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Record W4206166744 · doi:10.3390/life12020156

Plant-Derived Recombinant Vaccines against Zoonotic Viruses

2022· review· en· W4206166744 on OpenAlex

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.

Bibliographic record

VenueLife · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsUniversity of Manitoba
FundersEuropean Regional Development FundEuropean Commission
KeywordsVirologyBiologyVirusRecombinant DNAVaccinationVirus-like particleGeneticsGene

Abstract

fetched live from OpenAlex

Emerging and re-emerging zoonotic diseases cause serious illness with billions of cases, and millions of deaths. The most effective way to restrict the spread of zoonotic viruses among humans and animals and prevent disease is vaccination. Recombinant proteins produced in plants offer an alternative approach for the development of safe, effective, inexpensive candidate vaccines. Current strategies are focused on the production of highly immunogenic structural proteins, which mimic the organizations of the native virion but lack the viral genetic material. These include chimeric viral peptides, subunit virus proteins, and virus-like particles (VLPs). The latter, with their ability to self-assemble and thus resemble the form of virus particles, are gaining traction among plant-based candidate vaccines against many infectious diseases. In this review, we summarized the main zoonotic diseases and followed the progress in using plant expression systems for the production of recombinant proteins and VLPs used in the development of plant-based vaccines against zoonotic viruses.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.068
GPT teacher head0.308
Teacher spread0.241 · 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