Targeted inhibition of Ca2+/calmodulin signaling exacerbates the dystrophic phenotype in mdx mouse muscle
Bibliographic record
Abstract
In this study, we crossbred mdx mice with transgenic mice expressing a small peptide inhibitor for calmodulin (CaM), known as the CaM-binding protein (CaMBP), driven by the slow fiber-specific troponin I slow promoter. This strategy allowed us to determine the impact of interfering with Ca(2+)/CaM-based signaling in dystrophin-deficient slow myofibers. Consistent with impairments in the Ca(2+)/CaM-regulated enzymes calcineurin and Ca(2+)/CaM-dependent kinase, the nuclear accumulation of nuclear factor of activated T-cell c1 and myocyte enhancer factor 2C was reduced in slow fibers from mdx/CaMBP mice. We also detected significant reductions in the levels of peroxisome proliferator gamma co-activator 1alpha and GA-binding protein alpha mRNAs in slow fiber-rich soleus muscles of mdx/CaMBP mice. In parallel, we observed significantly lower expression of myosin heavy chain I mRNA in mdx/CaMBP soleus muscles. This correlated with fiber-type shifts towards a faster phenotype. Examination of mdx/CaMBP slow muscle fibers revealed significant reductions in A-utrophin, a therapeutically relevant protein that can compensate for the lack of dystrophin in skeletal muscle. In accordance with lower levels of A-utrophin, we noted a clear exacerbation of the dystrophic phenotype in mdx/CaMBP slow fibers as exemplified by several pathological indices. These results firmly establish Ca(2+)/CaM-based signaling as key to regulating expression of A-utrophin in muscle. Furthermore, this study illustrates the therapeutic potential of using targets of Ca(2+)/CaM-based signaling as a strategy for treating Duchenne muscular dystrophy (DMD). Finally, our results further support the concept that strategies aimed at promoting the slow oxidative myofiber program in muscle may be effective in altering the relentless progression of 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".