VictorJuiz/thesis huggingface dataset:
Transcriptional regulation of endothelial KLF2 in vascular development

The development of a functional vascular system is critically dependent on shear stress, a hemodynamic force exerted onto the vascular endothelium by flowing blood. Krüppel-like factor 2 (KLF2) is the central transcriptional regulator of the endothelial shear stress response, yet the mechanisms by which shear stress signalling controls KLF2 expression remain controversial. Activation of KLF2 by shear stress was previously hypothesised to occur through a MEK5-ERK5-MEF2 pathway directly interacting with the KLF2 promoter, thereby inducing KLF2 expression. However, KLF2 is expressed in many different cell types in response to a variety of different upstream signals, suggesting cell type-specific KLF2 expression might be regulated by yet undescribed distal enhancers. Further, MEF2 factors not only control differentiation of many non-endothelial cell types, but also regulate the expression of endothelial genes independent of shear stress signalling, suggesting additional transcriptional regulators must interact with MEF2 to induce context-specific KLF2 expression. In this thesis, I identify and characterise two KLF2 enhancers able to drive reporter gene expression specifically in endothelial cells (ECs) and endocardial cushions (ECCs) independently of the KLF2 promoter, which is by itself unable to drive any reporter expression in development. Pharmacological inhibition of cardiac contractions during development resulted in a reduction of reporter expression driven by both enhancers, suggesting they might be regulated by shear stress-responsive transcription factors (TFs). Validated phylogenetic foot-printing combined with mutational analysis of both KLF2 enhancers implicated roles for MEF2 binding alongside a number of other TFs. Crucially, a previously unidentified MEF2-HBOX double motif was found to be required for the endothelial activity of both KLF2 enhancers, and was sufficient to identify a novel EC-specific enhancer for KLF4, a gene that compensates for KLF2 in vivo. This work demonstrates previously unappreciated complexity in the transcriptional regulation of KLF2, and provides an opportunity to better understand transcriptional dynamics at the locus of this disease-relevant gene.

Keywords: KLF4
transcriptional regulation
vascular endothelium
KLF2
vascular development
shear stress
Advisor: de Val, S
Neal, A
Workhouse ecologies: Hampshire case studies, c. 1776-1845

While the historiography of the workhouse in England has largely followed a vertical line, namely taking a top-down or bottom-up approach, this thesis aims to extend the boundary of workhouse research horizontally by integrating multifaceted socio-economic factors, which have been overlooked or considered just in passing in previous discussions, in order to analyse often highly localised patterns of workhouse provision and regime. The term ‘ecologies’ recurring throughout this research is chosen to crystallise my holistic approach.
For this purpose, neither a national nor a parish-based study is appropriate because the former tends to generalise findings and the latter to seek peculiarity. This project focuses on a county, Hampshire, and does not just establish that there were intra-county variations in workhouse ecologies but goes further to compare and classify them using both quantitative and qualitative methods. Drawing on statistical analyses, it demonstrates that various factors, such as demographic characteristics, transport infrastructure, and socioeconomic structure possibly affected regional variations in workhouse provision under the Old Poor Law. Using parochial administrative records, we then examine how workhouse ecologies in the different divisions formed by differing combinations of socio-economic factors produced difference in practical terms.
Moreover, unlike most existing research that usually ends or begins in 1834, the year of the passage of the New Poor Law, this thesis covers both the Old and New Poor Laws to explore changes and continuities through the transitional period. A structural transformation in poor relief administration was brought about by the new act, but to varying degrees within the county, in ways affected by past regional patterns. Regional patterns surviving from the Old Poor Law made it unfeasible to impose the intended uniformity on poor law administration and workhouse practices.

Keywords: workhouse ecologies
Advisor: Innes, J
Novel hybrid multipolar RF cavities for transverse beam manipulations

This thesis describes the development and application of a method for tailoring the profile of electromagnetic fields in RF cavities for use in particle accelerators. This so-called azimuthal modulation method (AMM) is underpinned by an analytic expression of the basis of the electromagnetic modes in closed RF cavities whose cross-sections vary with the azimuth. This basis is derived and the notation {M}ηp is introduced to describe the azimuthal, radial and longitudinal form of the modes.
The scope of the AMM for designing realisable cavities is explored. The underlying reasons for the limitations on the range of magnitudes and orientations of multipoles that can be supported by azimuthally modulated cavities are derived and discussed.
This understanding provides the foundation for the latter half of the thesis where numerous applications of the AMM are presented. First, the AMM is used to construct a prototype cavity that supports a 3 GHz mode which could be used for the simultaneous acceleration and focusing of a particle beam. Experimental testing supported the multipolar content of the mode being as designed. Second, the AMM is applied to create RF cavities which support modes free from unwanted multipoles generated by power couplers and tuning pins. An example design of an RF structure which incorporates a single-slot power coupler and supports an accelerating mode free from dipole, quadrupole, sextupole and octupole components is analysed. Third, the AMM is used to design RF cavities that support modes tailored for the off-axis traversal of particle beams. An example optimisation of an accelerating field that remains as flat as possible along the horizontal is presented. Finally, the AMM also finds application in the creation of musical drums. This concept inspired an outreach workshop that was designed and delivered to showcase this research to 11-14 year-old school students.

