VictorJuiz/thesis huggingface dataset:
Analysis of patient-reported outcome following hip and knee replacement -- interpretation, strengths, limitations and solutions

Total knee replacement (TKR) and total hip replacement (THR) are surgical procedures frequently performed to alleviate pain and restore function of the affected joint for people with end-stage osteoarthritis (OA). In order to make a fully informed decision, patients and providers need to acquire a thorough understanding of the short- and long-term success or failure rate of the intervention. In previous studies, various methods have been used to analyse patient-reported outcome (PRO) following TKR and THR, generating a wide range of success rates for the same population.
The thesis aimed to address the following three questions:
1. How to define a "successful outcome" following TKR and THR? What are the limitations associated with the current analysis methods?
2. How best to monitor success rate following arthroplasty in the long-term?
3. Is there an alternative way of defining a "successful outcome" that can overcome the limitations in the current methods? If so, what is the potential usage of this novel approach in a clinical context?
To assess the success rate of knee replacement and hip replacement operation, the conceptual framework of "sufficient response" was introduced. A "sufficient response" consists of three components -- an instrument used to measure the outcome, a response criterion and its associated cut-off score. Using this framework, the first part of the thesis explored the short-term outcome following TKR and THR, as well as the stability and lability of long-term outcome following TKR. The limitations associated with the current methods for measuring the prevalence of success were also examined.
In the second part of this report, the Oxford patient-reported success index (OxPReSI), a novel, alternative method of defining sufficient response was introduced. OxPReSi was constructed upon two anchor questions, which are designed to address patients’ self-perceived improvement and satisfaction. Application of OxPReSi divides patients into three categorical outcome groups — high benefit, low benefit and no benefit.
The last part of the thesis investigates how OxPReSi can be used pre-operatively during the decision-making period to help patients and clinicians decide on the optimal timing and type of surgery. The results demonstrate that: I) For TKR patients, a pre-operative OKS of above 17 is desirable; once pre-operative score drops below 17, the proportion of
high benefit’’ decreases significantly. The negative effect of low pre-operative OHS is much more minor for the outcome of THR. II) For patients with medial compartmental osteoarthritis, the outcome of partial knee replacement appeared to be superior compared with total knee replacement .

Advisor: Price, A
Beard, D
Bayesian Gaussian processes for identifying the deteriorating patient

Patients discharged from the ICU will commonly be placed in intermediary care, such as the step-down ward, where the nurse-to-patient ratio is reduced (compared to that of the ICU). Although most of these patients will continue to recover and stabilise, a significant portion will suffer cardiac arrest and/or other clinical emergencies, and readmission into intensive care. Upon readmission, the risk of mortality is significantly higher than that of the general ICU population. Evidence suggests that early detection of deterioration may prevent or alleviate the severity of clinical emergencies. Notable shortcomings of current practices are that they (i) involve manual calculation of risk scores, (ii) depend on heuristic decision criteria, (iii) ignore time-series dynamics of physiological measurements, and (iv) lack patient-specificity.
Gaussian process regression (GPR) models are proposed as a principled, probabilistic method to address the clinical need to continuously monitor patient vital-sign time-series with the flexibility to address the aforementioned weaknesses of current methods. The proposed GPR models focus on the robust forecasting of patient vital-sign time-series and early detection of patient deterioration. The primary contributions of this thesis describe how:
1. Probabilistic models may be used to identify artefactual measurements from continuously-acquired vital-sign monitoring devices.
2. GP covariance functions may be constructed and regularised for robust modelling, suitable for both patient-cohorts and personalised care.
3. GPR-based methods may quantify erratic physiological time-series and provide useful advanced warning of deterioration events.
Each of the above contributions use the time-series correlation of vital-sign measurements for advantageous clinical inference.

