VictorJuiz/thesis huggingface dataset:
An investigation into Shaker-like potassium channel Kv1.6 and its role in the somatosensory nervous system

Pain is a fascinatingly malleable sensory percept, evoking a unique experience for each individual. Most people who have experienced pain have an inherent understanding of its unpleasantness, and under most conditions this negative affect drives short- and long-term behavioural changes, which serve to protect organisms from potential further harm relating to the offending stimulus. Most commonly, pain is short-lasting, associated with observable physical damage to the body, and reversible. Chronic pain is long-lasting, persisting even after recovery of tissue damage, which can instil societal stigma towards sufferers. ‘Neuropathic’ pain, associated with prior lesion of the nervous system, is typified by spontaneous pain sensation and pain evoked by non-noxious stimuli – a debilitating symptomatic experience and major global health burden.
Presently, we lack satisfactory treatments for neuropathic pain due to insufficient understanding of maladaptive structural and pathophysiological changes occurring in the nervous system. Neuronal hyperexcitability is a key feature of neuropathic pain. Potassium channels have long been known as regulators of neuronal activity – they are instrumental in ensuring appropriate generation and propagation of action potentials and regulate neural communication by influencing presynaptic neurotransmitter release. There is now a large body of evidence that K+ channel dysfunction is mechanistically involved in the initiation and maintenance of neuropathic pain, offering novel therapeutic targets.
Ostensibly, the relative ease of genetic manipulation in mice enables us to study individual genes in isolation and assess their functions in health or disease. This thesis comprises an in-depth genetic, anatomical, physiological, and behavioural investigation of two different Kv1.6 knock-out mice. The results of the present study simultaneously reveal an unconventional role for this potassium channel in thermal nociception and a major flaw in the design of certain transgenic animals – namely, that overexpression of exogenous LacZ gene products is not necessarily benign but may induce unsolicited and confounding neurotoxic effects.

Keywords: neuroscience
Kv1.6
potassium channels
neuropathic pain
nerve injury
LacZ
pain
Advisor: Bennett, D
Development of a self-silencing adenovirus for the efficient manufacture of adeno-associated virus vectors

Adeno-associated virus (AAV) shows great promise for gene therapy, however scalability, yield and quality remain significant issues. The most common ‘helper-free’ method used to produce recombinant AAV (rAAV) for pre-clinical/clinical application is based on plasmid transfection of HEK293 cells to provide all the components required for rAAV replication. While versatile and easy to adopt, the helper-free method is limited by a lack of scalability and vector yield.
Here we describe novel rAAV manufacturing strategies using ‘helper’ adenoviruses that self-inhibits its major late promoter (MLP) to truncate its own replication. Modification of the adenovirus MLP in situ to provide inducible repression has not previously been demonstrated, primarily because the virus DNA polymerase coding sequence is in the opposing DNA strand. We show that strategic insertion of tetracycline repressor binding sites into the MLP and encoding the tetracycline repressor under its transcriptional control allows for normal adenovirus replication in the presence of doxycycline, but only enhanced genome amplification and early gene expression (important for the ‘helper’ functions) in its absence.
Using this negative feedback system, we developed a complete transfection-free ‘self-repressing’ helper-vector approach to produces AAV particles. We demonstrate delivery of adenoviral helper functions, the rAAV transfer genome, and the AAV genes including rep, known to be toxic to adenovirus, to yield up to a 1000-fold increase in infectious rAAV2 compared to the helper-free plasmid system. We further extended this approach to produce rAAV5, -6, -8, -9 vector serotypes, and in all cases, yielding significant increases in intact particles over the standard manufacturing approach with over 8 log reduction in contaminating adenoviruses. To reduce manufacturing complexity and encapsidation of illegitimate DNA within rAAV particles, we also explored a unique strategy to manufacture rAAV vectors by propagating rAAV particles using self-silencing adenoviral vectors expressing the AAV components. This included a trans-pseudotyping or ‘capsid-exchange’ method to generate rAAV-5, -6, -8, and -9 from rAAV2 particles. We propose these as high-yielding contaminant-free production systems suitable for scalable rAAV manufacture.
Lastly, in exploring the use of the self-silencing adenovirus to promote rAAV production from mammalian cells stably encoding the AAV genes, we provide direct evidence that factor(s) expressed from the MLP during adenovirus replication was required to support CARE-dependent amplification, a unique mechanism that results in 100-1000 fold DNA amplification of the integrated AAV genes, and a prerequisite for high-titre rAAV production from the stable AAV packaging cells.

