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Record W4407640482 · doi:10.1099/acmi.0.000925.v3

Immunogenicity of virus-like particle vaccine candidates against SARS-CoV-2 infection

2025· article· en· W4407640482 on OpenAlex
Hai Trong Nguyen, Ravendra Garg, Andrea Kroeker, Volker Gerdts, Darryl Falzarano, Qiang Liu, Amelia Baconawa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAccess Microbiology · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute on Deafness and Other Communication DisordersCanadian Institutes of Health Research
KeywordsImmunogenicityVirologyVirusVaccinationAntibodyVirus-like particleNeutralizing antibodyBiologyImmunityImmune systemImmunologyGeneRecombinant DNAGenetics

Abstract

fetched live from OpenAlex

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve, potentially leading to variants of concern that could become more transmissible, resist treatment, evade host immunity and reduce the effectiveness of currently available vaccines. Improved vaccines are still required as vaccination remains the most effective strategy against this virus. We have produced two SARS-CoV-2 virus-like particles (VLPs) using a baculovirus BacMam expression platform and examined their immunogenicity in mice. VLP1 contains the spike protein from the Wuhan strain, whereas VLP2 contains that of an Omicron variant. Mice immunized with VLP1 and boosted with VLP2 developed significantly higher antibodies in the sera, as well as higher numbers of IFN-γ secreting cells than the control group. Furthermore, both VLPs induced virus-neutralizing antibodies against Wuhan and Omicron variants. In conclusion, VLPs have the potential for the development of a safe and effective vaccine against SARS-CoV-2 variants.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.369
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it