Drug resistance mutations and the cellular immune response: a valuable synergy for the development of novel immune therapies
Bibliographic record
Abstract
PURPOSE OF REVIEW: The escape of HIV-1 is a cardinal feature of the virus and a major hindrance to the development of effective therapeutic strategies. In highly active antiretroviral therapy-treated patients, the virus is subjected to selective pressures from cellular immune response directed against the viral proteome and antiretroviral treatment targetting a few genes of the HIV-1 genome. This review will focus on the relationship between these two pressures and its potential advantage in the development of novel immune therapies. RECENT FINDINGS: Recent studies have investigated the conflicting selective forces between viral fitness and escape to immunological and therapeutic pressures in natural HIV infection and the SIV model. Simultaneous pressures driven by cytotoxic T lymphocytes and highly active antiretroviral therapy could potentially reduce viral fitness, leading to better control of the viral load. Two studies have described a potential therapeutic vaccine strategy against viral escape mutant epitopes from reverse transcriptase inhibitors. SUMMARY: The emergence of multidrug-resistant viruses is associated with enhanced T-cell-mediated immune response as a possible consequence of reduced viral fitness. Amino acid substitutions generate potential cytotoxic T-lymphocyte epitopes that may elicit new reactivities against mutated viruses. Both could significantly enhance the immune response through direct and indirect mechanisms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".