Keywords: viral vectors
adeno-associated virus
TERA
Major late promoter
AAV
Self-silencing adenovirus
TESSA
TetR
Ad5
MLP
adenovirus
gene therapy
tetracycline repressor
Advisor: Seymour, L
Inductive biases and generalisation for deep reinforcement learning

In this thesis we aim to improve generalisation in deep reinforcement learning. Generalisation is a fundamental challenge for any type of learning, determining how acquired knowledge can be transferred to new, previously unseen situations. We focus on reinforcement learning, a framework describing how artificial agents can learn to interact with their environment to achieve goals. In recent years, by using neural networks to represent agents, it has achieved remarkable success and vastly expanded its scope of possible applications. Our goal is to improve the performance of these agents by allowing them to learn faster, to learn better solutions and to react robustly to previously unseen situations. On this quest, we explore a range of different methods and approaches.
We focus on incorporating additional structures, also called inductive biases, into the agent. Focussing on specific, yet widely applicable problem domains, we can develop specialised architectures which greatly improve performance. In Chapter 3 we focus on partially observable environments in which the agent is prevented full access to all task-relevant information at every moment in time. In Chapter 4 we turn our attention to multi-task and transfer learning and devise a novel training method allowing us to train hierarchically structured agents. Our method optimises for re-usability of individual solutions, greatly enhancing performance in transfer settings.
In the second part of this thesis, we turn our attention towards regularisation, another form of inductive bias, as a means to improve generalisation of deep agents. In Chapter 5 we first explore stochastic regularisation in reinforcement learning (rl). While these techniques have proven highly effective in supervised learning, we highlight and overcome difficulties in applying them directly to online rl algorithms, one of the most powerful and widely used types of learning in rl. In Chapter 6 we investigate generalisation in deep rl on a more fundamental level by exploring how transient non-stationarity in the training data can interfere with the stochastic gradient training of neural networks and can bias them towards worse solutions. Many state of the art rl algorithms introduce these types of non-stationarity into the training, even in stationary environments, by using a continuously improving policy for data collection. We propose a novel framework to reduce the non-stationarity experienced by the trained policy, thereby allowing for improved generalisation.

Keywords: Machine Learning
Generalisation
Inductive Bias
Reinforcement Learning
Advisor: Whiteson, S
Miranda Erin Wheeler - Thesis submitted in partial fulfilment of the degree of Doctor of Clinical Psychology (DClinPsych)

Objective: To investigate the relationship between standardised assessments of cognitive functioning and the functional test in the 2005 Mental Capacity Act (MCA) in adults with a neurodegenerative condition or neurological injury.
Method: Cochrane Library, MEDLINE, PubMed, CINAHL, PsycINFO, EMBASE, Scopus, and Web of Science databases were searched. Included studies reported outcomes of any cognitive test in adults with a clinically confirmed neurological diagnosis in relation to one or more of the four pillars of the MCA functional test (‘understanding’, ‘retention’, ‘using and weighing-up information’, ‘communication’). A narrative synthesis was structured in accordance with each pillar of the functional test.
Results: Of the 3,996 titles screened, 34 studies met inclusion criteria, comprising 40 eligible samples. The most consistent findings related to the pillar of ‘understanding’, where tests of information processing speed and attention/working memory were strongly correlated to ‘understanding’ in Alzheimer’s Disease (AD) samples and where tests of attention/working memory and executive functioning were strongly correlated to ‘understanding’ in non-AD samples. No studies explored the relationship between cognitive performance and ‘retention’ or ‘using and weighing-up information’. Eight studies reported associations between performance on cognitive measures and ‘communication’. Five studies explored the relationship between cognitive performance and ‘overall capacity’ in accordance with the functional test and reported inconsistent findings.
Conclusions: The four pillars of the functional test in the MCA are seldom referred to separately. Further research which clearly operationalises the pillars of capacity being assessed is required to elucidate both the utility and limits of cognitive measures in supporting complex functional assessments in line with the MCA.

