DUX4 reduction and muscle function improvement by subcutaneous delivery of gapmer antisense oligonucleotides
Bibliographic record
Abstract
Facioscapulohumeral muscular dystrophy (FSHD) is caused by aberrant expression of double homeodomain protein 4 ( DUX4 ). The disease has no effective treatment. Previously we demonstrated effective DUX4 knockdown in vitro and in vivo using 2′-O-methoxyethyl (2′MOE) and locked nucleic acid (LNA) gapmer antisense oligonucleotides delivered via intramuscular injections. This study aimed to evaluate in vivo efficacy of the gapmers via systemic delivery using mouse models expressing DUX4 at different levels. First, we injected the gapmers subcutaneously to FLExDUX4 mice at 20 mg/kg twice a week for 10 weeks. Results showed significant reduction in DUX4 mRNA and improved muscle function, assessed by grip strength. Muscle fibrosis and circulating TGFβ1 levels were significantly reduced, approaching baseline level. A dose-dependent DUX4 reduction was observed in 2′MOE gapmer treated. In the ACTA1-MCM;FLExDUX4 model, where DUX4 expression was induced by tamoxifen (5 mg/kg), treatment with 2′MOE gapmers effectively reduced DUX4 , improved muscle function, and decreased inflammation. These findings highlight the therapeutic potential of gapmer-based DUX4 reduction, leading to phenotypic improvement and restoration of muscle function in FSHD mouse models.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".