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Record W2925126737 · doi:10.1021/acsnano.8b07858

Lipid-Based DNA Therapeutics: Hallmarks of Non-Viral Gene Delivery

2019· review· en· W2925126737 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

VenueACS Nano · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of British Columbia
FundersFreiwillige Akademische GesellschaftSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNovartis
KeywordsGene deliveryGenetic enhancementComputational biologyDNAGeneEx vivoBiologyIn vivoBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Gene therapy is a promising strategy for the treatment of monogenic disorders. Non-viral gene delivery systems including lipid-based DNA therapeutics offer the opportunity to deliver an encoding gene sequence specifically to the target tissue and thus enable the expression of therapeutic proteins in diseased cells. Currently, available gene delivery approaches based on DNA are inefficient and require improvements to achieve clinical utility. In this Review, we discuss state-of-the-art lipid-based DNA delivery systems that have been investigated in a preclinical setting. We emphasize factors influencing the delivery and subsequent gene expression in vitro, ex vivo, and in vivo. In addition, we cover aspects of nanoparticle engineering and optimization for DNA therapeutics. Finally, we highlight achievements of lipid-based DNA therapies in clinical trials.

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 score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.034
GPT teacher head0.303
Teacher spread0.270 · 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