central metabolic hub, integrating signals from the gastrointestinal tract and adipose tissue to regulate carbohydrate, lipid, and amino acid metabolism. Gut-derived metabolites, such as acetate and ethanol, and non-esterified fatty acids from white adipose tissue influence hepatic processes, which rely on mitochondrial function to maintain systemic energy balance. Metabolic dysregulation caused by obesity, insulin resistance, and type 2 diabetes disrupts these pathways, leading to metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (MASH). In this review, we explore the metabolic fluxes within the gut-adipose tissue-liver axis, focusing on the pivotal role of de novo lipogenesis, dietary substrates like glucose and fructose, and changes in mitochondrial function during MASLD progression. We also highlight the contributions of white adipose tissue insulin resistance and impaired mitochondrial dynamics to hepatic lipid accumulation. Further understanding how the interplay between substrate flux from the gastro-intestinal tract integrates with adipose tissue and intersects with structural and functional alterations to liver mitochondria will be important to identify novel therapeutic targets and advance the treatment of MASLD and MASH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".