Prevention of Allergen-Specific, Th2-Biased Immune Responses In Vivo: Role of Increased IL-12 and IL-18 Responsiveness
Bibliographic record
Abstract
The factors that control development of adaptive responses to exogenous Ag remain incompletely understood. An ability to selectively direct immunity toward a specific phenotype would be of clinical benefit in numerous immunological disorders. Administration of chemically modified allergen glutaraldehyde-polymerized OVA (OA-POL) leads to >90% reductions in murine IgE and >500-fold increases in IgG2c responses that develop upon subsequent immunization with native Ag. In the present study, we examine the mechanisms underlying this reorientation of the type 2 dominant response that would normally develop. Lack of endogenous IL-12 or IFN-gamma results in markedly reduced induction of IgG2c responses following OA-POL treatment, but only IFN-gamma(-/-) mice demonstrate reduced capacity to prevent IgE induction. This indicates that while both IL-12 and IFN-gamma are critical promoters of type 1 immunity, only IFN-gamma is required to maximally inhibit development of type 2 immune responses. Compared with OVA-immunized mice, CD69(+) T cells from OA-POL-immunized mice demonstrate elevated IL-12Rbeta(2), IL-18Ralpha, and IL-18Rbeta mRNA levels, as well as increased IFN-gamma production in response to rIL-12 or rIL-18 stimulation. Collectively, these data indicate that preventing induction of type 2 immune responses is critically dependent on altered T cell responsiveness to these cytokines. The finding that targeted, Ag-specific manipulation of IL-12 and IL-18 responsiveness can be used to shape the phenotype of the dominant immune response that develops suggests that specifically targeting IL-12 and IL-18 receptor expression may offer clinical options for clinical prophylaxis or intervention.
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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".