Two zebrafish <i>cacna1s</i> loss-of-function variants provide models of mild and severe <i>CACNA1S</i>-related myopathy
Bibliographic record
Abstract
CACNA1S-related myopathy, due to pathogenic variants in the CACNA1S gene, is a recently described congenital muscle disease. Disease associated variants result in loss of gene expression and/or reduction of Cav1.1 protein stability. There is an incomplete understanding of the underlying disease pathomechanisms and no effective therapies are currently available. A barrier to the study of this myopathy is the lack of a suitable animal model that phenocopies key aspects of the disease. To address this barrier, we generated knockouts of the two zebrafish CACNA1S paralogs, cacna1sa and cacna1sb. Double knockout fish exhibit severe weakness and early death, and are characterized by the absence of Cav1.1 α1 subunit expression, abnormal triad structure, and impaired excitation-contraction coupling, thus mirroring the severe form of human CACNA1S-related myopathy. A double mutant (cacna1sa homozygous, cacna1sb heterozygote) exhibits normal development, but displays reduced body size, abnormal facial structure, and cores on muscle pathologic examination, thus phenocopying the mild form of human CACNA1S-related myopathy. In summary, we generated and characterized the first cacna1s zebrafish loss-of-function mutants, and show them to be faithful models of severe and mild forms of human CACNA1S-related myopathy suitable for future mechanistic studies and therapy development.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".