GLA-SE, a Synthetic Toll-like Receptor 4 Agonist, Enhances T-Cell Responses to Influenza Vaccine in Older Adults
Bibliographic record
Abstract
BACKGROUND: The decline in influenza vaccine efficacy in older adults is associated with a limited ability of current split-virus vaccines (SVVs) to stimulate cytotoxic T lymphocyte (CTL) responses required for clinical protection against influenza. METHODS: The Toll-like receptor 4 agonist glucopyranosyl lipid adjuvant-stable emulsion (GLA-SE) was combined with SVV to stimulate peripheral blood mononuclear cells (PBMCs) in vitro to determine the cytokine response in dendritic cell subsets. Stimulated PBMCs were then challenged with live influenza virus to mimic the response to natural infection following vaccination, using previously identified T-cell correlates of protection. RESULTS: GLA-SE significantly increased the proportion of myeloid dendritic cells that produced tumor necrosis factor α, interleukin 6, and interleukin 12. When combined with SVV to stimulate PBMCs in vitro, this effect of GLA-SE was shown to regulate a T-helper 1 cell response upon challenge with live influenza virus; interleukin 10 production was suppressed, thus significantly increasing the interferon γ to interleukin 10 ratio and the cytolytic (granzyme B) response to influenza virus challenge, both of which have been shown to correlate with protection against influenza in older adults. CONCLUSIONS: Our findings suggest that a novel adjuvant, GLA-SE, combined with standard SVV has the potential to significantly improve vaccine-mediated protection against influenza in older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".