ArticlebioRxiv : the preprint server for biology2024
High resolution kinematic approach for quantifying impaired mobility of dystrophic zebrafish larvae.
Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
9 authors.
Funding
Abstract
Dystrophin-deficient zebrafish larvae are a small, genetically tractable vertebrate model of Duchenne muscular dystrophy well suited for early stage therapeutic development. However, current approaches for evaluating their impaired mobility, a physiologically relevant therapeutic target, are characterized by low resolution and high variability. To address this, we used high speed videography and deep learning-based markerless motion capture to develop linked-segment models of larval escape response (ER) swimming. Kinematic models provided repeatable, high precision estimates of larval ER performance. Effect sizes for ER peak instantaneous acceleration and speed, final displacement, and ER distance were 2 to 3.5 standard deviations less for dystrophin-deficient mutants vs. wild-types. Further analysis revealed that mutants swam slower because of a reduction in their tail stroke frequency with little change in tail stroke amplitude. Kinematic variables were highly predictive of the dystrophic phenotype with ≤ 3% of larvae misclassified by random forest and support vector machine models. Tail kinematics also performed as well as
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