Magnitude and Breadth of the Neutralizing Antibody Response in the RV144 and Vax003 HIV-1 Vaccine Efficacy Trials
Bibliographic record
Abstract
BACKGROUND: A recombinant canarypox vector expressing human immunodeficiency virus type 1 (HIV-1) Gag, Pro, and membrane-linked gp120 (vCP1521), combined with a bivalent gp120 protein boost (AIDSVAX B/E), provided modest protection against HIV-1 infection in a community-based population in Thailand (RV144 trial). No protection was observed in Thai injection drug users who received AIDSVAX B/E alone (Vax003 trial). We compared the neutralizing antibody response in these 2 trials. METHODS: Neutralization was assessed with tier 1 and tier 2 strains of virus in TZM-bl and A3R5 cells. RESULTS: Neutralization of several tier 1 viruses was detected in both RV144 and Vax003. Peak titers were higher in Vax003 and waned rapidly in both trials. The response in RV144 was targeted in part to V3 of gp120.vCP1521 priming plus 2 boosts with gp120 protein was superior to 2 gp120 protein inoculations alone, confirming a priming effect for vCP1521. Sporadic weak neutralization of tier 2 viruses was detected only in Vax003 and A3R5 cells. CONCLUSION: The results suggest either that weak neutralizing antibody responses can be partially protective against HIV-1 in low-risk heterosexual populations or that the modest efficacy seen in RV144 was mediated by other immune responses, either alone or in combination with neutralizing antibodies.
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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 | 0.005 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".