Thermostable Allergens in Canned Fish: Evaluating Risks for Fish Allergy
Bibliographic record
Abstract
Major fish allergens can withstand extensive cooking. Most children with bony fish allergy strictly avoid fish, but some may tolerate canned fish. This study reviewed the safety of children with fish allergy consuming canned fish.Children (n = 53; ages 1–18 years) with clinically confirmed fish allergy and 4 controls were recruited at the Children’s Hospital at Westmead, Australia.The content and integrity of parvalbumin in 17 canned fish products (salmon n = 8; tuna n = 7; sardine n = 2) were examined by allergen-specific antibodies (sIgE). The sIgE binding of 5 products was evaluated in children with fish allergy, and sIgE-binding proteins were identified by mass spectrometry.Compared with cooked fish, canned fish showed reduced parvalbumin content and sIgE binding. Heat-stable parvalbumin, tropomyosin, and collagen allergens maintained their sIgE-binding capacity. Of the 53 children, 13 passed oral challenges to cooked salmon or tuna; 66% had sIgE binding to canned fish proteins: 51% to sardine, 43% to 45% to salmon, and 8% to 17% to tuna. Parvalbumin demonstrated greatest sIgE binding in sardine and salmon. Tropomyosin was relevant for tuna sIgE binding.Canned fish products are not safe for all children with bony fish allergy. Their introduction should be carefully considered using sIgE to heat-stable fish allergens and monitored oral food challenges as appropriate.This study highlights the variability of bony fish proteins present in canned fish, the distinction between sIgE content and binding capacity, and evaluation of new proteins that may, in the future, become registered allergens. The findings also underscore the importance of careful clinical evaluation by allergy testing and monitored oral challenge as indicated, before recommending introduction of canned fish into the diet of children with bony fish allergy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".