Clues to finding correlates of risk/protection for HIV-1 vaccines
Bibliographic record
Abstract
Almost a decade later, we still do not understand why in the STEP trial (2008), males with pre-existing antibodies to the Ad5 vector were associated with initial increased risk of HIV-1 acquisition. Similarly, we have little conclusive evidence of why in the RV144 trial (2009), vaccination with the ALVAC-HIV/AIDSVAX B/E was associated initially with almost a 60% vaccine efficacy at year one, which waned over 42 months to 31.2%, and where females were more protected than males. Based on the literature and trial outcomes, it was deduced that the elusive correlate of risk/protection may pertain to a novel, potent, innate protector mechanism launched by alternatively activated macrophages, which is probably induced by viruses and female steroid hormones. It was also suggested this mechanism was not likely amenable to discovery using standard or traditional approaches. A plausible, candidate mechanism was identified with these characteristics, namely the production of human endogenous retrovirus–K102 (HERV-K102) particles, which occurs in, and generates, foamy macrophages in vitro . Accumulating clinical, biological and phylogenetic evidence supports its role in the antagonism of HIV-1 replication and/or in the prevention of HIV-1 acquisition. Thus, it will be important to examine HERV-K102 particle production, increased integration and envelop antibody production as candidate correlates of protection in HIV-1 vaccine trials, as well as in HIV-1 highly exposed seronegative cohorts and elite controllers. The results of such efforts may have important ramifications for the HIV-1 cure in addition to 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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".