Analysis of bronchoalveolar immune cells and cytokines induced by immunization with different respiratory syncytial virus vaccines (P4395)
Bibliographic record
Abstract
Abstract Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infection and deaths in infants. Since the failure of formalin-inactivated RSV (FI-RSV) due to vaccine-enhanced pulmonary eosinophilia and pneumonia during 1960s, there is no licensed vaccine against RSV. In this study, we analyzed immune cell phenotypes and cytokines in bronchoalveolar lavage fluids (BALF) from mice immunized with FI-RSV, live RSV, or F plasmid and virus-like particles (VLP) containing RSV F and G glycoproteins (FFG VLP) at day 5 post RSV challenge. FI-RSV immunized mice showed severe eosinophilia, high levels of CD11b+ cells as well as IFN-gamma and IL-4 secreting CD4 T cells locally and systemically. Mice pre-immunized with live RSV showed no severe pulmonary eosinophilia, similar levels of IFN-gamma secreting CD4 and CD8 T cells, and low levels of IL-4 secreting cells. Mice immunized with FFG VLPs displayed no eosinophilia, relatively a low ratio of CD4/CD8 T cells secreting IFN-gamma, and no systemic cytokines. All 3 types of RSV vaccines were effective in clearing lung viral loads. Taken together, these results suggest no correlation between lung RSV clearance and inflammatory pulmonary disease, and that FFG VLP can be a promising RSV vaccine candidate conferring protection without lung disease.
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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 | 0.000 | 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 | 0.001 |
| 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".