Co‐expression of <scp>HLA</scp>‐<scp>B</scp>7 and <scp>HLA</scp>‐<scp>B</scp>27 alleles is associated with <scp>B</scp>7‐restricted immunodominant responses following influenza infection
Bibliographic record
Abstract
It is recognized that host response following viral infection is characterized by immunodominance, but deciphering the different factors contributing to immunodominance has proved a challenge due to concurrent expression of multiple MHC class I alleles. To address this, we generated H2-K(-/-)/D(-/-) double-knockout transgenic mice expressing either one or two human MHC-I alleles. We hypothesized that co-expression of different allele combinations figures critically in immunodominance and examined this in influenza-infected, double Tg MHC-I mice. In A2/B7 or A2/B27 mice, using ELISpot assays with the A2-restricted matrix I.58-66, the B7-restricted NP418-426 or the B27-restricted NP383-391 influenza A (flu) epitopes, we observed the expected recognition of both peptides for both alleles. In contrast, in flu-infected B7/B27 mice, a significantly reduced level of B27/NP383-restricted CTL response was detected while there was no change in the B7/NP418-restricted CTL response. Flu-specific tetramer studies revealed a partial deletion of Vβ8.1(+) NP383/B27-restricted CD8(+) T cells, and a diminished Vβ12(+) CD8(+) T-cell expansion in B7/B27 Tg mice. Using HLA Tg chimeric mice, we confirmed these findings. These findings shed light on the immune consequences of co-dominant expression of MHC-I alleles for host immune response to pathogens.
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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) | 0.001 | 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".