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Record W2113709410 · doi:10.4155/tde.14.37

Enhancing siRNA Delivery By Employing Lipid Nanoparticles

2014· review· en· W2113709410 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

VenueTherapeutic Delivery · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsAcuitas Therapeutics (Canada)
Fundersnot available
KeywordsNucleic acidGene silencingOligonucleotideIntracellularCytoplasmNanotechnologyGene deliverySmall interfering RNATransfectionmicroRNAChemistryBiophysicsComputational biologyCell biologyBiologyMaterials scienceBiochemistryGene

Abstract

fetched live from OpenAlex

For several decades extensive research has been conducted into the development of fusogenic lipid nanoparticles (LNPs) capable of introducing large, charged molecules into the cytoplasm of target cells. The majority of this work has focused on cationic LNPs encapsulating nucleic acids ranging from small oligonucleotides to large plasmid constructs thousands of bases long. However, since the introduction of siRNA payloads this quest for a non-viral, intracellular delivery systems has advanced significantly. Of particular importance was the demonstration that LNPs containing ionizable, dialkylamino lipids, enable potent hepatic gene silencing across species including humans. This review focuses on the evolution of this delivery system, summarizes the promising data now emerging from clinical trials and considers future directions for the platform.

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 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 score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.031
GPT teacher head0.300
Teacher spread0.269 · 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