Differentiation into an Effector Memory Phenotype Potentiates HIV-1 Latency Reversal in CD4<sup>+</sup>T Cells
Bibliographic record
Abstract
By performing phenotypic analysis of latency reversal in CD4 + T cells from virally suppressed individuals, we identify the T EM subset as the largest contributor to the inducible HIV reservoir. Differential responses of memory CD4 + T cell subsets to latency-reversing agents (LRAs) demonstrate that HIV gene expression is associated with heightened expression of transcriptional pathways associated with differentiation, acquisition of effector function, and cell cycle entry. In vitro modeling of the latent HIV reservoir in memory CD4 + T cell subsets identify LRAs that reverse latency with ranges of efficiency and specificity. We found that therapeutic induction of latency reversal is associated with upregulation of identical sets of T EM -associated genes and cell surface markers shown to be associated with latency reversal in our ex vivo and in vitro models. Together, these data support the idea that the effector memory phenotype supports HIV latency reversal in CD4 + T cells.
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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 | 0.000 | 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) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".