CpG oligodeoxynucleotide vaccination suppresses IgE induction but may fail to down-regulate ongoing IgE responses in mice
Bibliographic record
Abstract
Antigen-specific IgE plays an important role in the pathogenesis of allergic disorders. Immunostimulatory CpG motifs (CpG) in bacterial DNA or synthesized oligodeoxynucleotides (ODN) are gaining recognition as potential immunomodulators for switching on protectiveT(h)1-mediated immunity and preventing or potentially inhibiting T(h)2-dependent allergic responses. To date, allergic models used in CpG ODN studies have been established by immunization of mice with allergen in the presence of adjuvant. This, in addition to failure to assess specific IgE production in most of the studies, has limited understanding of the role of CpG ODN vaccination in allergic responses. Here, we examine the effects of synthesized CpG ODN on both developing and ongoing IgE responses in mice sensitized using a recombinant mosquito salivary antigen (rAed a 2) without adjuvant. Pretreatment of mice with CpG ODN mixed with rAed a 2 successfully inhibited subsequent induction of serum rAed a 2-specific IgE (but not IgG1) and antigen-induced IL-4 and IL-5 production in spleen cells. This was associated with an increase of serum IgG2a and IL-12, and increased IFN-gamma and IL-12 production by spleen cells. In this model, however, co-administration of CpG ODN with rAed a 2 to presensitized mice failed to down-regulate ongoing IgE responses despite significant up-regulation of serum IL-12 and specific IgG2a. Strikingly, a transient skin delayed-type hypersensitivity reaction occurred in CpG ODN-treated mice. These observations provide a new insight into the potential therapeutic application of CpG ODN to allergic disorders.
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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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".