HIV-1 proviral landscapes distinguish posttreatment controllers from noncontrollers
Bibliographic record
Abstract
HIV posttreatment controllers (PTCs) represent a natural model of sustained HIV remission, but they are rare and little is known about their viral reservoir. We obtained 1,450 proviral sequences after near-full-length amplification for 10 PTCs and 16 posttreatment noncontrollers (NCs). Before treatment interruption, the median intact and total reservoir size in PTCs was 7-fold lower than in NCs, but the proportion of intact, defective, and total clonally expanded proviral genomes was not significantly different between the 2 groups. Quantification of total but not intact proviral genome copies predicted sustained HIV remission as 81% of NCs, but none of the PTCs had a total proviral genome greater than 4 copies per million peripheral blood mononuclear cells (PBMCs). The results highlight the restricted intact and defective HIV reservoir in PTCs and suggest that total proviral genome burden could act as the first biomarker for identifying PTCs. Total and defective but not intact proviral copy numbers correlated with levels of cell-associated HIV RNA, activated NK cell percentages, and both HIV-specific CD4+ and CD8+ responses. These results support the concept that defective HIV genomes can lead to viral antigen production and interact with both the innate and adaptive immune systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".