<i>Lactobacillus reuteri</i> ingestion and IK<sub>Ca</sub> channel blockade have similar effects on rat colon motility and myenteric neurones
Bibliographic record
Abstract
BACKGROUND: We have previously shown that ingestion of Lactobacillus reuteri may modulate colonic enteric neuron activity but with unknown effects on colon motility. The aim of the present report was to elucidate the neuronal mechanisms of action of the probiotic by comparing the effects on motility of L. reuteri ingestion with blockade of a specific ionic current in enteric neurons. METHODS: We have used intraluminal pressure recordings from ex vivo rat colon segments and whole cell patch clamp recordings from neurons of rat longitudinal muscle myenteric plexus preparations to investigate the effects of L. reuteri and TRAM-34 on colon motility and neurophysiology. The effects of daily feeding of 10(9) L. reuteri bacteria or acute application of TRAM-34 on threshold fluid filling pressure or pulse pressure was measured. KEY RESULTS: Lactobacillus reuteri increased intraluminal fluid filling pressure thresholds for evoking pressure pulses by 51% from 0.47 +/- 0.17 hPa; the probiotic also decreased the pulse pressure amplitudes, but not frequency, by 18% from 3.91 +/- 0.52 hPa. The intermediate conductance calcium-dependent potassium (IK(Ca)) channel blocker TRAM-34 (3 micromol L(-1)) increased filling threshold pressure by 43% from 0.52 +/- 0.22 hPa and reduced pulse pressure amplitude by 40% from 2.63 +/- 1.11 hPa; contraction frequency was unaltered. TRAM-34 (3 micromol L(-1)) reduced membrane polarization, leak conductance and the slow afterhyperpolarization current in 16/16 myenteric rat colon AH cells but 19/19 S cells were unaffected. CONCLUSIONS & INFERENCES: The present results are consistent with L. reuteri enhancing tonic inhibition of colon contractile activity by acting via the IK(Ca) channel current in AH cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".