Sublingual allergen immunotherapy: mode of action and its relationship with the safety profile
Bibliographic record
Abstract
Allergen immunotherapy reorients inappropriate immune responses in allergic patients. Sublingual allergen immunotherapy (SLIT) has been approved, notably in the European Union, as an effective alternative to subcutaneous allergen immunotherapy (SCIT) for allergic rhinitis patients. Compared with SCIT, SLIT has a better safety profile. This is possibly because oral antigen-presenting cells (mostly Langerhans and myeloid dendritic cells) exhibit a tolerogenic phenotype, despite constant exposure to danger signals from food and microbes. This reduces the induction of pro-inflammatory immune responses leading to systemic allergic reactions. Oral tissues contain relatively few mast cells and eosinophils (mostly located in submucosal areas) and, in comparison with subcutaneous tissue, are less likely to give rise to anaphylactic reactions. SLIT-associated immune responses include the induction of circulating, allergen-specific Th1 and regulatory CD4+ T cells, leading to clinical tolerance. Although 40-75% of patients receiving SLIT experience mild, transient local reactions in the oral mucosa, these primary reactions rarely necessitate dose reduction or treatment interruption. We discuss 11 published case reports of anaphylaxis (all nonfatal) diagnosed according to the World Allergy Organization criteria and relate this figure to the approximately 1 billion SLIT doses administered worldwide since 2000. Anaphylaxis risk factors associated with SCIT and/or SLIT should be characterized further.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".