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1.
Int J Mol Sci ; 22(12)2021 Jun 16.
Article in English | MEDLINE | ID: mdl-34208464

ABSTRACT

Piezo channels are mechanosensitive ion channels located in the cell membrane and function as key cellular mechanotransducers for converting mechanical stimuli into electrochemical signals. Emerged as key molecular detectors of mechanical forces, Piezo channels' functions in bone have attracted more and more attention. Here, we summarize the current knowledge of Piezo channels and review the research advances of Piezo channels' function in bone by highlighting Piezo1's role in bone cells, including osteocyte, bone marrow mesenchymal stem cell (BM-MSC), osteoblast, osteoclast, and chondrocyte. Moreover, the role of Piezo channels in bone diseases is summarized.


Subject(s)
Bone and Bones/metabolism , Ion Channels/physiology , Animals , Bone Diseases , Chondrocytes/metabolism , Disease Susceptibility , Humans , Ion Channel Gating/drug effects , Ion Channels/agonists , Ion Channels/antagonists & inhibitors , Ion Channels/chemistry , Mechanotransduction, Cellular , Osteoblasts/metabolism , Osteoclasts/metabolism , Osteocytes/metabolism , Structure-Activity Relationship
2.
Guang Pu Xue Yu Guang Pu Fen Xi ; 33(9): 2478-82, 2013 Sep.
Article in Chinese | MEDLINE | ID: mdl-24369656

ABSTRACT

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

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