VictorJuiz/thesis huggingface dataset:
Novel approaches towards characterising the HIV reservoir: A combined microfluidic and target enrichment approach
Keywords: next-gen sequencing
single-cell
latent reservoir
HIV
droplet microfluidics

The latent reservoir in human immunodeficiency virus (HIV) infection is a small population of long-lived infected cells that remain quiescent during suppressive antiretroviral therapy (ART). This reservoir is widely considered to be the major barrier to HIV cure, as in the absence of effective therapy the cells can become reactivated and cause recrudescent viraemia. A number of assays have been developed in an attempt to both quantify and improve our understanding of the reservoir. However, despite early promise the key factors that contribute to its establishment and persistence remain elusive.
The work undertaken in this thesis was directed primarily at improving the suite of tools available to clinicians and researchers targeting the latent reservoir in HIV infection. To date, the assays that have been designed to quantify and characterise the reservoir have limitations leading to either imprecise measurements or potentially biased analysis of viral sequences. By developing a modified target enrichment protocol, it was shown that diverse full-length proviral sequences can be captured whilst avoiding the bias commonly introduced by PCR-based sequencing methods. In addition, this pipeline allows for the identification of integration sites from the same sample.
The major hurdle facing reservoir assays is the inability to distinguish a latently infected cell from an uninfected cell by cell surface markers. To bypass this requirement, this thesis presents a microfluidics pipeline aimed at using the resident provirus as a means of identifying a latently infected cell. By encapsulating single cells in water-in-oil droplets, it is possible to lyse the cells and perform a PCR reaction targeting the HIV genome. In the presence of HIV, droplets fluoresce and are labelled for dielectrophoretic sorting. Post sorting, nucleic acids can be reclaimed from the droplets for downstream analysis on a purified subset of latently infected cells.
The two assays proposed within this thesis have the potential to profoundly change our understanding of HIV latency. In addition to this, as clinicians enter a new era of treatment interruption studies, changes in reservoir size and composition are becoming a desirable metric.
Overall, the foundation laid down in this thesis provides a solid base from which to begin applying both assays to clinical cohorts.
Thomas Kling: a poet in the late Bonn Republic
Keywords: history of emotion
Thomas Kling (1957-2005)
colonialism
World War I
German identity
German Poetry after 1945
Holocaust
environmentalism
1980s
avantgarde poetry
World War II
gender
exoticism
masculinity
primitivism
German poetry
1970s
collective memory

This dissertation looks at Thomas Kling’s poetry in the context of the late Bonn Republic. While several studies have already investigated how Kling created history in his poetry, they rarely discussed how he himself was exposed to it. Thus, one of the main objectives of the following dissertation is to scrutinise Kling’s own historicisations and to expose the underlying assumptions of his version of the past and their rootedness in the current cultural climate. While many studies have echoed the opposition that Kling himself created between his poetry and that of the 1970s, this dissertation focusses on continuities instead. For this purpose, it looks at the history of the late Bonn Republic and West German poetry after 1945 in terms of changing emotional styles. The dissertation shows how Kling’s early poetry in the late 1970s was rooted in the emotional practices of the alternative Left (part I) and how their political and ecological concerns continued to resonate with his poetry in the following decade (part II). The question is how Kling went beyond the narrow concept of authenticity imposed by the alternative scene’s emotional style and which role models were available for his new self-stylisation (part III). While Kling’s poetry in the 1980s revealed authenticity and history as fundamentally unstable concepts that resulted from a set of culturally and historically determined practices (part IV), his poetry in the 1990s returned to more conservative and hierarchical models of history and authenticity characterised by modernist nostalgia (part V). Kling’s investment in an idealised version of the avant-garde and European modernity thus led to a limited version of the past that erased memories of German colonialism and its continuities with the First World War and the Holocaust.
Icelandic insular romance: replication, reflection, and networks of narrative and meaning
Keywords: Icelandic literature
riddarasögur
medieval romance
narrative studies