Keywords: stroke
interpretive phenomenological analysis
clinical psychology
depression
systematic review
stigma
coeliac disease
disclosure
cognitive impairment
awareness
neuropsychology
mental capacity act
anxiety
Advisor: King, N
Milosevich, E
Knight, M
David, A
Kennedy, J
Aiding diagnosis of rare diseases from photographs using machine learning

The objective of this thesis is to further research in the field of computational syndrome diagnosis from ordinary photographs of patient faces. As well as providing insight into the phenotypic scope of specific genetic disorders, the development of such tools may eventually help to shorten the process for patients to receive a clinical diagnosis.
The success of computer vision algorithms in this domain crucially depends on sourcing large labelled data sets of patient syndrome faces. In this thesis, we address this issue by creating a download pipeline to obtain facial images of genetic disorder patients from the published biomedical literature. The development of this pipeline has led to the creation of a novel biomedical figure classifier; and a syndrome annotation tool, which enables rapid diagnostic labelling of retrieved patient images.
Critical to modelling the craniofacial manifestations associated with genetic disorders is the need to separate phenotypic signals caused by the genetic disorder from the typical variation found among inherited facial features. Unfortunately, existing kinship data sets display several biases which undermine the task of facial kinship modelling. To demonstrate this, we build a classifier which can determine whether two facial images are cropped from the same original photo. Despite this classifier having no understanding of kinship, it is able to achieve comparable performance to many previously published methods on several existing kinship data sets.
To counter this, we construct two novel kinship data sets collected from the Geni ancestry website, being careful to avoid several common biases found in other kinship data sets. Finally, we attempt to benchmark the kinship signal in our newly produced data sets using feature aggregation methods. The data sets and techniques discussed in this thesis are currently being used to produce the next generation of diagnostic syndrome face models.

Keywords: Machine Learning
Deep Learning
Kinship Classification
Rare Diseases
Advisor: Zisserman, A
Nellaker, C
Political party survival after collapse: the Argentine radical party in comparative perspective

This dissertation adopts an elite-based approach to build a portable theory of party survival and national revival. The basic argument is that each stem from a process, by which elites arrive at certain pivotal decisions in the aftermath of a massive electoral defeat. To avoid breaking down due to mass defections, a party must continue to provide its ambitious politicians with adequate reasons to stay – namely, in the form of crucial electoral advantages. However, this dissertation also breaks new ground by asking how these very same elites can leverage their continued access to such advantages and channel them toward a revival in national politics. To do this, it attempts to open the “black box” of party organization to uncover the characteristics of a party that help resolve an additional and central problem of survival: party reform under conditions of voter rejection. I argue that for a revival to occur, politicians require more than a safe resource perch to ride out the storm. They need both autonomy from the central leadership to devise new electoral strategies, as well as an organizational framework that protects their reform efforts and keeps members bound to any deliberative decisions that may stem out of the internal reform process.

