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A Molecular Investigation of the Isoform-Specific Activities of Dictyostelium discoideum Class I PI3Ks During Macropinocytic Cup Formation
Get PDFClass I phosphoinositide 3-kinases (PI3Ks) are central regulators of membrane dynamics and actin remodelling in most eukaryotic cells, yet the isoform-specific roles of these enzymes remain poorly understood. In Dictyostelium discoideum, the Class I PI3K isoforms PikA and PikF are both essential for macropinocytosis, but the molecular basis of their non-redundant activities has not been resolved. This thesis investigates their distinct contributions to macropinocytic cup formation through a multidisciplinary approach combining structural biology, genetic engineering, live-cell imaging, and proteomics.
We demonstrate that PikA and PikF share highly conserved catalytic domains but differ substantially in their N-terminal regions, which likely drive their isoform-specific localisation and function. Spinning Disk Confocal and Lattice Light Sheet Microscopy reveal that PikA is enriched at the base of macropinocytic cups, where it plays a critical role in initiating cup formation and coordinating early actin assembly. In contrast, PikF localises throughout the entire cup, extending into the rim, and plays a key role in restricting Rac1 activity, thereby facilitating proper cup extension and closure. Live-cell imaging further reveals divergent trafficking behaviours, with PikA undergoing vesicular recycling and PikF remaining cytosolic when not membrane-bound.
Affinity Purification-Mass Spectrometry (AP-MS) reveals largely distinct interactomes: PikA associates with microtubule motors, myosins, and actin nucleators, while PikF interacts with actin disassembly factors, IQGAP scaffolds, and GTPase regulators. These isoform-specific networks suggest that PI3K function is not solely determined by lipid kinase activity, but also by spatially organised protein-protein interactions.
Together, these findings support a revised model of D. discoideum Class I PI3Ks, where isoform specificity arises from domain-dependent localisation and scaffolding roles that coordinate actin dynamics at distinct stages of macropinocytosis – extending beyond the traditional view of Class I PI3Ks as mere PIP3 producers. This work advances our understanding of PI3K-driven large-scale endocytosis and offers broader insight into how spatial signalling architectures govern cellular behaviour in eukaryotes
Assessing the Climate-Smartness of Oil Palm Production Systems: A Spatio-Temporal and Carbon Balance Approach
No full textThere have been on-going efforts to implement policy and practices to produce oil palm in a more sustainable way. Under climate change condition, improved policy and management practices must prioritise strategies that address the intertwined goals of mitigation, sustainable production and adaptation, the core pillars of climate-smart agriculture. However, to date, there has been a lack of empirical assessment of climate-smartness across oil palm production systems under current and projected future climate conditions.
This thesis aims to assess the potential climate-smartness of oil palm production systems in Indonesia, the world’s leading producer, which is responsible for over 50% of global palm oil production. A greenhouse gas (GHG) inventory with finer temporal resolution was used to investigate GHG emissions changes under current mitigation strategies using a coarse 500 m-grid across contrasting regions, management types, and soil types. At site-specific level, the APSIM-OilPalm model was employed to simulate the spatiotemporal variability of productivity and carbon balance for characterising climate mitigation and adaptation performance under current soil and management conditions in different oil palm sites. The APSIM-OilPalm model was also used to simulate the climate-smart metrics of various agronomic practice scenarios to identify the most climate-smart practice for oil palm production under a changing climate. The area of study for site-specific simulation is industrial oil palm plantations on mineral soils in non-deforested areas with zero-burning practices.
This study demonstrates a reduced emissions flux over periods and identifies low- and high-emission oil palm areas. Based on site-specific simulation, this study indicates that all observed OP sites act as a carbon sink ranging from –2.09 to –3.86 tCeq. ha⁻¹ yr⁻¹ across different sites, and that 11 of 25 observed oil palm sites have high climate mitigation and adaptation performance, which is indicated by higher carbon sink values, yields and soil organic carbon increment. The study demonstrates that irrigation emerges as the most climate-smart practice for oil palm production systems under climate change. A higher projected temperature, along with site-specific higher nitrogen fertiliser and lower plant density, decrease the climate-smartness of oil palm production systems.
