Identification and characterization of a novel antigen from the nematode <i>Nippostrongylus brasiliensis</i> recognized by specific IgE
Bibliographic record
Abstract
Identification and characterization of IgE-inducing antigens are important for elucidating the mechanisms involved in IgE-mediated immune responses in allergic diseases and parasite infections. While many allergens have been characterized, little is known about parasite antigens inducing specific IgE following infection. In order to identify antigens from the nematode Nippostrongylus brasiliensis, we generated an IgE-producing B cell hybridoma from N. brasiliensis-infected C57BL/6 mice and constructed a cDNA phage display library from N. brasiliensis. We successfully cloned and expressed an N. brasiliensis antigen (Nb-Ag1) that showed specific binding to anti-N. brasiliensis IgE. Nb-Ag1 localized to the pharynx of adult N. brasiliensis, suggesting that Nb-Ag1 is a potential pharyngeal gland antigen. Nb-Ag1-specific IgE could be detected in the serum of N. brasiliensis-infected mice, but only for a short time and only following a challenge infection. In contrast, local administration of Nb-Ag1 during primary, secondary and tertiary infections induced Nb-Ag1-specific IgE-mediated active cutaneous anaphylaxis. Therefore, amongst the high amounts of polyclonal total IgE, low levels of parasite-specific IgE responses are induced during primary helminth infections. Here, we show that even such low levels of parasite-specific IgE are sufficient to prime mast cells in vivo and mediate degranulation.
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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".