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Contact information


marissa.mueller@balliol.ox.ac.uk

Social media

Research groups

Collaborators

Marissa Mueller

Postgraduate Student

3D printing; assisting with and performing graft operations; analyzing post-implantation cortical sections (e.g. immunohistochemistry and calcium imaging)

Biography

Marissa is from the small town of Petrolia, Ontario, Canada. She earned her Bachelor of Science in Engineering (Cellular) from the University of Iowa where she competed as an NCAA D1 Track and Field athlete (Javelin). After becoming involved in undergraduate research on accelerometer algorithms, she was recognized as a National Academy of Engineering Grand Challenges Scholar and at global conferences for her scientific contributions. Having also been on the pre-medicine track, she has been accepted to Harvard Medical School and since deferred matriculation for her duration of study at Oxford. Marissa is currently reading for the MSc in Neuroscience and intends to extend her current research through doctoral training. She hopes her work will help demystify the molecular mechanisms, clinical applications, and ethical implications of regenerative technologies in neuroscience.

Research Interests

The Molnar lab’s association with the 3D Printing for Brain Repair project takes place is in collaboration with the labs of Prof Francis Szele and Prof Hagan Bayley. This work investigates whether human induced pluripotent stem cells can be 3D-printed to structurally resemble cortex architecture, show functional assimilation in mouse model systems, and eventually manifest in therapeutic application. This involves four main steps: generating hiPSC-derived neurons and glia; pre-organizing these cells into cortical columns using 3D-printing; in vivo construct culture; and implantation into mouse models of traumatic brain injury. Future tests, through printing and implantation, may include assessing the effects of bioink protein coating on extracellular matrix interactions. In doing so, questions involving the effects of 3D-printed droplet patterning and intrinsic hiPSC distribution can be analyzed.