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Record W2056752978 · doi:10.1016/j.ymthe.2003.09.008

Needle-free topical electroporation improves gene expression from plasmids administered in porcine skin

2003· article· en· W2056752978 on OpenAlexafffund
Shawn Babiuk, Maria E. Baca‐Estrada, Marianna Földvári, Lawrence Baizer, Richard Stout, Michael Storms, Dietmar Rabussay, Georg Widera, Lorne A. Babiuk

Bibliographic record

VenueMolecular Therapy · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsElectroporationPlasmidDNA vaccinationIn vivoGene deliveryGenetic enhancementGene expressionMolecular biologyLuciferaseTransfectionGene gunNaked DNADNAIntradermal injectionGeneBiologyImmunologyBiotechnologyBiochemistry

Abstract

fetched live from OpenAlex

Electroporation has been shown to increase the potency of DNA vaccines that have demonstrated significant potential in mice. However, there is a need to develop noninvasive or minimally invasive vaccination methods. In pigs, in vivo gene expression was assessed to compare intradermal needle injection to a needle-free dermal BioJect as a means of delivery of plasmids. Each administration method was further tested with and without surface electroporation. Experiments with plasmid DNA encoding luciferase demonstrated that needle-free administration results in higher gene expression levels than needle injection. Electroporation enhanced gene expression for both intradermal delivery methods. Needle-free plasmid injection in combination with electroporation led to a more rapid induction of immune responses compared to other methods of plasmid administration. It was concluded that needle-free topical electroporation significantly enhances gene expression, possibly by improving cellular uptake of plasmid DNA.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.236
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations86
Published2003
Admission routes2
Has abstractno

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