The Effect of Therapeutic HIV Vaccination With ALVAC-HIV With or Without Remune on the Size of the Viral Reservoir (A CTN 173 Substudy)
Bibliographic record
Abstract
OBJECTIVES: To assess whether therapeutic vaccination with ALVAC-HIV ± Remune affects viral reservoir size in antiretroviral therapy-treated individuals. METHODS: Participants in CTN 173, a multicentre, randomized, 3-arm, placebo-controlled, double-blind study, were vaccinated with ALVAC-HIV ± Remune (groups 1 and 2, respectively) or with placebos (group 3) over 20 weeks and assessed for changes in the size of their viral reservoirs from weeks 0 to 24. RESULTS: Sixteen participants completed the viral reservoir substudy. The median sizes (interquartile range) of the viral reservoir at baseline (week 0) were 0.07 (0.03-0.37), 0.04 (0.02-0.33), and 0.13 (0.06-0.99) infectious units per million peripheral blood mononuclear cells for groups 1, 2, and 3, respectively; these baseline viral reservoir sizes were not significantly different (P = 0.37). By week 24, the median sizes of the viral reservoirs were 0.04 (0.01-2.16), 0.04 (0.01-0.34), and 0.12 (0.01-0.44) infectious units per million peripheral blood mononuclear cells for groups 1, 2, and 3 respectively; these week 24 viral reservoir sizes were not significantly different (P = 0.91). Furthermore, there were no statistically significant differences between baseline and week 24 reservoir sizes for any of the 3 groups (P = 0.88, P = 1.00, and P = 0.44, respectively). CONCLUSIONS: Despite evidence that ALVAC-HIV ± Remune was associated with a trend toward a delay in viral rebound and a smaller decrease in CD4 T-cell counts following antiretroviral therapy interruption, ALVAC-HIV ± Remune did not influence the size of the viral 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".