Targeted Gene Addition of Microdystrophin in Mice Skeletal Muscle via Human Myoblast Transplantation
Bibliographic record
Abstract
Zinc finger nucleases (ZFN) can facilitate targeted gene addition to the genome while minimizing the risks of insertional mutagenesis. Here, we used a previously characterized ZFN pair targeting the chemokine (C-C motif) receptor 5 (CCR5) locus to introduce, as a proof of concept, the enhanced green fluorescent protein (eGFP) or the microdystrophin genes into human myoblasts. Using integrase-defective lentiviral vectors (IDLVs) and chimeric adenoviral vectors to transiently deliver template DNA and ZFN respectively, we achieved up to 40% targeted gene addition in human myoblasts. When the O(6)-methylguanine-DNA methyltransferase(P140K) gene was co-introduced with eGFP, the frequency of cells with targeted integration could be increased to over 90% after drug selection. Importantly, gene-targeted myoblasts retained their mitogenic activity and potential to form myotubes both in vitro and in vivo when injected into the tibialis anterior of immune-deficient mice. Altogether, our results could lead to the development of improved cell therapy transplantation protocols for muscular diseases.Molecular Therapy - Nucleic Acids (2013) 2, e68; doi:10.1038/mtna.2012.55; published online 29 January 2013.
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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) | 0.002 | 0.001 |
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.
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".