Lyophilized, thermostable Spike or RBD immunogenic liposomes induce protective immunity against SARS-CoV-2 in mice
Bibliographic record
Abstract
The COVID-19 pandemic has spurred interest in potent and thermostable SARS-CoV-2 vaccines. Here, we assess low-dose immunization with lyophilized nanoparticles decorated with recombinant SARS-CoV-2 antigens. The SARS-CoV-2 Spike glycoprotein or its receptor-binding domain (RBD; mouse vaccine dose, 0.1 μg) was displayed on liposomes incorporating a particle-inducing lipid, cobalt porphyrin-phospholipid (dose, 0.4 μg), along with monophosphoryl lipid A (dose, 0.16 μg) and QS-21 (dose, 0.16 μg). Following optimization of lyophilization conditions, Spike or RBD-decorated liposomes were effectively reconstituted and maintained conformational capacity for binding human angiotensin-converting enzyme 2 (hACE2) for at least a week when stored at 60°C in lyophilized but not liquid format. Prime-boost intramuscular vaccination of hACE2-transgenic mice with the reconstituted vaccine formulations induced effective antibody responses that inhibited RBD binding to hACE2 and neutralized pseudotyped and live SARS-CoV-2. Two days following viral challenge, immunized transgenic mice cleared the virus and were fully protected from lethal disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".