Intestinal Bacterial Dysbiosis and Liver Fibrosis in Mice Through Gut‐Liver Axis and NLRP3 Inflammatory Pathway Caused by Fine Particulate Matter
Bibliographic record
Abstract
ABSTRACT Fine particulate matter (PM 2.5 ) is associated with risks of liver diseases and intestinal bacterial dysbiosis, in which the gut‐liver axis regulation mechanisms induced by PM 2.5 exposure are still limited so far. In this study, after 12 weeks of exposure to atmospheric PM 2.5 (64 μg/m 3 ) and clean air in winter in Taiyuan, China, we collected liver and intestinal tissues and serum in male mice to perform toxicology experiments. The results showed that PM 2.5 significantly exacerbated the pathological injury in the liver and intestine and liver fibrosis in mice, along with elevated levels of pro‐inflammatory cytokines and lipopolysaccharide (LPS) levels in the serum. PM 2.5 caused abnormal liver function and activated TLR4/NF‐κB/NLRP3 pathway in mouse liver. PM 2.5 also significantly inhibited the expression of intestinal mucosal tight junction proteins such as ZO‐1 and occludin. Besides, from 16S rRNA gene sequencing results in intestinal and fecal samples, we found that PM 2.5 decreased the diversity and abundance of intestinal bacteria, along with reducing Shannon, Chao1 and Ace indices and increasing Simpson indices. Principal component analysis (PCA) showed that mice's intestinal bacterial composition and β‐diversity in the PM 2.5 ‐exposed group significantly differed from the control group. KEGG pathway analyzed key functional genes and metabolic pathways in important mouse bacterial communities in the PM 2.5 ‐exposed group. It suggested that PM 2.5 exposure exacerbates liver fibrosis in mice via the NLRP3 pathway. PM 2.5 caused intestinal mucosal injury, intestinal bacterial disorders and increased LPS levels, leading to the activation of inflammatory pathways, which can exacerbate liver fibrosis via the gut‐liver axis.
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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) | 0.001 | 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 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".