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Aberrant MYC Levels Shape Germinal Centre Dynamics and Lymphoma Potential
No full textChromosomal translocations leading to MYC overexpression are frequently observed in germinal centre B (GCB) cell-derived lymphomas. Although concomitant stabilising mutations in MYC, such as T58A, are less common, they are found in aggressive lymphomas like Burkitt and double-hit lymphomas and are associated with poorer prognosis. Under physiological conditions, MYC is transiently induced in positively selected GCB cells within the light zone (LZ), following B cell receptor (BCR) stimulation and T cell help (TCH). How pathological MYC levels reshape GCB cell dynamics and promote lymphomagenesis remains unclear. To mimic chromosomal translocation-driven MYC overexpression, we adopted novel mouse models enforcing either wild-type MYC (MYCWT) or the stabilising T58A mutant MYC (MYCT58A) in GCB cells. Surprisingly, while MYCWT triggered transient GC hyperplasia, MYCT58A did not. Instead, MYCT58A drove long-term accumulation of GCB cells and accelerated GCB cell lymphomagenesis. Although MYCT58A cells proliferated more than MYCWT, their higher apoptosis and altered FOXO1 regulation likely underpinned the loss of transient hyperplasia. Functionally, CITE-seq revealed enhanced proliferation and metabolism in MYCWT and MYCT58A GCB cells, accompanied by reduced activity in signalling pathways associated with positive selection. However, MYCWT and MYCT58A only protected GCB cells from transient but not sustained TCH deprivation, suggesting continued reliance on survival signals like mTOR. Notably, flow cytometry and CITE-seq demonstrated enrichment of an intermediate LZ-dark zone (DZ) phenotype in MYCT58A GCB cells. These intermediate LZ-DZ cells were metabolically active, whose transcriptional signatures were enriched in human B cell lymphomas, correlating with malignant subtypes Burkitt and double-hit lymphomas. This phenotype also corroborated the enrichment of CCND3 mutations in human Burkitt Lymphomas, particularly when concurrent with MYC stabilising mutations, suggesting selection for mutations that promote DZ programme during MYCT58A-driven lymphomagenesis. Together, these findings revealed how MYCWT and MYCT58A differentially remodel GC dynamics, transcriptional programmes, and metabolic dependencies, thereby promoting GCB cell lymphomagenesis
The temporal dynamics of adaptation to background noise
No full textThe auditory system’s remarkable ability to adapt its processing to the statistical properties of background noise is a key contributor to its ability to facilitate hearing in complex acoustic environments. However, the temporal dynamics of this process of adaptation and the precise acoustic features that influence them are not fully characterised on a perceptual level, particularly in response to complex, naturalistic sounds. This thesis aimed to comprehensively characterise the time course of perceptual adaptation to naturalistic background noise and the factors influencing its build-up and reset, as well as investigate the causal role of the non-primary auditory cortex in this process.
I conducted a series of psychophysical experiments in human listeners, using a behavioural paradigm in which continuous background noises switched in spectrotemporal identity and/or spatial location between trials. By systematically varying the target onset delay (0–1750 ms) relative to this change, I mapped the time course of adaptation. To test the causal contribution of non-primary auditory cortex to this process, I then adapted this paradigm in ferrets while incorporating optogenetic inactivation.
Human listeners consistently demonstrated a rapid perceptual benefit, developing over several hundred milliseconds and plateauing around 1000 ms. This adaptive benefit was reset by changes in both spectrotemporal and spatial shifts. Acoustic feature analysis of 109 naturalistic noises revealed that the magnitude of adaptation was strongly modulated by the temporal statistics of noise, with less stationary noises benefiting from a greater adaptive benefit. This time course was also found to be largely preserved in older listeners, irrespective of age-related hearing loss. In contrast, I was not able to demonstrate the same perceptual benefit in ferrets, likely due to attentional confounds, and consequently, cortical inactivation was inconclusive
Rational Design and Improvement of Cu-based catalysts in CO Oxidation
No full textCarbon monoxide is one of the most hazardous pollutants in automotive gas exhaust emissions due to its severe impact on the human body and environment. There are many methods for CO removal, including adsorption, methanation, and catalytic oxidation. Catalyst oxidation has been considered the most efficient technique for CO removal. Although CO oxidation has received extensive attention in past decades, achieving high activity and stability at both engine working and cold starting temperatures is still challenging. Noble metal catalysts generally exhibit excellent catalytic activity in high-temperature regions. However, it still suffers from several obstacles, such as over-absorption of CO in low-temperature regions for Pt-based catalysts. Therefore, researchers still focus on seeking alternative candidates for noble metals due to their high cost and low availability, promising non-noble metals including manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu) receive increasing attention due to their high catalytic activity and stability.
