TRPV4 stimulates colonic afferents through mucosal release of ATP and glutamate
Bibliographic record
Abstract
Background and Purpose Abdominal pain is a leading cause of morbidity for people living with gastrointestinal disease. Whereas the transient receptor potential vanilloid 4 (TRPV4) ion channel has been implicated in the pathogenesis of abdominal pain, the relative paucity of TRPV4 expression in colon‐projecting sensory neurons suggests that non‐neuronal cells may contribute to TRPV4‐mediated nociceptor stimulation. Experimental Approach Changes in murine colonic afferent activity were examined using ex vivo electrophysiology in tissues with the gut mucosa present or removed. ATP and glutamate release were measured by bioluminescence assays from human colon organoid cultures and mouse colon. Dorsal root ganglion sensory neuron activity was evaluated by Ca 2+ imaging when cultured alone or co‐cultured with colonic mucosa. Key Results Bath application of TRPV4 agonist GSK1016790A elicited a robust increase in murine colonic afferent activity, which was abolished by removing the gut mucosa. GSK1016790A promoted ATP and glutamate release from human colon organoid cultures and mouse colon. Inhibition of ATP degradation in mouse colon enhanced the afferent response to GSK1016790A. Pretreatment with purinoceptor or glutamate receptor antagonists attenuated and abolished the response to GSK1016790A when given alone or in combination, respectively. Sensory neurons co‐cultured with colonic mucosal cells produced a marked increase in intracellular Ca 2+ to GSK1016790A compared with neurons cultured alone. Conclusion and Implications Our data indicate that mucosal release of ATP and glutamate is responsible for the stimulation of colonic afferents following TRPV4 activation. These findings highlight an opportunity to target the gut mucosa for the development of new visceral analgesics.
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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) | 0.003 | 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".