Keywords: accelerator physics
RF cavities
multipole expansion
electromagnetic fields
Advisor: Sheehy, SL
Apsimon, R
Dosanjh, M
Viral modulation of the anti-glioblastoma immune response: rewiring host immunity to recognize & kill brain cancer

Glioblastoma (GBM) is a universally fatal solid malignancy of the central nervous system (CNS), hallmarked by a high mitotic index, intercellular heterogeneity, and low neo-antigen burden. Standard of care including surgery, radiation, and chemotherapy has failed to improve life expectancy beyond 15 months. The utility of local therapies is limited by the in-vasive nature of GBM, its protection behind the blood-brain barrier (BBB), and the absence of a single, druggable pathway. Advancing GBM therapies will likely require immune-based strategies given the ability of immune cells to traverse the BBB and evolve with the changing mutational landscape of the tumor. To this end, we employed a syngeneic murine GBM model, SB28, that recapitulates the highly inflamed environment observed in the brain fol-lowing surgical resection and that enables tracking by intravital two-photon (2P) microscopy. We uncovered that absent any additional immune stimulus, a negligible amount of tumor an-tigen is drained to the nodes and virtually no tumor-specific immune response is mounted. To stimulate anti-tumor immunity, we administered a noncytopathic arenavirus (lymphocytic choriomeningitis virus) into circulation that expressed the tumor antigen, Ovalbumin. This infection profoundly altered the tumor immune landscape, led to antigen drainage, tumor-specific lymphocyte expansion in the nodes and trafficking to the tumor milieu, resulting in significant extension on survival.

Keywords: cancer immunology
virology
meningitis
glioblastoma
Advisor: Powrie, F
McGavern, D
Deep learning applications in structure-based drug discovery

In recent years, machine learning and deep learning applications have permeated all fields of science thanks to rapid algorithmic advances and computer hardware developments. A very active area of research is the use of deep learning in structure-based drug design, where the goal is to design effective drugs against a pharmacological target of interest.
In this work, we explored the use of deep learning in the early stages of drug discovery. In particular, we focussed on structure-based virtual screening, binding affinity prediction, and de novo drug design.
First, we enabled docking with flexible residues within Gnina, a state-of-the- art docking software based on convolutional neural networks, and we performed a large-scale cross-docking study of such methodology, outlining its strengths and weaknesses.
Second, we extracted the convolutional neural network scoring function from the docking software into a standalone package for fast prototyping. With the new software at hand, we explored different annotations for supervised learning to improve the convolutional neural network scoring function for docking with flexible residues.
Third, we developed a novel scoring function for binding affinity prediction based on a successful deep learning architecture used to develop machine learning force fields.
Finally, we carefully evaluate a generative model for de novo design for the application in industrial drug discovery pipelines. We outline the weaknesses of the method and the problems with current evaluations of generative models.

Keywords: drug design
structure based drug design
neural networks
convolutional neural networks
drug discovery
deep learning
sbdd
machine learning
Advisor: Biggin, P
Morris, G
Improving the performance and reproducibility of lead - tin perovskite absorbers toward all-perovskite tandem solar cells

This thesis explores a subset of hybrid perovskites that incorporate tin into their crystal lattice alongside lead. Hybrid perovskite semiconductors have gained global interest over the past decade due to their remarkable optoelectronic properties, and excellent power conversion efficiencies, which now compete with well-established commercial technologies. By incorporating tin, these materials can achieve band gaps far narrower than their pure-lead counterparts. This property makes lead-tin perovskite materials suitable for the construction of all-perovskite tandem solar cells to improve power conversion efficiencies beyond the theoretical limit for a single junction device. Although these materials are promising and have been successfully demonstrated to achieve high power conversion efficiencies, they are still far below their theoretical efficiency and comparatively few studies have been conducted on how to maximise the potential of this class of materials. The work presented in this thesis explores three topics utilising an FA0.83Cs0.17Pb0.5Sn0.5I3 absorber. In the first instance a bulk passivation strategy is investigated with the aim to reduce non-radiative recombination in the absorber material, using several thiocyanate additives that are found to successfully enhance the photoluminescence quantum efficiency of the material and improve charge carrier diffusion length. Proceeding this, the influence that selective contact materials have on non-radiative recombination is explored culminating with a passivation strategy at the interface with the electron transport material. This led to enhanced performance of resulting devices. Chapter 5 details the fabrication of 2T-monolithic tandem solar cells. The successful resolution of fabrication issues, and optimisation of the lead-tin sub-cell generated highly efficient tandem solar cells. The final experimental chapter in this thesis investigates the removal of DMSO from the lead-tin precursor ink due to its ability to oxidise Sn2+ to Sn4+, which can cause detrimental effects within the material. This is achieved by the addition of the ammonium halide salt DMACl. It is shown that highly oriented thin films can be fabricated with enhanced grain sizes leading to a much-improved device stability, in air, of over four times that of the device utilising DMSO.

