Long-term immune responses to AS03-adjuvanted, low antigen dose influenza vaccines in BALB/c mice (P4299)
Bibliographic record
Abstract
Abstract During the 2009 pandemic influenza outbreak, a vaccine formulated with the oil-in-water adjuvant AS03 and 25% of the usual antigen dose was selected for administration to Canadians. Since the long-term (LT) immune response to this vaccine remains unclear, our objective is to study AS03-adjuvanted low antigen dose influenza vaccines in mice with a focus on LT immunity. We hypothesize that LT memory following unadjuvanted full-dose vaccine will be superior to adjuvanted low-dose vaccination. Mice received 2 IM injections of influenza A/Uruguay H3N2 split vaccine formulated with 3µg antigen only or low antigen dose with AS03 adjuvant. At 3 weeks post-boost, serum hemagglutination inhibition (HAI) titers were: 276 (3µg unadjuvanted); 1365 (0.03µg+AS03); and 1681 (0.003µg+AS03). Lower antigen doses (0.00003-0.0003µg) with AS03 failed to consistently produce detectable antibodies. LT studies with these same formulations (3µg, 0.03µg+AS03, 0.003µg+AS03) are ongoing for up to 18 weeks post-boost; we are examining spleen and bone marrow cells (eg: ELISpots, cytokine profiles, B cell subsets by flow cytometry). At 1, 3 and 6 weeks post-boost, splenocytes of mice immunized with antigen alone produced higher levels of IL-4 and IL-10 than mice immunized with adjuvanted low-dose vaccines. Conversely, splenocytes from the adjuvanted low-dose groups produced higher levels of IL-2 than those from mice immunized with antigen alone. These differences in LT immunity may affect vaccine efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 0.002 |
| 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 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".