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Record W2333638833 · doi:10.2174/157488412800228857

Polyethylenimine as a Promising Vector for Targeted siRNA Delivery

2012· review· en· W2333638833 on OpenAlexaff
Surendra Nimesh

Bibliographic record

VenueCurrent Clinical Pharmacology · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsPolyethylenimineSmall interfering RNARNA interferenceTransfectionGene silencingGene deliveryGenetic enhancementViral vectorRNASmall hairpin RNAChemistryNanotechnologyCell biologyBiologyMaterials scienceGeneBiochemistryRecombinant DNA

Abstract

fetched live from OpenAlex

Recent discovery of RNA interference (RNAi) technology for gene therapy has triggered explosive research efforts towards development of small interfering RNA (siRNA) as therapeutic modality for gene silencing. Owing to its large molecular weight (~13 kDa), polyanionic nature (~40 negative phosphate groups) and rapid enzymatic degradation, delivery of siRNA remains an unresolved issue. Hence, there arises a need of an appropriate delivery vector to overcome the intrinsic, poor intracellular uptake and limited in vitro and in vivo stability. Amongst the various non-viral delivery vectors, the application of polymeric vectors such as polyethylenimine (PEI) or its derivatives has attracted much attention due to its high transfection efficiency and ease of manipulation. PEI has been extensively investigated for DNA delivery, only recently this polymer has been employed for siRNA delivery. This review will focus on studies done on PEI to deliver siRNA, with emphasis on the targeted, self-assembled polymeric nanoparticles with promising potential to evolve as therapeutic tool in gene therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.204
GPT teacher head0.501
Teacher spread0.297 · 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 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

Citations60
Published2012
Admission routes1
Has abstractyes

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