The gut‐brain axis rewired: adding a functional vagal nicotinic “sensory synapse”
Bibliographic record
Abstract
It is generally accepted that intestinal sensory vagal fibers are primary afferent, responding nonsynaptically to luminal stimuli. The gut also contains intrinsic primary afferent neurons (IPANs) that respond to luminal stimuli. A psychoactive Lactobacillus rhamnosus (JB-1) that affects brain function excites both vagal fibers and IPANs. We wondered whether, contrary to its primary afferent designation, the sensory vagus response to JB-1 might depend on IPAN to vagal fiber synaptic transmission. We recorded ex vivo single- and multiunit afferent action potentials from mesenteric nerves supplying mouse jejunal segments. Intramural synaptic blockade with Ca(2+) channel blockers reduced constitutive or JB-1-evoked vagal sensory discharge. Firing of 60% of spontaneously active units was reduced by synaptic blockade. Synaptic or nicotinic receptor blockade reduced firing in 60% of vagal sensory units that were stimulated by luminal JB-1. In control experiments, increasing or decreasing IPAN excitability, respectively increased or decreased nerve firing that was abolished by synaptic blockade or vagotomy. We conclude that >50% of vagal afferents function as interneurons for stimulation by JB-1, receiving input from an intramural functional "sensory synapse." This was supported by myenteric plexus nicotinic receptor immunohistochemistry. These data offer a novel therapeutic target to modify pathological gut-brain axis activity.-Perez-Burgos, A., Mao, Y.-K., Bienenstock, J., Kunze, W. A. The gut-brain axis rewired: adding a functional vagal nicotinic "sensory synapse."
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".