Magnetic Resonance Imaging (MRI) Biomarkers for Therapeutic Response Prediction in Rectal Cancer

Prediction of chemoradiotherapy (CRT) response in rectal cancer would enable stratification of management whereby responders could undergo ‘watch-and-wait’ to avoid surgical morbidity, and non-responders could have early treatment intensification to improve therapeutic outcomes. Functional MRI can assess tumour function and heterogeneity, and may improve therapeutic response prediction. The aims of this PhD were to (i) prospectively evaluate multi-parametric MRI at 3.0 tesla in vivo combining diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI for prediction of CRT response and 2 year disease-free survival (DFS), and (ii) examine diffusion tensor imaging (DTI) MRI biomarkers of rectal cancer extent and heterogeneity at ultra-high field 11.7 tesla ex vivo in order to establish a pipeline for MRI biomarker discovery from ultra-high field to clinical field. Patients with locally advanced rectal cancer undergoing CRT followed by surgery underwent multi-parametric MRI before, during, and after CRT. A whole tumour voxelwise histogram analysis of apparent diffusion co-efficient (ADC) and Ktrans heterogeneity was performed and correlated with histopathology tumour regression grade. After CRT (before surgery) ADC 75th and 90th quantiles were significantly higher in responders than non-responders. Patients with higher Ktrans values after CRT or greater increase in Ktrans values from before to after CRT had a significantly higher risk of distant metastases, and lower 2 year DFS. Biobank tissue from patients with rectal cancer were examined at 11.7 tesla and DTI-MRI results correlated with histopathology. This work established a discovery framework for screening Biobank cancer tissue for novel MRI biomarkers of tumour extent and heterogeneity, and resulted in good preservation of tissue integrity and MRI-histopathology alignment. DTI-MRI derived fractional anisotropy (FA) was able to differentiate between tumour and desmoplasia, fibrous tissue, and muscularis propria, allowing for more accurate delineation of rectal cancer tumour extent and stromal heterogeneity ex vivo. In conclusion, DWI-MRI was predictive of CRT response, DCE-MRI was predictive of 2 year DFS, and DTI-MRI was able to more accurately define tumour extent and heterogeneity in rectal cancer. These findings could be useful for stratification of patients for individualised treatment based on accurate assessment of tumour extent and therapeutic response prediction

Hepatitis C elimination among people living with HIV

Background: Hepatitis C virus (HCV) is a major cause of liver-related morbidity and mortality among people living with HIV globally. Aims: The broad aim of this research was to evaluate progress towards HCV elimination among people living with HIV in Australia. Specific aims included evaluating incidence and factors associated with HCV reinfection and patterns of drug use and sexual risk behaviours after treatment and characterizing the HCV cascade of care and factors associated with engagement in HCV care among people living with HIV in Australia. Methods: In Chapter Two, the risk of HCV reinfection following successful therapy among people living with HIV was evaluated in a global systematic review and meta-analysis, with factors associated with reinfection assessed using meta-regression. In Chapter Three, patterns of drug use and sexual risk behaviours and HCV reinfection incidence were assessed before and after direct-acting antiviral (DAA) scale-up in Australia among people with HIV/HCV coinfection enrolled in CEASE. In Chapter Four, the HCV cascade of care, including HCV testing and treatment, among people living with HIV was characterized in the pre (2010–2015) and post (2016–2018) DAA era in a population-based linkage study including all people living with HIV in New South Wales, Australia with an HCV notification. Factors associated with HCV testing and DAA treatment were assessed using logistic regression. Key Findings: Globally, HCV reinfection incidence following treatment among people living with HIV was similar following interferon-based and DAA therapy, with the highest risk among men who have sex with men and those with recent HCV infection. Following unrestricted DAA access and broad treatment uptake among people living with xviii HIV in Australia, HCV reinfection incidence was low despite stable pattens of risk behaviours before and after DAA treatment. The HCV care cascade among people living with HIV demonstrated high HCV RNA testing coverage (91%) and treatment uptake following DAA availability (7% pre DAA, 73% post DAA). Younger age, female gender, and rural region of residence were negatively associated with testing; no factors were associated with DAA treatment. Conclusion: To maintain progress towards HCV elimination, ongoing HCV screening and treatment of (re)infection among people living with HIV will be required. Enabling access to and ensuring broad coverage of HCV testing, treatment and prevention will be essential