This study suggests that the climate-smartness of oil palm production systems is viable under current policy and management practices, with additional improvement needed to sustain this under future conditions. This finding provides insight for government to maintain current successful mitigation policy as well as for farmers and industry to monitor targeted management practices that enhance climate-smartness such as maintaining plant density, combatting pests and diseases, and optimising nitrogen fertiliser, as well as prepare for irrigation or water management to adapt to warmer conditions. This ensures meeting the rising demand for palm oil while improving productivity and compliance with global environmental standards
EMI and IEMI Resistant Signalling and Communication Systems for High-speed Rail
No full textSafety-critical railway operations increasingly rely on wireless communications to convey signals relating to train control, supervision, and passenger services under stringent reliability and ultra-low latency constraints. As railway electrification expands and services accelerate, the signal transmission is exposed to electromagnetic interference (EMI) from natural and onboard sources and to intentional EMI (IEMI) from hostile jammers. These disturbances threaten the security of communicating control messages and can trigger emergency braking if they are not promptly detected and mitigated. This thesis investigates the end-to-end impact of EMI/IEMI on modern railway wireless communications and proposes detection, classification, and localization methods designed for next-generation 5G-R/FRMCS systems operating at high speed.
First, a system-level network-based modeling framework is developed to represent EMI/IEMI sources, coupling paths, and vulnerable subsystems as nodes and edges, enabling unified reasoning from physical coupling to link-level performance. Four representative EMI source categories, pantograph catenary arcing, onboard power electronics, public cellular co-existence, and diverse jammers, are analyzed to expose coupling paths and performance degradation mechanisms.
Building on these insights, a real-time classification pipeline is introduced for high-mobility 5G-R links. Time-series signal features are extracted with fine time-frequency resolution using both real and imaginary components. An Attention-BiLSTM architecture performs adaptive multi-class detection of EMI/IEMI types under rapid channel variations. Assessed on four representative railway scenarios with the train speed up to 500 km/h, the method achieves 94.98% accuracy with a 7.43 ms decision latency; validation on measurement data from a 5G-R test facility attains 92.5% accuracy. These results confirm the sub-10 ms safety detection requirements while maintaining robustness across different scenarios.
To address evolving or previously unseen disturbances, an unsupervised anomaly detector based on an AE–BiLSTM learns nominal operations and flags deviations based on the reconstruction loss. The approach reduces dependence on labelled anomalies, improves accuracy by approximately 5% over strong baselines (93.24% overall), and achieves 4.51ms online decision speed. The framework demonstrates stable performance across different speeds and environments, supporting early warning before service degradation propagates to safety-critical functions.
Finally, a localization is proposed which combines a CNN–BiLSTM angle-of-arrival estimator using a circular 16-element array with multi-AOA fusion and a Kalman filtering for 3D triangulation. The system delivers 0.71° AOA RMSE at 2.69ms inference latency and achieves sub-3m position error across scenarios (sub-2m in 92% of cases), enabling timely site isolation and targeted mitigation.
To conclude, the contributions demonstrate that deep-learning-based, time-series-aware methods can meet the latency, accuracy, and robustness requirements in EMI and IEMI-resistant wireless communications for high-speed rail. The proposed models form a practical foundation for interference-aware detection, classification, and localization within operational time budgets, and provide actionable pathways toward resilient 5G-R/FRMCS deployments in intelligent transportation systems
International Trade and Firm Performance: Evidence from India
Get PDFOver the preceding three decades, international trade has played a transformative role in shaping firm performance in developing countries. In India, the trade liberalisation initiated in the early 1990s, coupled with rapid export expansion and greater involvement in global value chains (GVCs), has led to enhanced firm competitiveness. Utilising a range of econometric methods, this thesis investigates the underlying factors shaping international trade strategies of Indian manufacturing firms and the resultant direct and spillover effects. In looking at the international trade and firm performance nexus, we pay particular attention to i) diverse forms of engagement in international trade and GVCs; ii) Productivity spillover effects from exporting and importing firms on non-trading firms and iii) the role of finance in determining firms’ survival in GVCs. Our research spans from 2000 to 2019, a period marked by a progressive internationalisation of Indian firms in response to continuing trade liberalisation and firms’ engagement in GVCs.
The first empirical chapter examines Total Factor Productivity (TFP) spillovers from exporting and importing firms to non-trading firms. The analysis distinguishes between horizontal spillover effects (within the same industry) and vertical spillover effects (across different industries). We also perform a heterogeneity analysis by exploring spillover effects on firms belonging to and not belonging to business groups. Then we evaluate the impact of exporting and importing activities on non-trading firms’ persistent increase in TFP. The empirical analysis reveals that, exporting firms enhance the productivity of their upstream suppliers, benefiting all non-trading firms regardless of business group affiliation. In contrast, importing firms are found to have a negative effect on the TFP of upstream non-trading firms along with positive horizontal gains from imitation and labour mobility. Furthermore, while export-related productivity gains are driven largely by backward linkages and persist over time, especially among business group–affiliated firms with greater capacity to absorb, retain, and amplify external knowledge, whereas import-related spillovers show no lasting effect.
