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Development of drug-loaded PLGA microparticles to target microglial immunosuppression during glioblastoma
No full textDrugs and therapies used to treat glioblastoma multiforme (GBM) need to be able to enter the brain,
which is often confounded by the blood-brain barrier, meaning that treatments either have low
bioavailability in the brain, or require invasive surgery for delivery. One solution to this has been the
development of particle delivery systems for non-invasive delivery of therapeutics, allowing for
improved bioavailability, increased therapeutic stability, and the ability for cell-specific targeting.
Thus, current research approaches to designing nano- and micro-particle drug delivery systems for
GBM are discussed in Chapter 1.
Attempts to develop new immunotherapies, or repurpose immunotherapies that have been
successful in other solid tumours, have largely failed to work against GBM. It is likely that this lack of
success is due to the highly immunosuppressive microenvironment tumour cells promote by driving
local microglia and macrophages towards tumour-supportive, anti-inflammatory phenotypes. The
work presented in this thesis therefore focuses on repurposing existing immune-stimulatory drugs,
imiquimod, prostratin, and 2-NP, for use in GBM, by developing a poly(lactic-co-glycolic acid) (PLGA)-
based microparticle for microglia-targeted drug delivery.
Chapter 3 focuses on creating PLGA microparticles, testing single and double emulsion evaporation
methods for their drug loading efficiencies and microparticle size, ultimately settling on a protocol
using single emulsion with a high encapsulation efficiency across a range of drugs. The rate of drug
release from microparticles is also examined in Chapter 3, as well as the creation of fluorescently
labelled microparticles to allow for microparticle tracking during biological experiments.
In Chapter 4, the microparticles and selected drugs are examined for their behaviour in the brain,
using zebrafish models to assess the impact of microparticles on microglial inflammation and tumour
growth. It was confirmed that drug-loaded microparticles were able to upregulate inflammatory
cytokine expression in zebrafish microglia. Finally, using a zebrafish HRASv12 preneoplastic model of
glioma, it was observed that treatment with all three types of drug-loaded microparticle were able to
reduce tumour volume, particularly imiquimod-loaded microparticles.
Overall, using PLGA microparticles as a tool for drug delivery, this research highlights a potential role
for imiquimod, prostratin and 2-NP for treating immunosuppression in GBM, and further steps
required to take these treatments towards a clinical setting are discussed in Chapter 5
Setting the agenda: Rooting future woodland restoration research in practitioner needs
Full text linkThis report examines what knowledge woodland restoration practitioners say they need, with the goal of co-developing a shared plan for future research with researchers. We used a mixed- methods approach: an online survey, in-depth interviews, and a collaborative workshop. We bring together findings from all three to identify priority knowledge gaps; show how shortages in evidence, knowledge sharing, or practical implementation contribute to those gaps; and propose actions that practitioners and researchers can take to address them. We also consider how external factors — such as policy, funding, and organisational capacity — shape what is possible. The report concludes with a shared vision for future research in woodland restoration
Regulation of Cdc42 GEF Scd1 by stress in fission yeast
No full textCell polarity, characterized by the asymmetric distribution of cellular components, is essential for diverse cellular functions such as differentiation, migration, and cell division. The fission yeast Schizosaccharomyces pombe serves as an effective model organism for studying cell polarity due to its straightforward, polarized rod-shaped growth and conserved molecular pathways analogous to those in higher eukaryotes. In S. pombe, environmental stresses activate the Stress-Activated Protein Kinase (SAPK) pathway, a conserved MAP kinase cascade found across species from yeast to humans. Sty1 kinase, the MAP kinase within the SAPK pathway, disperses the conserved polarity regulator Cdc42 and its guanine-nucleotide exchange factor (GEF) Scd1 from cell tips. This study aims to elucidate the molecular basis of Scd1 removal from cell tips upon Sty1 activation.
