Diagnosis of Vespa affinis venom allergy: use of immunochemical methods and a passive basophil activation test
Bibliographic record
Abstract
Abstract Background Allergy toVespa affinisvenom is common in the Asia Pacific region. Venom preparations for diagnosis are not commercially available for this species. Methods The prominent allergens inV. affinisvenom were identifiedusing immunochemical methods. Use of ImmunoCAP ofVespula vulgariscrude venom/its components and a passive basophil activation test (BAT) in the diagnosis of patients who had anaphylaxis toV. affinisvenom (n = 30) were also accessed. The IgE double-positivity rates (positive to both hornet and honeybee) in ImmunoCAP and the passive BAT were determined. Results High IgE reactivity was seen with the five allergens inV. affinisvenom; 96% (29/30) for 34 and 24 kDa, 93% (28/30) for 45 kDa and 90% (27/30) reactivity for the 100 and 80 kDa respectively. IgE cross-reactivity was low with ImmunoCAP usingV. vulgarisvenom (43%; 13/30) and Ves v1 (3%; 1/30), but relatively high with Ves v5 (73%; 22/30). All patients (100%) were positive toV. affinisvenom in passive BAT. In ImmunoCAP, a high double-positivity rate (76%; 23/30) was detected while no double-positivity was detected in passive BAT. Conclusions High IgE reactivity for five allergens ofV. affinispoints to the potential of using these allergens in component resolved diagnosis (CRD). The passive BAT has shown its importance as a promising diagnostic tool with high accuracy. It would be particularly useful in cases with doubtful double-positive results of other diagnostic tests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".