Psychological Stress-Induced Local Immune Response to Food Antigens Increases Pain Signaling Across the Gut in Mice
Bibliographic record
Abstract
BACKGROUND & AIMS: We recently showed that a bacterial infection can break oral tolerance to food and lead to immunoglobulin E (IgE)-dependent mast cell activation and food-induced abdominal pain, which could constitute an important pathogenic mechanism in postinfectious irritable bowel syndrome (IBS). Here, we investigated whether similar immune mechanisms in response to psychological stress lead to food-evoked pain signaling, and thus potentially explain the pathophysiology in a larger group of patients with IBS. METHODS: Mice were exposed to ovalbumin (OVA) during water avoidance stress (WAS) and re-exposed to OVA 5 weeks later. Nociception was evaluated by visceromotor responses and afferent nerve recordings to intestinal distension, and patch-clamp recordings of sensory neurons incubated with intestinal supernatants. The role of IgE and type 2 immunity was evaluated using pharmacologic and genetic approaches. RESULTS: antagonist pyrilamine blocked the increased sensory neuron excitability, and reduced ileal afferent nerve firing to distension in WAS/OVA+OVA mice. CONCLUSIONS: Psychological stress induces a type 2 immune response to food antigens, with IgE-mediated mast cell activation and increased pain signaling in the small intestine and colon in response to food. These findings may explain the potential role of psychological stress in food-induced symptoms in 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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".