HIV-1 DNA Burden in Peripheral Blood CD4 <sup>+</sup> Cells Influences Disease Progression, Antiretroviral Efficacy, and CD4 <sup>+</sup> T-Cell Restoration
Bibliographic record
Abstract
Integration of human immunodeficiency virus type-1 (HIV-1) proviral DNA into host cell genomic DNA ensures viral persistence despite suppression of active replication. Because HIV RNA originates from integrated HIV DNA, HIV RNA and DNA loads should interrelate when suppression of viral replication is incomplete. In addition, the link between proviral DNA formation and generation of HIV-1 genetic diversity suggests that the ease with which HIV escapes immune or drug-based suppression should vary with proviral load. Thus, HIV proviral load should have unique prognostic significance independent of the highly labile plasma HIV RNA levels commonly used to monitor patient status. To test this possibility, we developed a simple standardized research assay estimating the proportion of CD4+ peripheral blood mononuclear cells (PBMC) carrying HIV-1 DNA and investigated associations between this parameter, plasma virus load, long-term efficacy of antiretroviral therapy and restoration of CD4+ T cells. Lower proportions of CD4+ PBMC carrying HIV-1 DNA were associated with lower peak plasma HIV RNA levels and with more favorable long-term responses to antiretroviral therapy. These results suggest that HIV proviral load affects both disease progression and responsiveness to antiretroviral therapy. Therefore, new anti-HIV therapies addressing the stable pool of HIV proviral DNA should be developed to improve long-term prospects for suppression of HIV replication.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".