Pre-clinical testing of T cell responses to influenza vaccine/adjuvant combinations in older adults (132.5)
Bibliographic record
Abstract
Abstract Objective: The purpose of this experiment was to determine whether inflammatory cytokines or TLR ligands could be combined with influenza vaccine in older adult PBMC to enhance the response to live influenza virus challenge. Methods: PBMC from five older adults (>65 years old) and six young (20-38 years old) adults were obtained at six months post-vaccination and cultured for five days with split-virus vaccine (SVV) and the TLR3 ligand, poly I:C, or a cocktail of pro-inflammatory cytokines (TNF-α, IL-1, IL-6; T/1/6). Stimulated PBMC were then challenged with live influenza virus for 20 hours and supernatants and lysates prepared for assays of IL-1, IL-6, TNF-α in 5-day supernatants, and the IFN-γ:IL-10 ratio and granzyme B activity in 20-hour virus-challenged PBMC. Results: We observed an increased response to SVV in younger compared to older adults, but a dose-response relationship between poly I:C (added to a fixed dose of SVV) and the IFN-γ:IL-10 ratio and granzyme B levels improved the response in older adult PBMC. This response was associated with a dose-response increase in pro-inflammatory cytokine levels in SVV/poly I:C-stimulated PBMC. However, a cocktail of these inflammatory cytokines (T/1/6) added to the PBMC culture suppressed rather than enhanced the T cell response in older adults. Conclusion: Poly I:C combined with influenza vaccine was shown to enhance the T cell response to influenza in aged PBMC by mechanisms that cannot be replicated by the simple addition of inflammatory cytokines to the vaccine.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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".