Targeting inflammatory skin disease using a novel immune modulating agent

Chronic inflammatory skin diseases such as psoriasis and atopic dermatitis (AD) are growing global health concerns and developing new therapeutics is much needed. RP23, a human self-derived peptide, has novel anti-inflammatory properties as an injected therapeutic in contact hypersensitivity and psoriasis mouse models. In this thesis, we have conducted further experiments to determine mechanistic insight of RP23 and optimised a topical therapy for its therapeutic use in inflammatory skin diseases. We found that murine BMDMs treated in vitro with RP23 had suppressed LPS-induced IL-6, IL-12p40 and IL-12p70 responses and increased IL-10. Reduction in IL-6 and IL-12p40 was also seen in human MDMs. Further, we observe cellular changes that resemble necrotic-like cell death in murine BMDMs. Induction of cell death required uptake of the peptide by phagocytosis, as it could be inhibited with cytochalasin D. Proteomic analysis showed upregulated M2 markers, antioxidant and metabolic proteins and downregulated interferon-inducible proteins. We have also developed a topical delivery system that penetrates both human and murine skin explants and offers superior protection from imiquimod-induced psoriasis applied daily, compared to a single injected dose. Topical RP23 also offers moderate protection from disease in the oxazolone-induced AD model. Use in either model did not affect spleen/ILN weights, suggesting localised suppression of inflammation. Topical RP23 treatment of inflamed and non-inflamed skin showed uptake by CD64+ macrophages and DCs and reduced proportions of total DCs. We also observed reduced IL-6, IL-12p40 and IL-17A/F production, neutrophil and Rorγt+ γδ T cell proportions in psoriatic murine skin and reduced CD11b+ cells in skin-draining lymph nodes. To conclude, we have demonstrated RP23 has significant therapeutic potential as a topical therapy for psoriasis and AD and identified molecular and cellular mechanisms that warrant further investigation

Multivariate Volatility Measures and Models with Applications

This thesis explores methodologies for modelling and estimating correlation and covariance dynamics, presenting advancements in statistical approaches and their applications across multiple domains. We provide a comprehensive literature review of existing methodologies for modelling covariance matrices, focusing on their advantages, limitations, and practical implications, which highlights the need for efficient estimators and dynamic modelling techniques to address challenges such as heteroskedasticity, non-positive definiteness, and dynamic correlation structures. With our proposed range-based correlation matrix measures, we extend the two-stage multivariate Conditional Autoregressive Range Model (MCARR)-return models to directly model covariance matrix series using the Wishart distribution. Through simulation studies, we compare two approaches: modelling the covariance matrices and modelling the variances and correlation matrices. Correlation matrix modelling demonstrates better performance, guided by specific priors and stationary conditions

Event-based Satellite Docking

Dataset to accompany Le Gentil et al. "Mixing Data-driven and Geometric Models for Satellite Docking Port State Estimation using an RGB or Event Camera", IEEE International Conference on Robotics and Automation (ICRA) 2025. In-orbit automated servicing is a promising path towards lowering the cost of satellite operations and reducing the amount of orbital debris. For this purpose, we present a pipeline for automated satellite docking port detection and state estimation using monocular vision data from standard RGB sensing or an event camera. Rather than taking snapshots of the environment, an event camera has independent pixels that asynchronously respond to light changes, offering advantages such as high dynamic range, low power consumption and latency, etc. This work focuses on satellite-agnostic operations (only a geometric knowledge of the actual port is required) using the recently released Lockheed Martin Mission Augmentation Port (LM-MAP) as the target. By leveraging shallow data-driven techniques to preprocess the incoming data to highlight the LM-MAP's reflective navigational aids and then using basic geometric models for state estimation, we present a lightweight and data-efficient pipeline that can be used independently with either RGB or event cameras. We demonstrate the soundness of the pipeline and perform a quantitative comparison of the two modalities based on data collected with a photometrically accurate test bench that includes a robotic arm to simulate the target satellite's uncontrolled motion

Matlab software for the paper "First predictions for images of Earth's foreshock radiation sources" by Cairns and Oppel

Examples of the Matlab software for the Cairns and Oppel paper on images for Earth's foreshock radiation sources. The file init.m gives the input parameters. The code hybrid_3DNov calculates the emissions for multiple planes from given input parameters. The code line_of_sight_new.m produces the view of the foreshock emissions from 9 locations.Matlab software

Validation of novel non-invasive diagnostic and prognostic methods in chronic kidney disease and kidney transplantation

