Importance of routes of exposure in the development of immune response to peanut
Notice bibliographique
Résumé
Immediate hypersensitivity reactions to food are a major health concern for Canadians due to severity of reactions they elicit and their increasing prevalence. Currently 6% of children develop food allergy. Peanut (PN) hypersensitivity is one of the major causes of food-related anaphylaxis. We tested the hypothesis that the route of initial exposure to food antigen dictates the nature of the immune response and hence the development of an allergic response/anaphylaxis vs . tolerance upon subsequent or secondary exposure. The aim of this study was to: 1) establish three independent animal models of peanut exposure via the oral, dermal and inhalational routes that will allow us to 2) investigate whether sensitization or tolerance develops following gastrointestinal, dermal or inhalational exposures, following initial exposures via the alternate route. Female Balb/c mice (8-weeks old) were sensitized to 1 mg of PN protein in combination with 5 μg cholera toxin as an adjuvant or PBS on days 0 and 14 via the oral, dermal or intranasal routes; and challenged with crude peanut extract (CPE) by oral gavage (2 mg), dermally (10 μg) or intranasally (500 μg) on days 28, 30, 32, 35, 37 and 39. Mice were assessed for allergy/anaphylaxis ( i.e. , rectal temperature at 10 minute intervals, scoring for clinical symptoms of anaphylaxis) for 40 minutes after the last allergen challenge and then euthanized for: 1) general ( e.g. , measurement of PN-specific immunoglobulins, plasma histamine and inflammatory cell infiltration into the target organ), and 2) route-specific end-points ( i.e. , measurement of wheal diameter and pulmonary function testing using the flexiVent after dermal and nasal challenge, respectively). A previously established murine model of peanut anaphylaxis was used as the positive control [ 1 ]. Data are expressed as the mean ± SEM (n = 12-16/group). Oral sensitization followed by oral challenge evoked the most clinically potent allergic reaction, as compared with dermal or nasal challenge (mean clinical scores of 1.7 ± 0.1, 1.0 ± 0.3 and 0.06 ± 0.04, respectively). To investigate peanut-specific humoral immune response we measured serum IgE and IgG subclass levels. Intragastric sensitization with peanut extract induced a significant IgE response (125.9 ± 21.7 ng/mL), whereas nasal or cutaneous priming favored elevated levels of the IgG subclasses. Higher IgG1/G2a ratios (10-25 folds within the cross sensitization/challenge groups) indicated Th2 polarization of the immune response. PN sensitization and challenge by all three routes resulted in similar increases of plasma histamine upon secondary challenge. Oral or nasal priming triggered greater inflammatory cell infiltration in the peritoneal cavity upon oral challenge. Dermal and nasal priming preferentially resulted in more severe skin inflammation as assessed by wheal diameter, compared with orally-sensitized animals. Upon inhalational challenge, orally-sensitized mice exhibited greater cellular infiltration into the airways with predominantly neutrophilic influx, whereas nasal sensitization favored mild eosinophilia in the BAL. However, PN priming via these routes and subsequent challenge did not affect methacholine responsiveness of the airways. Our observations indicate that 1) oral sensitization is the most likely to elicit a significant allergic response to peanut upon secondary challenge, dermal sensitization is less likely; nasal sensitization results in an intermediate likelihood. 2) Oral sensitization resulted in higher production of allergen-specific IgE antibodies, whereas nasal or cutaneous sensitization induced greater IgG responses; higher IgG1/G2a ratios point to Th2 biased response. 3) Initial exposure via the oral route triggered neutrophilia, while inhalational priming elicited an eosinophilic influx into the target organs. Comparison of the immune and cellular mediators of tolerance and anaphylaxis via the different routes may help to identify the causative mediator/cell population that could lead to novel therapeutic targets for intervention.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».