A Neonatal Swine Model of Allergy Induced by the Major Food Allergen Chicken Ovomucoid (Gal d 1)
Bibliographic record
Abstract
BACKGROUND: Food allergy is a serious health problem for which a validated outbred large animal model would be useful in comparative investigations of immunopathogenesis and treatment and in testing hypotheses relevant to complex host-environmental interactions in predisposition to and expression of food allergy. OBJECTIVE: To establish a neonatal swine model of IgE-mediated allergy to the egg protein ovomucoid (Ovm) that may mimic human allergy. METHODS: In order to induce Ovm sensitivity, piglets at days 14, 21 and 35 of age were sensitized by intraperitoneal injection of 100 microg of crude Ovm and cholera toxin (50, 25 or 10 microg). Controls received 50 microg of cholera toxin in phosphate-buffered saline. The animals were challenged orally on day 46 with a mixture of egg white and yoghurt. Outcomes were reported as direct skin tests, clinical signs, IgG-related antibody and passive cutaneous anaphylaxis. RESULTS: Sensitized pigs developed immediate wheal and flare reactions, and after oral challenge, sensitized but not control animals displayed signs of allergic hypersensitivity. Serum IgG-related, Ovm-specific antibodies were detected only in the sensitized pigs and IgE-mediated antibody response to Ovm was confirmed by positive passive cutaneous anaphylaxis reactions induced by sera of sensitized but not by heat-treated sera from Ovm-sensitized pigs or sera of unsensitized control pigs. CONCLUSION: The present results confirm induction of Ovm-specific allergy in pigs and provide opportunity to investigate allergic predisposition and immunopathogenesis of IgE-induced Ovm allergy using outbred neonatal swine. This may better simulate allergic disease in humans and allow investigation of candidate prophylactic and therapeutic approaches.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".