There is an emerging need to accurately detect chronic kidney disease (CKD) at an early stage so timely intervention can be implemented to optimize clinical outcomes. There remains a critical unmet requirement to develop non-invasive methodologies for early CKD diagnosis and prognostication. Using human urine samples, our group developed novel approaches based on indirect immunomagnetic extraction of urinary exfoliated proximal tubule cells (PTCs), to assess if urinary exfoliated PTCs can be assessed as an approach to inform CKD severity; and whether CKD staging and progression can be determined by utilizing multispectral autofluorescence in exfoliated PTCs. We have also assessed cell-free urine samples to evaluate their urinary volatile organic compound profiles and demonstrated this could potentially be applied as a novel metabolomic biomarker to assess CKD progression. In the scenario when CKD progresses to kidney failure, patients may elect to receive kidney replacement therapy in the form of dialysis or kidney transplantation. Although kidney transplantation is often the preferred option of treatment for kidney failure, optimal outcomes following kidney transplantation may be challenged due to various post-transplant complications. There is no strongly validated method apart from transplant kidney biopsy which can definitively predict the cause of delayed or deteriorating graft function currently. Hence, there is also an unmet need for accurate non-invasive diagnostic approaches to identify the cause of kidney dysfunction following transplantation. This thesis also provides novel proof of concept data supporting the application of urinary exfoliated PTCs multispectral autofluorescence to non-invasively differentiate between individuals with different causes of kidney transplant dysfunction

Application of Deep Learning in Image Processing

Deep learning has revolutionized computer vision, achieving remarkable success in complex visual tasks such as image classification, segmentation, and object detection. This thesis explores advanced deep learning techniques for image processing, with a particular focus on remote sensing imagery. Specifically, this research addresses two critical challenges: (1) achieving high segmentation accuracy in scenarios with limited labeled data and (2) integrating multi-modality data into model training. To tackle these challenges, this work proposes innovative solutions leveraging semi-supervised learning and multi-modality learning. By employing consistency learning and advanced data augmentation techniques, the proposed approaches effectively utilize unlabeled data, significantly boosting segmentation accuracy. Furthermore, integrating complementary data modalities, such as spectral and spatial information, enhances model robustness and overall performance. Experimental results on benchmark datasets validate the effectiveness of these methods, demonstrating their potential for real-world applications, including environmental monitoring, urban planning, and disaster management. The primary contributions of this thesis include advancing the theoretical understanding of semi-supervised and multi-modality learning in remote sensing segmentation, developing novel methodologies to address data scarcity, and providing practical frameworks that are applicable across various domains. However, limitations related to scalability and generalizability highlight avenues for future research, such as exploring dynamic augmentation strategies, advanced fusion mechanisms, and extensions to other fields like medical imaging. This research provides a comprehensive framework for overcoming segmentation challenges in remote sensing, delivering significant advancements in deep learning-based image analysis

The Subsidy Question: Community Theatre and the Integral State

This thesis explores how historical shifts in capitalist accumulation strategies have influenced Australian cultural subsidy. It examines the origins of Australian neoliberalism and its impact on federal arts funding from 1972 to 1997, focusing on the relationship between the state, community arts, and cultural policy. The methodology is historical materialism, guided by Antonio Gramsci’s theory of cultural hegemony, which views the state as integral to capitalism. The first half of the thesis traces the evolution of federal arts funding as a Keynesian economic policy, through its transformation under the Whitlam government, to the destabilisation of the arts council model amid economic crises, and examines how these changes shaped Australia’s federal community arts program. The second half analyses how shifts in accumulation strategies are reflected in community arts through four case studies: Art and Working Life (1982-c1995), an arts program jointly funded by the Australia Council and the Australian Council of Trade Unions targeting projects linked to labour culture; Melbourne Workers Theatre (1987-2012), a theatre company dedicated to working exclusively with the labour movement; Creative Nation (1994), Australia’s first federal cultural policy, which entrenched an economic rationalist “creative industries” paradigm into policymaking; and The Essentials (1997), a community theatre production created with emergency services and domestic violence support workers about their experiences under a state-wide restructure by former Victorian Premier Jeff Kennett. These case studies are examined in the context of declining organised labour power in Australia, and the rise and consolidation of neoliberalism as the dominant hegemony of advanced capitalism. This thesis finds that the industrial problems of the Australian arts sector result from a structural antagonism between a sector that relies on public funding and the imperatives of the neoliberal state

Exploring evolutionary rates and patterns of diversification across the Tree of Life