The second empirical chapter of this thesis investigates how various participation modes in global value chains and their duration influence firm-level productivity. While previous research has been focused on backward GVC participation (importing foreign inputs and exporting finished goods), we adopt a comprehensive approach and categorise firms’ participation in GVCs into backward, forward (exporting inputs used to produce exported items abroad), and dual (importing foreign inputs and exporting semi-finished goods). By also including traditional exporters (exporting final goods), this chapter enables a clear comparison of productivity outcomes across different trade engagement modes. The empirical findings reveal a strong positive relationship between forward GVC participation and firm-level TFP. Notably, duration analysis provides the evidence that sustained forward participation in GVC builds experience and strengthens firms’ absorptive capacity, which raises productivity.
Finally, the third empirical chapter examines the relationship between financial constraints and firms’ survival in GVCs. We construct a multivariate financial constraint index utilising seven key indicators of financial condition, including, firm size, profitability, liquidity, cash flow generation capacity, solvency, trade receivables, and debt repayment capacity. Empirical results indicate that firms with greater financial constraints have a significantly higher likelihood of exiting global value chains, highlighting the essential role of financial resilience in maintaining long-term participation in GVCs
Activity-dependent adaptation in single neurons in the Drosophila mushroom body
Get PDFHow do neural circuits maintain stable function in the face of developmental changes and natural variability? Many neurons use homeostatic plasticity to adjust their activity to maintain a ‘set point’ level of activity. I investigate Kenyon cells, a population of ~2000 neurons that store olfactory associative memories in the Drosophila mushroom body. Our computational models suggest individual Kenyon cells should equalize the average level of activity across the population to avoid a few neurons responding to most odours while a minority are silent or respond very little. This would increase overlap between representations and impair learned odour discrimination. In this thesis I tested whether single Kenyon cells have activity-dependent compensation mechanisms to prevent such a situation. I tested this by artificially activating single Kenyon cells using the heat-activated cation channel TrpA. I find that in flies heated for 24-96 hours, TrpA-expressing γ Kenyon cells have fewer claws (dendritic input sites) than controls. However, the other two Kenyon cell subtypes, α’/β’ and α/β showed no such adaptation, suggesting different compensatory mechanisms exist between subtypes. Furthermore, this adaptation is not a result of early development flexibility but does disappear with significant age. I propose that this morphological change compensates for increased activity by reducing the number of excitatory inputs the cell receives and thereby decreasing Kenyon cell activity. This is supported by preliminary single cell live imaging experiments using the calcium indicator GCaMP, which showed that the activity of γ KCs hyperactivated for 24 hours is reduced. Together, these results reveal previously unidentified compensatory, potentially homeostatic, mechanisms in single Kenyon cells
Impact of RNA-Binding Deficiency on TDP-43-Mediated Neurodegeneration
No full textNeurodegenerative diseases are an ever-increasing burden within our ageing population, with over 1 in 3 people affected globally, and a lack of effective treatments. Neurodegenerative disorders are broadly characterised by the gradual deterioration and death of neurons in the brain and/or spinal cord causing irreversible damage to the nervous system, leading to a decline in cognitive function and/or motor skills amongst other neurological functions. Genetic, environmental factors and general ageing are all risk factors for neurodegeneration, driving complex pathological mechanisms that underly disease development and progression. Dissecting these disease mechanisms therefore becomes a critical issue, as a better understanding of fundamental mechanisms will allow more development of effective therapeutic interventions.
This thesis investigates a critical protein, TAR DNA-binding protein 43 (TDP-43), an RNA-binding protein which is closely linked to many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). In 2019, an ALS and FTD-associated RNA-binding deficient mutation of TDP-43 was identified, K181E. To study how RNA-binding deficiency contributes to TDP-43-mediated neurodegeneration in disease-specific contexts, the mutation was introduced to three separate models alongside wild-type TDP-43 and C-terminal mutations: at endogenous levels in a human neuroblastoma cell line, via overexpression in primary rodent cortical and hippocampal cells, and through overexpression in Drosophila melanogaster. Using these models, we characterised the localisation and functional effects of K181E-TDP-43 in neurons and astrocytes, identifying a novel neuronal overgrowth phenotype in K181E-TDP-43-neurons in response to activation of the stress-responsive JNK/AP-1 signalling pathway, potentially underlying its involvement in both cognitive and motor dysfunction. Furthermore, we observe TDP-43-mediated dysfunction in neuron-astrocyte interactions, irrespective of RNA-binding capability, contributing to non-cell autonomous mechanisms of toxicity. Overall, by using these models, this study unveils how disease-associated RNA-binding deficits contributes to TDP-43 proteinopathy in ALS/FTD, providing a deeper understanding of these overlapping disorders and neurodegenerative diseases as a whole
Aerodynamics shape optimization with parameter reduced adjoint method
No full textShape optimization is important for improving the performance of industrial designs, but adjoint-based methods often require hundreds or thousands of design variables, which makes optimization costly and difficult. This study proposes a parameter reduction method that keeps the flexibility of the design space while reducing computational effort.
