Combination of Innate Immune Modulators as Vaccine Adjuvants in Mice
Bibliographic record
Abstract
The development of new, effective, and safe vaccines necessarily requires the identification of new adjuvant(s) to enhance the potency and longevity of antigen-specific immune responses. In the present study, we compare the antibody-mediated and cell-mediated immune (CMI) responses within groups of mice vaccinated subcutaneously with ovalbumin (OVA; as an experimental antigen) plus polyphosphazene (an innate immune modulator), Polyinosinic:polycytidylic acid (poly-I:C; (an RNA mimetic) and glycopeptide ARC5 (which is a Toll-like receptor (TLR), TLR2 ligand and PAM3CSK4 analogue) formulated together in a soluble vaccine. We also investigated the effect of a polymeric nanoparticle of ARC4 and ARC7 (which are a novel muramyl dipeptide analogue and a monophosophoryl lipid A (MPLA) analogue, respectively) plus OVA +/- ARC5 as a subcutaneous vaccine in mice. OVA+ARC4/ARC7 nanoparticle +/- ARC5 triggered a robust and balanced Th1/Th2-type humoral response with significant anti-OVA IgA in serum, and significant interferon (IFN)-γ and interleukin (IL)-17 production in splenocytes after 35 days relative to the controls. Formulation of OVA with ARC4/ARC7 nanoparticles should be investigated for inducing protective immunity against infectious pathogens in mice and other species.
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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 | 0.001 | 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".