VictorJuiz/thesis huggingface dataset:
Role of diabetes mellitus in atrial fibrillation and potential new treatments
Keywords: atrial fibrillation
diabetes mellitus
tetrahydrobiopterin

Chapter 1 explains the relative importance of diabetes mellitus (DM) and cardiovascular complications in a global perspective. It then describes the current understanding of how diabetic cardiomyopathy develops and what the underlying mechanisms are. Afterwards, atrial fibrillation (AF), another DM-related complication, is presented followed by the description of the main related pathological mechanisms. Finally, the chapter discusses the therapeutic potential of tetrahydrobiopterin (BH4) as a cofactor of nitric oxide synthase (NOS). Chapter 2 describes in full detail all methods used in the experimental work of this research thesis. Chapter 3 shows that the myocardial overexpression of the rate-limiting enzyme for the synthesis of BH4, GTP cyclohydrolase 1 (GCH1), in mice (mGCH1-Tg) prevents the development of left ventricular (LV) diastolic dysfunction in the presence of streptozotocin (STZ)-induced diabetes. Interestingly, the mechanism underpinning this beneficial effect is not suppression of myocardial superoxide production, prevention of BH4 oxidation and restoration of coupled NOS activity, or reduction of interstitial myocardial fibrosis. Instead, the overexpression of GCH1 with an associated increase in the myocardial BH4 level and myocardial NOS activity prevents myocardial energetic impairment in diabetic hearts by increasing glucose uptake via the insulin-independent glucose transporter 1 (GLUT-1). Chapter 4 explores the atrial electrophysiological characteristics of STZ diabetic mice. Diabetic mice have increased risk for in vivo pacing-induced AF, enlarged relative atrial size and impaired in vivo atrial conduction, as indicated by prolonged ECG PQ interval. Furthermore, experiments in isolated whole atria demonstrate a significant focal increase in fibrosis in the medial part of the right atrium, which results in a significant decrease in the conduction velocity in the same area followed by an increase in the conduction wave-front heterogeneity in the left atrium. Chapter 5 investigates the electrophysiological phenotype of the mGCH1-Tg mice. The transgenic mice have lower heart rates, they spontaneously develop AV nodal escape rhythm, and have prolonged ECG QT interval. The underlying mechanisms for those changes are a global decrease in the atrial conduction velocity, decrease in the conduction through the AV node, as well an increase in the action potential duration (APD). Furthermore, oral BH4 treatment was also tested in diabetic mice, but it did not decrease the risk of AF or improved LV diastolic dysfunction significantly. Chapter 6 summarises the key results and presents the relative impact of each finding. It also discusses the main limitations of the study as well as future research directions.
Ca2+i and the pancreatic α cell – intrinsic regulation and dysfunction in type 2 diabetes
Keywords: Diabetes
Intracellular Calcium
High fat diet
Ion Channels
Type 2 diabetes
Glucagon
Insulin
Somatostatin
Physiology
Paracrine
Hormone secretion

