five

DataSheet3_Effect of Tension on Human Periodontal Ligament Cells: Systematic Review and Network Analysis.PDF

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/DataSheet3_Effect_of_Tension_on_Human_Periodontal_Ligament_Cells_Systematic_Review_and_Network_Analysis_PDF/16457046
下载链接
链接失效反馈
官方服务:
资源简介:
Orthodontic tooth movement is based on the remodeling of tooth-surrounding tissues in response to mechanical stimuli. During this process, human periodontal ligament cells (hPDLCs) play a central role in mechanosensing and mechanotransduction. Various in vitro models have been introduced to investigate the effect of tension on hPDLCs. They provide a valuable body of knowledge on how tension influences relevant genes, proteins, and metabolites. However, no systematic review summarizing these findings has been conducted so far. Aim of this systematic review was to identify all related in vitro studies reporting tension application on hPDLCs and summarize their findings regarding force parameters, including magnitude, frequency and duration. Expression data of genes, proteins, and metabolites was extracted and summarized. Studies’ risk of bias was assessed using tailored risk of bias tools. Signaling pathways were identified by protein-protein interaction (PPI) networks using STRING and GeneAnalytics. According to our results, Flexcell Strain Unit® and other silicone-plate or elastic membrane-based apparatuses were mainly adopted. Frequencies of 0.1 and 0.5 Hz were predominantly applied for dynamic equibiaxial and uniaxial tension, respectively. Magnitudes of 10 and 12% were mostly employed for dynamic tension and 2.5% for static tension. The 10 most commonly investigated genes, proteins and metabolites identified, were mainly involved in osteogenesis, osteoclastogenesis or inflammation. Gene-set enrichment analysis and PPI networks gave deeper insight into the involved signaling pathways. This review represents a brief summary of the massive body of knowledge in this field, and will also provide suggestions for future researches on this topic.
创建时间:
2021-08-27
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作