Keywords: Party Politics
Argentine Politics
Democracy
Radical Civic Union
Political Parties
Comparative Politics
Democratization
Argentina
Latin American Politics
High throughput bioprinting of colorectal cancer tumour spheroids

There is a significant unmet need for the development of complex and scalable 3D colorectal cancer (CRC) models. Presently, there is no known method for predicting patient-response to chemotherapy, and many nonresponding patients undergo this treatment which has no therapeutic value and significant negative impacts on health and wellbeing.
It has been recently demonstrated that patient-specific microtumours, known as tumour spheroids, can be cultured in vitro from patient biopsy’s and are predictive of chemotherapy-response in CRC. However, current approaches are low throughput and cannot be readily scaled to address the large clinical need. Bioprinting, the controlled 3D patterning of cell-laden biocompatible materials known as ‘bioinks’, has untapped potential to reproduce the CRC tumour spheroid model in a robust, high throughput manner.
At this time, no scalable bioprinted CRC tumour spheroid model has been reported in the literature. Consequently, this thesis addresses this space, outlining the development of a high throughput bioprinting assay for CRC tumour spheroid chemotherapy-response. In Chapter 3, a bioink was formulated which ubiquitously supports spontaneous spheroid self-assembly in every tested CRC line. In Chapter 4, the characteristics of these tumour spheroids are explored, and found to exhibit important characteristic features of tumours in vivo, such as zonal hypoxia and necrosis.
Finally, in Chapter 5, work from the previous two chapters is used to develop a high throughput, bioprinted chemotherapy and radiotherapy-response assay, using non-invasive high content microscopy to measure the growth of spheroids challenged by therapy. Here, the throughput and utility of the system is validated through the accurate measurement of many thousands of tumour spheroids simultaneously, paving the way for future use of scalable bioprinted CRC spheroid assays as a clinical tool.

Keywords: Bioprinting
3D Cell Culture
Tumour Spheroid
Advisor: Perriman, A
Bayley, H
A study of diverse identities during the Roman period in the Severn Valley: a cultural network approach 

The traditional Romanisation model of Roman Britain is disputed by a number of researchers who claim that it is an artificial construct. Instead they posit models of identity formation in which a number of heterogeneous collective identities coexisted (e.g. nativism, creolisation and discrepant experiences, among others). Evidence for this is based on heterogeneous archaeological remains found in a number of archaeological sites and from recent research on status, gender and mobility. However, little research has been developed to assess the coexistence of heterogeneous identities in rural areas. This thesis aims to add to the body of evidence by studying rural areas in Gloucestershire and Shropshire. For this purpose, a novel methodological approach to evidence collection was used based on a mixed method strategy employing a quantitative network phase followed by a phenomenological phase. Using this approach, it was found that the identity evolution in Shropshire is consistent with the nativist model of identity formation because it reflects a polarisation between Roman and native identities suggesting native resistance against Roman ways. In contrast, the results for Gloucester are more aligned to a process of creolisation because it reflects the emergence of hybrid/mixed culture in lower order societies that may be attributed to differentials between post-conquest and non-egalitarian societies. This finding indicates that the dynamic of identity formation in Roman Britain was a complex social process that cannot be captured by the simpler Romanisation approach. On the contrary, it supports the discrepant experiences view suggesting that heterogeneous identities reflect different perceptions of history, culture and relations between coloniser and colonised societies.

Keywords: Discrepant Experiences
Cultural Network
Nativism
Endogenous Cultural Material Network Model
Diverse Identities
Roman Britain
Creolisation
Identity Evolution
Mixed Method
Phenomenology
Advisor: MacDonald, A
Smith, A
An argument with God: Bhagavannindā in the Mahābhārata tradition