Adsorption and Separation Characteristics of Graphene Oxide

Graphene oxide is a single layer of carbon atoms with decorated oxygen functional groups. Stacked monolayers in the laminate form create an interlayer space of sub-nanometer scale with oxygenated functional group to attract water molecules, and graphitic domains to allow frictionless flow of water molecules and achieve maximum efficiency of water transportation. The research reported herein is aimed to understand and explore characteristics of the diffusion-dependent mass transportation across an array of cascading nanochannels confined by graphene oxide laminates at sub-nanometer level. This dissertation has 6 Chapters. Chapter 1 is the introduction and Chapter 2 reports the recent progress in graphene oxide for mass transport application. Chapter 3 discusses efforts of engineering the channel confinement, which is represented by the interlayer spacing in between graphene oxide laminates. By adjusting the fundamental factors of graphene oxide suspension, the interlayer spacing can be controlled at 0.7 to 0.8 nm. Based on the engineered interlayer spacing, separation of vaporous mixture by graphene oxide membrane is studied in Chapter 4. Numerical description of nanochannels enclosed by graphene oxide monolayers is determined by time lag analysis. The feature of ethanol vapor transportation with the support of water vapor is revealed, showing accelerated transportation of non-permeable matter, which enriches the existing knowledge. A geometrical model of graphene oxide membrane for vapor separation was established and analyzed. In Chapter 5, adsorption and intercalated of molecules and solvated ions are studied and proved as a size-dependent enlargement of graphene oxide nanochannels. Carriers such as water and ethanol are used for transporting ions and molecules into graphene oxide slits. Taking the adsorption into consideration, permeation of vaporous substances through adsorbed graphene oxide membrane is investigated in Chapter 6. The research initiates researching crystallization of adsorbed matters in graphene oxide interlayer structure. A simplified model was directed to predict the water vapor permeation behavior of intercalated graphene oxide membrane. Such efforts not only lead to a better understating of graphene oxide membrane for gas separation but also give a hint of spatially efficient matter transport in achieving excellent electrochemical devices with graphene oxide components

Corrosion Engineering of Fe-Based Electrocatalysts for Oxygen Evolution Reactions at Industrially Relevant Conditions

The urgency of developing sustainable and renewable energy sources has been heightened by limited fossil fuel reserves as well as environmental concerns. Hydrogen is an efficient alternative to traditional fossil fuels because of its clean combustion emissions and high energy density. Water splitting is a clean method for producing green hydrogen but is limited by the slow reaction kinetics of oxygen evolution reaction (OER). In recent years, multi-metallic electrocatalysts with high activity and minimum energy consumption have been developed for efficient OER. The objective of this thesis is to take advantage of the spontaneous corrosion electrochemistry to make nonprecious multi-metallic hydroxides for efficient oxygen evolution reaction and evaluate their performance in industrial alkaline water electrolysis. First, oxygen- and sulfate-mediated corrosion engineering were developed by using macroporous iron foam to produce Cr-doped FeNi and FeCo ternary hydroxides. This strategy was successfully achieved to modulate and accelerate the in-situ phase transition of the Ni-O species to the oxyhydroxide active phase which results in high surface-intermediate interactions and intrinsic electrocatalytic activity. The promising long-term OER stability, reproducible performance at high current densities indicates the great potential of designing efficient polymetallic electrocatalysts for water splitting technology through corrosion engineering. In addition, the long-term stability of FeNiCr under industrially relevant conditions was further investigated. It was found that the doping of Cr reduced the OER overpotential of the FeNi binary system, however, at the same time increased the sensitivity of the FeNi binary system to high pH and temperature. After characterization and testing before and after the OER reaction, it was found that the causes of catalyst deactivation include dissolution of the active material at high potentials and high pH values, surface morphology changes, phase transitions, and physical detachment. The results obtained in this thesis demonstrate that corrosion engineering and Cr doping are efficient strategies to design nonprecious multi-metallic electrocatalysts for OER. The deactivation mechanism of FeNiCr ternary catalysts under industrial conditions suggests that high pH and temperature are important factors for the evaluation of OER catalysts for industrial applications

