LNP-mediated delivery of CRISPR RNP for wide-spread in vivo genome editing in mouse cornea
Bibliographic record
Abstract
CRISPR/Cas9-based genome-editing therapies are poised to change the clinical outcome for many diseases with validated therapeutic targets awaiting an appropriate delivery system. Recent advances in lipid nanoparticle (LNP) technology make them an attractive platform for the delivery of various forms of CRISPR/Cas9, including the efficient and transient Cas9/gRNA ribonucleoprotein (RNP) complexes. In this study, we initially tested our novel LNP platform by delivering pre-complexed RNPs and template DNA to cultured mouse cortical neurons, and obtained successful ex vivo genome editing. We then directly injected LNP-packaged RNPs and DNA template into the mouse cornea to evaluate in vivo delivery. For the first time, we demonstrated wide-spread genome editing in the cornea using our LNP-RNPs. The ability of our LNPs to transfect the cornea highlights the potential of our novel delivery platform to be used in CRISPR/Cas9-based genome editing therapies of corneal 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 | 0.001 | 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".