Many forms of catalysts have been studied exclusively, such as metal catalysts, metal oxide catalysts, supported catalysts, zeolite, and carbon-based catalysts. Supported catalysts with available metal surface area and unique metal-support interfacial perimeter play pivotal roles in heterogeneous catalysis across various industrial applications. Depending on the size of supported active metal, supported metal catalysts can be categorized into particle, cluster, and single-atom catalysts. Among these, single-atom catalysts (SACs) with relatively specific active structures offer prominent advantages in optimizing catalytic activity and product selectivity, leading to an increasing interest in this research area. In recent years, the catalytic performance of SACs has been largely improved through some reported methods including adjusting coordination number, doping heterogeneous atoms, modulating support anchoring sites, and so on. Despite these advancements, it has always been ignored that with the change of the catalyst synthetic process as well as the metal-support interaction (MSI), supported active sites may appear at different positions in catalyst supports, especially at surface or subsurface, thus exhibiting distinct different catalytic behaviour with surrounding molecules. However, the isolated metal site-related location effect is very difficult to deeply explore, because the complexity of catalyst synthesis, combined with the absence of a metal atom location descriptor, poses significant obstacles to achieving precise control over the location of active metal.
Herein, we first proposed an electronic metal-support-carbon interaction (EMSCI), which provides a complete picture of the mass and electron flow and expands on the traditional electronic metal-support interactions (EMSI) concept. Furthermore, we reported an exception of EMSI where the interaction between support and metal is not necessary to achieve a high catalytic activity in the CO oxidation reaction, especially in low-temperature regions. The reducibility of CeO2 is investigated by Ce L3 and M4,5 edge NEXAFS, it is confirmed that CeO2 cannot be reduced even under the reductive conditions. Moreover, the location-dependent Cu species have been investigated which are formed during the hydrothermal process using both ex situ and in situ X-ray techniques. The CO oxidation activity shows a positive relation to the percentage of Cu(CO)+ species detected during the reaction. Such behaviour resembles the intrinsic catalytic activity of a true Cu(CO)+ single site, in which the support is completely inactive. This unique phenomenon provides a new scope of understanding metal support interaction and a pathway to optimizing single-atom catalyst performance and catalyst design
Thesis on Environment and Transport Economics
No full textThis thesis examines how supply-side carbon pricing and demand-side purchase sub-
sidies reshape market structure and welfare in Europe’s two largest transport sectors:
aviation and automobiles. Chapter 1 analyses the European airline industry using
a two-stage entry-and-pricing model that captures key institutional features such
as airport slot constraints and point-to-point business models. Fixed-cost parame-
ters are estimated through a hybrid approach combining moment inequalities with
maximum likelihood, ensuring policy simulations remain consistent with observed
market structures. The analysis shows that carbon pricing induces asymmetric
network adjustments concentrated among low-cost and regional carriers, while full-
service groups at hub airports remain relatively resilient. Although industry profits
decline, the reallocation of capacity improves allocative efficiency and redistributes
welfare unevenly across Europe. Chapter 2 evaluates electric-vehicle purchase sub-
sidies in the UK, France, and Germany (2010–2021) using a random-coefficients
logit demand model with micro-moment calibration and a static Bertrand pricing
framework. The results show that the expansion of the EV market has been driven
mainly by product innovation and model fleet turnover rather than by flat purchase
incentives. Subsidy effectiveness varies across countries, with limited impacts in the
UK and France but stronger effects in Germany. An income-targeted subsidy de-
sign achieves similar emissions reductions at substantially lower fiscal cost and with
greater equity. Together, the chapters demonstrate that environmental policies op-
erate through distinct mechanisms—reconfiguring airline networks and influencing
car buyers’ choices—and that well-designed instruments can achieve decarbonisation
with higher efficiency and fairer distributional outcomes
Artificial Ageing of Cellulose-Derived Fibres Under Abiotic Conditions for the Characterisation of Degradation Markers
No full textThere has recently been renewed interest in cellulose-derived fibres, both for their historical
significance and their potential to replace synthetic fibres in the textile industry. One aspect is that these fibres are increasingly present in heritage collections due to their early adoption in the 1900s and the contemporary shift toward sustainable textiles. By contrast, due to their biodegradable nature and more sustainable life cycle, there has been a surge in demand from the textile industry. Despite their growing importance, the long-term degradation behaviour of cellulose-derived fibres remains insufficiently understood, particularly regarding abiotic environmental conditions.