Smartphones and consumer electronics for eye examinations and ophthalmology teaching – proof of concepts for five novel and inexpensive optical instruments.

The ability to examine eyes and identify pathology in Ophthalmology is dependent on the availability and capability of optical instrument technologies. For many clinicians, teachers and medical students who cannot access appropriate optical instruments, these users have been blinded to seeing inside eyes. In comparison, the optical technology in iPhones and other smartphones is widely available. Their extraordinary inbuilt cameras and photo processing software makes smartphones an ideal readymade platform to develop new optical instruments to examine eyes. This thesis developed five inexpensive optical instrument prototypes and showed proofs of concepts for an iPhone Direct Ophthalmoscope, Near Infrared Non-Mydriatic iPhone Ophthalmoscope, iPhone Exophthalmometer, Operating Microscope Recording System and a ‘Heads up’ repurposed Slit Lamp. The prototypes were substantially lower in cost when compared with existing devices on the market, offering viable alternative optical instruments in clinical practice. A working prototype of the Near Infrared Non-Mydriatic Ophthalmoscope can be developed in future research, which would eliminate the need for using mydriatic eye drops to dilate pupils before retinal examinations. This research can be used to develop affordable and widely available precision optical instruments based on smartphones for eye examinations in clinics, classrooms and throughout developing countries

Assessment and management of structural heart disease in an ageing population.

Structural heart disease interventions represent a rapidly evolving branch of percutaneous treatments to correct valvular lesions that were previously treated surgically, or simply not addressed. In the past decade, the therapeutic landscape for patients with degenerative aortic valve stenosis (AS) and secondary mitral regurgitation (MR) has changed dramatically. As transcatheter innovations continue to develop, cardiac physiologists and clinicians alike are challenged by the need to more accurately discriminate between those who will benefit from intervention, and those who will not. Interpreting valvular function in the setting of impaired contractile performance and/or poor arterial compliance is especially difficult. Hemodynamic loading conditions in these settings are often unique, and not adequately accounted for using traditional cardiac imaging techniques. Load independent assessment of contractile function requires the simultaneous measurement of left ventricular (LV) pressure, volume and flow in order to determine the relationship between these parameters at various points in the cardiac cycle. Our work incorporates advances in cardiac magnetic resonance and echocardiography imaging techniques to allow better non-invasive assessment of ventricular mechanics and ventricular-vascular interactions in response to structural aortic and mitral valve interventions. We have devised precise and accurate non-invasive tools to quantify LV and aortic pressure, LV volume and aortic flow, and have coalesced this data to determine the LV pressure-volume and aortic pressure-flow relationships in patients with degenerative AS and secondary MR. It is our intention that the development of high-quality non-invasive data on ventricular contractility and ventricular-vascular coupling, will provide a better platform to evaluate cardiovascular performance in those with valvular heart disease

Machine Learning Aided Stochastic Elastoplastic and Damage Analysis of Functionally Graded Structures