My thesis provides substantial insight into evolutionary processes across the Tree of Life. I have analysed the geological record as well as phenotypic traits and genomes from extant organisms to better understand the processes of diversification and change. I begin by challenging the notion that the diversification of flowering plants was intimately linked to a contemporaneous diversification of pollinating insects. This evolutionary event, which propelled flowering plants to dominate terrestrial landscapes, may instead have been bolstered by unique environmental factors, and by insect pollinators that were primed by previous interaction with seed plants. I then examine the tempo of evolution for many diverse taxa by inferring evolutionary rates. I first validate and assess five methods for detecting evolutionary rate correlations between molecular sequences and morphological traits, using a comprehensive simulation study with thousands of replicate data sets. After determining the most statistically accurate and powerful methods, I apply these methods to diverse taxa from the eukaryote Tree of Life. This spans groups including, but not limited to, worms, tetrapods, fish, insects, plants, and parasites. In doing so, I uncover powerful evidence for decoupled evolutionary rates of molecules and morphology across all groups tested, demonstrating the disparate mechanisms that govern the evolution of morphology, which is under the constraint of natural selection, and molecules, which exhibit more stochastic evolution. Finally, I analyse evolutionary rates in land plant genomes, testing the link between rates in the three genomic compartments of land plants (nucleus, chloroplast, and mitochondrion). In this chapter I demonstrate that there is a shared evolutionary rate between the genomic compartments in land plants – effectively extending the hypothesis of 'mitonuclear covariation' from animals to plants

An improved method of capture and immobilisation for medium to large-size macropods

Macropods are very susceptible to stress during capture. Capture methods for macropods fall into two categories: trapping and darting. Trapping by nets or a triggered trap mechanism is commonly used for small macropods. Darting is most often used for large macropods that are more prone to stress and capture myopathy when caught in traps. Aim. To describe a modified ‘nylon drop-net’ technique for safely capturing medium to large macropods; and post-capture treatments that reduce stress and the potential for myopathy. Methods. We used a drop-net to capture 40 agile wallabies (Notamacropus agilis) (24 females and 16 males), ranging in weight from 6 to 24 kg. For immobilisation, a single dose of intramuscular Diazepam (1 mg/kg) and Richtasol, a multivitamin, was administered to reduce the risk of capture myopathy. The longer-term effects of capture on animal condition were monitored in 34 radio-collared individuals for 2 months. Key results. No deaths occurred during or as a result of capture or in the 8 weeks following capture. Conclusions. Our modified drop-net and handling/treatment regime provides a cost-effective method for capturing medium and small-sized macropod species with very low risk of mortality or morbidity. Implications. Our methods improve the welfare and safety of captured medium-sized macropods

Exploring Changing Treatment Paradigms in Medullary Thyroid Carcinoma, the Immune Milieu of the Tumour Microenvironment and a Novel Targeted Therapy for Advanced Disease

The immune milieu of the tumour microenvironment (TME) in Medullary Thyroid Cancer (MTC) and the potential role of immune therapies have not been extensively explored. This study aimed to define the current treatment landscape and changing management paradigms in MTC, describe the nature of the immune microenvironment of these tumours, and ultimately explore a novel targeted therapy for advanced disease. Tumour-infiltrating lymphocytes (TILs) in the TME of MTC patients were assessed and correlated with clinicopathological prognostic variables and survival outcomes. All patients with MTC had low TILs (≤10%), and there was no significant association between TILs and local recurrence or disease-specific survival on multivariable analysis. These findings highlight that MTC is an immune-quiescent tumour. A novel targeted therapy for advanced MTC was also investigated. The EDV™ (EnGeneIC Dream Vector) is a bacterially-derived construct loaded with cytotoxic drugs and conjugated with a bispecific antibody directed against specific overexpressed surface receptors on tumour cells. The EDV™ effectively killed human MTC cells in vitro and in a nude-mouse xenograft and syngeneic neuroendocrine tumour model. In addition to targeted delivery of the cytotoxin PNU-159682 mediated by antibody binding, EDV treatment triggered an innate and adaptive immune response against tumour cells, with upregulation of M1 macrophages, cytotoxic natural killer (NK) cells, and invariant natural killer T cells, followed by CD8 effector T cells. The shift to an immune-activated phenotype in the TME correlated with changes in the cytokine and chemokine profile, with upregulation of the key drivers of macrophage, NK cell and T cell activation and chemotaxis in the serum and TME. These results provide preclinical data demonstrating the efficacy of a novel targeted therapy for advanced MTC and form the evidence base to support a human clinical trial to confirm the translational relevance of the results