Comparing the effect of intestinal bacteria from rabbit, pig, and chicken on inflammatory response in cultured rabbit crypt and villus
Bibliographic record
Abstract
Rabbit is susceptible to intestinal infection, which often results in severe inflammatory response. To investigate whether the special community structure of rabbit intestinal bacteria contributes to this susceptibility, we compared the inflammatory responses of isolated rabbit crypt and villus to heat-treated total bacteria in pig, chicken, and rabbit ileal contents. The dominant phylum in pig and chicken ileum was Firmicutes, while Bacteroidetes was dominant in rabbit ileum. The intestinal bacteria from rabbit induced higher expression of toll-like receptor 4 (TLR4) in rabbit crypt and villus (P < 0.05). TLR2 and TLR3 expression was obviously stimulated by chicken and pig intestinal bacteria (P < 0.05) but not by those of rabbit. The ileal bacteria from those three animals all increased the expression of tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) in crypts and villus (P < 0.05). Chicken and pig ileal bacteria also stimulated the expression of anti-inflammatory factors interferon beta (IFN-β) and IL-10 (P < 0.05), while those of rabbit did not (P > 0.05). In conclusion, a higher abundance of Gram-negative bacteria in rabbit ileum did not lead to more expressive pro-inflammatory cytokines in isolated rabbit crypt and villus, but a higher percentage of Lactobacillus in chicken ileum might result in more expressive anti-inflammatory factors.
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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 | 0.000 | 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 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".