Protective effects of <i>Lactobacillus reuteri</i> and <i>Bifidobacterium infantis</i> in murine models for colitis do not involve the vagus nerve
Bibliographic record
Abstract
The vagus nerve is an important pathway signaling immune activation of the gastrointestinal tract to the brain. Probiotics are live organisms that may engage signaling pathways of the brain-gut axis to modulate inflammation. The protective effects of Lactobacillus rhamnosus [corrected] (LR) and Bifidobacterium infantis (BI) during intestinal inflammation were studied after subdiaphragmatic vagotomy in acute dextran sulfate sodium (DSS) colitis in BALB/c mice and chronic colitis induced by transfer of CD4(+) CD62L(+) T lymphocytes from BALB/c into SCID mice. LR and BI (1 x 10(9)) were given daily. Clinical score, myeloperoxidase (MPO) levels, and in vivo and in vitro secreted inflammatory cytokine levels were found to be more severe in mice that were vagotomized compared with sham-operated animals. LR in the acute DSS model was effective in decreasing the MPO and cytokine levels in the tissue in sham and vagotomized mice. BI had a strong downregulatory effect on secreted in vitro cytokine levels and had a greater anti-inflammatory effect in vagotomized- compared with sham-operated mice. Both LR and BI retained anti-inflammatory effects in vagotomized mice. In SCID mice, vagotomy did not enhance inflammation, but BI was more effective in vagotomized mice than shams. Taken together, the intact vagus has a protective role in acute DSS-induced colitis in mice but not in the chronic T cell transfer model of colitis. Furthermore, LR and BI do not seem to engage their protective effects via this cholinergic anti-inflammatory pathway, but the results interestingly show that, in the T cell, transfer model vagotomy had a biological effect, since it increased the effectiveness of the BI in downregulation of colonic inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".