Fluoxetine prevents dystrophic changes in a zebrafish model of Duchenne muscular dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a common and relentlessly progressive muscle disease. Some interventions have been identified that modestly slow progression and prolong survival, but more meaningful therapies are lacking. The goal of this study is to identify new therapeutic pathways for DMD using a zebrafish model of the disease. To accomplish this, we performed a non-biased drug screen in sapje, a zebrafish line with a recessive nonsense mutation in dystrophin. We identified 6 positive hits (out of 640 total drugs tested) by their ability to prevent abnormal birefringence in sapje. Follow-up analyses demonstrated that fluoxetine, a selective serotonin reuptake inhibitor (SSRI), provided the most substantial benefit. Morpholino-based experimentation confirmed that modulation of the serotonin pathway alone can prevent the dystrophic phenotype, and transcriptomic analysis revealed changes in calcium homeostasis as a potential mechanism. In all, we demonstrate that monoamine agonists can prevent disease in a vertebrate model of DMD. Given the safe and widespread use of SSRIs in clinical practice, our study identifies an attractive target pathway for therapy development.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".