Adjuvanted influenza vaccines in young and aged BALB/c mice (166.25)
Bibliographic record
Abstract
Abstract Although the available influenza vaccines are generally safe, they are far from ideal. They have reduced efficacy in the most at risk groups: the very young and the elderly. To address such concerns, the vaccine industry is increasingly turning its attention to the use of adjuvants to enhance the immune responses generated by these vaccines. During the 2009 pandemic H1N1 influenza outbreak, an adjuvanted influenza vaccine was selected for administration to Canadians; it was formulated with the oil-in-water adjuvant AS03 and consisted of 1/4 the usual antigen dose of vaccine. This study investigated the immune responses generated following immunization with adjuvanted influenza vaccines in aged and young mice. We tested two ages of BALB/c mice (2 months, 1.4 years), two doses of Influenza A/Uruguay H3N2 split vaccine (0.75ug, 3ug), and two adjuvants (alhydrogel, AS03). The use of an adjuvant increased serum HAI titers compared to vaccination with unadjuvanted vaccine. We found no significant difference in using the high dose of vaccine antigen with both adjuvants. At the low dose of vaccine, the AS03 adjuvant gave significantly higher HAI titers in both age groups. Finally, aged mice given a low dose of the AS03-adjuvanted split vaccine showed significantly lower HAI titers than young mice. We are identifying additional differences between the immune responses of young and aged mice with an overall goal to be able to design more effective vaccines, especially for the elderly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".