An imbalance in mucosal cytokine profile causes transient intestinal inflammation following an animal's first exposure to faecal bacteria and antigens
Bibliographic record
Abstract
Intestinal microflora play a critical role in the initiation and perpetuation of chronic inflammatory bowel diseases. In genetically susceptible hosts, bacterial colonization results in rapid-onset chronic intestinal inflammation. Nevertheless, the intestinal and systemic immune response to faecal bacteria and antigen exposure into a sterile intestinal lumen of a post-weaned animal with a mature immune system are not understood clearly. This study examined the effects of faecal bacteria and antigen exposure on the intestinal mucosal and systemic immune system in healthy axenic mice. Axenic wild-type mice were inoculated orally with a crude faecal slurry solution derived from conventionally raised mice and were analysed prior to and then at days 3, 7, 14 and 28 post-treatment. Ingestion of faecal slurry resulted in a transient, early onset of proinflammatory interferon (IFN)-gamma, tumour necrosis factor (TNF)-alpha and interleukin (IL)-17 response that was maximal at day 3. In contrast, the transient release of the anti-inflammatory cytokines IL-10 and IL-4 occurred later and was maximal at day 7. Both responses subsided by day 14. This early cytokine imbalance was associated with a brief rise in colonic and caecal histopathological injury score at day 7. The bacterial antigen-specific systemic response was found to follow the intestinal immune response with a maximal release of both pro- and anti-inflammatory cytokines at day 7. Thus, first exposure of healthy axenic wild-type mice to normal faecal flora and antigens results in an early proinflammatory cytokine response and transient colonic inflammation that then resolves in conjunction with a subsequent anti-inflammatory cytokine profile.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".