Project description:The advent of high-throughput measurements of gene expression and bioinformatics analysis methods offers new ways to study gene expression patterns. The primary goal of this study was to determine the time sequence for gene expression in a bone subjected to mechanical loading, during key periods of the bone formation process, including expression of matrix-related genes, the appearance of active osteoblasts, and bone desensitization. A standard model for bone loading was employed in which the right forelimb was loaded axially for three minutes per day, while the left forearm served as a non-loaded, contralateral control. We evaluated loading-induced gene expression over a time course of 4 hours to 32 days after the first loading session. Six distinct, time-dependent patterns of gene expression were identified over the time course and categorized into three primary clusters: genes upregulated early in the time course, genes upregulated during matrix formation, and genes downregulated during matrix formation. Genes were then grouped based on function and/or signaling pathways. Many gene groups known to be important in loading-induced bone formation were identified within the clusters, including AP-1-related genes in the early response cluster, matrix-related genes in the upregulated gene clusters, and Wnt/?-catenin signaling pathway inhibitors in the downregulated gene clusters. Several novel gene groups were identified as well, including chemokine-related genes which were upregulated early but downregulated later in the time course, solute carrier genes which were both up- and downregulated, and muscle-related genes which were primarily downregulated. Time Course with 11 time points, each plus & minus mechanical stimulation with 5 replicates per experimental group (except 12d group which has 4 replicates). Daily mechanical loading was applied to the forearm (24 hours between loading sessions), and ulnae were sampled at indicated time points (4h, 12h, 1d, 2d, 4d, 6d, 8d, 12d, 16d, 24d, or 32d).

Project description:Proctor2016 - Circadian rhythm of PTH and the dynamics of signaling molecules on bone remodeling This model is described in the article: Simulated Interventions to Ameliorate Age-Related Bone Loss Indicate the Importance of Timing. Proctor CJ, Gartland A. Front Endocrinol (Lausanne) 2016; 7: 61 Abstract: Bone remodeling is the continuous process of bone resorption by osteoclasts and bone formation by osteoblasts, in order to maintain homeostasis. The activity of osteoclasts and osteoblasts is regulated by a network of signaling pathways, including Wnt, parathyroid hormone (PTH), RANK ligand/osteoprotegrin, and TGF-?, in response to stimuli, such as mechanical loading. During aging there is a gradual loss of bone mass due to dysregulation of signaling pathways. This may be due to a decline in physical activity with age and/or changes in hormones and other signaling molecules. In particular, hormones, such as PTH, have a circadian rhythm, which may be disrupted in aging. Due to the complexity of the molecular and cellular networks involved in bone remodeling, several mathematical models have been proposed to aid understanding of the processes involved. However, to date, there are no models, which explicitly consider the effects of mechanical loading, the circadian rhythm of PTH, and the dynamics of signaling molecules on bone remodeling. Therefore, we have constructed a network model of the system using a modular approach, which will allow further modifications as required in future research. The model was used to simulate the effects of mechanical loading and also the effects of different interventions, such as continuous or intermittent administration of PTH. Our model predicts that the absence of regular mechanical loading and/or an impaired PTH circadian rhythm leads to a gradual decrease in bone mass over time, which can be restored by simulated interventions and that the effectiveness of some interventions may depend on their timing. This model is hosted on BioModels Database and identified by: BIOMD0000000612. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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