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Record W4295706100 · doi:10.1126/sciadv.abp9435

Exosome-mediated delivery of Cas9 ribonucleoprotein complexes for tissue-specific gene therapy of liver diseases

2022· article· en· W4295706100 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

VenueScience Advances · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExosomeRibonucleoproteinGene deliveryGenome editingCas9BiologyGenetic enhancementCRISPRElectroporationCell biologyMicrovesiclesCancer researchGeneRNAmicroRNAGenetics

Abstract

fetched live from OpenAlex

CRISPR-Cas9 gene editing has emerged as a powerful therapeutic technology, but the lack of safe and efficient in vivo delivery systems, especially for tissue-specific vectors, limits its broad clinical applications. Delivery of Cas9 ribonucleoprotein (RNP) owns competitive advantages over other options; however, the large size of RNPs exceeds the loading capacity of currently available delivery vectors. Here, we report a previously unidentified genome editing delivery system, named exosome RNP , in which Cas9 RNPs were loaded into purified exosomes isolated from hepatic stellate cells through electroporation. Exosome RNP facilitated effective cytosolic delivery of RNP in vitro while specifically accumulated in the liver tissue in vivo. Exosome RNP showed vigorous therapeutic potential in acute liver injury, chronic liver fibrosis, and hepatocellular carcinoma mouse models via targeting p53 up-regulated modulator of apoptosis ( PUMA ), cyclin E1 ( CcnE1 ), and K (lysine) acetyltransferase 5 ( KAT5 ), respectively. The developed exosome RNP provides a feasible platform for precise and tissue-specific gene therapies of liver diseases.

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 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 score0.032
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.272
Teacher spread0.253 · 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