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Environmental factors contribute to skeletal muscle and spinal cord regeneration
Published in David M. Gardiner, Regenerative Engineering and Developmental Biology, 2017
Ophelia Ehrlich, Yona Goldshmit, Peter Currie
Skeletal muscle is a paradigmatic example of a tissue harboring an adult muscle stem cell niche. Skeletal muscle stem cells are mononucleate cells termed satellite cells, as they are located adjacent to muscle fibers underneath the basement membrane surrounding individual fibers (Mauro 1961; Hack et al. 2000; Guyon et al. 2005; Bunnell et al. 2008). Quiescent muscle stem cells become stimulated by muscle damage, and the local microenvironment is crucial in modulating the muscle stem cell activation. Extracellular matrix molecules and secreted factors have multiple interactions with stem cells that regulate cell fate and determine if they are to proliferate, migrate, differentiate, or self-renew (Hynes 1987; Serrano and Muñoz-Cánoves 2010; Dumont et al. 2015a). Activated satellite cells re-enter the cell cycle to generate a population of daughter cells that commit to differentiate to produce myoblasts that will fuse to other fibers (Shimaoka and Springer 2003; Figeac et al. 2007; Keefe et al. 2015). Pax7 is the most commonly used marker of satellite cells; however, there are many other markers that are used to identify these cells or a subset of them, including c-met, Pax3, and integrin-α7 (Williams et al. 1994; Clark and Brugge 1995; Giancotti and Ruoslahti 1999; Seale et al. 2000; Takada et al. 2007; Morgan and Zammit 2010). On injury, the process of muscle regeneration includes phases of inflammation, fiber renewal, and fibrosis (Pierschbacher and Ruoslahti 1983; Hawke 2001).
GASN: gamma distribution test for driver genes identification based on similarity networks
Published in Connection Science, 2023
Dazhi Jiang, Runguo Wei, Zhihui He, Senlin Lin, Cheng Liu, Yingqing Lin
Notice that most existing methods to evaluate the functional impact of mutations always focus on non-synonymous somatic mutations, such as mutation suppressors, polymers, and screening factors. Synonymous mutations and some mutations affect proteins. If nonsense mutations and small index fission deletion, the average FIS of mutations with silencing and ineffective effects cannot be calculated from the mutant synthon. In general, silent, non-coding, non-silent, and null mutations have a progressively more significant effect on proteins. Silent mutation does not affect the amino acids of protein sequence, and its FIS should be the smallest. Although non-coding mutation does not change amino acids, it will promote the development of cancer cells. For example, the non-coding mutation in the 3'-untranslated region (3'-UTR) can change the binding efficiency of microRNA (miRNA), resulting in the loss/increase of gene function (Akdeli et al., 2014). The non-silent mutation changes the amino acid sequence of the protein and has a significant functional impact on protein, accelerating tumour progression. For example, the R132 mutation in the IDH1 gene was found to be associated with early glioma formation (Cui et al., 2016). Null mutation, including “nonsense mutation”, “splice site”, “frameshift insertion”, and “frameshift deletion” will lead to continuous changes in amino acid sequences and have a more significant impact on organisms. For example, Waldenberg syndrome is caused by splicing mutation of PAX3 (Barber et al., 1999), and exon mutation is caused by nonsense/frameshift mutation of DMD gene, resulting in Becker muscular dystrophy (Al-Zaidy et al., 2015). Based on the above analysis, when the average FIS effect t cannot be calculated, the deletion FIS of mutation r with mutation effect t can be obtained as shown in Equation (4): The observed FIS of gene is obtained by accumulating the FIS of all mutation effects t of cumulative mutation r as follows: where is the total number of all mutation effects of mutation r.