Immunoglobulin E-Binding Pattern of Canadian Peanut Allergic Children and Cross-Reactivity with Almond, Hazelnut and Pistachio
Bibliographic record
Abstract
Peanut allergic individuals can be both co-sensitized and co-allergic to peanut and tree nuts. At the moment, standard diagnostic approaches do not always allow differentiation between clinically relevant sensitization and nonsignificant cross-reactions, and the responsibility of each allergen remains unclear. The objective of this study was therefore to determine a peanut sensitization profile in a cohort of Canadian peanut allergic children and assess the immunoglobulin E (IgE) molecular cross-reactivity between peanut, almond, hazelnut and pistachio. The specific IgE (sIgE) levels of each patient serum were determined by ImmunoCAP, indirect ELISA and immunoblot to examine their sIgE-binding levels and profiles to peanut proteins. Reciprocal inhibition ELISA and immunoblotting were used to study sIgE cross-reactions between peanut and the selected tree nuts using an adjusted and representative serum pool of the nine allergic patients. The results showed that the prepared peanut and tree nut protein extracts allowed for the detection of the majority of peanut and selected tree nut known allergens. The reciprocal inhibition ELISA experiments showed limited sIgE cross-reactivities between peanut and the studied tree nuts, with peanut being most likely the sensitizing allergen and tree nuts the cross-reactive ones. In the case of hazelnut and pistachio, a coexisting primary sensitization to hazelnut and pistachio was also demonstrated in the serum pool. Reciprocal inhibition immunoblotting further revealed that storage proteins (2S albumin, 7S vicilin and 11S legumin) could possibly account for the observed IgE-cross-reactions between peanut and the studied tree nuts in this cohort of allergic individuals. It also demonstrated the importance of conformational epitopes in the exhibited cross-reactions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".