This thesis investigates the degradation of cellulose-derived fibres in the context of cultural heritage preservation and environmental textile waste. This work explores how their chemical and structural properties govern their interactions with their degradation environments through developing accelerated ageing methods to evaluate a range of
degradation drivers, enabling precise monitoring of fibre deterioration. Key degradation factors include temperature, relative humidity, pH, and ultraviolet light. By analysing a broad sample set, from historic textiles to unaged textiles, the study establishes a robust framework for applying analytical techniques across conservation and sustainability contexts.
A multifaceted approach is employed, combining infrared spectroscopy, gas chromatography, X-ray diffraction, and microscopy to identify and evaluate key degradation markers. The thesis further enhances the applicability of these techniques by establishing correlations between physical metrics, such as mass loss and discolouration, to improve the tracking and interpretation of degradation mechanisms.
By bridging heritage science and environmental sustainability, this research provides interdisciplinary insights into the cellulose-derived fibre degradation process, with applicability across conservation and waste management. Its findings contribute to improved conser vation strategies for historical textiles while also informing the degradation behaviour of these materials as textile waste
Machine Learning for Real-Time Flavour Tagging and Background Modelling in 4b Final States with the ATLAS Experiment
No full textThis thesis demonstrates the application of advanced machine learning techniques to improve the identification and analysis of b-jet final states within the ATLAS experiment at the Large Hadron Collider. Two complementary studies are presented, addressing challenges at both the online event selection stage and in offline searches for new physics.
The first study develops graph neural network (GNN)-based algorithms for b-jet identification in the high-level trigger (HLT). Building on the DL1d tagger used in early Run 3 data taking, the GN1 tagger was deployed in 2023, achieving up to a factor of two improvement in light-jet rejection compared to Run 2 performance. This directly reduced trigger rates for HH –> 4b analyses while preserving signal efficiency.
The second study presents a search for a new resonance X decaying into a scalar S and a Higgs boson, with both subsequently decaying to bb. Using 126.9 fb-1 of pp collision data at √s = 13 TeV from Run 2, the analysis focuses on the resolved 4b final state in the mass ranges mX ∈ [300, 3000] GeV and mS ∈ [70, 2500] GeV. To overcome challenges posed by large QCD multijet backgrounds, data-driven background modelling techniques based on normalizing flows and Gaussian processes are employed. No significant excess above the Standard Model expectation is observed, and 95% confidence-level upper limits on σ(pp –> X –> SH –> 4b) are set, ranging from 2.5 to 1978.9 fb.
