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Strategies for improved formulation and delivery of DNA vaccines to veterinary target species

2004· review· en· W1973493403 on OpenAlex
Sylvia van Drunen Littel‐van den Hurk, Shawn Babiuk, Lorne A. Babiuk

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

VenueImmunological Reviews · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDNA vaccinationElectroporationImmune systemImmunizationTransfectionBiologyImmunologyGene gunImmunityBiotechnologyGeneGenetics

Abstract

fetched live from OpenAlex

Interest in DNA immunization of animals continues, despite the fact that immune responses induced by DNA vaccines are generally lower than those elicited by conventional vaccines. In attempts to enhance the immune response to DNA vaccines, individuals have tried a variety of immune modulators, cytokines, and costimulatory molecules, but these only boost immune responses marginally. These results clearly demonstrate that the major challenge to improving DNA-based vaccines is to improve the transfection efficiency. Gene gun and electroporation can increase transfection and improve immune responses significantly, but these technologies have not yet advanced to the stage of routine use in livestock. Hopefully, transfection efficiency can be increased further in a user-friendly manner to ensure that the benefits of using DNA vaccines become a reality.

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 score0.993
Threshold uncertainty score0.970

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 head0.088
GPT teacher head0.347
Teacher spread0.260 · 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