I identified Scd1 interactors using immunoprecipitation and mass spectrometry (IP-MS) under stressed and unstressed conditions. To specifically study SAPK effects, I used Stress-Independent Sty1 Activation (SISA) system which replaces wild-type Sty1 with an analog-sensitive allele, allowing precise activation without other stress pathways interference. Combining data-dependent and data-independent acquisition (DDA and DIA), I identified a network of Scd1 interactors—including Scd2, SEA complex proteins, Tea proteins, and Rho1 GEFs—and established DIA as a sensitive method for pulldown analysis. Time-course experiments revealed that Scd1 remains associated with its partners during Sty1 activation, suggesting regulation within a stable complex. Functional analysis of domain deletion mutants showed that the CH, DH, and PB1 domains are required for Scd1 localization and activity, while its unstructured region mediates dispersal upon Sty1 activation. Finally, phosphoproteomics identified Sty1-dependent phosphorylation sites on Scd1 and its interactors
Introducing the Dryland Futures Academy: Strengthening capacities for food security early action in East Africa
Full text linkPresented at Building the Resilience and Prosperity of Pastoralists and Dryland Communities, Nairobi, Kenya, 1-2 October 202
Dynamics of polymers embedded in nematic and active fluids
Full text linkComplex fluids—including suspensions of polymers, colloids, and liquid crystals—
exhibit fascinating rheological properties that vary with time, stress, and
temperature. Their inherent versatility enables a broad spectrum of applications
in both biology (e.g., lubrication, protection and digestion via mucus and saliva)
and manufacturing (e.g., shear-thinning behaviour in extrusion-based additive
manufacturing and injectable hydrogels for controlled drug delivery). Extensive
research has provided a detailed understanding of these materials, paving the
way for the development of composite or hypercomplex systems that combine
multiple complex fluids to yield emergent properties not present in the individual
components.
This thesis investigates hypercomplex polymeric materials, focusing on systems
in which polymers are embedded in rheologically complex or active backgrounds.
Simulating such systems requires a versatile computational framework capable of
capturing thermal fluctuations, hydrodynamic interactions, and spatiotemporally
varying active forces—features that become critical on mesoscopic length scales
and energy scales comparable to thermal energy. To this end, a hybrid coarsegrained
simulation approach is employed: the background fluid is modelled via
multi-particle collision dynamics, while the polymer dynamics are resolved using
molecular dynamics. This framework enables the exploration of passive polymeric
suspensions in hypercomplex environments.
The first part of this work examines polymers embedded in nematic liquid
crystalline media. Despite extensive studies on both liquid crystals and polymers
individually, the behaviour of a single polymer in a nematic background remains
largely uncharted. Here, we explore the coupling between the polymer backbone
and the orientational order of a passive nematic fluid. We show that the polymer
adopts conformations featuring hairpins—sudden kinks along the backbone—that
allow it to conform to the nematic symmetry while maintaining a diverse range of
configurations. These hairpins are responsible for inducing anisotropic diffusivity
in the polymer.
The second part addresses systems in which passive polymers are immersed
in an active nematic fluid, with activity introduced via locally injected energy
through force dipoles. In this scenario, active, self-organised coherent flows advect
the polymer, resulting in a thousand-fold increase in diffusivity compared to
equilibrium conditions. This dramatic enhancement is governed by the interplay
of key dimensionless numbers—the Peclet number and the Weissenberg number,
which are intrinsically linked through the Ericksen number that characterises the
ratio of fundamental length scales in the system.
The third part investigates how flexible polymers respond to active nematic flows
and uncovers a length-dependent transition in their conformations. Depending on
the balance between polymer size and the emergent flow scale, chains either compress
or stretch: short polymers collapse due to asymmetric, transient interactions
with motile defects, while long polymers align and elongate along coherent flow
structures. This behaviour reflects a general principle—conformational control
through competition between intrinsic polymer dimensions and the structural
length scale of the active medium—offering a unified framework for interpreting
polymer conformational dynamics in diverse active environments.