Together, these studies illustrate how modern machine learning approaches enhance real-time b-jet identification in the trigger system and enable robust analyses of complex b-jet signatures in the search for new physics
Investigating the Effects of Placental Hormones in an In Vitro Model of Hepatic Steatosis
No full textNon-alcoholic fatty liver disease (NAFLD) represents a range of liver conditions, from lipid accumulation (steatosis) to more serious steatohepatitis and fibrosis. Its global rise is closely linked to increasing obesity rates. Of particular concern, are women of childbearing age and those who are pregnant, who face a rising prevalence of both obesity and NAFLD. During normal pregnancy, maternal metabolic system adapts to support foetal growth, primarily through the development of transient insulin resistance (IR), a process regulated by placental hormones e.g. placental lactogen (PL) and placental growth hormone (pGH). In pregnancies complicated by hepatic steatosis and IR, hepatic metabolism may fail to adapt, leading to pregnancy complications like gestational diabetes mellitus (GDM). The effects of placental hormones on metabolic pathways in the steatotic state remain unclear, particularly if they further impact insulin signalling and contribute to GDM. The project aimed to investigate the effects of PL and pGH on hepatic metabolism and insulin signalling pathways in an in vitro hepatic steatosis model. The model was developed using HepG2 cells incubated in a mixture of oleic and palmitic free fatty acids (FFA) in a 2:1 ratio for 24 hours. Lipid accumulation was confirmed in the model, with triglycerides increasing to 5.3-fold compared to controls. The addition of PL and pGH to steatotic cells, led to a slight decrease and increase in TG content respectively, though not significantly. Metabolomics analysis using 1H NMR-based and multivariate statistical methods revealed that lipid loading of the HepG2 cells affected several pathways associated with energy, glucose and lipid metabolism. For example, FFA-treated cells exhibited increased lactate and glutamate levels, alongside reductions in glucose and creatine. Co-treatment with PL or pGH produced distinct metabolomic profiles compared to lipid-loaded cells, although no clear hormone-specific pattern was observed. Effects of hormones on a major regulatory pathway in lipid metabolism, i.e. AMPK/ACC signalling pathway and on insulin signalling was studied by Western blot of phosphoproteins. FFA treatment increased phosphorylation of AMPK by 4.4-fold and ACC by 2-fold. PL and pGH co-treatments showed opposing trends in AMPK/ACC phosphorylation compared to FFA alone, with PL tending to increase and pGH to reduce phosphorylation levels, though differences were not statistically significant. PL and pGH significantly reduced insulin-stimulated Akt phosphorylation in FFA-loaded HepG2 cells by 66.6% and 76%, respectively, compared to control. While these reductions were not significantly greater than the 44% decrease observed with FFA alone. Overall, FFA loading in HepG2 cells induced significant alterations in lipid accumulation, metabolite levels, AMPK/ACC signalling, and insulin sensitivity. While PL and pGH modulated some pathways, they did not significantly alter the steatotic phenotype
Rational Design of Anion-Exchange Chromatography for Lentiviral Vectors Through Mechanistic Insights into Sorption Behaviour
No full textThe expansion of cell and gene therapy clinical trials has sharply increased demand for viral vectors. Lentiviral vectors (LVs) have become the primary tools for engineering patient cells to produce CAR-T therapies, an emerging form of cancer treatment. However, efficient LV purification remains a major bottleneck to delivering these therapies affordably and at scale. Product loss during anion-exchange (AIEX) chromatography, the dominant method for primary capture, is the main contributor. Large-scale recoveries are exceptionally low (~20%), and reported yields vary widely (0-100%), reflecting limited understanding of the complex adsorption phenomena and loss mechanisms underpinning LV AIEX. Consequently, no consensus has been reached on optimal chromatography configurations. Addressing this challenge requires identifying dominant loss mechanisms and defining how LV structural attributes and adsorbent morphology influence performance. Such insights will support the rational design of next-generation AIEX strategies capable of reliably achieving high LV recovery.
This research demonstrates that time spent in the adsorbed state (contact time) is a critical, and likely the major, source of LV product loss on commercial Q-membrane adsorbents. This loss was attributed to a process of increased irreversible binding, rather than vector inactivation. Characterization of loss kinetics demonstrated half of all recoverable product was lost within 13-19 minutes, highlighting the rapid rate of material loss. By using low contact times (5 min), significant improvement to AIEX recovery is achieved (~60%). Increasing adsorbent occupancy reduced this effect, while no correlation with overall LV charge was observed. These findings identify contact time as the predominant factor limiting LV recovery in commercial Q-membranes, suggesting that their current interaction strengths are incompatible with high LV recovery.
