HIV-1 Tat B-cell epitope vaccination was ineffectual in preventing viral rebound after ART cessation
Bibliographic record
Abstract
CD4 T cell activation, essential for productive HIV infection, is provided initially in acute HIV infection by innate immune system secretion of activating cytokines. This cytokine response wanes with time and long-term activation of CD4 cells is maintained by HIV Tat protein secreted by HIV infected cells. Structured treatment interruption (STI) in well-controlled antiretroviral-treated (ART) subjects was explored a decade ago with a consensus finding that, in most subjects, HIV levels rebounded within four weeks to pre-ART levels. Based on these observations we initiated a randomized placebo-controlled study of a universal anti-Tat epitope vaccine, TUTI-16, to determine if immunological blockade of Tat would prevent HIV rebound after ART cessation. TUTI-16 immunization was safe, with predominantly mild local and systemic injection-related adverse reactions. TUTI-16 was also immunogenic, with high levels of anti-Tat antibodies compared with levels previously shown to reduce HIV replication in vivo. Of 21 subjects analyzed, 13 (62%) had HIV rebounds vs. 8 (38%) that remained aviremia, but this distribution was not vaccine-related (p = 0.61 log-rank (Mantel-Cox) test), nullifying our hypothesis that anti-Tat antibodies would block rebound of Tat-dependent set-point HIV viremia after ART cessation. Our present findings are consistent with recent molecular findings that rebounding virus following STI is homogeneous and unrelated to previous circulating HIV, suggesting that rebounding HIV represents new founder virus, akin to the original acute HIV infection. We propose, therefore, that STI may have potential as a practical and economical approach to testing the safety and efficacy of candidate prophylactic HIV vaccines.
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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 | 0.000 |
| 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 | 0.000 | 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".