Ochratoxin A induces liver inflammation: involvement of intestinal microbiota
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Ochratoxin A (OTA) is a widespread mycotoxin and induces liver inflammation to human and various species of animals. The intestinal microbiota has critical importance in liver inflammation; however, it remains to know whether intestinal microbiota mediates the liver inflammation induced by OTA. Here, we treated ducklings with oral gavage of OTA (235 μg/kg body weight) for 2 weeks. Then, the microbiota in the cecum and liver were analyzed with 16S rRNA sequencing, and the inflammation in the liver was analyzed. To explore the role of intestinal microbiota in OTA-induced liver inflammation, intestinal microbiota was cleared with antibiotics and fecal microbiota transplantation was conducted. RESULTS: Here, we find that OTA treatment in ducks altered the intestinal microbiota composition and structure [e.g., increasing the relative abundance of lipopolysaccharides (LPS)-producing Bacteroides], and induced the accumulation of LPS and inflammation in the liver. Intriguingly, in antibiotic-treated ducks, OTA failed to induce these alterations in the liver. Notably, with the fecal microbiota transplantation (FMT) program, in which ducks were colonized with intestinal microbiota from control or OTA-treated ducks, we elucidated the involvement of intestinal microbiota, especially Bacteroides, in liver inflammation induced by OTA. CONCLUSIONS: These results highlight the role of gut microbiota in OTA-induced liver inflammation and open a new window for novel preventative or therapeutic intervention for mycotoxicosis.
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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) | 0.002 | 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 it