Strength and muscle specificity of a compact promoter derived from the slow troponin I gene in the context of episomal (gutless adenovirus) and integrating (lentiviral) vectors
Bibliographic record
Abstract
BACKGROUND: Gutless adenovirus (helper-dependent adenoviral vector; HDAd) and lentiviral vectors (LV) are attractive vectors for the gene therapy of muscle diseases. Because the organization of their DNA (episomal versus integrated) differs, we investigated whether the strength and specificity of ΔUSEx3, a novel muscle-specific promoter previously tested with plasmid, were maintained in the context of these vectors. METHODS: Two HDAds expressing β-galactosidase regulated by ΔUSEx3 or CAG [cytomegalovirus (CMV) enhancer/β-actin promoter], and three LV expressing green fluorescent protein regulated by ΔUSEx3, CMV or a modified skeletal α-actin promoter (SPcΔ5-12), were constructed. Gene expression was compared in cell culture and after intravenous (HDAd only) and intramuscular injection of mice. RESULTS: Irrespective of the vector used, ΔUSEx3 remained poorly active in nonmuscle cells and tissues. In myotubes, ΔUSEx3 was as strong as CMV and SPcΔ5-12, although it was ten-fold weaker than CAG, a proven powerful promoter in muscle. In cell culture, ΔUSEx3 activity in the context of LV was more stable than CMV, indicating it is less prone to silencing. In the context of HDAd, the behavior of ΔUSEx3 in skeletal muscle mirrored that of cell culture (10% of the CAG activity and half the number of transduced fibers). Surprisingly, in muscles treated with LV, ΔUSEx3 activity was five-fold lower than SPcΔ5-12. CONCLUSIONS: The data obtained in the present study confirm that ΔUSEx3 is a strong and robust muscle-specific promoter in the context of HDAd (cell culture and in vivo) and LV (cell culture). However, it was less efficient in vivo in the context of LV.
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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".