HIV-1 Epitope-Specific CD8+ T Cell Responses Strongly Associated with Delayed Disease Progression Cross-Recognize Epitope Variants Efficiently
Bibliographic record
Abstract
The ability of HIV-1-specific CD8(+) T cell responses to recognize epitope variants resulting from viral sequence variation in vivo may affect the ease with which HIV-1 can escape T cell control and impact on the rate of disease progression in HIV-1-infected humans. Here, we studied the functional cross-reactivity of CD8 responses to HIV-1 epitopes restricted by HLA class I alleles associated with differential prognosis of infection. We show that the epitope-specific responses exhibiting the most efficient cross-recognition of amino acid-substituted variants were those strongly associated with delayed progression to disease. Not all epitopes restricted by the same HLA class I allele showed similar variant cross-recognition efficiency, consistent with the hypothesis that the reported associations between particular HLA class I alleles and rate of disease progression may be due to the quality of responses to certain "critical" epitopes. Irrespective of their efficiency of functional cross-recognition, CD8(+) T cells of all HIV-1 epitope specificities examined showed focused TCR usage. Furthermore, interpatient variability in variant cross-reactivity correlated well with use of different dominant TCR Vbeta families, suggesting that flexibility is not conferred by the overall clonal breadth of the response but instead by properties of the dominant TCR(s) used for epitope recognition. A better understanding of the features of T cell responses associated with long-term control of viral replication should facilitate rational vaccine design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".