Autologous Transplantation of Muscle Precursor Cells Modified with a Lentivirus for Muscular Dystrophy: Human Cells and Primate Models
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is characterized by the absence of dystrophin. We tested the ability of lentiviral vectors to deliver a transgene into myogenic cells before their transplantation. Enhanced green fluorescent protein (eGFP) transgene was efficiently transferred into cells and eGFP-positive fibers were generated following transplantation. An eGFP-micro-dystrophin transgene under the control of a cytomegalovirus promoter was then transferred with the same viral vector but caused some toxicity to the mono-nucleated cells. We then used instead a muscle creatine kinase promoter. Dystrophin expression was observed in the muscle fibers after the transplantation of such genetically modified cells into mdx and severe combined immunodeficient mice. Micro-dystrophin expression was also observed in monkey muscles a month after allogenic or autologous transplantation of genetically modified myoblasts. Therapeutic exon skipping was induced by infecting myoblasts of a DMD patient, deleted for dystrophin exons 49 and 50, with a lentivirus expressing a U7 small nuclear RNA containing antisense sequences against exon 51. The modification led to correct exon skipping and to the expression of a quasi-dystrophin in vitro and in vivo. These results demonstrate the feasibility of lentiviral-based ex vivo gene therapy for DMD.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".