Intestinal microbiota influence the early postnatal development of the enteric nervous system
Bibliographic record
Abstract
BACKGROUND: Normal gastrointestinal function depends on an intact and coordinated enteric nervous system (ENS). While the ENS is formed during fetal life, plasticity persists in the postnatal period during which the gastrointestinal tract is colonized by bacteria. We tested the hypothesis that colonization of the bowel by intestinal microbiota influences the postnatal development of the ENS. METHODS: The development of the ENS was studied in whole mount preparations of duodenum, jejunum, and ileum of specific pathogen-free (SPF), germ-free (GF), and altered Schaedler flora (ASF) NIH Swiss mice at postnatal day 3 (P3). The frequency and amplitude of circular muscle contractions were measured in intestinal segments using spatiotemporal mapping of video recorded spontaneous contractile activity with and without exposure to lidocaine and N-nitro-L-arginine (NOLA). KEY RESULTS: Immunolabeling with antibodies to PGP9.5 revealed significant abnormalities in the myenteric plexi of GF jejunum and ileum, but not duodenum, characterized by a decrease in nerve density, a decrease in the number of neurons per ganglion, and an increase in the proportion of myenteric nitrergic neurons. Frequency of amplitude of muscle contractions were significantly decreased in the jejunum and ileum of GF mice and were unaffected by exposure to lidocaine, while NOLA enhanced contractile frequency in the GF jejunum and ileum. CONCLUSIONS & INFERENCES: These findings suggest that early exposure to intestinal bacteria is essential for the postnatal development of the ENS in the mid to distal small intestine. Future studies are needed to investigate the mechanisms by which enteric microbiota interact with the developing ENS.
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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".