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In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing

机译:体内下肢肌肉损伤后转录动力学的监测实现了治疗的定量分类

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Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual’s muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3?hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.
机译:创伤性下肢肌肉骨骼损伤普遍存在于运动员和军人中,通常情况下,个人在完全康复之前会恢复活动,从而增加了额外受伤和慢性疼痛的易感性。监测肌肉骨骼损伤后的愈合进展通常涉及不同类型的成像,但是这些方法存在若干缺点。从受伤部位隔离和分析成绩单将消除这些缺陷,并提供有关受伤后肌肉再生潜力的枚举性见解。在这项研究中,对小鼠模型进行了创伤性损伤,并使用高通量RNA测序(RNA-Seq)从3小时到1个月检查了愈合过程。对全基因组数据集的全面解剖显示,受伤的部位是一个动态的异质环境,由多种细胞类型和成千上万的基因组成,这些基因在高度调控的网络中发生明显的表达变化。四种独立的方法用于确定损伤后不同时间点最具特征的基因,同工型和遗传途径的集合,并开发了两种新颖的方法对不同时间点的受伤组织进行分类。这些结果凸显了使用高通量测序通过转录谱分析定量追踪原位愈合进展的可能性。

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