Balancing the process of bone formation and resorption is important in the maintenance of healthy bone. Therefore, the discovery of novel factors that can regulate bone metabolism remains needed. Irisin is a newly identified hormone-like peptide. Recent studies have reported the involvement of irisin in many physiological and pathological conditions with bone mineral density changes, including osteopenia and osteoporotic fractures. In this study, we generated the first line of Osx-Cre:FNDC5/ irisin KO mice, in which FNDC5/irisin was specifically deleted in the osteoblast lineage. Gene and protein expressions of irisin were remarkably decreased in bones but no significant differences in other tissues were observed in knockout mice. FNDC5/irisin deficient mice showed a lower bone density and significantly delayed bone development and mineralization from early-stage to adulthood. Our phenotypical analysis exhibited decreased osteoblast-related gene expression and increased osteoclast-related gene expression in bone tissues, and reduced adipose tissue browning due to bone-born irisin deletion. By harvesting and culturing MSCs from the knockout mice, we found that osteoblastogenesis was inhibited and osteoclastogenesis was increased. By using irisin stimulated wildtype primary cells as a gainof-function model, we further revealed the effects and mechanisms of irisin on promoting osteogenesis and inhibiting osteoclastogenesis in vitro. In addition, positive effects of exercise, including bone strength enhancement and body weight loss were remarkably weakened due to irisin deficiency. Interestingly, these changes can be rescued by supplemental administration of recombinant irisin during exercise. Our study indicates that irisin plays an important role in bone metabolism and the crosstalk between bone and adipose tissue. Irisin represents a potential molecule for the prevention and treatment of bone metabolic diseases.
In this paper, the optimal output regulation problem for partially model-free heterogeneous linear multiagent systems with disturbance generated by an exosystem is addressed by using adaptive dynamic programming and double compensator method. The topology graph for the information exchange of the agents has a spanning tree. The dynamic of individual agent is assumed to be nonidentical and of different dimensions. One distributed compensator is designed to deal with the nonidentical agents, and the other compensator is used to handle the optimal performance index. By constructing the double compensator, the distributed feedback control laws are designed to make the output of each agent synchronize with the reference output and minimize the energy of the output error simultaneously. To overcome the lack of the dynamics knowledge of each agent, a novel online policy iteration algorithm is developed to obtain the optimal feedback gain matrix. Finally, two examples are presented to illustrate the effectiveness of our results.
In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph. The inverse optimal theory is developed by introducing the notion of partial stability. As a result, the necessary and sufficient conditions for inverse optimality are proposed. By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs. Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically. Finally, two examples are given to illustrate the effectiveness of the proposed methods.
SUMMARYThis paper presents a control algorithm for biped walking by extension of previous work in the fields of central pattern generator (CPG) and passive walking. The algorithm takes advantage of the passive dynamics of walking, assisting only when necessary with an intermittent sinusoidal oscillator. The parameterized oscillator is used to drive the hip joint; the triggering and ceasing of the oscillator during a walking cycle can be modulated by the sensory feedback. The results from simulation indicate a stable, efficient gait, and robustness against model inaccuracy and environmental variation. We also examine the effects of oscillator parameters and link parameters on the gait, and design a controller to suppress the bifurcation phenomenon based on the error of prior step periods.
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