Exosome-mediated delivery of Cas9 ribonucleoprotein complexes for tissue-specific gene therapy of liver diseases
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".