Electroanalytical engineering strategies for monitoring molecules in neuroscience
File(s)
Author(s)
Parke, Brenna
Type
Thesis
Abstract
Depression is a complex neuropsychiatric disease whose exact aetiology has eluded scientists for decades. Theories such as the monoamine hypothesis and the newer inflammation hypothesis attribute the physiological underpinnings of depression to be within the brain or a brain-immune axis. Validating these theories has been difficult to execute because, until recently, few tools were available to measure neurotransmitters in the brain. This technology gap has left diagnosis and treatment of depressed patients up to the opinion of physicians (i.e. no chemical basis). Over the last few decades reliable tools to probe the brain in real-time have been developed and used in animals. While many useful studies have resulted using these technologies, conclusions from animal experiments are not easily translated to the human condition. Therefore, the focus of this thesis is to probe peripheral organs that share an inflammation axis with the brain. This thesis begins by introducing the topics of neurochemical signalling, immune signalling and neurotransmitter measurement techniques. Chapter 2 describes the general methods used for the work with specific methods mentioned in each chapter. To bridge the gap between in vivo and in vitro measurements, chapter 3 optimizes histamine measurements in tissue slice preparations to prepare for the cell work. Chapter 4 describes neurotransmitter release from hair cells, which share an immune axis with the brain. Chapter 5 extends this work to skin cells, where we show ambient neurochemical release from dermal fibroblasts is mediated by histaminergic receptors. In chapter 6 we pivot to endocrine signalling in the pancreas, where we develop novel methodology to co-detect serotonin and insulin and apply our new technology to insulin-secreting cells for the first real-time measurements of insulin. Finally, chapter 7 summarizes the entirety of the work and I offer my own perspectives on where this work should be taken in the future.
Version
Open Access
Date Issued
2023-12-21
Date Awarded
01/03/2024
License URL
Advisor
Hashemi, Parastoo
Publisher Department
Bioengineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)