Muscle-specific increased expression of <i>JAG1</i> improves the skeletal muscle phenotype in dystrophin-deficient mice
Bibliographic record
Abstract
Therapeutic strategies for Duchenne muscular dystrophy (DMD) will likely require complementary approaches. One possibility is to explore genetic modifiers that improve muscle regeneration and function. The beneficial effects of the overexpression of Jagged-1 were described in escaper golden retriever muscular dystrophy (GRMD) dogs that had a near-normal life and validated in dystrophin-deficient zebrafish. To clarify the underlying biology of JAG1 overexpression in dystrophic muscles, we generated a transgenic mouse (mdx 5cv - JAG1 ) model that lacks dystrophin and overexpresses human JAG1 in striated muscles. Skeletal muscles from mdx 5cv - JAG1 and mdx 5cv mice were studied at 1-, 4-, and 12-mo time points. JAG1 expression in mdx 5cv - JAG1 increased by 3 to 5 times compared to mdx 5cv . Consequently, mdx 5cv - JAG1 muscles were significantly bigger and stronger than dystrophic controls, along with an increased number of myofibers. Proteomics data show increased dysferlin in mdx 5cv - JAG1 muscles and an association of the histone methyltransferase Nsd1 with the phenotype. Our data support the positive effect of JAG1 overexpression in dystrophic muscles.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".