Temporary increase in circulating replication-competent latent HIV-infected resting CD4+ T cells after switch to an integrase inhibitor based antiretroviral regimen
Bibliographic record
Abstract
BACKGROUND: The principal barrier to an HIV cure is the presence of the latent viral reservoir (LVR), which has been understudied in African populations. From 2018 to 2019, Uganda instituted a nationwide rollout of ART consisting of Dolutegravir (DTG) with two NRTI, which replaced the previous regimen of one NNRTI and the same two NRTI. METHODS: Changes in the inducible replication-competent LVR (RC-LVR) of ART-suppressed Ugandans with HIV (n = 88) from 2015 to 2020 were examined using the quantitative viral outgrowth assay. Outgrowth viruses were examined for viral evolution. Changes in the RC-LVR were analyzed using three versions of a Bayesian model that estimated the decay rate over time as a single, linear rate (model A), or allowing for a change at time of DTG initiation (model B&C). FINDINGS: Model A estimated the slope of RC-LVR change as a non-significant positive increase, which was due to a temporary spike in the RC-LVR that occurred 0-12 months post-DTG initiation (p < 0.005). This was confirmed with models B and C; for instance, model B estimated a significant decay pre-DTG initiation with a half-life of 6.9 years, and an ∼1.7-fold increase in the size of the RC-LVR post-DTG initiation. There was no evidence of viral failure or consistent evolution in the cohort. INTERPRETATION: These data suggest that the change from NNRTI- to DTG-based ART is associated with a significant temporary increase in the circulating RC-LVR. FUNDING: Supported by the NIH (grant 1-UM1AI164565); Gilead HIV Cure Grants Program (90072171); Canadian Institutes of Health Research (PJT-155990); and Ontario Genomics-Canadian Statistical Sciences Institute.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".