The roles of CD4+ T cell help, sex, and dose in the induction of protective CD8+ T cells against a lethal poxvirus by mRNA-LNP vaccines
Bibliographic record
Abstract
The role of CD4+ T cells in the induction of protective CD8+ T cells by mRNA lipid nanoparticle (LNP) vaccines is unknown. We used B6 or Tlr9−/− mice depleted or not of CD4+ T cells and LNP vaccines loaded with mRNAs encoding the ectromelia virus (ECTV) MHC class I H-2 Kb-restricted immunodominant CD8+ T cell epitope TSYKFESV (TSYKFESV mRNA-LNPs) or the ECTV EVM158 protein, which contains TSYKFESV (EVM-158 mRNA-LNPs). Following prime and boost with 10 μg of either vaccine, Kb-TSYKFESV-specific CD8+ T cells fully protected male and female mice from ECTV at 29 (both mRNA-LNPs) or 90 days (EVM158 mRNA-LNPs) post boost (dpb) independently of CD4+ T cells. However, at 29 dpb with 1 μg mRNA-LNPs, males had lower frequencies of Kb-TSYKFESV-specific CD8+ T cells and were much less well protected than females from ECTV, also independently of CD4+ T cells. At 90 dpb with 1 μg EVM158 mRNA-LNPs, the frequencies of Kb-TSYKFESV-specific CD8+ T cells in males and females were similar, and both were similarly partially protected from ECTV, independently of CD4+ T cells. Therefore, at optimal or suboptimal doses of mRNA-LNP vaccines, CD4+ T cell help is unnecessary to induce protective anti-poxvirus CD8+ T cells specific to a dominant epitope. At suboptimal doses, protection of males requires more time to develop.
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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 | 0.001 | 0.001 |
| 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".