MétaCan
Menu
Back to cohort
Record W2101578637 · doi:10.2174/092986712803414141

Nonviral Approach for Targeted Nucleic Acid Delivery

2012· review· en· W2101578637 on OpenAlexafffund
Mohammadamin Jafari, M. Soltani, Sheva Naahidi, D. Nedra Karunaratne, P. Chen

Bibliographic record

VenueCurrent Medicinal Chemistry · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGene deliveryNucleic acidTransfectionGenetic enhancementElectroporationCationic liposomeGene knockdownOligonucleotideDNAPlasmidBiologyChemistryMolecular biologyBiochemistryGene

Abstract

fetched live from OpenAlex

Despite their relatively lower efficiency, nonviral approaches are emerging as safer alternatives in gene therapy to viral vectors. Delivery of nucleic acids to the target site is an important factor for effective gene expression (plasmid DNA) or knockdown (siRNA) with minimal side effects. Direct deposition at the target site by physical methods, including ultrasound, electroporation and gene gun, is one approach for local delivery. For less accessible sites, the development of carriers that can home into the target tissue is required. Cationic peptides, lipoplexes, polyplexes and nanoplexes have been used as carriers for delivery of nucleic acids. Targeting ligands, such as cell targeting peptides, have also been applied to decorate delivery vehicles in order to enhance their efficacy. This review focuses on delivery strategies and recent progress in non-viral carriers and their modifications to improve their performance in targeting and transfection.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.063
GPT teacher head0.330
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations116
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueCurrent Medicinal ChemistrySame topicRNA Interference and Gene DeliveryFrench-language works237,207