The elastoplastic and damage analyses, which serve as key indicators for the nonlinear performances of engineering structures, have been extensively investigated during the past decades. However, with the development of advanced composite material, such as the functionally graded material (FGM), the nonlinear behaviour evaluations of such advantageous materials still remain tough challenges. Moreover, despite of the assumption that structural system parameters are widely adopted as deterministic, it is already illustrated that the inevitable and mercurial uncertainties of these system properties inherently associate with the concerned structural models and nonlinear analysis process. The existence of such fluctuations potentially affects the actual elastoplastic and damage behaviours of the FGM structures, which leads to the inadequacy between the approximation results with the actual structural safety conditions. Consequently, it is requisite to establish a robust stochastic nonlinear analysis framework complied with the requirements of modern composite engineering practices. In this dissertation, a novel uncertain nonlinear analysis framework, namely the machine leaning aided stochastic elastoplastic and damage analysis framework, is presented herein for FGM structures. The proposed approach is a favorable alternative to determine structural reliability when full-scale testing is not achievable, thus leading to significant eliminations of manpower and computational efforts spent in practical engineering applications. Within the developed framework, a novel extended support vector regression (X-SVR) with Dirichlet feature mapping approach is introduced and then incorporated for the subsequent uncertainty quantification. By successfully establishing the governing relationship between the uncertain system parameters and any concerned structural output, a comprehensive probabilistic profile including means, standard deviations, probability density functions (PDFs), and cumulative distribution functions (CDFs) of the structural output can be effectively established through a sampling scheme. Consequently, by adopting the machine learning aided stochastic elastoplastic and damage analysis framework into real-life engineering application, the advantages of the next generation uncertainty quantification analysis can be highlighted, and appreciable contributions can be delivered to both structural safety evaluation and structural design fields

Characterising the RNA modification and polyadenylation landscape at single molecule resolution using third-generation sequencing technologies

RNA modifications, collectively referred to as the ‘epitranscriptome’, are not mere decorations of RNA molecules, but can be dynamically regulated upon environmental queues and changes in cellular conditions. This dynamic behaviour is achieved through the RNA modification machinery, which comprises “writer”, “reader” and “eraser” proteins that modify, recognize and remove the modification, respectively. Chapter1 presents a comprehensive analysis of the RNA modification machinery (readers, writers and erasers) across species, tissues and cancer types, revealing gene duplications during eukaryotic evolution, changes in substrate specificity and tissue- and cancer-specific expression patterns. Chapters 2 and 3 presents the exploration and development of novel methods to map and analyze RNA modifications transcriptome-wide. Nanopore direct-RNA sequencing technology was used to provide RNA modification maps in full-length native RNA molecules. Firstly, it is shown that RNA modifications can be detected in the form of base-calling ‘errors’, thus allowing us to train Support Vector Machine models that can distinguish m6A-modified from unmodified sites, both in vitro and in vivo. Secondly, it is demonstrated that distinct RNA modification types have unique base-calling ‘error’ signatures, allowing us to exploit these signatures to distinguish different RNA modification types. It is found that pseudouridine has one of the most distinct signatures, appearing in the form of C-to-U mismatches. Finally, this information was used to predict novel pseudouridine sites on ncRNAs and mRNAs transcriptome-wide, as well as to obtain quantitative measurements of the stoichiometry of modified sites. Chapter 4 presents the development of a novel nanopore-based method, which is termed ‘Nano3P-seq’, to simultaneously quantify RNA abundance and tail length dynamics in individual molecules in both the coding and non-coding transcriptome, from cDNA reads. It is demonstrated that Nano3P-seq offers a simple approach to study the coding and non-coding transcriptome at single molecule resolution regardless of the tail ends. Together, this work provides a comprehensive framework for the study of RNA modifications and polyA tail dynamics using third generation sequencing technologies, opening novel avenues for future works that aim to characterize their dynamics and biological roles both in health and in disease