Critical study of Icelandic insular romances has been limited due to assumptions of poor literary quality and a lack of editions. This thesis constructs a corpus of Icelandic insular riddarasögur from thirty-four texts and explores the ways in which meaning is interwoven into their seemingly simple narratives through widespread repetitions and connections. The study introduces the concepts of “replication” (overt linking of two distinct elements) and “reflection” (the implications of such a comparison). Examples include lexical repetitions, recognisable narrative structures such as tripartite episodes, and broader semiotic features such as names and intertextual references. The aim of this thesis is threefold: to accumulate evidence in support of these conceptual networks; to explain and explore the effects these techniques have across the selected texts; and to interact with existing discussions about medieval Icelandic literature.
The first chapter focuses on a subgenre of romances, maiden-king narratives, to establish the basic principles of replication and reflection, while also considering the influence of exemplary literature. The second chapter uses the models of Continental romance to assess the presentation of knightly characters and demonstrates how replication and reflection can convey the value judgements of a particular composer or redactor. The third chapter contrasts this knightly world with a pool of broadly “Germanic” or “legendary” inherited material, showing how the composers engage in textual debates regarding the significance of Icelandic and Scandinavian heritage. The final chapter considers religious influences upon the romances, and how the narrative structures explored in the previous chapters can be augmented or subverted for spiritual purposes.
This thesis provides groundwork for further work on the genre. The study provides readings of specific texts, carefully situated within detailed analysis of their language and structures, and also introduces methodology and terminology for broader use.
Learning to reconstruct and segment 3D objects
Keywords: 3D Segmentation
3D Reconstruction
3D Point Clouds
3D Scene Understanding

To endow machines with the ability to perceive the real-world in a three dimensional representation as we do as humans is a fundamental and long-standing topic in Artificial Intelligence. Given different types of visual inputs such as images or point clouds acquired by 2D/3D sensors, one important goal is to understand the geometric structure and semantics of the 3D environment. Traditional approaches usually leverage hand-crafted features to estimate the shape and semantics of objects or scenes. However, they are difficult to generalize to novel objects and scenarios, and struggle to overcome critical issues caused by visual occlusions. By contrast, we aim to understand scenes and the objects within them by learning general and robust representations using deep neural networks, trained on large-scale real-world 3D data. To achieve these aims, this thesis makes three core contributions from object-level 3D shape estimation from single or multiple views to scene-level semantic understanding.
In Chapter 3, we start by estimating the full 3D shape of an object from a single image. To recover a dense 3D shape with geometric details, a powerful encoder-decoder architecture together with adversarial learning is proposed to learn feasible geometric priors from large-scale 3D object repositories. In Chapter 4, we build a more general framework to estimate accurate 3D shapes of objects from an arbitrary number of images. By introducing a novel attention-based aggregation module together with a two-stage training algorithm, our framework is able to integrate a variable number of input views, predicting robust and consistent 3D shapes for objects. In Chapter 5, we extend our study to 3D scenes which are generally a complex collection of individual objects. Real-world 3D scenes such as point clouds are usually cluttered, unstructured, occluded, and incomplete. By drawing on previous work in point-based networks, we introduce a brand-new end-to-end pipeline to recognize, detect, and segment all objects simultaneously in a 3D point cloud.
Overall, this thesis develops a series of novel data-driven algorithms to allow machines to perceive our real-world 3D environment, arguably pushing the boundaries of Artificial Intelligence and machine understanding.
Uncovering the role of RNA-binding proteins in plant immunity
Keywords: Nicotiana benthamiana
RBPome
Solanum lycopersicum
plants
RBP
Physcomitrella
Oryza sativa
Arabidopsis
immune system
RNA-binding proteome
ptRIC
PAMP-triggered immunity
Plant pathology
RNA-interactome capture
flg22
RIC
Marchantia
Nicotiana tabacum
RNA-binding proteins
Phaseolus vulgaris
Zea mays
Solanum tuberosum
Pseudomonas syringae
immunity

RNA-binding proteins (RBPs) are essential regulators of RNA fate, from synthesis to decay. Hence, changes in the RBPome orchestrate the reprograming of RNA metabolism and gene expression that occur during plant responses to a myriad of cues, including pathogen attack. Although RBPs are known to play critical roles in plants, we lack comprehensive information on the identity and function of RBPs in different species. Moreover, it remains unknown how RBPs globally respond to different environmental, physiological and pathological cues.
Here, we have developed ‘plant RNA-interactome capture’ (ptRIC), a variant of RNA-interactome capture (RIC) optimised for plant tissues that allows efficient system-wide identification of RBPs in leaves. We used ptRIC to identify the most extensive Arabidopsis RBPome to date, which includes more than 1100 RBPs, and showed that it displays all the hallmarks expected from a high-quality RBPome. We have used ptRIC to uncover, for the first time, the RBPome of six additional plant species that span across the plant kingdom. This revealed hundreds of unconventional RBPs with no known RNA-binding domains or previously unlinked to RNA biology, including photosynthetic components and metabolic enzymes. By comparing the RBPomes discovered in these different species we have determined the ‘core plant RBPome’, which is composed by RBPs conserved from bryophytes to angiosperms. Using ptRIC we discovered that the Arabidopsis RBPome is extensively reconfigured during plant immune responses. Almost 300 RBPs displayed altered association with RNA in response to the bacterial elicitor flg22. Moreover, these alterations that cannot be explained due to changes in protein abundance, indicating that they are due to changes in RNA-binding activity. Through immunity-based mutant screens, we have discovered that several of these flg22- responsive RBPs play a role in immunity against bacterial pathogens.
Taken together, the results from this thesis provide a significant advance in the knowledge of RBPs in plants and their regulation during immunity. Hence, my results provide a framework for future studies on the role of RBPs in regulating important processes in plants.
Environmental drivers of earthen heritage deterioration in dryland regions
Keywords: drylands
cellular automata model
rain
deterioration
wind
earthen heritage

