Bibliographic record
Abstract
Allergic diseases including asthma are characterized by an increase of serum IgE levels. Since IgE was discovered in 1966, it has been considered to be the most important biological target in the treatment of allergy and asthma. Indeed, recent studies reveal that IgE, through its high affinity IgE receptors (FcepsilonRI), is now considered a critical regulator of Th2 responses. This is supported by the great success of the anti-IgE monoclonal antibody (mAb) in the treatment of allergy and asthma. Nonetheless, adverse reactions such as anaphylaxis, urticaria and serum sickness have been reported with this therapy and repeated injections at extremely high costs are required to maintain effectiveness. To overcome these disadvantages, a new strategy using vaccines against IgE that may offer long-term efficacy with fewer adverse effects is being investigated. This article reviews IgE's role in allergy and asthma, currently used anti-IgE mAb omalizumab, and the advantages, types, effectiveness and development stages of vaccines against IgE. This review also discusses concerns with the vaccine strategy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".