Dystrophic Skeletal Muscle Phenotypes Can Be Horizontally Transferred via Fecal Microbiome Transplantations
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) has no cure and accounts for > 80% of muscular dystrophy cases around the world. DMD patients experience severe muscle degeneration that continues until death and also suffer from gastrointestinal complications that undoubtedly impact their microbiotas. It is unclear whether dystrophic microbiotas simply reflect the disease or whether microbes are directly involved in muscle phenotypes. Here, we sought to determine the microbiota's causal role in promoting dystrophic muscles by performing intra/inter-genotype fecal microbiota transplantations (FMT) between wildtype and mdx mice; assessing FMT's impact on muscles and microbiotas over 9 weeks. Transplanting mdx microbiotas into wildtype mice induced an mdx-like muscle phenotype while the inverse improved muscle features. We identified several taxa differentially abundant between wildtype mice receiving either wildtype or mdx FMT, highlighting their potential role in muscle health. Our results highlight the active role microbes have in impacting muscle health through both beneficial and detrimental mechanisms. Accordingly, microbes represent unexploited therapeutic targets for improving health outcomes in muscular dystrophies.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".