Calcium and the damage pathways in muscular dystrophyThis article is one of a selection of papers published in this special issue on Calcium Signaling.
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a severe muscle-wasting disease caused by the absence of the cytoskeletal protein dystrophin. Experiments on the mdx mouse, a model of DMD, have shown that mdx muscles are particularly susceptible to stretch-induced damage. In this review, we discuss evidence showing that a series of stretched contractions of mdx muscle fibres causes a prolonged increase in resting intracellular calcium concentration ([Ca2+]i). The rise in [Ca2+]i is caused by Ca2+ entry through a class of stretch-activated channels (SACNSC) for which one candidate gene is TRPC1. We review the evidence for activation of SACNSC in muscle by reactive oxygen species (ROS) and suggest that stretch-induced ROS production is part of the pathway that triggers increased channel activity. When the TRPC1 gene was transfected into C2 myoblasts, expression occurred throughout the cell. Only when the TRPC1 gene was coexpressed with caveolin-3 did the TRPC1 protein express in the membrane. When TRPC1 was expressed in the membrane, it could be activated by ROS to produce Ca2+ entry and this entry was inhibited by PP2, an inhibitor of src kinase. These results suggest that stretched contractions activate ROS production, which activates src kinase. Activity of this kinase causes opening of SACNSC and allows Ca2+ entry. This pathway appears to be a significant cause of muscle damage in DMD.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".