HIV-1 Viremia Prevents the Establishment of Interleukin 2–producing HIV-specific Memory CD4+ T Cells Endowed with Proliferative Capacity
Bibliographic record
Abstract
CD4+ T cell responses are associated with disease control in chronic viral infections. We analyzed human immunodeficiency virus (HIV)-specific responses in ten aviremic and eight viremic patients treated during primary HIV-1 infection and for up to 6 yr thereafter. Using a highly sensitive 5-(and-6)-carboxyfluorescein diacetate-succinimidyl ester-based proliferation assay, we observed that proliferative Gag and Nef peptide-specific CD4+ T cell responses were 30-fold higher in the aviremic patients. Two subsets of HIV-specific memory CD4+ T cells were identified in aviremic patients, CD45RA- CCR7+ central memory cells (Tcm) producing exclusively interleukin (IL)-2, and CD45RA- CCR7- effector memory cells (Tem) that produced both IL-2 and interferon (IFN)-gamma. In contrast, in viremic, therapy-failing patients, we found significant frequencies of Tem that unexpectedly produced exclusively IFN-gamma. Longitudinal analysis of HIV epitope-specific CD4+ T cells revealed that only cells that had the capacity to produce IL-2 persisted as long-term memory cells. In viremic patients the presence of IFN-gamma-producing cells was restricted to periods of elevated viremia. These findings suggest that long-term CD4+ T cell memory depends on IL-2-producing CD4+ T cells and that IFN-gamma only-producing cells are short lived. Our data favor a model whereby competent HIV-specific Tcm continuously arise in small numbers but under persistent antigenemia are rapidly induced to differentiate into IFN-gamma only-producing cells that lack self-renewal capacity.
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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 | 0.001 |
| 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".