Functional EGFP–dystrophin fusion proteins for gene therapy vector development
Bibliographic record
Abstract
Transfection and transduction studies involving the use of the full-length dystrophin (11 kb) or the truncated mini-gene (6 kb) cDNAs are hampered by the large size of the resulting viral or non-viral expression vectors. This usually results in very low yields of transgene-expressing cells. Moreover, the detection of the few transgene-expressing cells is often tedious and costly. For these reasons, expression vectors containing the enhanced green fluorescent protein (EGFP) fused with the N-termini of mini- and full-length human dystrophin were constructed. These constructs were tested by transfection of Phoenix cells with Effectene, resulting after 48 h in a green fluorescent signal in 20% of cells. Analysis of the cell extracts by immunoblotting with the use of a monoclonal antibody specific to the dystrophin C-terminus confirmed the expression of EGFP-mini- (240 kDa) and EGFP-full-length human dystrophin (450 kDa) fusion proteins. Moreover, following the in vivo electroporation of the plasmids containing the EGFP-mini- and full-length dystrophin in mouse muscles, both fluorescent proteins were observed in cryostat sections in their normal location under the plasma membrane. This indicates that the fusion of EGFP to dystrophin or mini-dystrophin did not interfere with the normal localization of the protein. In conclusion, the fusion of EGFP provides a good tool for the search of the best methods to introduce mini- or full-length dystrophin cDNA in the cells (in vitro) or muscle fibers (in vivo) for the establishment of a treatment by gene therapy of Duchenne muscular dystrophy patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".