Immediate antiviral therapy appears to restrict resting CD4 <sup>+</sup> cell HIV-1 infection without accelerating the decay of latent infection
Bibliographic record
Abstract
HIV type 1 (HIV-1) persists within resting CD4(+) T cells despite antiretroviral therapy (ART). To better understand the kinetics by which resting cell infection (RCI) is established, we developed a mathematical model that accurately predicts (r = 0.65, P = 2.5 × 10(-4)) the initial frequency of RCI measured about 1 year postinfection, based on the time of ART initiation and the dynamic changes in viremia and CD4(+) T cells. In the largest cohort of patients treated during acute seronegative HIV infection (AHI) in whom RCI has been stringently quantified, we found that early ART reduced the generation of latently infected cells. Although RCI declined after the first year of ART in most acutely infected patients, there was a striking absence of decline when initial RCI frequency was less than 0.5 per million. Notably, low-level viremia was observed more frequently as RCI increased. Together these observations suggest that (i) the degree of RCI is directly related to the availability of CD4(+) T cells susceptible to HIV, whether viremia is controlled by the immune response and/or ART; and (ii) that two pools of infected resting CD4(+) T cells exist, namely, less stable cells, observable in patients in whom viremia is not well controlled in early infection, and extremely stable cells that are established despite early ART. These findings reinforce and extend the concept that new approaches will be needed to eradicate HIV infection, and, in particular, highlight the need to target the extremely small but universal, long-lived latent 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 | 0.001 |
| 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 | 0.001 | 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".