Effector activity of peanut allergens: a critical role for Ara h 2, Ara h 6, and their variants
Bibliographic record
Abstract
RATIONALE: An important property of allergens is their ability to cross-link IgE and activate mast cells and basophils. The effector activity of peanut allergens has not been well characterized. METHODS: Crude extracts of fresh peanut flour were fractionated by gel filtration. Effector function was assayed by measuring degranulation of RBL SX-38 cells sensitized with IgE from individual sera and from pools of sera of peanut-allergic donors. RESULTS: Following gel filtration, 75 +/- 7% of the applied protein and 76 +/- 16% (n=3) of the applied activity (assayed with a pool of 11 sera) were recovered in the resultant fractions. The majority (85 +/- 2%; n=3) of the recovered activity resided in a fraction with a theoretical average molecular weight of approximately 20 kDa and a range of 13-25 kDa. When all the individual fractions were recombined, the measured activity was similar to that of the original extract [140 +/- 43% when measured with a pool of serum (n=2) and 66 +/- 7% when measured with individual sera (n=4)]; when all individual fractions excluding the 20 kDa fraction were recombined, the measured activity was only 8 +/- 2% (n=2) of the original extract when assayed with the serum pool and 10 +/- 4% (n=3) when assayed with the individual sera. Two-dimensional gel electrophoresis of this biologically active fraction revealed >60 protein spots. Analysis of 50 of the most prominent spots by matrix-assisted laser-desorption ionization time-of-flight mass spectrometry and of the full mixture by automated tandem mass spectrometry coupled to online capillary liquid chromatography revealed that >97% of the protein mass consisted of Ara h 2.0101, Ara h 2.0201, Ara h 6 isoforms, and variants of these proteins. CONCLUSIONS: Ara h 2 and Ara h 6 account for the majority of the effector activity found in a crude peanut extract.
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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 | 0.001 |
| 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".