Single-component multilayered self-assembling protein nanoparticles presenting glycan-trimmed uncleaved prefusion optimized envelope trimers as HIV-1 vaccine candidates
Bibliographic record
Abstract
Uncleaved prefusion-optimized (UFO) design can stabilize diverse HIV-1 envelope glycoproteins (Envs). Single-component, self-assembling protein nanoparticles (1c-SApNP) can display 8 or 20 native-like Env trimers as vaccine candidates. We characterize the biophysical, structural, and antigenic properties of 1c-SApNPs that present the BG505 UFO trimer with wildtype and modified glycans. For 1c-SApNPs, glycan trimming improves recognition of the CD4 binding site without affecting broadly neutralizing antibodies (bNAbs) to major glycan epitopes. In mice, rabbits, and nonhuman primates, glycan trimming increases the frequency of vaccine responders (FVR) and steers antibody responses away from immunodominant glycan holes and glycan patches. The mechanism of vaccine-induced immunity is examined in mice. Compared with the UFO trimer, the multilayered E2p and I3-01v9 1c-SApNPs show 420 times longer retention in lymph node follicles, 20-32 times greater presentation on follicular dendritic cell dendrites, and up-to-4 times stronger germinal center reactions. These findings can inform future HIV-1 vaccine development.
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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) | 0.000 | 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 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".