Sustained exposure to multivalent antigen-decorated nanoparticles generates broad anti-coronavirus responses
Bibliographic record
Abstract
The threat of future coronavirus pandemics requires developing effective vaccine technologies that provide broad and long-lasting protection against circulating and emerging strains. Here we report a multivalent liposomal hydrogel vaccine technology comprising the receptor binding domain (RBD) of up to four SARS and MERS coronavirus strains non-covalently displayed on the surface of the liposomes within the hydrogel structure. The multivalent presentation and sustained exposure of RBD antigens improved the potency, neutralizing activity, durability, and consistency of antibody responses across homologous and heterologous coronavirus strains in a naïve murine model. When administrated in animals pre-exposed to wild-type SARS-CoV-2 antigens, liposomal hydrogels elicited durable antibody responses against the homologous SARS and MERS strains for over six months and elicited neutralizing activity against the immune-evasive SARS-CoV-2 variant Omicron BA.4/BA.5. Overall, the tunable liposomal hydrogel platform we report here generates robust responses against diverse coronaviruses, supporting global efforts to respond to future viral outbreaks.
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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".