Generation and characterization of a novel mouse model of Becker Muscular Dystrophy with a deletion of exons 52 to 55
Bibliographic record
Abstract
Abstract Becker Muscular Dystrophy (BMD) is a rare X-linked recessive neuromuscular disorder caused by in-frame deletions in the DMD gene that result in the production of a truncated, yet functional, dystrophin protein. BMD is often considered a milder form of Duchenne Muscular Dystrophy, in which mutations typically result in the disruption of the reading frame and the malfunction or loss of dystrophin. The consequences of BMD-causing in-frame deletions on the organism are more difficult to predict, especially in regard to long-term prognosis. Here, we employed CRISPR-Cas9 technology to generate a new Dmd del52-55 mouse model by deleting exons 52-55, resulting in a typical BMD-like in-frame deletion. To delineate the long-term effects of this deletion, we studied these mice over 52 weeks. Our results suggest that a truncated dystrophin is sufficient to maintain wildtype-like muscle and heart functions in young mice. However, the truncated protein appears insufficient to maintain normal muscle homeostasis and protect against exercise-induced damage at 52 weeks. To further delineate the effects of the exons 52-55 in-frame deletion, we performed RNA-Seq pre– and post-exercise and identified several differentially expressed pathways that could explain the abnormal muscle phenotype observed at 52 weeks in the BMD model. Summary Statement We generated and characterized the long-term effects of a Becker Muscular Dystrophy-like in-frame deletion of exon 52 to 55 in mice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.003 | 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".