Novel HLA-B7-restricted human metapneumovirus epitopes enhance viral clearance in mice and are recognized by human CD8+ T cells
Bibliographic record
Abstract
Abstract Human metapneumovirus (HMPV) is a leading cause of acute lower respiratory tract illness in children and adults. Repeated infections are common and can be severe in young, elderly, and immunocompromised persons due to short-lived protective humoral immunity. In turn, few protective T cell epitopes have been identified in humans. Thus, we infected transgenic mice expressing the common human HLA MHC-I allele B*07:02 (HLA-B7) with HMPV and screened a robust library of overlapping and computationally predicted HLA-B7 binding peptides. Six HLA-B7-restricted CD8+ T cell epitopes were identified using ELISPOT screening in the F, M, and N proteins, with M195–203 (M195) eliciting the strongest responses. MHC-tetramer flow cytometric staining confirmed HLA-B7 epitope-specific CD8+ T cells migrated to lungs and spleen of HMPV-immune mice. Immunization with pooled HLA-B7-restricted peptides reduced viral titer and protected mice from virulent infection. Finally, we confirmed that CD8+ T cells from HLA-B7 positive humans also recognize the identified epitopes. These results enable identification of HMPV-specific CD8+ T cells in humans and help to inform future HMPV vaccine design.
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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 | 0.001 |
| 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".