Keywords: narrow band gap
lead-tin
tandem solar cells
DMSO-free
perovskites
precursor phase
photovoltaics
Advisor: Snaith, H
Unravelling the degradation pathways and charging mechanism in the Li-O2 battery: the role of singlet oxygen


Lithium-oxygen batteries (LOBs) have attracted immense research interest as they have the highest theoretical energy density among the advanced battery systems. Achieving such high energy densities can substantially reduce the need for fossil fuels, enable greater use of renewable energy, and revolutionise the transportation sector. However, due to the complexity of oxygen reduction and evolution reaction chemistries and reactivity of reduced oxygen species, LOBs still need significant improvement in their fundamental understanding to overcome the electrolyte and cathode stability issues.
In the Thesis, firstly, the redox mediated charging process was studied to understand the mechanism to enable fast charging with low overpotentials and side reactions. It is demonstrated that the redox mediated oxidation follows Marcus theory of electron transfer and the rate limiting step is the first 1-electron oxidation, Li2O2 → LiO2. The kinetically dominant step is the LiO2 disproportionation. It is also shown that the singlet oxygen (1O) yield does not correlate with the amount of degradation. This casts doubt on whether 1O2 is the main cause of degradation in LOBs.
Secondly, due to the discrepancy in 1O and electrolyte degradation amounts, the stability of the common LOB salts and solvents towards 1O2 were tested. It is shown that tetraglyme-LiTFSI, one of the most widely used electrolytes, is stable towards 1O2 under chemical conditions. In the LOB literature, 1O2 is mainly detected and quantified using DMA, a 1O2 trap. Here, it is revealed that DMA can react with superoxide depending on the salt-solvent combination and DMAO2, the reaction product of 1O2 with DMA, can degrade into by-products depending on the solvent environment.
Finally, the stability of the electrolyte and the cathode towards 1O2 under electrochemical conditions and the real cause of faradaic efficiency loss are investigated. It is demonstrated that 1O2 is not the main source of degradation and fresh Li2O2 surfaces is the culprit. This finding should redirect the focus of LOB research from avoiding 1O2 to developing electrolytes inert towards peroxide and peroxide-derived side products for an electro/chemically stable cell.

Keywords: Rechargeable batteries
Singlet Oxygen
Li-O₂ batteries
Li-air batteries
Advisor: Bruce, P
Sublinear rigidity of lattices in semisimple lie groups

In this thesis I prove metric rigidity results for lattices in real semisimple Lie groups without compact factors and with trivial centre. Let G be such a group. The first result is that if the sublinear neighbourhood of a discrete subgroup of G contains a lattice, then it is itslef a lattice. In case the group G does not admit real rank 1 factors, I prove that the classses of uniform and non-uniform lattices of G are SBE-complete, generalizing the well known quasi-isometric completeness of these classes.

Keywords: metric rigidity
Lie groups
sublinear neighbourhoods
Quasi-isometry
SBE
sublinear bilipschitz equivalence
quasiisometry
lattices
discrete subgroups of Lie groups
buildings
Advisor: Drutu badea, C
Individualising the use of radiotherapy for the treatment of people with Hodgkin lymphoma

