Interplay of diverse adjuvants and nanoparticle presentation of native-like HIV-1 envelope trimers
Bibliographic record
Abstract
The immunogenicity of HIV-1 envelope (Env) trimers is generally poor. We used the clinically relevant ConM SOSIP trimer to compare the ability of different adjuvants (squalene emulsion, ISCOMATRIX, GLA-LSQ, and MPLA liposomes) to support neutralizing antibody (NAb) responses in rabbits. The trimers were administered as free proteins or on nanoparticles. The rank order for the adjuvants was ISCOMATRIX > SE > GLA-LSQ ~ MPLA liposomes > no adjuvant. Stronger NAb responses were elicited when the ConM SOSIP trimers were presented on ferritin nanoparticles. We also found that the GLA-LSQ adjuvant induced an unexpectedly strong antibody response to the ferritin core of the nanoparticles. This "off-target" effect may have compromised its ability to induce the more desired antitrimer antibodies. In summary, both adjuvants and nanoparticle display can improve the magnitude of the antibody response to SOSIP trimers but the best combination of trimer presentation and adjuvant can only be identified experimentally.
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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) | 0.000 | 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 | 0.000 |
| 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".