This thesis tells two stories—one of how the god Kṛṣṇa’s humanity and divinity came to be defined in the aftermath of the Mahābhārata’s composition. Another is how the Mahābhārata itself was taken seriously as a Vaiṣṇava text in its reception history. Through a close reading of Sanskrit commentaries, polemics, and narrative texts, I examine how these texts—and the religious communities that composed them—developed a theology of a fully-divine Kṛṣṇa in late-medieval and early modern South India, and how the Mahābhārata became explicitly Vaiṣṇava through the reinterpretation of the god Kṛṣṇa’s humanity. With the proliferation of Sanskrit commentaries and treatises on the overall meaning of the epic in the medieval and early modern period, clarifying Kṛṣṇa’s role becomes an explicit part of explaining the Sanskrit epic. The theology of a fully-divine human incarnation of Viṣṇu required a justification of the conduct, censures, and diminishment of Kṛṣṇa in the Mahābhārata, and a clarification of his role. This included justifying his conduct, explaining why he is rebuked constantly, and reinterpreting his ‘human’ death and his worship of other gods.
Through a study of late-medieval and early modern polemics, philosophical texts, and commentaries from the South Indian Śaiva and Vaiṣṇava communities (13th-17th c.), I posit that this discourse on Kṛṣṇa was important to the emergence of the Mahābhārata as an explicitly Vaiṣṇava text on the supremacy of Viṣṇu. Both in the Mahābhārata and in its reception in the early Vaiṣṇava Purāṇas and commentaries, readers sought to reconcile the humanity of the god with his divine status. For the Mādhva and Śrīvaiṣṇava communities, answering the ‘Kṛṣṇa question’ was a key component of articulating the Mahābhārata as a text that belonged to the Vaiṣṇava community, largely in contradistinction to the Śaiva polemics of Appaya Dīkṣita in the 16th century. This discourse on Kṛṣṇa gave rise to the emergence of the Mahābhārata as an explicitly Vaiṣṇava text on the supremacy of Viṣṇu in South India during this period. The end result is to posit a fully divine Kṛṣṇa who is less human than the Mahābhārata presents him and coincides with the emergence of the avatāra theology in Purāṇas.

Keywords: Appayya Dīkṣita
Mahābhārata
epic commentary
Dvaita
Madhva
Avatāra
Mahābhāratatātparyanirṇaya
blasphemy
dveṣabhakti
Vādirāja
Advisor: Minkowski, C
Virus-induced cell-cell fusion as a driver of metastasis

Viral infection is thought to be responsible for 15% of all cancers and has previously been linked to cancer progression through the virus induced cell fusion theory of metastasis. This theory proposes that fusion of different cells may endow the result- ing hybrid cells with metastatic properties. I developed a number of measures that I applied to WGS data from 6,337 tumours to identify tumours in which cell fusion may have occurred. Based on these measures I identified 15 primary tumours, and 31 metastatic tumours with evidence of cell fusion, and further characterised their genomes. I also investigated cell fusion in vitro and generated a number of cell lines which underwent either virus induced cell fusion, or became tetraploid after a failure of cytokinesis, to study changes in karytoype and genome stability over time, and to elucidate whether differences could be observed resulting from the mechanism by which the genomes were duplicated. While the scope of this work was limited by experimental constraints, the conclusions were consistent with previous literature suggesting that whole genome duplication by any means results in an initial increase in heterogeneity, followed by adoption of a stable karyotype over time.
Viral infection has also been associated with activation of several members of the Apolipoprotein B mRNA editing enzyme catalytic polypeptide 3 (APOBEC3) family of cytidine deaminases that act on cytosines in single stranded DNA, in spe- cific cellular contexts including the developing immune system and as a response to invading viral pathogens. The action of these enzymes on DNA leaves specific, well defined, mutational signatures characterised by C to T and C to G transitions in particular contexts (single base substitution signatures known as SBS2 and SBS13, attributed to the activity of APOBEC3A and APOBEC3B). SBS2 and SBS13 mu- tations are observed in most cancer types, and have previously been associated with sites of chromosomal rearrangements. In this thesis I show that the presence and number of SBS2 and SBS13 mutations in the genome is associated with increasing genomic instability, and I introduce novel measures of genomic instability in whole genome sequencing (WGS) data. The relationship between viral infection, genomic instability, and APOBEC3 activity was also investigated but results remain inconclusive.

Keywords: APOBEC3
cancer
metastasis
whole genome sequencing
virus
Advisor: Green, C
Wedge, D
Padilla-Parra, S