Psychoactive bacteria<i>Lactobacillus rhamnosus</i>(JB-1) elicits rapid frequency facilitation in vagal afferents
Bibliographic record
Abstract
Mounting evidence supports the influence of the gut microbiome on the local enteric nervous system and its effects on brain chemistry and relevant behavior. Vagal afferents are involved in some of these effects. We previously showed that ingestion of the probiotic bacterium Lactobacillus rhamnosus (JB-1) caused extensive neurochemical changes in the brain and behavior that were abrogated by prior vagotomy. Because information can be transmitted to the brain via primary afferents encoded as neuronal spike trains, our goal was to record those induced by JB-1 in vagal afferents in the mesenteric nerve bundle and thus determine the nature of the signals sent to the brain. Male Swiss Webster mice jejunal segments were cannulated ex vivo, and serosal and luminal compartments were perfused separately. Bacteria were added intraluminally. We found no evidence for translocation of labeled bacteria across the epithelium during the experiment. We recorded extracellular multi- and single-unit neuronal activity with glass suction pipettes. Within minutes of application, JB-1 increased the constitutive single- and multiunit firing rate of the mesenteric nerve bundle, but Lactobacillus salivarius (a negative control) or media alone were ineffective. JB-1 significantly augmented multiunit discharge responses to an intraluminal distension pressure of 31 hPa. Prior subdiaphragmatic vagotomy abolished all of the JB-1-evoked effects. This detailed exploration of the neuronal spike firing that encodes behavioral signaling to the brain may be useful to identify effective psychoactive bacteria and thereby offer an alternative new perspective in the field of psychiatry and comorbid conditions.
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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 | 0.000 |
| 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".