Skeletal Muscle Pathology in X-Linked Myotubular Myopathy: Review With Cross-Species Comparisons
Bibliographic record
Abstract
X-linked myotubular myopathy (XLMTM) is a devastating, rare, congenital myopathy caused by mutations in the MTM1 gene, resulting in a lack of or dysfunction of the enzyme myotubularin. This leads to severe perinatal weakness and distinctive muscle pathology. It was originally thought that XLMTM was related to developmental arrest in myotube maturation; however, the generation and characterization of several animal models have significantly improved our understanding of clinical and pathological aspects of this disorder. Myotubularin is now known to participate in numerous cellular processes including endosomal trafficking, excitation-contraction coupling, cytoskeletal organization, neuromuscular junction structure, autophagy, and satellite cell proliferation and survival. The available vertebrate models of XLMTM, which vary in severity from complete absence to reduced functional levels of myotubularin, recapitulate features of the human disease to a variable extent. Understanding how pathological endpoints in animals with XLMTM translate to human patients will be essential to interpret preclinical treatment trials and translate therapies into human clinical studies. This review summarizes the published animal models of XLMTM, including those of zebrafish, mice, and dogs, with a focus on their pathological features as compared to those seen in human XLMTM patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".