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Exercise and physical activity are known to impart beneficial effects throughout the different stages of cancer treatment, including reduced risk of primary disease and prevention of secondary metastasis, for various types of cancers. Many pre-clinical studies on cancer patients have shown the positive outcomes of exercise not only on their general physiological conditions such as physical function, body composition and sleep, but also on tumour growth and metastasis.
Although a growing body of evidence indicates improved clinical outcomes from regular exercise in cancer patients, the underlying molecular mechanism of its beneficial effects on cancer prognosis is elusive. The impact of exercise on cellular metabolism is also more profound and quantitative than on other cellular networks. Thus, a detailed, systems-level mechanistic understanding of exercise on the metabolic behaviour of cancer cells can lead to developing exercise-based intervention strategies or treatment procedures for cancer patients.
This project, aims to apply both computational and experimental approaches in cancer systems biology and metabolic engineering to develop systems-level mathematical models of cancer cell metabolism for unveiling the underlying molecular mechanisms of the beneficial impact of exercise on the metabolic phenotypes of cancer cells.
The project will leverage systems-level, high throughput experimental ‘omics’ data from a 3D in vitro organoid model of cancer cells cocultured with skeletal muscle myotubes. In addition, state-of-the-art 13C metabolic flux analysis technique will be implemented to capture metabolic behaviour of cancer cells under exercised conditions. This information, together with a plethora of literature data will be used to develop the model that can ultimately lead to the development of exercise-based cancer treatment and prevention strategies.
This project provides an excellent opportunity to work with multidisciplinary research groups within the Chemical Engineering Department and in the School of Sport, Exercise and Health Sciences at Loughborough University. You will be joining a vibrant and multidisciplinary research community, focusing on tackling some of the most pressing and demanding societal challenges related to sustainability, environment and human health through harnessing the power of machine learning, systems biology, synthetic biology, and metabolic engineering. Due to the involvement of an industrial partner, the project offers the candidate a unique opportunity not only to learn and master cutting-edge research tools but also to obtain hands-on training in the industry.
Exercise and physical activity are known to impart beneficial effects throughout the different stages of cancer treatment, including reduced risk of primary disease and prevention of secondary metastasis, for various types of cancers. Many pre-clinical studies on cancer patients have shown the positive outcomes of exercise not only on their general physiological conditions such as physical function, body composition and sleep, but also on tumour growth and metastasis.
Although a growing body of evidence indicates improved clinical outcomes from regular exercise in cancer patients, the underlying molecular mechanism of its beneficial effects on cancer prognosis is elusive. The impact of exercise on cellular metabolism is also more profound and quantitative than on other cellular networks. Thus, a detailed, systems-level mechanistic understanding of exercise on the metabolic behaviour of cancer cells can lead to developing exercise-based intervention strategies or treatment procedures for cancer patients.
This project, aims to apply both computational and experimental approaches in cancer systems biology and metabolic engineering to develop systems-level mathematical models of cancer cell metabolism for unveiling the underlying molecular mechanisms of the beneficial impact of exercise on the metabolic phenotypes of cancer cells.
The project will leverage systems-level, high throughput experimental ‘omics’ data from a 3D in vitro organoid model of cancer cells cocultured with skeletal muscle myotubes. In addition, state-of-the-art 13C metabolic flux analysis technique will be implemented to capture metabolic behaviour of cancer cells under exercised conditions. This information, together with a plethora of literature data will be used to develop the model that can ultimately lead to the development of exercise-based cancer treatment and prevention strategies.
This project provides an excellent opportunity to work with multidisciplinary research groups within the Chemical Engineering Department and in the School of Sport, Exercise and Health Sciences at Loughborough University. You will be joining a vibrant and multidisciplinary research community, focusing on tackling some of the most pressing and demanding societal challenges related to sustainability, environment and human health through harnessing the power of machine learning, systems biology, synthetic biology, and metabolic engineering. Due to the involvement of an industrial partner, the project offers the candidate a unique opportunity not only to learn and master cutting-edge research tools but also to obtain hands-on training in the industry.
Admission Requirements
3.2+
6.5+
92+
Applicants will normally need to hold, or expect to gain, at least a 2:1 undergraduate degree (or UK equivalent) in Chemical Engineering, Bioengineering, Biotechnology, Bioinformatics, Computational Biology, Microbiology, Systems Biology, Synthetic Biology, or an appropriate Master’s degree.
10 Feb 2025
3 Years
Oct
Tuition fees
International
28,600
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Unveiling Molecular Mechanisms of the Beneficial Impact of Exercise on Cancer Metabolism PhD
Loughborough University, Loughborough, United Kingdom
# 201-250QS Subject Rankings
36 monthsProgram duration
28,600 Tuition Fee/year
10 Feb, 2025Application Deadline
Program overview
Main Subject
Engineering - Chemical
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Exercise and physical activity are known to impart beneficial effects throughout the different stages of cancer treatment, including reduced risk of primary disease and prevention of secondary metastasis, for various types of cancers. Many pre-clinical studies on cancer patients have shown the positive outcomes of exercise not only on their general physiological conditions such as physical function, body composition and sleep, but also on tumour growth and metastasis.
