Enhancing Human Immunodeficiency Virus-Specific CD8+ T Cell Responses with Heteroclitic Peptides
Bibliographic record
Abstract
Human immunodeficiency virus (HIV)-specific CD8(+) T cells play a critical role in containing HIV replication and delaying disease progression. However, HIV-specific CD8(+) T cells become progressively more "exhausted" as chronic HIV infection proceeds. Symptoms of T cell exhaustion range from expression of inhibitory receptors and selective loss of cytokine production capacity through reduced proliferative potential, impaired differentiation into effector cells and increased susceptibility to apoptosis. While effective combination antiretroviral therapy (cART) durably reduces HIV viremia to undetectable levels, this alone does not restore the full pluripotency of HIV-specific CD8(+) T cells. In a number of studies, a subset of peptide epitope variants categorized as heteroclitic, restimulated more potent cellular immune responses in vitro than did the native, immunizing peptides themselves. This property of heteroclitic peptides has been exploited in experimental cancer and chronic viral infection models to promote clearance of transformed cells and persistent viruses. In this review, we consider the possibility that heteroclitic peptides could improve the efficacy of therapeutic vaccines as part of HIV immunotherapy or eradication strategies. We review literature on heteroclitic peptides and illustrate their potential to beneficially modulate the nature of HIV-specific T cell responses toward those found in the small minority of HIV-infected, aviremic cART-naïve persons termed elite controllers or long-term non-progressors. Our review suggests that the efficacy of HIV vaccines could be improved by identification, testing, and incorporation of heteroclitic variants of native HIV peptide epitopes.
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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 | 0.001 | 0.001 |
| 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".