Immunologic analysis of monoclonal and immunoglobulin E antibody epitopes on natural and recombinant Amb a 1
Bibliographic record
Abstract
BACKGROUND: Amb a 1 is the major allergen from ragweed pollen and more than 90% of ragweed-allergic patients react with this protein. Although Amb a 1 was cloned and sequenced in 1991, little is known of the specificity of anti-Amb a 1 antibodies or of the immunologic properties of the recombinant allergen. OBJECTIVE: To compare binding of monoclonal antibodies (mAb) and IgE antibodies to purified natural Amb a 1 (nAmb a 1) and recombinant Amb a 1 (rAmb a 1). METHODS: Binding of a panel of anti-Amb a 1 mAb and IgE antibodies to nAmb a 1 or rAmb a 1 was compared by immunoblotting. Chimeric ELISA was used to measure specific IgE to these allergens using 89 ragweed-allergic sera from Austria, Italy, Canada and the United States. RESULTS: The 8 mAb bound to a 38 kDa Amb a 1 band in ragweed pollen extract and a subset of 5 mAb also bound to the 26 kDa chain of nAmb a 1. A two-site ELISA was developed using a mAb pair, which was approximately 10-fold more sensitive to rAmb a 1. There was a significant correlation between IgE antibody binding to nAmb a 1 and rAmb a 1 (n=89, r=0.79, P<0.001). A subset of approximately 40% of patients showed greater reactivity to nAmb a 1 than to rAmb a 1. CONCLUSIONS: The data suggest that there is less reactivity of human IgE to rAmb a 1 compared with nAmb a 1. The development of more sensitive, quantitative ELISA for Amb a 1 will require the production of new mAb especially directed against nAmb a 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 | 0.000 | 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) | 0.002 | 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".