Although a growing body of evidence indicates improved clinical outcomes from regular exercise in cancer patients, the underlying molecular mechanism of its beneficial effects on cancer prognosis is elusive. The impact of exercise on cellular metabolism is also more profound and quantitative than on other cellular networks. Thus, a detailed, systems-level mechanistic understanding of exercise on the metabolic behaviour of cancer cells can lead to developing exercise-based intervention strategies or treatment procedures for cancer patients.
This project, aims to apply both computational and experimental approaches in cancer systems biology and metabolic engineering to develop systems-level mathematical models of cancer cell metabolism for unveiling the underlying molecular mechanisms of the beneficial impact of exercise on the metabolic phenotypes of cancer cells.
The project will leverage systems-level, high throughput experimental ‘omics’ data from a 3D in vitro organoid model of cancer cells cocultured with skeletal muscle myotubes. In addition, state-of-the-art 13C metabolic flux analysis technique will be implemented to capture metabolic behaviour of cancer cells under exercised conditions. This information, together with a plethora of literature data will be used to develop the model that can ultimately lead to the development of exercise-based cancer treatment and prevention strategies.
This project provides an excellent opportunity to work with multidisciplinary research groups within the Chemical Engineering Department and in the School of Sport, Exercise and Health Sciences at Loughborough University. You will be joining a vibrant and multidisciplinary research community, focusing on tackling some of the most pressing and demanding societal challenges related to sustainability, environment and human health through harnessing the power of machine learning, systems biology, synthetic biology, and metabolic engineering. Due to the involvement of an industrial partner, the project offers the candidate a unique opportunity not only to learn and master cutting-edge research tools but also to obtain hands-on training in the industry.
Program overview
Main Subject
Engineering - Chemical
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Exercise and physical activity are known to impart beneficial effects throughout the different stages of cancer treatment, including reduced risk of primary disease and prevention of secondary metastasis, for various types of cancers. Many pre-clinical studies on cancer patients have shown the positive outcomes of exercise not only on their general physiological conditions such as physical function, body composition and sleep, but also on tumour growth and metastasis.
Although a growing body of evidence indicates improved clinical outcomes from regular exercise in cancer patients, the underlying molecular mechanism of its beneficial effects on cancer prognosis is elusive. The impact of exercise on cellular metabolism is also more profound and quantitative than on other cellular networks. Thus, a detailed, systems-level mechanistic understanding of exercise on the metabolic behaviour of cancer cells can lead to developing exercise-based intervention strategies or treatment procedures for cancer patients.
This project, aims to apply both computational and experimental approaches in cancer systems biology and metabolic engineering to develop systems-level mathematical models of cancer cell metabolism for unveiling the underlying molecular mechanisms of the beneficial impact of exercise on the metabolic phenotypes of cancer cells.
The project will leverage systems-level, high throughput experimental ‘omics’ data from a 3D in vitro organoid model of cancer cells cocultured with skeletal muscle myotubes. In addition, state-of-the-art 13C metabolic flux analysis technique will be implemented to capture metabolic behaviour of cancer cells under exercised conditions. This information, together with a plethora of literature data will be used to develop the model that can ultimately lead to the development of exercise-based cancer treatment and prevention strategies.
This project provides an excellent opportunity to work with multidisciplinary research groups within the Chemical Engineering Department and in the School of Sport, Exercise and Health Sciences at Loughborough University. You will be joining a vibrant and multidisciplinary research community, focusing on tackling some of the most pressing and demanding societal challenges related to sustainability, environment and human health through harnessing the power of machine learning, systems biology, synthetic biology, and metabolic engineering. Due to the involvement of an industrial partner, the project offers the candidate a unique opportunity not only to learn and master cutting-edge research tools but also to obtain hands-on training in the industry.