The method combines Inverse Distance Weighting (IDW) interpolation and Radial Basis Function (RBF) interpolation for mesh deformation. IDW, with a surface smoothing procedure, provides an explicit one-to-one mapping without solving additional linear systems, which ensures efficient deformation. However, IDW alone may result in poor smoothness in the aerodynamic surface and its gradients. To overcome this, RBF interpolation is introduced, so that parameter reduction acts on control points instead of dense mesh nodes, improving both smoothness and convergence. In this framework, adjoint sensitivities are used to rank and select the most important design parameters, allowing the optimizer to focus on the aerodynamic regions that matter most, without pre-defined topologies.
The approach was tested on a 2D aerofoil, a gas turbine blade tip, and a large wind turbine blade. In the aerofoil case, the reduced-parameter method achieved a 6.8% drag reduction, comparable to the full adjoint method, while using more than 70% fewer variables. For the turbine tip, the optimized design reduced leakage mass flow by 12%. In the wind turbine blade case, aerodynamic efficiency improved with 40% less computational time compared to the full design space. In all cases, the optimizer maintained or improved design quality at much lower cost.
The results show that combining IDW and RBF with sensitivity-based parameter reduction provides a robust and scalable strategy for high-dimensional aerodynamic optimization
Adaptation in an unpredictable world: consequences for insect responses to environmental stress
No full textClimate change is driving temperatures to become more variable and less predictable,
which is increasing the threat of extreme thermal stress in natural populations. In this
thesis, I investigated how historical exposure to different magnitudes of unpredictable
thermal variation affected population responses to future stress.
Using the moth, Plodia interpunctella, I established three experimental selection lines,
which experienced either constant, or low or high variation stochastic temperatures. After
multiple generations of exposure, the lines expressed altered phenotypes, and responded differently to acute heat stress, which had strong negative effects on life history traits. Building on this, I investigated the effects of acute heat stress, and chronic resource stress, across developmental stages. The stochastic, variable lines showed evidence of increased resistance, as well as vulnerability to stress, depending on the stress combination, developmental timing, and trait. This indicated historical, stochastic thermal variation could drive distinct life history strategies, depending on the thermal variance. To explore the mechanisms underpinning these different strategies, I performed ddRAD sequencing on each selection line, to characterise the genetic differences between them. The lines were genetically differentiated, indicating that stochastic thermal variation was driving genetic adaptation. I also found evidence for alleles under selection, which were associated with development and adult body plan specification. Finally, I investigated male fertility, by assessing the sensitivity of sperm production and mating behaviours to heat stress, between the three lines. I showed exposure to historical thermal variation altered both behavioural and sperm responses to stress, which were overall, highly negative, and suggest that fertility would be degraded at sub-lethal levels of heat stress in this species. These results suggest that stochastic thermal variation can shape complex phenotypic and genetic changes, depending on the level of temperature variance, which can prepare, or impair populations to damaging climate stress
Stabilisation of functional proteins in a synthetic membrane, with the structure-dependent emission of fluorescent dyes
No full textBilayers are widely studied and critically important to a wide range of biological systems, a full understanding of which requires a deeper understanding of the interactions that occur within the bilayer. As interactions between lipids and proteins underpin the functions of the cell membrane and how proteins removed from a cell membrane behave. Here I present two different methods using a bottom up approach
that can be used to investigate the interactions that occur within a bilayer, both natural, lipid, and artificial, polymer.
A bottom-up approach to understanding the mammalian cell is to develop an artificial cell using either lipids or amphiphilic polymers to make the bilayer membrane, but keeping proteins stable in these membranes has proven difficult. Here, I show that the key to stabilising proteins within the membrane is the thickness of the membrane, and through the minimisation of the hydrophobic mismatch between the protein and the bilayer, the relative activity of a light-harvesting complex in a polymer membrane
can be significantly improved by an order of magnitude. When this is combined with the inherent stability of polymer vesicles (polymersomes), a system that remains stable for several months has been developed using low (around 1000Da) molecular weight polymers.
This is, however, only one aspect of the complex environment that makes up a cell membrane. The formation of membrane rafts is thought to be driven by the desire to minimise the hydrophobic mismatch between the lipid bilayer and proteins. Using Fluorescence Lifetime Imaging (FLIM) microscopy, I have been able to image micron-sized lipid domains and distinguish between liquid ordered and liquid disordered domains from the fluorescent signal from Texas Red, NBD and DI-4-ANEPPDHQ. Providing
a toolkit that can be used in future investigations
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