Natural history of a mouse model of X-linked myotubular myopathy
Bibliographic record
Abstract
X-linked myotubular myopathy (XLMTM) is a severe monogenetic disorder of the skeletal muscle. It is caused by loss-of-expression/function mutations in the myotubularin (MTM1) gene. Much of what is known about the disease, as well as the treatment strategies, has been uncovered through experimentation in pre-clinical models, particularly the Mtm1 gene knockout mouse line (Mtm1 KO). Despite this understanding, and the identification of potential therapies, much remains to be understood about XLMTM disease pathomechanisms, and about the normal functions of MTM1 in muscle development. To lay the groundwork for addressing these knowledge gaps, we performed a natural history study of Mtm1 KO mice. This included longitudinal comparative analyses of motor phenotype, transcriptome and proteome profiles, muscle structure and targeted molecular pathways. We identified age-associated changes in gene expression, mitochondrial function, myofiber size and key molecular markers, including DNM2. Importantly, some molecular and histopathologic changes preceded overt phenotypic changes, while others, such as triad structural alternations, occurred coincidentally with the presence of severe weakness. In total, this study provides a comprehensive longitudinal evaluation of the murine XLMTM disease process, and thus provides a critical framework for future investigations.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".