Targeting <scp>IL</scp>‐23 by employing a p40 peptide‐based vaccine ameliorates murine allergic skin and airway inflammation
Bibliographic record
Abstract
BACKGROUND: Studies have found that the IL-23/Th17 pathway plays an important role in the pathogenesis of atopic dermatitis (AD) and severe and steroid-resistant asthma. Targeting IL-23/Th17 pathway with monoclonal antibodies (mAb) has been successful in the reduction of skin and airway inflammation in animal models. However, the mAb has a short half-life, requiring repeated administrations. For the long-term suppression of IL-23/Th17 pathway, we have previously developed an IL-23p40 peptide-based virus-like particle vaccine, which induces long-lasting autoantibodies to IL-23. OBJECTIVE: We sought to evaluate the effects of this IL-23p40 peptide-based vaccine on the down-regulation of allergic skin and airway inflammation in mice. METHODS: Mice were subcutaneously injected three times with the IL-23p40 vaccine, or the vaccine carrier protein or saline as controls. Two weeks later, mice were epicutaneously sensitized with ovalbumin four times at a 2-week interval. One week after the final sensitization, mice were nasally administrated with ovalbumin daily for 3 days. One day later, bronchoalveolar lavage fluids (BALF), sera, lung and skin tissues were obtained and analysed. RESULTS: Mice immunized with the vaccine produced high levels of IgG antibodies to IL-23, p40 and IL-12 that in vitro inhibited IL-23-dependent IL-17 production. The numbers of total cells, neutrophils, and eosinophils in BALF were significantly reduced in the vaccine group, compared with controls. The levels of IL-13, IL-5, IL-23 and, IL-17 in BALF and levels of serum ovalbumin-specific IgE, IgG1, and total IgE were also significantly decreased. Histological analysis showed less inflammation of the lung and skin tissues in the vaccine group, compared with controls. CONCLUSION AND CLINICAL RELEVANCE: Administration of an IL-23p40 peptide-based vaccine down-regulates allergic skin and airway inflammation, suggesting that this strategy may be a potential therapeutic approach in the treatment of AD and 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) | 0.000 | 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 | 0.000 | 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".