In summary, this work demonstrates how hypercomplex environments—formed
by embedding polymers in structured or active fluids—can fundamentally reshape
polymer dynamics and conformations. By tuning parameters, such as the
coupling to the nematic orientation, active length scale or polymer length, it
becomes possible to drive transitions between compact and extended states, or to
control transport. This perspective provides a foundation for the rational design
of responsive soft materials and offers a unifying framework for understanding the
interplay between structure and dynamics in non-equilibrium polymeric systems.
In doing so, it opens new directions for exploring self-organisation and functional
behaviour in active and biologically relevant environments
Resonance analysis for dispersive equations: numerical schemes and normal forms
Full text linkResonance-based schemes make use of convenient cancellations in the resonances of Hamiltonian systems to reduce the regularity required of the initial data to ensure convergence of the scheme in the relevant space. In this thesis, I explore the application of such schemes to dispersive equations driven by spatially smooth but white-in-time noise. There are two main differences from the deterministic setting. Firstly, one cannot perform resonance analysis at orders greater than \mcO(t^2) because the random variables involved do not have an explicit closed-form interpretation. Secondly, the convergence analysis is more technically challenging due to the cumulative effects of noise over long time periods. The former is specific to resonance schemes, and the latter is ubiquitous in the numerical analysis of stochastic differential equations (SDE). In the second part of my thesis, I extend the results to structure-preserving integrators. These schemes are designed to preserve specific physically relevant quantities, such as mass and energy. Structure preservation is possible in the stochastic setting for the mass and the energy, as long as the energy is averaged in space. Such schemes are applicable in long-term numerical studies due to their conservation properties, but in the stochastic setting, they are almost surely unstable. Progress can be made in this area, but proving convergence for these schemes is generally much more challenging than for their deterministic counterparts. In the final part of the thesis, we focus our attention on the Birkhoff normal-form reduction. This technique is classical in studying long-term dynamics of Hamiltonian systems. We derive an explicit formula for the general Birkhoff normal forms of Hamiltonian PDEs
Using and improving neurosymbolic AI for biomedical applications
Full text linkNeurosymbolic artificial intelligence (AI) involves hybrid methods between deep learning approaches and symbolic ones, such as logic programs. Although most previous research in this area has focused upon the development of neurosymbolic architectures and systems, some defining features of neurosymbolic AI are complementary to the constraints and characteristics of ongoing challenges in biomedicine. Thus, neurosymbolic AI holds potential for addressing such applied challenges. Specifically, in many neurosymbolic approaches, the inherent interpretability that is characteristic of symbolic methods is not only preserved, but it also provides interpretability into the deep learning components which do not typically possess this trait. Interpretability is important for communicating model outcomes to healthcare providers and biomedical researchers. Doing so helps to ensure that real-world decisions based upon such outcomes are ethical, fair, and productive. Additionally, logic programming has shown potential for representing rules or knowledge about some domain. Thus, when a neurosymbolic approach involves logical rules, it may constrain or guide some deep learning component to comply with such rules. This is particularly relevant and applicable for biomedical data science, for which there are ample sources of structured domain knowledge, ranging from ontologies to rule-based clinical systems.
