Cross-competition shapes CD8+ T cell hierarchies and differentiation after RNA vaccination
Bibliographic record
Abstract
Short Summary Immunodominance is a universal feature of adaptive immunity that constrains T cell expansion, clonal diversity and breadth resulting in a narrowly focused T cell response. While observed across diverse priming settings and vaccine platforms, the influence of immunodominance on T cell phenotype remains unclear. Using an mRNA lipoplex vaccine encoding multiple antigens to study how immunodominance influences CD8+ T cell fate, we found that dominant CD8+ T cell responses alter the magnitude and phenotype of subdominant responses through peptide-MHC-I stability-mediated T cell cross-competition. Dominant CD8+ T cell responses preferentially acquired markers associated with terminal differentiation and cytotoxic function, while sub-dominant responses adopted memory-precursor and stem-like features. Removal of dominant responses allowed increased expansion of sub-dominant T cell responses and adoption of terminally differentiated effector phenotypes. These findings reveal that immunodominance dynamically shapes the magnitude, breadth and differentiation of CD8+ T cell responses and highlights opportunities to fine-tune T cell responses for therapeutic vaccination.
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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) | 0.002 | 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".