Admission Requirements
Tuition fees
International
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
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Advanced Modelling of Carbon Black Morphology in Methane Pyrolysis for CO2-Free Hydrogen Production PhD
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Agricultural Robot Navigation in Complex Farm and Rugged Terrain Environments Using Deep Reinforcement Learning AI. PhD
An Integrated Approach for Damage Identification in Composite Materials PhD
Antimicrobial Gels for Biomedical Applications PhD
Application of Machine Learning for Job Scheduling in Computing Clouds PhD
Artificial Intelligence-Assisted Modular Metabolic Engineering for Netzero Commodity Manufacture PhD
Beyond Normal - Proteins in Alien Environments PhD
BioDyes - Expanding the Scope of Renewed and Renewable Textiles
Building Community Climate Resilience with Large Language Models and Remote Sensing PhD
CSC PhD Studentship in Exploring Advanced Materials for Wearable Sensors PhD
Catalytic And Adsorption Properties Of Polymeric Silver And Zinc Oxide Stabilized Nanocomposites Decorated On Reduced Graphene Oxide PhD
Cell Mechanics and Tumour Growth PhD
Cellular Automaton to Model Rapid Crystal Growth and Recrystallisation PhD
Cognitive Monitoring of Human Operators using Multi-modal Artificial Intelligence PhD
Continuous Manufacturing Of Nano-Assemblies For Mrna Based Therapies And Vaccines: From Batch To Industry Scale PhD
Countering Cyberattacks in Autonomous Vehicles PhD
Cryptographic Primitives for Symmetric Cryptography PhD
Crystallisation with 3D Printing Template and Hydrogel Templates PhD
Data and AI Powered Turbulence Modelling for Fusion Energy Cooling Flows PhD
Design and fabrication Custom Foot Orthotics PhD
Design of Programmable Mechanical Metamaterials PhD
Developing Diffusion Models for Electric Vehicle: Spatial-temporal analysis and Policy Evaluation PhD
Developing Natural Surfactants from Biomass for Industrial Applications PhD
Development of New Digital Technologies and Generative Artificial Intelligence Tools For The Next Generation Green-By-Design and Sustainable Pharmaceuticals PhD
Development of Robust Wall Modelling for Practical Aerodynamic High Fidelity Prediction Phd
Dynamic Deformation, Damage and Fracture Of Composites PhD
Energy Efficiency Optimisation of Electric Vehicles In Dynamic Driving Scenarios PhD
Engineering New Materials for Solid-State Cooling Phd
Enhancing Human-Robot Interaction: Leveraging Artificial Intelligence for Emotional Intelligence in Robotics PhD
Unveiling Molecular Mechanisms of the Beneficial Impact of Exercise on Cancer Metabolism PhD
Using the Metabolome to Study Aging and Geroprotectors in 3D Cell Models PhD
Visual Data Mining on Proteins and Biomedicine Crystallisation PhD
Waste-derived Bioplastics for a Circular and Sustainable Food Packaging Economy PhD
Life Sciences and Medicine (6)
Adaptive and Predictive Computational Modelling of Biomaterials: A Digital Twin Framework for Next-Generation Personalised Healthcare PhD
Adaptive and Predictive Computational Modelling of Biomaterials: A Digital Twin Framework for Next-Generation Personalised Healthcare PhD
Biomarkers of Aging PhD
Biomarkers of Aging PhD
Developing Prescription Guidelines for Passive Heat Therapy PhD
Developing Prescription Guidelines for Passive Heat Therapy PhD
Does Socialised Real-Life Body Exposure Promote Body Image Positivity PhD
Does Socialised Real-Life Body Exposure Promote Body Image Positivity PhD
Energy Dissipation In Human Soft Tissue During Impacts PhD
Energy Dissipation In Human Soft Tissue During Impacts PhD
Natural Sciences (6)
Accelerated Screening and Synthesis of New Chemotherapeutic Agents for Pancreatic Cancer PhD
Accelerated Screening and Synthesis of New Chemotherapeutic Agents for Pancreatic Cancer PhD
Bespoke Organometallic Compounds for Anticancer Studies PhD
Bespoke Organometallic Compounds for Anticancer Studies PhD
Bio-based Sustainable Materials for Autonomous Thermal Management in Wearables PhD
Bio-based Sustainable Materials for Autonomous Thermal Management in Wearables PhD
Biomimmetic Catalytic Asymmetric Synthesis of the Bisorbicillinoids and Related Products PhD
Biomimmetic Catalytic Asymmetric Synthesis of the Bisorbicillinoids and Related Products PhD
Climate and Ecological Transitions Hub Studentship PhD
Climate and Ecological Transitions Hub Studentship PhD
Coherent State Methods in Spectral Asymptotics PhD
Coherent State Methods in Spectral Asymptotics PhD
Computational Modelling of Sustainable Alloys PhD
Designing Classroom Tasks To Improve Students’ Learning Of Mathematics PhD
Developing Novel Antibiofilm Coatings for Sustainable Biofilm-Free Surfaces PhD
Development of Hybrid Microcomb Sources with Topologically Protected Dark Resonances for Simultaneous Classical and Quantum PhD
Development of Novel Bicyclopentanes (BCP) Bioisosteres From Bench Stable [1.1.1]-Propellane Precursors PhD
Digital Twins for Biofilm Management PhD
Dispersionless Integrable Systems In 2+1 Dimensions PhD
Social Sciences and Management (6)
An Evaluation of Erasmus+ Sport Projects and Their Impact on EU Sport Policy Development PhD
An Evaluation of Erasmus+ Sport Projects and Their Impact on EU Sport Policy Development PhD
Climate Change, Work Design and Worker Wellbeing Phd
Climate Change, Work Design and Worker Wellbeing Phd
Communication and Social Change (CSC) Hub Studentship PhD
Communication and Social Change (CSC) Hub Studentship PhD
Enhancing Motivation in Sport and Exercise Contexts PhD
Enhancing Motivation in Sport and Exercise Contexts PhD
Out of School Youth Provision: An Analysis of Funding and Operational Resilience within the Sector PhD
Out of School Youth Provision: An Analysis of Funding and Operational Resilience within the Sector PhD