###Developing a new therapy for treatment-resistant depression: magnetomechanical stimulation of astrocytes facilitated by MRI-guided focused ultrasound
Project ID: 2228bd1088 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Division of Medicine
Lead Supervisor: Mark Lythgoe
Project Summary:
Treatment-resistant depression (TRD) is one of the biggest threats to wellbeing worldwide.
We have recently developed a novel technique, magnetomechanical stimulation (MMS) technology, which is a method for controlling brain activity with an improved prospect for clinical application than existing technologies.
Converging evidence show that the gliotransmitter ATP released by astrocytes in the medial prefrontal cortex (mPFC) have strong antidepressant effects.
This presents an opportunity to transform our recently developed magnetomechanical stimulation (MMS) technology, which can induce ATP release remotely and selectively from astrocytes, into a therapy for TRD. MMS involves attaching magnetic nanoparticles to astrocytes and applying a magnetic field to activate mechanosensitive ATP signalling pathways. We aim to utilise MRI-guided focused ultrasound (FUS) to temporarily open the blood-brain barrier in the mPFC and enable intravenously injected particles to exit the brain vasculature and bind to astrocytes, thereby making the procedure free of brain surgery. This will create a minimally invasive, non-genetic, but still cell-type-specific neuromodulation technique, in contrast to existing methods such as deep brain stimulation, optogenetics and chemogenetics.
This PhD offers an exciting opportunity to join a team of leading UCL scientists (Mark Lythgoe) together with neuroscientists (Alex Gourine and Yichao Yu) to develop the next generation of treatments for major depression.
What you will be doing: This project will consist of two lines of work: 1) developing an MRI-guided FUS system within an existing MRI system; 2) developing MMS facilitated by MRI-guided FUS and testing its efficacy in reversing molecular, network-level, and behavioural abnormalities in animal models of depression.
Who we are looking for: The ideal candidate would have a passion for developing new healthcare technologies and enjoy interdisciplinary work that spans engineering, medical imaging and neuroscience. Candidates with a background in biomedical engineering, physics, or biology will be considered.