In type 2 diabetes (T2D), elevated plasma glucagon concentration (hyperglucagonaemia) exacerbates hyperglycaemia due to inappropriate insulin secretion. Despite this, very little is known about why glucagon secreting α cells become dysfunctional.
In α cells, intracellular Ca2+ ([Ca2+]i) oscillations drive glucagon secretion but much of their regulation remains obscure. Here we investigate how [Ca2+]i oscillations are regulated, and whether α cell [Ca2+]i dynamics change when mice are fed a high fat diet (to induce a T2D-like state).
Mice expressing the genetically encoded calcium sensor GCaMP3 specifically in α cells were fed a control (10% calories from fat; CTL) or high fat (60% calories from fat; HFD) diet. After 12 weeks, glucose tolerance was impaired in HFD fed mice and plasma glucagon levels were elevated. Plasma glucagon was elevated in HFD mice in vivo during insulin-induced hypoglycaemia and in the perfused pancreas in situ. Glucagon secretion from HFD islets was elevated ex vivo suggesting that intra-islet (intrinsic) effects are involved. While the [Ca2+]i oscillation frequency in α cells was reduced by high (6-15 mM) glucose in both CTL and HFD islets, the frequency was higher in HFD fed mice. Following HFD, α cell [Ca2+]i oscillations and glucagon secretion were also less sensitive to inhibition by somatostatin (SST), an effect that correlated with reduced SST secretion from δ cells in mice fed the HFD.
Collectively, these data indicate that altered α cell activity underlies hyperglucagonaemia in HFD. These data provide evidence that α cell dysfunction and altered intra-islet signalling manifests early in T2D. Correcting the glucagon secretion defects may provide therapeutic advantages, highlighting the potential of the α cell as a potential pharmacological target.
Mathematical models of pathological oscillatory activity and effects of deep brain stimulation in movement disorders
Keywords: isostable amplitude
phase response curve
Wilson-Cowan model
deep brain stimulation
beta burst dynamics
amplitude response curve
pathological oscillations
phase-locked stimulation
essential tremor
beta oscillations
local field potential dynamics
Parkinson's disease

Essential tremor and Parkinson’s disease are the most common movement disorders affecting patients globally. When pharmacological treatment options have been exhausted, continuous, high-frequency deep brain stimulation (DBS) is an effective therapy option. Despite its success, DBS is limited by side effects such as speech and motor impairment, as well as impulsivity. Closed-loop DBS could address these limitations by stimulating in a way that is more parsimonious and by targeting the pathology more selectively to spare physiological processing. In closed-loop DBS, pathological activity is recorded, and stimulation is delivered based on the current state and knowledge of its association with symptoms. Experimental closed-loop strategies include phase-locked DBS in essential tremor and adaptive DBS in Parkinson’s disease. In phase-locked DBS, a precise understanding of the phase-dependence of the response to stimulation is difficult to attain experimentally because of patient fatigue. In Parkinson’s disease, refining adaptive DBS likely requires a better understanding of the dynamics of bursts in the recorded beta band activity (13-35 Hz), which have been implicated in motor symptoms. To inform closed-loop DBS strategies, we use patient data as a starting point to formulate and constrain mathematical models of pathological oscillatory activity and of the effects of DBS. In Chapter 2, we model the effects of phase-locked stimulation in essential tremor patient data. Models fitted to patient data can be used to optimise DBS in silico, and provide insights into the pathophysiology of the disease. In Chapter 3, we relate changes in beta oscillation temporal patterning between medication states in Parkinson’s disease to changes in dynamical properties of the system generating beta bursts. In particular, we show that the system generating beta oscillations is more non-linear in the pathological state, which has implications for closed-loop DBS. In Chapter 4, we compare two definitions of amplitude to measure the effects of phase-locked DBS, and to optimise stimulation in models. We demonstrate that a dynamical measure of amplitude, isostable amplitude, can in some cases be more beneficial to optimise stimulation than envelope amplitude. Together, this thesis sheds light on key aspects of Parkinson’s disease and essential tremor, and contributes to advancing closed-loop DBS.
Seeing the forest through the trees: Structure representation under noisy processing
Keywords: EEG
computational modelling
noisy processing
number representation
Decision-making
selective integration
magnitude representation
representational similarity
normalization

For humans to optimally handle the constant stream of input they receive from their surroundings, they need to be able to separate signal from noise. The understanding that information is structured can help humans to organize information better and improve the detection of signal in a noisy input. This thesis deals with two main themes: the neural representation of structure and how structure representation can adapt in the light of noisy processing. First, I investigate how the human brain represents the structure of magnitude and how through structural alignment it can learn efficiently about new stimuli that have the same underlying structure. Next I present evidence from a new task that magnitude is represented neurally along a single axis but separated in parallel lines based on the current context. In the following chapter I investigate through model simulations how normalization can confer robustness under accumulation noise and test these predictions in humans. Finally, I present neural evidence for a computational model of robust processing when two pieces of information have to be assessed simultaneously. Taken together I hope to demonstrate that neural signals carry a low-dimensional representation of structure and that the brain can adaptively change those representations to improve performance.
Internal migration and human capital accumulation among youth in developing countries
Keywords: Human capital
Migration
Youth

