Luminal administration <i>ex vivo</i> of a live <i>Lactobacillus</i> species moderates mouse jejunal motility within minutes
Bibliographic record
Abstract
Gut commensals modulate host immune, endocrine, and metabolic functions. They also affect peripheral and central neural reflexes and function. We have previously shown that daily ingestion of Lactobacillus reuteri (LR) for 9 d inhibits the pseudoaffective cardiac response and spinal single-fiber discharge evoked by visceral distension, and decreases intestinal motility and myenteric AH cell slow afterhyperpolarization (sAHP) by inhibiting a Ca-activated K (IK(Ca)) channel. We tested whether luminal LR could acutely decrease motility in an ex vivo perfusion model of naive Balb/c jejunum. Live LR dose dependently decreased motor complex pressure wave amplitudes with 9- to 16-min onset latency and an IC(50) of 5 × 10(7) cells/ml Krebs. Heat-killed LR or another live commensal, Lactobacillus salivarius, were without effect. The IK(Ca) channel blocker TRAM-34, but neither the opener (DCEBIO) nor the hyperpolarization-activated cationic channel inhibitor ZD7288 (5 μM) (or TTX 1 μM), mimicked the LR effect on motility acutely ex vivo. We provide evidence for a rapid, strain-specific, dose-dependent action of a live Lactobacillus on small intestinal motility reflexes that recapitulates the long-term effects of LR ingestion. These observations may be useful as a first step to unraveling the pathways involved in bacteria to the nervous system communication.
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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 | 0.000 |
| 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".