Linear gradient elution consistently produced a two-peak profile, as widely reported in the literature. Elucidating the LV structural factors driving this behaviour is therefore essential for rational process design. Enzymatic digestion and peak re-injection experiments revealed two distinct LV subpopulations, each binding via different envelope components: a strongly binding population interacting through glycosaminoglycans (Peak 2), and a weaker-binding population likely interacting via the phospholipid membrane and/or envelope proteins (Peak 1). Importantly, these subpopulations displayed differences in primary T cell transduction efficiency, highlighting a potential new source of product heterogeneity.
Manipulating structural features of Q-nanofiber adsorbents influenced both LV recovery and the distribution of the two-peak elution profile. Increasing adsorbent porosity improved recovery, likely by mitigating time-dependent loss, while nanofiber diameter and ligand density primarily influenced peak separation within the two-peak gradient elution profile. The best performing adsorbent configuration achieved high LV recovery (∽70%) and enhanced resolution between LV subpopulations, offering a potential route to isolate high-potency LVs.
These insights were formalised in a physics-based mathematical model of LV AIEX chromatography. A modified multi-state steric mass action framework accurately captured both two-peak elution behaviour and contact time-dependent loss, providing a key first step in developing a predictive tool for in silico process development.
Collectively, the findings of this thesis provide a deeper understanding of LV sorption behaviour, offering a foundation for the rational design of high-yield LV AIEX processes, in silico process models, and future vector-specific separation materials
Exploring Sterile Neutrinos at High and Low Energy Scales
No full textThe inability of the Standard Model (SM) to explain certain observations, such as neutrino masses, hints at new physics Beyond the SM (BSM). Sterile neutrinos – hypothetical right-handed neutral leptons appearing in numerous BSM theories – are compelling extensions of the SM as they can remedy several of these issues. This thesis offers a phenomenological study of light and massive sterile neutrinos in future experiments.
Without model predictions, the neutrino mass needs to be determined experimentally. Single beta-decay is the only available direct probe, thus we explore whether these experiments can search for new physics beyond the SM, such as keV-mass sterile neutrinos, which manifest as distortions in the energy and angular spectra of the emitted beta-electron. Studying these distributions, we conclude that the next generation of tritium beta-decay experiments utilising Cyclotron Radiation Emission Spectroscopy can improve existing bounds by an order of magnitude. Furthermore, we find that such experiments will also be sensitive to BSM couplings parameterising exotic interactions differing from the usual V-A structure of the weak Lagrangian.
In Effective Field Theory (EFT) frameworks, the SM can be extended with Dirac and Majorana sterile neutrino states. In the EFT formalism, the interactions are approximated by operators, and their relative coupling strength is parameterised by Wilson Coefficients (WC). Considering the Future e⁺e⁻ Circular Collider (FCC-ee), we study monophoton final states originating from active-sterile mixing by performing and analysing computer simulations of the process using MadGraph and derive projected sensitivities to the mixing angle. Additionally, we study monophoton final states from four-fermion processes, displaced di-electron final states, and effective Z and W⁺⁻ mediated processes. We estimate the sensitivity of the FCC to the WCs and conclude that the FCC will place stringent limits on the operator scales of the relevant WCs associated with GeV-mass sterile states
Durables and lemons: Private information and the market for cars
No full textPrivate information on car quality means the sale price reflects the average quality of cars sold, which can be lower than the average quality in the population. This difference is the lemons penalty imposed on holders of high‐quality cars. We estimate the evolution of the lemons penalty through an equilibrium model of car ownership with private information using Danish linked registry data on car ownership, income, and wealth. We examine the aggregate implications and distributional consequences of these penalties. In the first year of ownership, we estimate that the lemons penalty is 12% of the price. The penalty declines sharply with the length of ownership. It reduces the self‐insurance value of cars and leads to a large reduction in transaction volumes and the rate of car turnover. The market does not collapse: income shocks induce households to sell their cars, even if they are of good quality, and this helps mitigate the lemons problem. The size of the lemons penalty declines when income uncertainty in the economy increases and when the supply of credit decreases