T cells regulate intestinal motility and shape enteric neuronal responses to intestinal microbiota
Bibliographic record
Abstract
How the gut microbiota and immune system maintain intestinal homeostasis in concert with the enteric nervous system (ENS) remains incompletely understood. To address this gap, we assessed small intestinal transit, enteric neuronal density, enteric neurogenesis, intestinal microbiota, immune cell populations and cytokines in wildtype and T-cell deficient germ-free mice colonized with specific pathogen-free (SPF) microbiota, conventionally raised SPF and segmented filamentous bacteria (SFB)-monocolonized mice. SPF microbiota increased small intestinal transit in a T cell-dependent manner. SPF microbiota increased neuronal density in the myenteric and submucosal plexuses of the ileum and colon, similar to conventionally raised SPF mice, independently of T cells. SFB increased neuronal density in the ileum in a T cell-dependent manner, but independently of T cells in the colon. SPF microbiota stimulated enteric neurogenesis (Sox2 expression in enteric neurons) in the ileum in a T cell-dependent manner, but in the colon this effect was T cell-independent. T cells regulated nestin expression in the ENS. SPF colonization increased Th17 cells, RORγT+ Treg cells, and IL-1β and IL-17A levels in the ileum and colon. By neutralizing IL-1β and IL-17A, we observed that they control microbiota-mediated enteric neurogenesis but were not involved in the regulation of motility. Together, these findings provide new insights into the microbiota-neuroimmune dialog that regulates intestinal physiology.
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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 | 0.001 |
| 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".