A respiratory syncytial virus (RSV) F protein nanoparticle vaccine focuses antibody responses to a conserved neutralization domain
Bibliographic record
Abstract
A stabilized form of the respiratory syncytial virus (RSV) fusion (F) protein has been explored as a vaccine to prevent viral infection because it presents several potent neutralizing epitopes. Here, we used a structure-based rational design to optimize antigen presentation and focus antibody (Ab) responses to key epitopes on the pre-fusion (pre-F) protein. This protein was fused to ferritin nanoparticles (pre-F-NP) and modified with glycans to mask nonneutralizing or poorly neutralizing epitopes to further focus the Ab response. The multimeric pre-F-NP elicited durable pre-F-specific Abs in nonhuman primates (NHPs) after >150 days and elicited potent neutralizing Ab (NAb) responses in mice and NHPs in vivo, as well as in human cells evaluated in the in vitro MIMIC system. This optimized pre-F-NP stimulated a more potent Ab response than a representative pre-F trimer, DS-Cav1. Collectively, this pre-F vaccine increased the generation of NAbs targeting the desired pre-F conformation, an attribute that facilitates the development of an effective RSV vaccine.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| 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 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".