This thesis consists of a short introduction, an overview of the context and data used, three self-contained analytical chapters on migration and human capital in developing countries, and overall conclusions. The first paper documents detailed patterns of internal mobility and estimates the predictors of migration by gender and reasons for moving using a Linear Probability Model and a Multinomial Logit Model, respectively. My main finding is that young migrants are a very heterogeneous segment of the population and that “favourable selection” only holds for those who move for studies. The second paper explores the impact of internal migration on cognitive and psychosocial skills by estimating a 2-Stage Least Squares (2SLS) model, using weather shocks as instruments for migration. My key finding is that migration affects both cognitive and psychosocial skills, but these effects differ across migrants depending on their reason for moving: those that move for studies have higher cognitive and psychosocial skills than non migrants do, whereas those that moved for family formation have lower cognitive skills than non-migrants do. Lastly, the third paper focuses on whether age at migration has an impact on cognitive and psychosocial skills. I use sibling pairs to estimate a household fixed effects-2SLS model, using weather shocks as instruments for migration. My main finding is that younger migrants perform better than older migrants, although this effect can be offset or even dominated by input responses as a result of migration. In conclusion, this thesis provides evidence of the heterogeneous character of young migrants, as well as supports the claims that migration matters for skills formation and that the earlier it takes place, the better.
Exploring electronic delocalization in porphyrin oligomers
Keywords: porphyrins
aromaticity
2D-IR
Möbius topology
ring current
ultrafast spectroscopy

The general theme of this thesis is a study of electronic communication within porphyrin oligomers. Chapter 1 reviews briefly the porphyrins: their chemical structure, advantages of their use in supramolecular chemistry and some of their basic photo-physical properties. Chapter 2 discusses a study of the origin of an unusual intensity of certain IR bands in two porphyrin oligomer cations. The study uses a polarised time-resolved IR (TR-IR) to understand relative orientation of the intensified vibrations, corroborated with DFT calculations. Coupling between individual IR modes and with the electronic band is documented by 2D-IR spectroscopy and further understanding of the system dynamics upon excitation is understood thanks to the detail kinetic analysis. Chapter 3 focuses on aromaticity. The basis of aromaticity as a concept is reviewed and examples of theoretical and experimental investigations of aromaticity of some π-conjugated species is presented. The experimental part discusses the preparation of large globally (anti)aromatic species via oxidation of the otherwise globally non-aromatic nanorings and its evaluation with NMR. All these studies are supported with DFT calculations corroborating the correct interpretation. Chapter 4 discuses the design and synthesis of a large Möbius-strip-shaped porphyrin nanoring. Firstly, a brief overview of the concept of Möbius aromaticity is reviewed, followed by examples of various designs and reported syntheses of Möbius molecules. This is followed by the design and synthesis and study of two novel nanorings, one which is suspected of adopting Möbius confirmation.
Investigating surgical site infection after hip fracture surgery
Keywords: Surgical site infection
Randomised controlled trials
Hip fracture

