rAed a 4: A New 67-kDa <b><i>Aedes aegypti</i></b> Mosquito Salivary Allergen for the Diagnosis of Mosquito Allergy
Bibliographic record
Abstract
BACKGROUND: Accurate diagnosis of mosquito allergy has been hampered by the laborious task of obtaining mosquito salivary allergens. We have previously studied 3 recombinant (r) Aedes aegypti mosquito salivary allergens: rAed a 1, rAed a 2 and rAed a 3. Here, we report the expression, purification, identification and evaluation of rAed a 4, a 67-kDa α-glucosidase. METHODS: rAed a 4 was expressed using a baculovirus/insect cell system, purified by a combination of anion- and cation-exchange chromatography, and identified by immunoblotting. A. aegypti saliva extract was prepared in our laboratory. An indirect enzyme-linked immunosorbent assay (ELISA) was developed to measure rAed a 4-specific immunoglobulin E (IgE) and IgG antibodies in sera from 13 individuals with a positive mosquito-bite test from a laboratory-reared mosquito. Sera from 18 individuals with a negative bite test served as controls. RESULTS: Purified rAed a 4 bound to the IgE in mosquito-allergic sera, as detected by ELISA and immunoblotting. The binding of rAed a 4 to IgE could be inhibited in a dose-dependent manner by the addition of an A. aegypti extract. Mosquito-allergic individuals had significantly higher mean levels of rAed a 4-specific IgE and IgG than controls. Using the mean of the controls ± 2 SD as a cut-off level, 46% of the 13 allergic individuals had a positive IgE, while none of the controls was positive (p < 0.001). CONCLUSIONS: Aed a 4 is a major allergen in mosquito saliva. Its recombinant form has the hydrolase function and can be used for the diagnosis of mosquito allergy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".