T-Cell Receptor-Mediated Anergy of a Human Immunodeficiency Virus (HIV) gp120-Specific CD4<sup>+</sup>Cytotoxic T-Cell Clone, Induced by a Natural HIV Type 1 Variant Peptide
Bibliographic record
Abstract
Human immunodeficiency virus type 1 (HIV-1) infection triggers a cytotoxic T-lymphocyte (CTL) response mediated by CD8(+) and perhaps CD4(+) CTLs. The mechanisms by which HIV-1 escapes from this CTL response are only beginning to be understood. However, it is already clear that the extreme genetic variability of the virus is a major contributing factor. Because of the well-known ability of altered peptide ligands (APL) to induce a T-cell receptor (TCR)-mediated anergic state in CD4(+) helper T cells, we investigated the effects of HIV-1 sequence variations on the proliferation and cytotoxic activation of a human CD4(+) CTL clone (Een217) specific for an epitope composed of amino acids 410 to 429 of HIV-1 gp120. We report that a natural variant of this epitope induced a functional anergic state rendering the T cells unable to respond to their antigenic ligand and preventing the proliferation and cytotoxic activation normally induced by the original antigenic peptide. Furthermore, the stimulation of Een217 cells with this APL generated altered TCR-proximal signaling events that have been associated with the induction of T-cell anergy in CD4(+) T cells. Importantly, the APL-induced anergic state of the Een217 T cells could be prevented by the addition of interleukin 2, which restored their ability to respond to their nominal antigen. Our data therefore suggest that HIV-1 variants can induce a state of anergy in HIV-specific CD4(+) CTLs. Such a mechanism may allow a viral variant to not only escape the CTL response but also facilitate the persistence of other viral strains that may otherwise be recognized and eliminated by HIV-specific CTLs.
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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".