Interrogation of Antigen Display on Individual Vaccine Nanoparticles for Achieving Neutralizing Antibody Responses against Hepatitis C Virus
Bibliographic record
Abstract
Elicitation of neutralizing antibody responses against hepatitis C virus (HCV) has been a challenging goal. While the E2 subunit of the HCV envelope glycoprotein complex is a promising target for generating cross-genotype neutralizing antibodies, vaccinations with soluble E2 immunogens generally induce weak neutralizing antibody responses. Here, E2 immunogens (i.e., E2.661 and E2c.661) were loaded into lipid-based nanovaccines and examined for induction of neutralizing antibody responses. Compared with soluble E2 immunogens, E2 nanoparticles elicited 6- to 20-fold higher E2-specific serum IgG titers in mice. Importantly, E2 vaccine nanoparticles analyzed at a single particle level with a flow cytometry-based method revealed interesting dynamics between epitope display on the surfaces of nanoparticles in vitro and induction of neutralizing antibody responses in vivo. E2c.661 nanoparticles that are preferentially bound by a broadly neutralizing antibody, HCV1, in vitro elicit neutralizing antibody responses against both autologous and heterologous HCV virions in vivo. In stark contrast, E2.661 nanoparticles with reduced HCV1-antibody binding in vitro mainly induce autologous neutralizing antibody responses in vivo. These results show that rationale antigen design coupled with interrogation of epitope display on vaccine nanoparticles at a single particle level may aid in vaccine development toward achieving neutralizing antibody responses in vivo.
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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 | 0.001 | 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 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".