Hodgkin lymphoma is a cancer of the lymphatic system that typically affects young adults. Chemotherapy and radiotherapy are both highly effective treatments, and 80-90% of patients now become long-term survivors, living long enough to experience late toxicities. Radiotherapy in particular has been shown to increase the long-term risk of cardiovascular disease and second malignancies, and recent trials have attempted to identify patients in whom radiotherapy can be omitted. Omission of radiotherapy has, however, been shown to substantially increase the chance of Hodgkin lymphoma recurrence. The decision about whether or not to use radiotherapy for an individual patient therefore involves weighing up the proven benefit against the potential risks of late toxicity.
The aim of this thesis is to understand the decision-making process about radiotherapy, and provide data that can be used to inform patients and clinicians at various steps. I explore patients’ and clinicians’ experience of radiotherapy decision-making, and propose a new decision-making model that fits this context. I present a comprehensive summary of the late toxicities of radiotherapy, including the dose-response relationships that can be used to estimate risks from modern radiotherapy. I report the radiation dose received by abdominopelvic organs in a historic cohort of Hodgkin lymphoma survivors, and show how the data has been used to estimate the dose-response relationship for the risk of colorectal cancer. Finally, I present a multivariable linear regression model that estimates the dose a patient’s heart would receive from radiotherapy using measures available at the time of their diagnosis. I use the model to estimate individual patient’s risk of ischaemic heart disease, and show its accuracy is greatest in the medium heart dose range, where the balance of the benefits and risks of radiotherapy are most uncertain.
Overall, this thesis helps inform individualised decision-making about radiotherapy by highlighting how clinicians can support patient involvement in decisions and providing methods to help individualise risk estimates of radiotherapy late toxicity.

Keywords: decision-making
risk estimation
radiotherapy
late-effects
hodgkin lymphoma
Advisor: Cutter, D
Peters, M
Ntentas, G
Ramroth, J
The critique of Kantian Epistemology in the early religious philosophy of S. L. Frank

This thesis presents the first critical analysis of the early religious philosophy of Semyon Liudwigovich Frank (1877-1950). The analysis aims to demonstrate that Frank’s early philosophy contains a powerful attack on Kantian epistemology and later Kantian thought. Although the methodology here is primarily intellectual-historical, attempt is made throughout to present Frank’s thought as a ‘powerful’ rebuttal, precisely by re-emphasising its philosophical merits. Frank remains drastically undiscovered in Western philosophy of religion and his highly original and carefully developed epistemology deserves a thorough examination.
The analyses of Frank’s work are preceded by intellectual-historical accounts of Frank’s previous alignment with Neo-Kantianism and the essential broader context of the key treatise of his early period, The Object of Knowledge. The analyses themselves reconstruct Frank’s philosophy in seven chapters, which critically address key areas of his thought. The six arguments which stand out as ‘powerful’ are Frank’s epistemological argument for our ‘knowledge’ of all things, the argument from consciousness, the arguments from syllogism and predication, Frank’s original Ontological Argument, and finally the argument from universals. The fourth and final section takes a more evaluative approach and defends two aspects of Frank’s thought in light of contemporary philosophy of religion: Frank’s apophaticism and his realism of universals.
In light of these considerations, it can be concluded that Frank’s early religious thought, as presented in The Object of Knowledge, should be considered, first and foremost, as a powerful attack on the Kantian epistemology which Frank himself had once professed.

Keywords: Semyon Frank
Russian Philosophy
philosophy of religion
Kant
Bayesian methods for battery state of health estimation

Estimating the state of health of battery energy storage systems is key to their operational safety and reliability, both of which affect lifetime cost. However, accurate estimation of state of health remains challenging, as measurement techniques used in laboratory environments are not available in real-world operating environments. In this work, a framework is developed that combines the relative strengths of commonly applied model- and data-driven approaches to state of health estimation. Gaussian process regression, a flexible Bayesian method of learning arbitrary functions from input-output data, is applied to estimate the parameters of low-order battery models as functions of internal states, operating conditions and lifetime. The approach is first motivated by the difficulty of parameter identification for physics-based battery models from real-world data. Then it is shown how electrical equivalent circuit models can be extended to include parameter dependencies on operating conditions and lifetime in a data-driven manner. The framework is then applied to two different usage scenarios. First, internal resistance is estimated for a fleet of solar-connected lead-acid batteries located in sub-Saharan Africa, where the resulting health metric is shown to provide an early indication of end-of-life failure. Second, a first-order RC circuit, coupled with a one-state thermal model, is parameterised in a joint process that also simultaneously estimates battery states, using data from a Li-ion cell under laboratory conditions. The only prerequisite was the cell-level open-circuit voltage versus charge curve and, in the case of the Li-ion cell model, a single thermal parameter. Given this, the method is agnostic to chemistry and battery construction. Enabling robust and fast state of health estimation for large fleets of batteries has the potential to `close the loop' in terms of battery energy storage system design. Instead of performing laboratory-based ageing experiments, field data can be used directly to determine factors that affect battery life. By incorporating this information into fault diagnosis and health-aware battery management systems, safety and reliability will be improved. Furthermore, with deeper understanding of degradation in the real world, better design of energy storage systems will ultimately lead to better cost efficiency through reduced over-engineering.

Keywords: lead-acid
Gaussian Process regression
battery state of health
parameterisation
li-ion
bayesian methods