Earthen sites form a key part of our heritage: providing us with evidence for past civilisations, acting as a focal point for community identity and forming aesthetically pleasing buildings and structures. These sites are found on every continent but are concentrated in dryland regions, such as across northwest China and central Asia. Due to the low durability of earthen materials, many earthen heritage sites exposed to harsh dryland environments are experiencing extensive deterioration. If we are to pass on these sites to future generations, we need to understand how earthen heritage sites are impacted by environmental drivers of deterioration and how the risk of deterioration could be minimised. To address this challenge, this thesis determines the likely impacts of the main environmental drivers of earthen heritage deterioration under current and future conditions in dryland regions.
The research presented in this thesis examines the impact of wind and rain as drivers of deterioration at Suoyang Ancient City. Suoyang is an archaeological city built out of rammed earth in the Han (206 BC–220 AD) and Tang (618 – 907 AD) dynasties and is located in Gansu Province, northwest China, on the ancient Silk Road. It exhibits a range of deterioration features from the detachment of surface material to wall slumps and collapses. In 2015, an experimental area was established at the site, which includes several test walls.
This thesis uses a combined fieldwork-modelling approach. A controlled field experiment was used to investigate the deteriorative impact of key individual environmental processes on earthen structures. Geomorphological signatures were used to assess the relative importance of wind and rain as drivers of deterioration. These field results were used to develop and parameterise the Vegetation and Sediment TrAnsport model for Heritage Deterioration (ViSTA-HD), a cellular automaton model that spatially resolves the risk of environmental driven deterioration across earthen heritage wall faces. ViSTAHD was used to test the impact of future climatic and conservation scenarios on the risk of earthen heritage deterioration.
Findings showed that even though individual wind events are of low magnitude, their high frequency occurrence results in a significant cumulative impact of wind-driven deterioration under both current and potential future conditions. Increasing natural vegetation cover was found to minimise the risk of deterioration under a range of climatic scenarios.
Given the similarities in material properties, history and location of Suoyang to other earthen heritage sites in Northwest China and central Asia, findings in this thesis can be applied to many other earthen sites in these regions.
Multilevel Monte Carlo methods for uncertainty quantification in brain simulations
Keywords: brain fluids
quasi Monte Carlo
multilevel Monte Carlo
partial differential equations with random coefficients
paravascular spaces
non-nested meshes
brain simulation
glymphatic system
Gaussian fields
multilevel quasi Monte Carlo
supermesh
finite elements
white noise

This thesis consists of two parts. In the first, we develop two new strategies for spatial white noise and Gaussian-Mat\'ern field sampling that work within a non-nested multilevel (quasi) Monte Carlo (ML(Q)MC) hierarchy. In the second, we apply the techniques developed to quantify the level of uncertainty in a new stochastic model for tracer transport in the brain.
The new sampling techniques are based on the stochastic partial differential equation (SPDE) approach, which recasts the sampling problem as the solution of an elliptic equation driven by spatial white noise. We present a new proof of an a priori error estimate for the finite element (FEM) solution of the white noise SPDE. The proof does not require the approximation of white noise in practice, and includes higher order elliptic operators and p-refinement.
Within the SPDE approach, the efficient sampling of white noise realisations can be computationally expensive. In this thesis, we present two new sampling techniques that can be used to efficiently compute white noise samples in a FEM-MLMC and FEM-MLQMC setting. The key idea is to exploit the finite element matrix assembly procedure and factorise each local mass matrix independently, hence avoiding the factorisation of a large matrix. In a multilevel framework, the white noise samples must be coupled between subsequent levels. We show how our technique can be used to enforce this coupling even in the case of non-nested mesh hierarchies.
In the MLQMC case, the QMC integrand variables must also be ordered in order of decaying importance to achieve fast convergence with respect to the number of samples. We express white noise as a Haar wavelet series whose hierarchical structure naturally exposes the leading order dimensions. We split this series in two terms which we sample via a hybrid standard Monte Carlo/QMC approach.
We demonstrate the efficacy of our sampling methods with numerical experiments. In a multilevel setting, a good coupling is enforced and the telescoping sum is respected. In the MLQMC case, the asymptotic convergence rate is the same as standard Monte Carlo, but significant computational gains are obtained in practice thanks to a pre-asymptotic QMC-like regime.
In the final part of the thesis, we employ a combination of the methods presented to solve a PDE with random coefficients describing tracer transport within the interstitial fluid of the brain. Numerical simulations support the claim that diffusion alone cannot explain the penetration of tracers within deep brain regions as observed in clinical experiments, even when uncertainties in the diffusivity have been accounted for. A convective velocity field may however increase tracer transport, provided that a directional structure is present in the interstitial fluid circulation.
Deng Xiaoping and Jimmy Carter: technology transfer and the origin of U.S.-China anti-Soviet cooperation during the Cold War, 1977-1981
Keywords: United States
China
U.S.-China relations
technology
diplomatic history
Cold War
nonproliferation

