Dietary monosodium glutamate increases visceral hypersensitivity in a mouse model of visceral pain
Bibliographic record
Abstract
BACKGROUND: Monosodium glutamate (MSG) has been identified as a trigger of abdominal pain in irritable bowel syndrome (IBS), but the mechanism is unknown. This study examined whether MSG causes visceral hypersensitivity using a water-avoidance stress (WAS) mouse model of visceral pain. METHODS: Mice were divided into four groups receiving treatment for 6 days: WAS + MSG gavage, WAS + saline gavage, sham-WAS + MSG gavage, and sham-WAS + saline gavage. The acute effects of intraluminal administration of 10 μM MSG on jejunal extrinsic afferent nerve sensitivity to distension (0-60 mmHg) were examined using ex vivo extracellular recordings. MSG was also applied directly to jejunal afferents from untreated mice. Glutamate concentration was measured in serum, and in the serosal compartment of Ussing chambers following apical administration. KEY RESULTS: Acute intraluminal MSG application increased distension responses of jejunal afferent nerves from mice exposed to WAS + MSG. This effect was mediated by wide dynamic range and high-threshold units at both physiologic and noxious pressures (10-60 mmHg, p < 0.05). No effect of MSG was observed in the other groups, or when applied directly to the jejunal afferent nerves. Serum glutamate was increased in mice exposed to WAS + MSG compared to sham-WAS + saline, and serosal glutamate increased using WAS tissue (p = 0.0433). CONCLUSIONS AND INFERENCES: These findings demonstrate that repeated exposure to MSG in mice leads to sensitization of jejunal afferent nerves to acute ex vivo exposure to MSG. This may contribute to visceral hypersensitivity reported in response to MSG in patients with IBS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".