Programmed cell death-1 contributes to the establishment and maintenance of HIV-1 latency
Bibliographic record
Abstract
OBJECTIVE: In HIV-infected individuals on antiretroviral therapy (ART), latent HIV is enriched in CD4 T cells expressing immune checkpoint molecules, in particular programmed cell death-1 (PD-1). We therefore assessed the effect of blocking PD-1 on latency, both in vitro and in vivo. METHODS: HIV latency was established in vitro following coculture of resting CD4+ T cells with myeloid dendritic cells. Expression of PD-1 was quantified by flow cytometry, and latency assessed in sorted PD-1high and PD-1low/-nonproliferating CD4+ memory T cells. The role of PD-1 in the establishment of latency was determined by adding anti-PD-1 (pembrolizumab) to cocultures before and after infection. In addition, a single infusion of anti-PD-1 (nivolumab) was administered to an HIV-infected individual on ART with metastatic melanoma, and cell-associated HIV DNA and RNA, and plasma HIV RNA were quantified. RESULTS: HIV latency was significantly enriched in PD-1high compared with PD-1low/- nonproliferating, CD4 memory T cells. Sorting for an additional immune checkpoint molecule, T-cell immunoglobulin domain and mucin domain-3, in combination with PD-1, further enriched for latency. Blocking PD-1 prior to HIV infection, in vitro, resulted in a modest but significant decrease in latently infected cells in all donors (n = 6). The administration of anti-PD-1 to an HIV-infected individual on ART resulted in a significant increase in cell-associated HIV RNA in CD4 T cells, without significant changes in HIV DNA or plasma HIV RNA, consistent with reversal of HIV latency. CONCLUSION: PD-1 contributes to the establishment and maintenance of HIV latency and should be explored as a target, in combination with other immune checkpoint molecules, to reverse latency.
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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 | 0.001 |
| 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".