Protective effects of combined Mycobacterium bovis BCG and interleukin-12 vaccination on airway inflammation in a murine model of allergic asthma
Bibliographic record
Abstract
PURPOSE: Allergic asthma is characterized by chronic airway inflammation and airway hyperresponsiveness driven by allergen-specific T helper (Th)2 cells. Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccination has been documented to suppress Th2 responses and allergic airway inflammation in animal models. Since interleukin (IL)-12 is capable of inhibiting Th2 responses, we sought to investigate whether IL-12 could function as an adjuvant to increase the efficacy of BCG vaccination against allergic asthma. METHODS: BALB/c neonatal mice (24 mice, 48-72 h old) were randomly divided into 3 subgroups (n = 8 for each group) to be immunized with PBS (control) or BCG with or without DNA plasmid-expressing IL-12. All of the mice were then sensitized and provoked with ovalbumin (OVA) to establish a model of allergic asthma. RESULTS: Mice vaccinated with BCG alone showed a significant reduction in airway inflammation, percentage of eosinophils in bronchoalveolar lavage (BAL) fluid, and serum OVA-specific immunoglobulin E (IgE) levels in comparison with control animals. The suppressive effects of BCG were substantially augmented by the combination with IL-12. Furthermore, a decreased IL-4 and increased interferon-gamma (IFN-gamma) production in BAL fluid were observed in animals inoculated with BCG alone or with IL-12 relative to control animals. CONCLUSION: Our data indicate that the combined vaccination with BCG and IL-12 yields a favorable outcome in prevention of experimental allergic airway inflammation, which is likely mediated through triggering a shift from a Th2 response to a Th1 response.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".