This thesis studies how the diverging visions between Jimmy Carter and Deng Xiaoping had shaped the beginning of United States and China’s relationship after the establishment of U.S.-China diplomatic relations. Based on primary sources from the United States, Europe, the Chinese Mainland, Taiwan, and Russia, this study argues that even though both sides were driven together by their shared anti-Soviet views, there were fundamental differences in how the Carter Administration and Deng Xiaoping approached the Cold War: While the Carter administration itself was escalating between the choices of saving détente with the Soviet Union through arms control or using China to pressure the Brezhnev regime, Deng Xiaoping and his Comrades were far more interested in using the escalating tensions between the United States and the Soviet Union to access American and Western military and due-use technologies in order to modernize the Chinese army and to gain a military advantage over Taiwan. This differences not only complicated a series of major cold war issues, from cross-strait relations, nuclear nonproliferation, U.S.-Soviet detente, and China’s role in the European Cold War, but also sow the seeds for future disputes and confrontations between the United States and China.
Mechanisms underlying statin-induced modulation of ryanodine receptors 
Keywords: ryanodine receptors
pharmacophore
HMG-CoA reductase
statins
ion channels

Statins, a class of HMG-CoA reductase inhibitors, are amongst the most widely prescribed drugs for the treatment of elevated cholesterol. Despite their success, their use is associated with debilitating muscle side effects such a myopathy, myalgia and in the most serious cases, rhabdomyolysis. These effects have limited the ability of many patients to tolerate statin treatment. There is mounting evidence suggesting that statins cause a dysfunction of cellular Ca2+-release in skeletal muscle, which results in muscle damage and myopathy.
In this thesis, I have investigated, using single-channel techniques, how statins interact with the skeletal ryanodine receptor (RyR1), the channel which acts as the pathway for Ca2+-release in skeletal muscle. I have shown that statins as a class, activate RyR1 in a concentration-dependent, reversible manner. These effects were seen at nanomolar levels, which correspond to concentrations found in the skeletal muscle during statin treatment. In contrast, statin effects on the cardiac isoform (RyR2) were more complex, causing inhibition at low concentrations, and activation at higher concentrations, a finding that may be clinically important given the reports that statins reduce instances of arrhythmia.
To investigate if the ability of statins to bind to RyR1 can be reduced without affecting their binding HMG-CoA reductase, the statin minimal pharmacophore was synthesised. It was found not to activate RyR1, indicating that the activation could be separated from the effect on their intended target. Subsequently, single-channel experiments indicated that the RyR1 ATP-site is a plausible location for statin binding, and a molecular modelling study ultilising Autodock software revealed the key structural features required for binding to this site. This facilitated the identification of statin analogues with no effect on RyR1, but potent HMG-CoA reductase inhibition.
In summary, my experiments have revealed that statins can potently alter the activity of cardiac and skeletal RyR channels by distinct gating mechanisms. I suggest that these interactions of statins with RyR channels may contribute to the statin-induced changes in muscle Ca2+-release that are reported in the literature and hence may be the main underlying cause of statin-induced myopathy. In view of this hypothesis, I have screened a number of atorvastatin analogues and identified new statin compounds devoid of the ability to activate RyR1. This work will provide a firm foundation for future work investigating the usefulness of these compounds as lipid lowering agents with reduced side effects.