The lipid interaction capacity of Sin a 2 and Ara h 1, major mustard and peanut allergens of the cupin superfamily, endorses allergenicity
Bibliographic record
Abstract
BACKGROUND: Sin a 2 (11S globulin) and Ara h 1 (7S globulin) are major allergens from yellow mustard seeds and peanut, respectively. The ability of these two allergens to interact with lipid components remains unknown. OBJECTIVE: To study the capacity of Sin a 2 and Ara h 1 to interact with lipid components and the potential effects of such interaction in their allergenic capacity. METHODS: Spectroscopic and SDS-PAGE binding assays of Sin a 2 and Ara h 1 with different phospholipid vesicles and gastrointestinal and endolysosomal digestions in the presence or absence of lipids were performed. The capacity of human monocyte-derived dendritic cells (hmoDCs) to capture food allergens in the presence or absence of lipids, the induced cytokine signature, and the effect of allergens and lipids to regulate TLR2-L-induced NF-kB/AP-1 activation in THP1 cells were analyzed. RESULTS: Sin a 2 and Ara h 1 bind phosphatidylglycerol (PG) acid but not phosphatidylcholine (PC) vesicles in a pH-dependent manner. The interaction of these two allergens with lipid components confers resistance to gastrointestinal digestion, reduces their uptake by hmoDCs, and enhances their stability to microsomal degradation. Mustard and peanut lipids favor a proinflammatory environment by increasing the IL-4/IL-10 ratio and IL-1β production by hmoDCs. The presence of mustard lipids and PG vesicles inhibits TLR2-L-induced NF-kB/AP-1 activation in THP1 cells. CONCLUSION: Sin a 2 and Ara h 1 interact with lipid components, which might well contribute to explain the potent allergenic capacity of these two clinically relevant allergens belonging to the cupin superfamily.
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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 | 0.000 | 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) | 0.001 | 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".