Nucleoside-modified mRNA vaccines induce potent T follicular helper and germinal center B cell responses
Bibliographic record
Abstract
T follicular helper (Tfh) cells are required to develop germinal center (GC) responses and drive immunoglobulin class switch, affinity maturation, and long-term B cell memory. In this study, we characterize a recently developed vaccine platform, nucleoside-modified, purified mRNA encapsulated in lipid nanoparticles (mRNA-LNPs), that induces high levels of Tfh and GC B cells. Intradermal vaccination with nucleoside-modified mRNA-LNPs encoding various viral surface antigens elicited polyfunctional, antigen-specific, CD4+ T cell responses and potent neutralizing antibody responses in mice and nonhuman primates. Importantly, the strong antigen-specific Tfh cell response and high numbers of GC B cells and plasma cells were associated with long-lived and high-affinity neutralizing antibodies and durable protection. Comparative studies demonstrated that nucleoside-modified mRNA-LNP vaccines outperformed adjuvanted protein and inactivated virus vaccines and pathogen infection. The incorporation of noninflammatory, modified nucleosides in the mRNA is required for the production of large amounts of antigen and for robust immune responses.
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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) | 0.001 | 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".