Oral immunotherapy with the ingestion of house dust mite extract in a murine model of allergic asthma
Bibliographic record
Abstract
BACKGROUND: Allergen-specific immunotherapy (ASIT) has the potential to modify allergic diseases, and it is also considered a potential therapy for allergic asthma. House dust mite (HDM) allergens, a common source of airborne allergen in human diseases, have been developed as an immunotherapy for patients with allergic asthma via the subcutaneous and sublingual routes. Oral immunotherapy with repeated allergen ingestion is emerging as another potential modality of ASIT. The aim of this study was to evaluate the therapeutic efficacy of the oral ingestion of HDM extracts in a murine model of allergic asthma. METHODS: on day 1 and day 8. Then, the mice received challenge to induce airway inflammation by intratracheal instillation of HDM extracts on days 29-31. The treatment group received immunotherapy with oral HDM extracts ingestion before the challenge. All the mice were sacrificed on day 32 for bronchoalveolar inflammatory cytokines, mediastinal lymph node T cells, lung histology, and serum HDM-specific immunoglobulins analyses. RESULTS: Upon HDM sensitization and following challenge, a robust Th2 cell response and eosinophilic airway inflammation were observed in mice of the positive control group. The mice treated with HDM extracts ingestion had decreased eosinophilic airway inflammation, suppressed HDM-specific Th2 cell responses in the mediastinal lymph nodes, and attenuated serum HDM-specific IgE levels. CONCLUSIONS: Oral immunotherapy with HDM extracts ingestion was demonstrated to have a partial therapeutic effect in the murine model of allergic asthma. This study may serve as the basis for the further development of oral immunotherapy with HDM extracts in allergic asthma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".