This thesis explores the usage of methods in neurosymbolic AI by applying and altering them for applications in biomedical domains. This PhD project had three major research outputs. Firstly, Neurosymodal Data Fusion, a neurosymbolic pipeline for the classification of Alzheimer’s Disease state, is developed. This pipeline combines a biomarker-based rule system with data-driven approaches to classify the disease state and progression risk of participants within a clinical cohort study. Secondly, to assess the capabilities of neurosymbolic methods on larger datasets and more complex prediction tasks, like drug discovery, the use of neurosymbolic approaches on biomedical knowledge graphs (KGs) was surveyed. Finally, the mechanism-of-action retrieval system (MARS) was developed and tested. MARS, a KG-based, neurosymbolic approach, was used to predict the cellular effects induced by drug compounds as well as the molecular interactions which led to such effects. Through these studies, this thesis provides comprehensive analyses and discussion toward the capabilities, limitations, and potential of neurosymbolic approaches for biomedical data science
Building the Resilience and Prosperity of Pastoralists and Dryland Communities: Summary report of the research and policy dialogue, Nairobi, Kenya, 1–2 October 2025
Full text linkInvolving development partners and investors, governments, civil society actors, pastoral associations, policy and research organizations, this two-day dialogue on ‘Building the Resilience and Prosperity of Pastoralists and Dryland Communities’ was convened by three research for policy and practice institutions: the IGAD Centre for Pastoral Areas and Livestock Development (ICPALD), the Jameel Observatory for Food Security Early Action, and the Supporting Pastoralism and Agriculture in Recurrent and Protracted Crises (SPARC) programme. The conference offered a mix of sessions with presentations, plenary and panel discussions, space for audience interaction and showcased case studies, findings and good practices. Together, the sessions were designed to highlight: 1) pathways to prosperity and resilience for drylands and pastoralists; 2) advancing dryland’s futures through innovation and technology; and 3) investing in and delivering for dryland people
Miniaturised folded-short patch antenna designs for compact platforms: CubeSats and UAVs
No full textThe increasing demand for compact platforms such as unmanned aerial vehicles (UAVs) and
small satellites, particularly CubeSats, has necessitated the need for innovative compact antenna
solutions offering high performance at a low cost. Therefore, the increasing demand for
compact, lightweight, and high-performance antennas has driven significant research in miniaturised
designs suitable for modern communication systems. However, implementing antennas
for compact platforms has many challenges, mainly relating to size, weight, and power limitations,
making it a crucial yet intricate aspect of these compact platforms. Researchers have investigated
novel methods to enhance compact antennas, addressing size and weight challenges
through techniques such as folding, shorting, and miniaturisation to decrease both dimensions
and mass. Furthermore, employing additive manufacturing techniques like 3-D printing can
enhance manufacturing efficacy. Moreover, these techniques help to facilitate the low-cost
realisation of such non-deployable and compact antennas, which might be favourable when
compared to more conventional manufacturing solutions and deployable antenna designs.
It is also important that these compact platforms employ circularly polarised (CP) antennas and
beam steering arrays. Having CP capability is crucial for supporting reliable as well as resilient
communication links and connectivity in dynamic and multipath environments. CP also reduces
polarisation mismatch losses, improving signal reception when sending and receiving antennas
are not perfectly aligned and can mitigate depolarisation effects when signals are propagating
through the Earth’s atmosphere. This capability is especially beneficial for compact platforms,
where platform rotation or misalignment frequently occurs. Therefore, broad angle radiation
and link coverage (enabled by wide angle half-power beamwidths) guarantee more robust signal
connectivity, and this enhances link reliability. Furthermore, beam-steering functionality
is essential for dynamic and adaptive communication systems, as it allows the antenna phased
array to redirect its primary radiation beam towards the intended target without the need for
physical movement of the platform. This increases tracking precision, signal strength, and angular
coverage for UAVs and small satellites. Integrating beam-steering into compact antennas
also facilitates real-time modifications to sustain optimal communications with ground stations
or other airborne and spaceborne systems, enhancing both data flow and system adaptability.
In this thesis, the main goal is to address these needs for small and compact antennas to be
integrated on said compact platforms. In addition, this thesis presents an extensive study of
the design and development of miniaturised folded-short patch (FSP) antennas for compact
ground planes while also minimising the space and weight requirements for the antennas and
arrays. Furthermore, this work studies dual-band functionality, dual-circularly polarised (DCP)
radiation, and beam steering functionality while also employing new and innovative additive
manufacturing techniques.
