Antiretroviral Drug Resistance Mutations Sustain or Enhance CTL Recognition of Common HIV-1 Pol Epitopes
Bibliographic record
Abstract
Antiretroviral drug resistance and escape from CTL are major obstacles to effective control of HIV replication. To investigate the possibility of combining drug and immune-based selective pressures against HIV, we studied the effects of antiretroviral drug resistance mutations on CTL recognition of five HIV-1 Pol epitopes presented by common HLA molecules. We found that these common drug resistance mutations sustain or even enhance the antigenicity and immunogenicity of HIV-1 Pol CTL epitopes. Variable patterns of cross-reactive and selective recognition of wild-type and corresponding variant epitopes demonstrate a relatively diverse population of CD8(+) T cells reactive against these epitopes. Variant peptides with multiple drug resistance mutations still sustained CTL recognition, and some HIV-infected individuals demonstrated strong CD8(+) T cell responses against multiple CTL epitopes incorporating drug resistance mutations. Selective reactivity against variant peptides with drug resistance mutations reflected ongoing or previous exposure to the indicated drug, but was not dependent upon the predominance of the mutated sequence in endogenous virus. The frequency and diversity of CTL reactivity against the variant peptides incorporating drug resistance mutations and the ability of these peptides to activate and expand CTL precursors in vitro indicate a significant functional interface between the immune system and antiretroviral therapy. Thus, drug-resistant variants of HIV are susceptible to immune selective pressure that could be applied to combat transmission or emergence of antiretroviral drug-resistant HIV strains and to enhance the immune response against HIV.
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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) | 0.001 | 0.000 |
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".