Downregulation of CD46 During Muscle Differentiation: Implications for Gene Transfer to Human Skeletal Muscle Using Group B Adenoviruses
Bibliographic record
Abstract
Adenoviral vectors that use the coxsackievirus and adenovirus receptor do not transduce mature muscle efficiently. Group B adenoviruses use CD46 as their cell attachment receptor. To evaluate the utility of vectors based on group B adenoviruses for gene transfer to human skeletal muscle, we assessed the expression of CD46 in biopsied normal skeletal muscle samples and in muscles from patients with Duchenne muscular dystrophy. Transcript levels of CD46 were extremely low in mature muscle and CD46 immunoreactivity was detected only on blood vessels in the muscle sections. Although myoblasts cultured from biopsied samples had robust cell surface CD46 expression by flow cytometry, CD46 transcript levels were barely detectable after differentiation of the myoblasts into myotubes. The myotubes were also much less susceptible to infection with an adenoviral vector carrying the fiber of serotype 35 adenovirus (AdF35). These results suggest that for skeletal muscle, vectors derived from group B adenoviruses may not be a suitable alternative to the commonly used Ad5 vectors.
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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 | 0.000 | 0.000 |
| 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".