Markers of activated inflammatory cells are associated with disease severity and intestinal microbiota in�adults with non‑alcoholic fatty liver disease
Bibliographic record
Abstract
Several mechanisms contribute to the pathogenesis of non‑alcoholic fatty liver disease (NAFLD). The intestinal microbiota (IM) and liver immune cells (LIC) may serve a role, but there has been no previous study assessing potential associations between IM and LIC. The aim of the present study was to investigate whether there are differences in LIC markers between patients with NAFLD and healthy controls (HC), and to determine whether these markers are associated with specific IM. The present prospective, cross‑sectional study examined a cohort of adults with liver biopsy‑confirmed NAFLD and HC. Clinical and laboratory data were collected. Fecal IM was assessed by quantitative polymerase chain reaction and LIC, by immunohistochemistry. NAFLD activity score (NAS) was used for disease severity. Liver immune cell counts were increased in patients with NAFLD (n=34) vs. HC (n=8) and this was associated with disease severity. Hematopoietic cell marker cluster of differentiation (CD)45+ and Kupffer cell marker CD163+ were higher in NAFLD compared with HC, and those with an NAS ≥5 had higher levels of CD20+ cells, a marker of B cells, vs. a NAS of 0 or 1‑4. Additionally, from those patients (5 HC, 34 NAFLD), IM was measured. Specific immune cells in portal or lobular areas correlated with specific fecal IM, suggesting a potential association between IM and liver inflammation in patients with NAFLD. Specifically, Faecalibacterium prausnitzii was negatively correlated with CD45+ (r= ‑0.394; P=0.015) and CD163+ (r= ‑0.371; P=0.022) cells in the portal tract and Prevotella was negatively correlated with CD20+ (r= ‑0.353; P=0.028) cells in the liver lobule. Other taxa exhibited no correlation. In conclusion, the present study demonstrated a potential association between IM and liver inflammation in NAFLD.
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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) | 0.000 | 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 | 0.000 |
| 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".