A1 MARKERS OF ACTIVATED INFLAMMATORY CELLS ARE ASSOCIATED WITH NON-ALCOHOLIC FATTY LIVER DISEASE AND INTESTINAL MICROBIOTA
Bibliographic record
Abstract
Several mechanisms contribute to the pathogenesis of non-alcoholic fatty liver disease (NAFLD). The intestinal microbiota (IM) and liver immune function cells have been implicated in NAFLD, but data on their potential associations have been scarce. The aim of this study was to investigate whether there are differences in hepatic inflammatory cell markers between NAFLD and healthy controls (HC), using the antigens CD45, CD163, CD20 and CD3, and to determine whether these markers are associated with specific IM. This was a prospective, cross-sectional study of adults with biopsy-confirmed NAFLD and healthy controls (HC). Clinical and laboratory data were collected. Fecal IM were assessed by qPCR and immune cells by immunohistochemistry. NAFLD activity score (NAS) was used for disease severity. 42 subjects were studied: 8 HC and 34 NAFLD. Hematopoietic cell marker CD45+ and Kupffer cell marker CD163+ were higher in NAFLD compared to HC, and those with a NAS ≥5 had higher levels of CD20+ cells a marker of B cells versus a NAS of 0 or 1–4. In 39 patients (5 HC, 34 NAFLD) IM was measured: 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; Prevotella was negatively correlated with CD20+ (r=-0.353, p=0.028) cells in the liver lobule and Archaea were positively correlated with CD20+ (r=0.468, p=0.003) in the liver lobule. Hepatic immune cell counts are increased in NAFLD versus HC and associated with disease severity. Specific immune cells in portal or lobular areas correlated with specific fecal IM, suggesting a role for IM in hepatic inflammation. CIHR
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".