title: A Murine Model of Robotic Training to Evaluate Skeletal Muscle Recovery after Injury.
abstract: In vivo studies have suggested that motor exercise can improve muscle regeneration after injury. Nevertheless, preclinical investigations still lack reliable tools to monitor motor performance over time and to deliver optimal training protocols to maximize force recovery. Here, we evaluated the utility of a murine robotic platform (i) to detect early impairment and longitudinal recovery after acute skeletal muscle injury and (ii) to administer varying intensity training protocols to enhance forelimb motor performance.
  
  
  
  A custom-designed robotic platform was used to train mice to perform a forelimb retraction task. After an acute injury to bilateral biceps brachii muscles, animals performed a daily training protocol in the platform at high (HL) or low (LL) loading levels over the course of 3 wk. Control animals were not trained (NT). Motor performance was assessed by quantifying force, time, submovement count, and number of movement attempts to accomplish the task. Myofiber number and cross-sectional area at the injury site were quantified histologically.
  
  
  
  Two days after injury, significant differences in the time, submovement count, number of movement attempts, and exerted force were observed in all mice, as compared with baseline values. Interestingly, the recovery time of muscle force production differed significantly between intervention groups, with HL group showing a significantly accelerated recovery. Three weeks after injury, all groups showed motor performance comparable with baseline values. Accordingly, there were no differences in the number of myofibers or average cross-sectional area among groups after 3 wk.
  
  
  
  Our findings demonstrate the utility of our custom-designed robotic device for the quantitative assessment of skeletal muscle function in preclinical murine studies. Moreover, we demonstrate that this device may be used to apply varying levels of resistance longitudinally as a means manipulate physiological muscle responses.
authors.affiliation: 1Scuola Superiore Sant'Anna, Translational Neural Engineering Area, The BioRobotics Institute, Pisa, ITALY; 2Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA; 3McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA; 4Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA; 5Department of Rehabilitation Science and Technology, University of Pittsburgh, Pittsburgh, PA; and 6Ecole Polytechnique Federale de Lausanne (EPFL), Bertarelli Foundation Chair in Translational NeuroEngineering Laboratory, Center for Neuroprosthetics and Institute of Bioengineering, Lausanne, SWITZERLAND.
authors.forename: Stefano
authors.initials: S
authors.lastname: Lai
authors.forename: Alessandro
authors.initials: A
authors.lastname: Panarese
authors.forename: Ross
authors.initials: R
authors.lastname: Lawrence
authors.forename: Michael L
authors.initials: ML
authors.lastname: Boninger
authors.forename: Silvestro
authors.initials: S
authors.lastname: Micera
authors.forename: Fabrisia
authors.initials: F
authors.lastname: Ambrosio
mesh_terms: D000818:Animals; D005552:Forelimb / Q000293:injuries; D008297:Male; D008810:Mice, Inbred C57BL; D023421:Models, Animal; D018482:Muscle, Skeletal / Q000293:injuries* / Q000502:physiology*; D010805:Physical Conditioning, Animal; D026741:Physical Therapy Modalities; D012038:Regeneration; D012371:Robotics; D014945:Wound Healing