Infection after surgery or surgical site infection (SSI) is a devastating complication for patients and healthcare providers. Hip fracture patients are particularly vulnerable to SSI, and its consequences. Despite its importance, there is uncertainty around the true rate of SSI. This parameter is crucially important to properly power studies that seek to assess interventions that may reduce SSI. One such intervention is the wound dressing. Some dressings including incisional Negative Pressure Wound Therapy (iNPWT) are used in high-risk surgical wounds, and may reduce SSI. There is a need to assess in this context.
Three contrasting methods were used to assess hip fracture patients. Firstly a systematic review was undertaken of patients undergoing surgery in the United Kingdom. Data were extracted and meta-analysed. Secondly, administrative data were explored to look at the incidence of SSI after hip fracture. Data were additionally interrogated for evidence of treatment for SSI and possible risk factors for SSI. Finally a randomised controlled feasibility trial was undertaken comparing standard care to incisional negative pressure wound therapy in 464 patients. These patients were allocated on a 1:1 basis across 5 centres. Each patient was assessed at 30 days and 90 days against the Centre for Disease Control definition of SSI.
The systematic review identified 20 studies of 88615 hip fracture patients. A pooled estimate of 2.08% (95% CI 1.54-2.62) was seen in studies reporting SSI in ‘all hip fractures’. There was variation between types of surgery. The administrative data gave an SSI estimate of between 1.4% (95% CI 1.2%-1.6%) and 1.7% (95% CI 1.4%-2.0%). The feasibility study recruited all patients in 6 months. Eighteen patients were diagnosed with SSI according to the CDC criteria at 30 days-a rate of 4.2% (95% CI 2.5%-6.5%). At 120 days an additional new case of SSI was identified-a rate of 4.4% (95% CI 2.6%-6.8%).
The rate of SSI may be significantly higher than suggested by evidence synthesis and national screening programmes. The data from published and administrative data show higher estimates of SSI, despite possible underestimates in each data source. Prospective studies using recognised criteria show even higher rates of SSI.
The rate of surgical site infection appears to influenced by the study design and data collection procedure.
Translating ribosome affinity purification from C9orf72-associated amyotrophic lateral sclerosis patient-derived iPSC motor neurons
Keywords: TRAP
C9orf72
Motor neuron
iPSC
ALS
Amyotrophic lateral sclerosis
Translating ribosome affinity purification
RNA Sequencing

The C9orf72 hexanucleotide repeat expansion [GGGGCC]n is the most common cause of familial amyotrophic lateral sclerosis. The endogenous role of the C9orf72 protein has not been fully characterised, nor how the presence of the repeat expansion affects downstream mechanisms. Numerous cellular and molecular pathologies have been characterised in patient-derived induced pluripotent stem cell (iPSC) motor neuron cultures. This includes the accumulation of nuclear RNA foci and cytoplasmic dipeptide repeat proteins, altered calcium homeostasis, accumulation of apoptotic factors, nucleocytoplasmic defects and reduced excitability. Targeted antisense oligonucleotide knockdown of mutant C9orf72 mRNA transcripts mitigates some of these pathological phenotypes, though whether gene expression is restored to normal is unknown. Transcriptomic analysis of iPSC-motor neurons is challenging due to multiple sources of experimental variance, such as the presence of up to 30% of cells in culture being of unknown identity. The aim of this project is to establish a translating ribosome affinity purification (TRAP) method to isolate an enriched population of RNA from human iPSC-motor neurons. This will help achieve a more accurate analysis of the translatome profile of this model. Differential gene expression analysis between control and C9orf72 ALS motor neurons will be performed to identify patient motor neuron-specific changes in gene expression.
Asymptotics of operator semigroups and applications
Keywords: Quantified asymptotics
Semigroups of operators
Direct integrals
Coupled systems

This thesis is concerned with the quantified asymptotic theory of operator semigroups and its applications. There are two sides of this story that are studied in the two main parts of the thesis respectively. The first side of the story is the asymptotic theory of strongly continuous operator semigroups arising from the study of damped wave equations and the countable spectrum theorem for strong stability. In the first half of the thesis, we apply known theory to two coupled wave-heat systems in order to derive energy decay estimates, before developing new direct integral theory so that one may explore asymptotic ideas there. The second side of the story is the asymptotic theory of discrete operator semigroups arising from the much celebrated Katznelson--Tzafriri and mean ergodic theorems. In the second half of the thesis, we establish new abstract results in this area, proving sharp estimates for the rate of decay between consecutive powers of operators on Hilbert spaces. Additionally, we prove upper and lower bounds for this same decay in the case of multiplication-like operators that improve on previously known theory.
Prenatal assessment of placenta accreta spectrum disorders from ultrasound images using deep learning
Keywords: placenta accreta spectrum disorders
prenatal assessment
deep learning

