Precision cut intestinal slices, a novel model of acute food allergic reactions
Bibliographic record
Abstract
BACKGROUND: Food allergy affects up to 10% of the pediatric population. Despite ongoing efforts, treatment options remain limited. Novel models of food allergy are needed to study response patterns downstream of IgE-crosslinking and evaluate drugs modifying acute events. Here, we report a novel human ex vivo model that displays acute, allergen-specific, IgE-mediated smooth muscle contractions using precision cut intestinal slices (PCIS). METHODS: PCIS were generated using gut tissue samples from children who underwent clinically indicated surgery. Viability and metabolic activity were assessed from 0 to 24 h. Distribution of relevant cell subsets was confirmed using single nucleus RNA sequencing. PCIS were passively sensitized using plasma from peanut allergic donors or peanut-sensitized non-allergic donors, and exposed to various stimuli including serotonin, histamine, FcɛRI-crosslinker, and food allergens. Smooth muscle contractions and mediator release functioned as readouts. A novel program designed to measure contractions was developed to quantify responses. The ability to demonstrate the impact of antihistamines and immunomodulation from peanut oral immunotherapy (OIT) was assessed. RESULTS: PCIS viability was maintained for 24 h. Cellular distribution confirmed the presence of key cell subsets including mast cells. The video analysis tool reliably quantified responses to different stimulatory conditions. Smooth muscle contractions were allergen-specific and reflected the clinical phenotype of the plasma donor. Tryptase measurement confirmed IgE-dependent mast cell-derived mediator release. Antihistamines suppressed histamine-induced contraction and plasma from successful peanut OIT suppressed peanut-specific PCIS contraction. CONCLUSION: PCIS represent a novel human tissue-based model to study acute, IgE-mediated food allergy and pharmaceutical impacts on allergic responses in the gut.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".