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Record W4413384729 · doi:10.1371/journal.ppat.1013389

Multivalent mpox protein nanoparticle vaccines confer cross-protection against orthopoxvirus infection

2025· article· en· W4413384729 on OpenAlexfundno aff
Lijun Zhang, Chuanyu Liu, Chenxi Yang, Xueqi Xiao, Senyu Xu, Shengfeng Wan, Kun Xu, Yan Li, Lianpan Dai

Bibliographic record

VenuePLoS Pathogens · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsnot available
FundersInstitute of GeneticsInstitute of Microbiology, Chinese Academy of SciencesNational Key Research and Development Program of ChinaInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesChinese Academy of SciencesBill and Melinda Gates Foundation
KeywordsVacciniaVirologyVirusOrthopoxvirusImmune systemAntigenHeterologousBiologyMonkeypoxMicrobiologyChemistryRecombinant DNAImmunologyBiochemistry

Abstract

fetched live from OpenAlex

The outbreak of mpox since 2022 has driven the development of mpox virus (MPXV)-specific, subunit-based, next-generation vaccines, instead of the currently used live-attenuated vaccinia virus (VACV) vaccines. Here, we describe a self-assembling protein nanoparticle against MPXV using lumazine synthase to present viral surface proteins. Multivalent nanoparticles elicited broader and stronger immune responses against MPXV and provided superior heterologous protection in rodent models against lethal VACV challenges compared to monovalent formulations. The three antigens with the best protective efficacy (intracellular mature virus antigens M1 and E8, and extracellular enveloped virus antigen B6) were further combined as the trivalent cocktail or mosaic nanoparticle. The trivalent nanoparticles elicited higher humoral responses compared to the modified vaccinia virus Ankara, and were protective against lethal VACV challenge in mice, with the protection correlation revealed. These findings highlight the potential of multivalent nanoparticle as vaccines against MPXV and other orthopoxviruses.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.035
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.027
GPT teacher head0.286
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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