This thesis addresses the task of developing deep-learning-based tools for assessing placenta accreta spectrum disorders (PASD), a series of placental abnormalities that drastically affect maternal health, on placental ultrasound scans obtained from prenatal examinations. The contribution of this thesis is a novel design of an image analysis pipeline consisting of computational modules that automatically search for clinically relevant sonographic patterns in placental ultrasound images and perform PASD assessment. This involves identifying informative image planes that clearly depict the anatomy around the placenta within a three-dimensional ultrasound volume; localizing the randomly distributed sonolucent spaces within the placenta (also known as placenta lacunae) caused by abnormal placental vasculature; detecting the utero-placenta interface where abnormal placenta adherence or invasion may occur; integrating ultrasound signs in a collaborative manner to classify PASD. This is the first work to attempt image-based automated prenatal assessment of PASD. The computational modules are formulated as deep convolutional neural networks, whose parameters are gradually learnt by optimizing objective functions that minimize differences between network outputs and experts' reference annotations. Multi-scale representation learning is considered critical in localizing sonographic patterns with variable sizes and shapes such as patterns associated with placenta lacunae and utero-placental interface. The resulting deep learning models aggregate intermediate features from shallow to deep stages whilst exploiting global contextual cues to model placenta geometry. Apart from architectural refinement, methods are presented to further regularize network behaviours via auxiliary learning, based on additional supervision signals derived from experts' annotations. A complete, fully automated image-based PASD assessment pipeline is presented by effectively combining these computational modules to carry out plane-wise and volume-wise PASD assessment. A cross-institutional placental ultrasound image analysis database is presented to validate the algorithms proposed in this thesis. The computational modules are compared against a number of competitive benchmark models. Assessment results are further compared to estimates made by a panel of experts who specialize in PASD diagnosis. The results suggest that the proposed PASD assessment pipeline has the potential to be integrated in clinical scenarios to assist in prenatal diagnosis.
Poetic metaphysics in Karoline von Günderrode
Keywords: Spinozism
German Romanticism

This thesis looks at poetic metaphysics in the work of the Romantic poet and philosopher Karoline von Günderrode (1780-1806). There has hitherto been no attempt to write Günderrode into a Problemgeschichte that would account for her significance as both a poet and a philosopher in the late eighteenth century. This thesis recontextualises Günderrode in the aftermath of the Pantheismusstreit of the 1780s. Günderrode’s work is underpinned by series of metaphysical commitments that correspond to Spinozist panentheism, and specifically to the variant that emerged with Herder’s vitalist reading of Spinoza. When viewed in this context, Günderrode emerges as the most consistent adherent to panentheism not just in Romanticism, but also in the period more generally.
Panentheism is an attractive construct since it lies between deism and deterministic materialism (the latter carrying associations with fatalism and atheism) and presents a heterodox way of retaining certain cherished concepts, such as teleology, perfectibility, and the development of the self. This thesis interprets Günderrode’s recourse to panentheism as significant because her political texts cannot be understood without presupposing a metaphysical grounding of reality, since they make use of an understanding of individual agency that rests on a form of moral universalism. Broadly speaking, Günderrode’s more metaphysical texts are engaged in a project of naturalisation: of re-writing the individual into nature, as a riposte to extreme forms of scientific empiricism and instrumentalising reason. The logical endpoint of this project is that panentheism absorbs materialism entirely: it becomes a form of spiritualised materialism, inflected with Platonic and Neoplatonist ideas. Günderrode’s distinctiveness also lies in how far she pushes this idea of naturalising the individual, to the point where nature and the human are no longer separate orders of being. Rather, all is subsumed into the subjectivity of nature.