Towards the Identification of Biomarkers for Muscle Function Improvement in Myotonic Dystrophy Type 1
Bibliographic record
Abstract
BACKGROUND: Myotonic dystrophy type 1 (DM1) is the most common muscular dystrophy in adults. In DM1 patients, skeletal muscle is severely impaired, even atrophied and patients experience a progressive decrease in maximum strength. Strength training for these individuals can improve their muscle function and mass, however, the biological processes involved in these improvements remain unknown. OBJECTIVE: This exploratory study aims at identifying the proteomic biomarkers and variables associated with the muscle proteome changes induced by training in DM1 individuals. METHODS: An ion library was developed from liquid chromatography-tandem mass spectrometry proteomic analyses of Vastus Lateralis muscle biopsies collected in 11 individuals with DM1 pre-and post-training. RESULTS: The proteomic analysis showed that the levels of 44 proteins were significantly modulated. A literature review (PubMed, UniProt, PANTHER, REACTOME) classified these proteins into biological sub-classes linked to training-induced response, including immunity, energy metabolism, apoptosis, insulin signaling, myogenesis and muscle contraction. Linear models identified key variables explaining the proteome modulation, including atrophy and hypertrophy factors. Finally, six proteins of interest involved in myogenesis, muscle contraction and insulin signaling were identified: calpain-3 (CAN3; Muscle development, positive regulation of satellite cell activation), 14-3-3 protein epsilon (1433E; Insulin/Insulin-like growth factor, PI3K/Akt signaling), myosin-binding protein H (MYBPH; Regulation of striated muscle contraction), four and a half LIM domains protein 3 (FHL3; Muscle organ development), filamin-C (FLNC; Muscle fiber development) and Cysteine and glycine-rich protein 3 (CSRP3). CONCLUSION: These findings may lead to the identification for DM1 individuals of novel muscle biomarkers for clinical improvement induced by rehabilitation, which could eventually be used in combination with a targeted pharmaceutical approach to improving muscle function, but further studies are needed to confirm those results.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".