Chromatin Functional States Correlate with HIV Latency Reversal in Infected Primary CD4 <sup>+</sup> T cells
Bibliographic record
Abstract
ABSTRACT Human immunodeficiency virus (HIV) infection cannot be cured due to a small reservoir of latently infected CD4 + T cells in treated patients. The “shock and kill” approach proposes to eliminate the reservoir by inducing its activation and the direct or indirect killing of infected cells. Current latency reversing agents (LRAs) do not reduce the viral reservoir in treated patients. We use a novel dual-fluorescent HIV reporter to identify and purify latent cells, and to determine the fraction of latent cells that undergo viral reactivation after infection of primary CD4 + T cells. Unexpectedly, LRAs reactivate less than 5% of latent proviruses. Analysis of HIV integration sites from induced and non-induced latent populations reveals distinct provirus integration sites between these two populations in terms of chromatin functional states. These findings challenge “shock and kill”, and suggest the need of more potent LRAs in combination with immunomodulatory approaches to eradicate HIV reservoir.
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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) | 0.004 | 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".