The mouse dystrophin muscle enhancer-1 imparts skeletal muscle, but not cardiac muscle, expression onto the dystrophin Purkinje promoter in transgenic mice
Bibliographic record
Abstract
A subset of patients harboring mutations in the dystrophin gene suffer from X-linked dilated cardiomyopathy (XLCM), a familial heart disease that is not accompanied by any clinical signs of skeletal muscle myopathy. As the muscle (M) isoform of dystrophin is not expressed in these patients, the absence of skeletal muscle symptoms has been attributed to expression of the brain (B) and cerebellar Purkinje (CP) isoforms of dystrophin in skeletal, but not cardiac, muscles of XLCM patients. The compensatory mechanism of dystrophin B and CP promoter upregulation is not known but it has been suggested that the dystrophin muscle enhancer from intron 1, DME-1, may be important in this activity. Previous studies have shown that the presence of the DME-1 is essential for a significant increase in dystrophin B and CP promoter activity in skeletal muscle cells in culture. Here, we demonstrate that the mouse dystrophin CP promoter drives expression of a lacZ reporter gene specifically to the cerebellar Purkinje cell layer but not to skeletal or cardiac muscle of transgenic mice. However, if the mouse counterpart of DME-1 is present in the transgene construct, the dystrophin CP promoter is now activated in skeletal muscle, but not in cardiac muscle. Our findings provide in vivo evidence for the importance of the dystrophin muscle enhancer sequences in activating the dystrophin CP promoter in skeletal muscle. Furthermore, they provide support for the model in which muscle enhancers, like DME-1, activate the dystrophin B and CP promoters in skeletal muscle, but not in cardiac muscle, of XLCM 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".