Archaeal glycolipid adjuvanted vaccines induce strong influenza-specific immune responses through direct immunization in young and aged mice or through passive maternal immunization
Bibliographic record
Abstract
Vaccine induced responses are often weaker in those individuals most susceptible to infection, namely the very young and the elderly, highlighting the need for safe and effective vaccine adjuvants. Herein we evaluated different archaeosome formulations as an adjuvant to the H1N1 influenza hemagglutinin protein and compared immune responses (anti-HA IgG and hemagglutination inhibition assay titers) as well as protection to an influenza A virus (strainA/PuertoRico/8/1934H1N1)homologous challenge to those generated using a squalene-based oil-in-water nano-emulsion, AddaVax™ in a murine model. The impact of age (young adult vs aged) on vaccine induced immune responses as well as the protection in pups due to the transfer of maternal antibodies was measured. Overall, we show that archaeal lipid based adjuvants can induce potent anti-HA responses in young and aged mice that can also be passed from vaccinated mothers to pups. Furthermore, young and aged mice immunized with archaeal lipid adjuvants as well as pups from immunized mothers were protected from challenge with influenza. In addition, we show that a simple admixed archaeosome formulation composed of a single sulfated glycolipid namely sulfated lactosylarchaeol (SLA; 6'-sulfate-β-D-Galp-(1,4)-β-D-Glcp-(1,1)-archaeol) can give equal or better protection compared to AddaVax™ or the traditional antigen-encapsulated archaeosome formulations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".