Bibliographic record
Abstract
PURPOSE OF REVIEW: Allergic reactions, including severe local and systemic reactions to mosquito bites, are immunological in nature, and involve immunoglobulin E, immunoglobulin G, and T-lymphocyte-mediated hypersensitivities in response to allergens in mosquito saliva. Naturally acquired desensitization to mosquito saliva may occur during childhood or during long-term exposure to mosquitoes. Due to the lack of availability of mosquito salivary preparations for use in skin tests and in-vitro tests, allergic reactions to mosquito bites are under diagnosed and under treated. RECENT FINDINGS: Recombinant saliva allergens with biological activity are being developed. Recombinant Aedes aegypti salivary allergen rAed a 2 has been expressed, purified, characterized and used in in-vitro diagnosis of mosquito allergy. Mosquito saliva-induced non-immunoglobulin E-mediated skin mast cell degranulation was found to induce macrophage-inflammatory protein 2 in the skin and interleukin-10 in draining lymph nodes. SUMMARY: In this review, we discuss the allergic reactions to mosquito salivary allergens, the immune mechanisms involved, natural desensitization and immunotherapy with mosquito extracts, characteristics of salivary allergens and their recombinant forms, and prevention and treatment of allergic reactions to mosquito bites. Eventually, recombinant salivary allergens will significantly improve the diagnosis of mosquito allergy, and will also improve specific immunotherapy for patients with systemic reactions to mosquito bites.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".