Characterization of liver, adipose, and fecal microbiome in obese patients with MASLD: links with disease severity and metabolic dysfunction parameters
Bibliographic record
Abstract
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a range of histological findings from the generally benign simple steatosis to steatohepatitis (MASH) which can progress to fibrosis and cirrhosis. Several factors, including the microbiome, may contribute to disease progression. RESULTS: Here, we demonstrate links between the presence and abundance of specific bacteria in the adipose and liver tissues, inflammatory genes, immune cell responses, and disease severity. Overall, in MASLD patients, we observed a generalized obesity-induced translocation of gut bacteria to hepatic and adipose tissues. We identified microbial patterns unique to more severely diseased tissues. Specifically, Enterococcus, Granulicatella, and Morganellaceae abundance is positively correlated with immune cell counts and inflammatory gene expression levels, and both genera are significantly enriched in MASH patients. Brevibacterium is enriched in adipose tissues of patients with liver fibrosis. CONCLUSION: Together, these results provide further insight into the microbial factors that may be driving disease severity. Video Abstract.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".