Followed by Introduction and Background Chapters, the first contribution of this thesis (in
Chapter 3) presents a new FSP array that provides dual-band functionality and DCP radiation,
suitable for communications, geolocation, and other wireless applications. The proposed 2 ×
2 FSP array design with a total size of 50 mm x 50 mm, operates at about 1:1 and 2:4 GHz
and offers good radiation performance. In addition, this approach achieves high efficiency and
stable radiation properties while maintaining a compact footprint. In Chapter 4, a 3-D metalprinted
dual-band compact antenna array is reported with a total size of 268 mm x 66 mm.
The 1x4 compact linearly polarised array can offer beam-steering capabilities with dual-band
operation; i.e. in the L-band at 1.15 GHz and the S-band at 2:38 GHz. In addition, the measured
peak realised gain is 4.7 dBi at 1.15 GHz and 4.2 dBi at 2.38 GHz. This array design can
offer beam-steering and can improve the communications link as well as reliability in dynamic
circumstances. This design has shown promise for 3D metal printing by additive manufacturing
(AM) techniques, for such aerospace and airborne applications. The third contribution in
Chapter 5 examines AM-inspired compact and lightweight antenna designs, exploring hybrid
methods; i.e. AM, more conventional subtractive manufacturing, and, printed circuit board
(PCB) material integration. This hybridisation of the different fabrication methods achieves
structural effectiveness as well as new antenna functionalities, in particular, design tunability.
The proposed 2x2 compact array operates in the lower frequency band (UHF/VHF) with a total
size of 90 mm x 90 mm. This demonstrates the compactness of the antenna design, as the
operating wavelength can be approximately 1 metre. The array also offers CP radiation. Moreover,
the study demonstrates how advanced AM techniques may be employed, along with more
conventional assembly approaches, to offer further miniaturisation, reduce mass by introducing
air-holes (AH), and enhance antenna efficiency while still maintaining antenna performances.
In summary, the various antennas designed and measured in this final contribution demonstrate
the feasibility of reduced mass and controllable operating frequency by the hybridisation of the
aforementioned manufacturing techniques. For example, the structure can be tuned to operate
between 300 MHz and 600 MHz, while not changing the physical antenna footprint of 90 mm
x 90 mm.
All in all, this PhD research can enhance next-generation compact antenna technology, specifically
when considering placement on small satellites (i.e., CubeSats), UAVs, and other related
compact platforms, in terms of mass reduction and selective antenna performances
Vertical Land Motion in Orogenic Headwaters: A Multi-Basin Assessment of Tectonic, Geomorphic, and Anthropogenic Controls on the NE Tibetan Plateau
No full textThe northeastern Tibetan Plateau represents one of the most tectonically active margins of the India-Eurasia collision, and present-day vertical land motion (Vu) provides an opportunity to improve our understanding of ongoing fault-river interactions. This study develops a systematic, multi-basin pipeline that screens for Vu perturbations at fault-river intersections, using Sentinel-1 InSAR-derived Vu across 14 basins. After residualizing the basin-scale curvature and applying conservative statistical filter, only five crossings across four basins (~0.4% of 1,141 candidates) remained significant. Of these five crossings, two (Basin 1 and Basin 9) were able to withstand the geomorphic and sensitivity checks, and therefore represent the strongest candidates for further assessment. However, all significant detections occurred in rangeland settings, which could suggest possible anthropogenic or hydrologic influences on the signals. Independent GNSS datasets were used to benchmark the InSAR-derived Vu data, revealing weak overall agreement (r = 0.06, RMSE ~2.3mm yr -1) and highlighting the inherent difficulty in attributing subtle motions to tectonic processes alone. These findings showcase both the potential and the limitations of isolating tectonic signals from Vu fields; with future progress requiring longer InSAR stacks, improved atmospheric correction, and explicit treatment of hydrologic and land-use loading
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