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Exploring the Impact of Sclerostin Antibody Treatment on Bone Remodeling through Single-Cell Mechanomics Cluster Analysis
Bone exhibits a remarkable ability to adapt its microstructure in response to mechanical and metabolic demands. This process involves a dynamic balance between bone-forming osteoblasts and bone-resorbing osteoclasts, with osteocytes playing a crucial role in signaling micro-mechanical cues. Disruptions in these mechanisms, as seen in conditions like postmenopausal osteoporosis, lead to decreased bone density and increased fracture risk. Sclerostin is pivotal in determining bone formation or resorption in response to mechanical stimuli and is targeted by FDA-approved osteoporosis medications. However, the drug's mechanism and its interaction with mechanical loading remain unclear. This project aims to investigate bone's response to sclerostin antibody treatment and uncover the cellular mechanisms governing bone adaptation using single-cell mechanomics cluster analysis.
Bone undergoes remarkable ability to continuously adapt its internal trabecular microstructure in response to both mechanical and metabolic demands. Bone remodeling is an intricate process characterized by a dynamic equilibrium between building bone forming cells osteoblasts and bone resorbing cells osteoclasts. Osteocytes are thought to have a pivotal role in transmitting localized micromechanical signals to the effector cells, including osteoblasts and osteoclasts. In postmenopausal osteoporosis or metabolic disorders, these bone cells experience a disruption in their regulatory mechanisms, leading to a decrease in bone density and an increased risk of fractures. Sclerostin plays an essential role in signalling the specific requirements for cellular bone formation or resorption in response to mechanical stimuli. Moreover, Sclerostin antibodies, an FDA-approved medication for osteoporosis, suppress bone resorption and enhance bone formation. However, the mechanism of action of the drug and the impact of additional mechanical loading remain unknown.
Therefore, the aim of the project is to investigate the bone response to sclerostin-antibody treatment and unravel the cellular mechanisms that influence the loading regime of bone using single-cell mechanomics cluster analysis.
**What we expect:**
• You have a Bachelor's or Master's degree in Bioinformatics, Data Science, Systems Biology, Physics, Mathematics, or any other relevant discipline
• Strong knowledge and interest in image analysis, machine learning, data mining, statistics, and quantitative data analysis
• Working knowledge in Python/R and Parallel computing
• Strong communication, and writing skills, and ability to work in interdisciplinary group
Bone undergoes remarkable ability to continuously adapt its internal trabecular microstructure in response to both mechanical and metabolic demands. Bone remodeling is an intricate process characterized by a dynamic equilibrium between building bone forming cells osteoblasts and bone resorbing cells osteoclasts. Osteocytes are thought to have a pivotal role in transmitting localized micromechanical signals to the effector cells, including osteoblasts and osteoclasts. In postmenopausal osteoporosis or metabolic disorders, these bone cells experience a disruption in their regulatory mechanisms, leading to a decrease in bone density and an increased risk of fractures. Sclerostin plays an essential role in signalling the specific requirements for cellular bone formation or resorption in response to mechanical stimuli. Moreover, Sclerostin antibodies, an FDA-approved medication for osteoporosis, suppress bone resorption and enhance bone formation. However, the mechanism of action of the drug and the impact of additional mechanical loading remain unknown. Therefore, the aim of the project is to investigate the bone response to sclerostin-antibody treatment and unravel the cellular mechanisms that influence the loading regime of bone using single-cell mechanomics cluster analysis.
**What we expect:**
• You have a Bachelor's or Master's degree in Bioinformatics, Data Science, Systems Biology, Physics, Mathematics, or any other relevant discipline
• Strong knowledge and interest in image analysis, machine learning, data mining, statistics, and quantitative data analysis
• Working knowledge in Python/R and Parallel computing
• Strong communication, and writing skills, and ability to work in interdisciplinary group
The primary objective of this project is to conduct cluster analysis on data from a micro-multiphysics agent-based model. This analysis aims to identify events related to bone formation, resorption, and quiescence within the entire trabecular region, considering both the mechanical loading of the bone and the impact of Sclerostin antibody treatment.
The primary objective of this project is to conduct cluster analysis on data from a micro-multiphysics agent-based model. This analysis aims to identify events related to bone formation, resorption, and quiescence within the entire trabecular region, considering both the mechanical loading of the bone and the impact of Sclerostin antibody treatment.
Please contact me to get more detailed information about the project by email or reach out in person at GLC H 20.1, Gloriastrasse 37/39, 8092 Zürich, Switzerland.
Email: amit.singh@hest.ethz.ch and friederike.schulte@hest.ethz.ch
LinkedIn: https://www.linkedin.com/in/amit-singh-63373417/
Please contact me to get more detailed information about the project by email or reach out in person at GLC H 20.1, Gloriastrasse 37/39, 8092 Zürich, Switzerland.
Email: amit.singh@hest.ethz.ch and friederike.schulte@hest.ethz.ch