Controlling light-matter interaction with resonant semiconductor nanostructure

This thesis aims to bridge dielectric materials' optical and electronic properties to obtain full control of light-matter interaction at the nanoscale. The outcomes may open the way for tunable, ultra-thin, cost-effective, and energy-saving optoelectronic devices. This research first studies the optical modes of dielectric nanostructures, including toroidal dipole (TD) excitation under illuminations of structured light. The quantitative comparison between the structured light and plane wave illuminations shows a lot of promise for exciting dominant toroidal response in the geometrically simple photonic systems. The tightly focused radially polarised illumination shows a near-pure excitation of the TD in dielectric nanodisk. Additionally, it will be shown that the focused doughnut pulse could be a promising tool for the resonant excitation of toroidal response in photonic structures. Toroidal excitations are a potential way of increasing light-harvesting and boosting nonlinear light-matter interactions. This thesis is then involved in pioneering research in light detection by utilising nontrivial optical modes of dielectric nanostructures to improve the electrical characteristics of conventional photodetectors. It would open the way for all-dielectric nanophotonics to be at the same level of consumer products as electronics. We study the realisation of the high-speed and highly efficient photodetectors using germanium (Ge) metasurfaces. Semiconductors such as Ge are materials that are compatible with the complementary metal–oxide–semiconductor process and thus are the proper building material for the high-volume foundry process of photonic integrated circuits (PICs). The optical properties and steady-state and transient electric behaviours will be studied to analyse the electrical response at the telecommunication C-band, a major spectral choice for optical communication and signal processing in PICs. We also propose a polarisation-independent metasurface superabsorber by exploring the quasi-bound state in the continuum (QBIC) to improve photodetectors’ electrical characteristics, including their responsivity. As the asymmetry parameter mostly governs the Q-factor of QBICs, it gives a straightforward and efficient way of optimising the light absorption using critical coupling. The metasurface is designed to operate at the C-band, but it can be tuned for other bands in the telecommunication frequency range. Two designs boosting the light collection efficiency up to 50% in the transmission and up to 100% in the reflection modes will be proposed in this thesis. Despite the symmetry-broken nature of QBICs, our metasurface is insensitive to the polarisation of incoming light and thus provides great flexibility in the practical applicability of QBIC-based metasurfaces

The temporal pattern of impulses in primary afferents analogously encodes touch and hearing information

An open question in neuroscience is the contribution of temporal relations between individual impulses in primary afferents in conveying sensory information. We investigated this question in touch and hearing, while looking for any shared coding scheme. In both systems, we artificially induced temporally diverse afferent impulse trains and probed the evoked perceptions in human subjects using psychophysical techniques. First, we investigated whether the temporal structure of a fixed number of impulses conveys information about the magnitude of tactile intensity. We found that clustering the impulses into periodic bursts elicited graded increases of intensity as a function of burst impulse count, even though fewer afferents were recruited throughout the longer bursts. The interval between successive bursts of peripheral neural activity (the burst-gap) has been demonstrated in our lab to be the most prominent temporal feature for coding skin vibration frequency, as opposed to either spike rate or periodicity. Given the similarities between tactile and auditory systems, second, we explored the auditory system for an equivalent neural coding strategy. By using brief acoustic pulses, we showed that the burst-gap is a shared temporal code for pitch perception between the modalities. Following this evidence of parallels in temporal frequency processing, we next assessed the perceptual frequency equivalence between the two modalities using auditory and tactile pulse stimuli of simple and complex temporal features in cross-sensory frequency discrimination experiments. Identical temporal stimulation patterns in tactile and auditory afferents produced equivalent perceived frequencies, suggesting an analogous temporal frequency computation mechanism. The new insights into encoding tactile intensity through clustering of fixed charge electric pulses into bursts suggest a novel approach to convey varying contact forces to neural interface users, requiring no modulation of either stimulation current or base pulse frequency. Increasing control of the temporal patterning of pulses in cochlear implant users might improve pitch perception and speech comprehension. The perceptual correspondence between touch and hearing not only suggests the possibility of establishing cross-modal comparison standards for robust psychophysical investigations, but also supports the plausibility of cross-sensory substitution devices