Potential contribution of gut microbiota and systemic inflammation on HIV vaccine effectiveness and vaccine design
Bibliographic record
Abstract
The quest for an effective HIV-1 vaccine began as soon as the virus causing AIDS was identified. After several disappointing attempts, results of the Phase-III RV144 trial in Thailand were a beacon of hope for the field demonstrating correlation between protection and immunological markers. In order to optimize vaccine response, we underline results from yellow fever and hepatitis B vaccines, where protective responses were predicted by the pre-vaccination level of immune activation in healthy individuals. Such findings support the assessment and reduction of pre-vaccine immune activation in order to optimize vaccine response. Immune activation in healthy individuals can be influenced by age, presence of CMV infection, gut dysbiosis and microbial translocation. We speculate that the level of immune activation should therefore be assessed to better select participants in vaccine trials, and interventions to reduce inflammation should be used to increase protective HIV vaccine response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".