Proof-of-Principle for Immune Control of Global HIV-1 Reactivation In Vivo
Bibliographic record
Abstract
BACKGROUND: Emerging data relating to human immunodeficiency virus type 1 (HIV-1) cure suggest that vaccination to stimulate the host immune response, particularly cytotoxic cells, may be critical to clearing of reactivated HIV-1-infected cells. However, evidence for this approach in humans is lacking, and parameters required for a vaccine are unknown because opportunities to study HIV-1 reactivation are rare. METHODS: We present observations from a HIV-1 elite controller, not treated with combination antiretroviral therapy, who experienced viral reactivation following treatment for myeloma with melphalan and autologous stem cell transplantation. Mathematical modeling was performed using a standard viral dynamic model. Enzyme-linked immunospot, intracellular cytokine staining, and tetramer staining were performed on peripheral blood mononuclear cells; in vitro CD8 T-cell-mediated control of virion production by autologous CD4 T cells was quantified; and neutralizing antibody titers were measured. RESULTS: Viral rebound was measured at 28,000 copies/mL on day 13 post-transplant before rapid decay to <50 copies/mL in 2 distinct phases with t1/2 of 0.71 days and 4.1 days. These kinetics were consistent with an expansion of cytotoxic effector cells and killing of productively infected CD4 T cells. Following transplantation, innate immune cells, including natural killer cells, recovered with virus rebound. However, most striking was the expansion of highly functional HIV-1-specific cytotoxic CD8 T cells, at numbers consistent with those applied in modeling, as virus control was regained. CONCLUSIONS: These observations provide evidence that the human immune response is capable of controlling coordinated global HIV-1 reactivation, remarkably with potency equivalent to combination antiretroviral therapy. These data will inform design of vaccines for use in HIV-1 curative interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".