Ara h 1 Peptide Immunotherapy in a Mouse Model of Peanut-Induced Anaphylaxis
Bibliographic record
Abstract
Background: Despite the clinical severity and rising prevalence of peanut allergy, there is a marked absence of widespread, practical treatments available for peanut-allergic patients. Peptide immunotherapy, a disease-modifying treatment that uses short peptides recognized by T cells, has been shown to reduce allergic symptoms of allergic rhinoconjunctivitis. This project investigated the ability of peptides from the major peanut allergen Ara h 1 to protect against peanut-induced anaphylaxis and induce immunomodulatory changes in a mouse model. Methods: Mice transgenic for the human leukocyte antigen DRB1*0401 were sensitized to peanut epicutaneously and treated with two intraperitoneal injections of peptides from Ara h 1. Mice were then challenged with intraperitoneal whole peanut and observed for signs of anaphylaxis. Flow cytometry was used to isolate peanut-specific CD4+ T cells labelled with Ara h 1 peptide-loaded tetramers and additional Th1, Th2, and regulatory markers. Results: Peptide-treated mice were protected from severe peanut-induced anaphylaxis. Control mice treated with a sham peptide experienced a mean maximum temperature drop of 3.2°C, while mice treated with Ara h 1 peptides experienced a drop of 1.6°C (p=0.067 vs control). Maximum clinical score was 2.5 in control mice, and 1.4 in treated mice (p=0.0097). Mean hematocrit for control mice was 52.5%, and 47% for treated mice (p=0.013). PD-1+CD4+ T cells were significantly increased in the mesenteric lymph nodes (p = 2.28e-0.05) and spleens (p = 0.014) of peptide-treated mice. MIP1-a+CD4+ T cells were significantly decreased in the peritoneal lavage (p = 0.008). Conclusion: Ara h 1 peptide immunotherapy protected against severe peanut-induced anaphylaxis in a mouse model. Peptide-treated mice experienced significantly reduced drops in core body temperature, clinical signs of allergic reaction, and hemoconcentration. Clinical protection was associated with decreased expression of the pro-inflammatory chemokine macrophage 1-a and increased expression of the surface marker programmed cell death protein 1.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".