Autotransplantation in mdx Mice of mdx Myoblasts Genetically Corrected by an HSV-1 Amplicon Vector
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder, characterized by a lack of dystrophin. To eliminate the need for immunosuppressive drugs, transplantation of genetically modified autologous myoblasts has been proposed as a possible therapy for this myopathy. An HSV-1 amplicon vector (HSVDGN), containing a 17.3-kb full-length MCK-driven mouse dystrophin cDNA, an eGFP gene, and a neomycin resistance gene driven by CMV or SV40 promoters, respectively, was constructed and used to transduce mdx primary myoblasts. The presence of the eGFP and neomycin resistance genes facilitated the evaluation of the initial transduction efficiency and the permanent transduction frequency. At low multiplicities of infection (MOI 1-5), the majority of myoblasts (60-90%) expressed GFP. The GFP-positive mdx myoblasts were sorted by FACS and selected with neomycin (300 microg/ml) for 2 weeks. Up to 2% of initially infected mdx myoblasts stably expressed the three transgenes without further selection at that time. These altered cells were grafted into the tibialis anterior muscles of 18 mdx mice. Some of the mice were immunosuppressed with FK506 due to the anticipation that eGFP and the product of neomycin resistance gene might be immunogenic. One month after transplantation, numerous muscle fibers expressing mouse dystrophin were detected by immunohistochemistry, in both immunosuppressed (10-50%) and nonimmunosuppressed (5-25%) mdx mice. Our results demonstrated the capability of permanently expressing a full-length dystrophin in dystrophic myoblasts with HSV-1 amplicon vector and raised the possibility of an eventual treatment of DMD based on the transplantation of genetically modified autologous myoblasts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".