Molecular Diagnosis and Novel Therapies for Neuromuscular Diseases
Bibliographic record
Abstract
With the development of novel targeted therapies, including exon skipping/inclusion and gene replacement therapy, the field of neuromuscular diseases has drastically changed in the last several years. Until 2016, there had been no FDA-approved drugs to treat Duchenne muscular dystrophy (DMD), the most common muscular dystrophy. However, several new personalized therapies, including antisense oligonucleotides eteplirsen for DMD exon 51 skipping and golodirsen and viltolarsen for DMD exon 53 skipping, have been approved in the last 4 years. We are witnessing the start of a therapeutic revolution in neuromuscular diseases. However, the studies also made clear that these therapies are still far from a cure. Personalized genetic medicine for neuromuscular diseases faces several key challenges, including the difficulty of obtaining appropriate cell and animal models and limited its applicability. This Special Issue "Molecular Diagnosis and Novel Therapies for Neuromuscular/Musculoskeletal Diseases" highlights key areas of research progress that improve our understanding and the therapeutic outcomes of neuromuscular diseases in the personalized medicine era.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".