Demographic models of the evolution of cooperation

Demographic models of the evolution of cooperation

Advisor/s

A/Prof Ulf Schmitz, Dr Daniel Xing, Prof Andreas Lopata

College or Research Centre

College of Medicine & Dentistry; College of Public Health, Medical & Veterinary Science

Summary of Project

Join our dynamic research team at JCU and the Townsville Cancer Centre (TCC) for an exciting HDR (Higher Degree by Research) project that merges cutting-edge technology with critical clinical applications. Our umbrella project encompasses two groundbreaking research initiatives aimed at improving cancer treatment outcomes and patient care. Project 1: Enhancing Glioblastoma Treatment with Magnetic Resonance and Radiotherapy Glioblastoma (GBM) remains one of the most aggressive brain cancers, with limited survival rates despite recent advances in treatment. Our research focuses on the novel application of tumour treating fields and the integration of a magnetic resonance linear accelerator (MRL) to explore the biological effects of combining magnetic fields with ionizing radiation. We aim to uncover how these combined modalities impact tumour and immune cell interactions, ultimately seeking to improve GBM treatment efficacy. Project 2: Developing Blood-Based Surveillance for HPV-Associated Oropharyngeal Cancer Human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (HPV-OPSCC) presents unique challenges in post-treatment surveillance, particularly for patients in remote regions. Our research aims to develop and validate a blood-based circulating HPV-DNA (cHPV-DNA) test using next-generation sequencing (NGS). This innovative approach will enable earlier detection of recurrent disease, reduce patient burden, and improve survival outcomes for HPV-OPSCC patients.

Cooperation has driven many major transitions in the evolution of life, such as the transition from solitary individuals to group living and social societies. Cooperative breeding is an extreme example of group living in which some individuals forego their own opportunity to produce offspring and instead help other group members to reproduce. Kin selection is thought to be an important driver of such behaviour when the help is directed towards genetically related individuals. However, there may also be other more direct benefits of group living (e.g. increased foraging or protection in groups) that do not include kin selection considerations. Furthermore, it is often ignored that there are also costs to group living due to competition for resources. To determine the relative important of (i) direct benefits and costs of group living and (ii) indirect benefits and costs due to kin selection, one needs to determine the overall inclusive fitness outcomes for individuals. Current theoretical inclusive fitness models have proven to be challenging to apply to empirical data, as they do not align with what can be measured in the field. This project could develop demographic models of inclusive fitness that allow us to determine the selective forces on behavioural decisions on group living, and decompose the contribution of both direct and indirect costs and benefits to the evolution of group living. Matrix population models and the use of reproductive values as an integrative fitness measure can be applied within the context of kin selection theory, such that they are parameterizable with empirical data. Empirical data from a long-term study on Australian cooperatively breeding birds is available to look at the selective forces on decisions to join and leave groups, and how this varies among group members (intra-group conflict) and depends on the environment (how does climate change affect group living?).

Key Words

brain cancer; head and neck cancer; radiation oncology; biomarker; bioinformatics next generation sequencing

Would suit an applicant who

We invite motivated students with a passion for oncology, molecular biology, and innovative technology to apply. This is a unique opportunity to contribute to transformative research with the potential to significantly impact patient care and treatment outcomes.

has an interest in ecological modelling.

Updated: 15 Nov 2021