Enhanced T helper 1 (Th1) responses with Fluzone® adjuvanted with a synthetic TLR4 agonist in an emulsion (45.15)
Bibliographic record
Abstract
Abstract Impairments in anti-influenza Th1 responses are associated with the significantly greater risk of influenza related mortality in the elderly population. Developing appropriate adjuvants for seasonal influenza vaccines could therefore improve protection against influenza in the elderly. In this study we compare the activity of three different adjuvants, an oil-in-water emulsion and a synthetic lipid A adjuvant formulated with or without an emulsion, to enhance the immunogenicity of the Fluzone influenza vaccine. Fluzone combined with lipid A plus an emulsion was the most effective vaccine tested in mice, which induced greater vaccine-specific IgG2a and IgG titers, enhanced HI titers and the production of Th1-mediated cytokine responses (IFN-γ and IL-2) to each of the Fluzone components. In contrast, while the Fluzone vaccine plus the emulsion induced good antibody responses and HI titers to all of the vaccine components following a boost, a Th2-mediated cytokine response (IL-5) and IL-10 was induced. We demonstrate that in addition to antibody responses, cytokine responses may also be needed for evaluation and characterization of new adjuvants formulations for influenza vaccines. This work was supported in part by Grant #42387 from the Bill & Melinda Gates Foundation
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".