Keywords: Precision Medicine
Bayesian Statistics
Artificial Intelligence
Medical Statistics
Personalised Medicine
Gaussian Processes
Bayesian Timeseries
Timeseries
Machine learning
Healthcare
Essays in experimental economics

In the first chapter, I investigate the impact of income inequality on anti-social behaviour through an experiment. Participants are first assigned to two different kinds of groups: equality groups, where everyone is paid the same amount for performing a simple task, and inequality groups, where people receive different amounts for completing the same task. Each participant is then told that one member of their group will have the possibility of taking some of the money earned by another group member. Contrary to the predictions made by the Becker model and the Fehr-Schmidt inequity aversion model, participants in the inequality groups steal significantly less from a fellow group member with the same income as them than people in the equality groups. The second chapter, jointly written with Christopher Roth, examines the influence of economic status on pro-social behaviour using a large experiment with a representative sample of the US population. We exogenously alter people's perceived economic status by changing where they think their household stands in the US income distribution. Half of the people who over-estimated their position in the income distribution are told that they are relatively poorer than they thought. Conversely, half of those who under-estimated their position in the income distribution are informed that they are relatively richer than they thought. Then, participants play a series of four incentivised games, which measure different social preferences, such as trust, negative reciprocity, honesty and altruism. We show that individuals who learn that they are lower (resp. higher) in the income distribution than they thought become less (resp. more) satisfied with their relative position in the income distribution, but that their behaviour remains unchanged in the four behavioural games. The third chapter, co-written with Christopher Roth and Diego Ubfal, studies whether providing information about immigrants affects people's attitude towards them. First, we use a large representative cross-country experiment to show that, when people are told the share of immigrants in their country, they become less likely to state that there are too many of them. Then, we conduct two online experiments in the US, where we provide half of the participants with five statistics about immigration, before evaluating their attitude towards immigrants with self-reported and behavioural measures. This more comprehensive intervention improves people's attitude towards existing immigrants, although it does not, on average, change people's policy preferences regarding immigration. However, Republicans become more willing to increase legal immigration after receiving the information treatment.

Keywords: behavioral economics
survey experiments
social preferences
Advisor: Abeler, J
Genome annotation errors and how to fix them

Many inferences about the biological properties of an organism depend on the completeness and accuracy of its genome annotation. Advances in sequencing technologies and the associated decreased costs have brought whole genome sequencing projects into the reach of individual laboratories, precipitating a huge acceleration in the publication of draft genome assemblies and annotations. While genome assembly quality metrics have received substantial attention, adequate frameworks for quantifying and controlling errors in genome annotations are lacking, and thus the completeness and accuracy of published genome annotations are unknown. Moreover, genome annotations are frequently taken at face value by those using them, and any errors present are propagated in downstream inferences and analyses. Despite underpinning much of comparative genomic research, little attention has been paid to quantifying the extent of genome annotation inaccuracies and the majority of attempts to systematically rectify such errors have relied either on manual input, which is impractical on a large scale, or on universally conserved gene sets, which only account for a small percentage of genes. The aim of the research described in this thesis is to provide methods to assess and rectify two main classes of genome annotation errors (missing genes and incorrect gene models) at a phylogenetically local level, by mutually improving genome annotations for sets of related species, in the absence of extrinsic experimental data. I introduce several non-extrinsic metrics for assessing genome annotation completeness and the accuracy of the gene models contained therein, and provide two self-contained methods that improve genome annotation accuracy. In summary, this thesis reveals that genome annotation errors are widespread, even in widely studied community annotated genomes, and that many of these errors can be identified and corrected using automated phylogenetically local approaches.

Advisor: Kelly, S
Modulation of proteolysis counteracts oxidative stress but impairs base excision repair in ATM-depleted cells

Ataxia-telangiectasia (A-T), also known as Louis-Bar syndrome, is a neurodegenerative autosomal recessive disease caused by bi-allelic mutations in the ataxia-telangiectasia mutated (ATM) gene. The product of the ATM gene is a serine/threonine kinase that acts as primary mediator of cellular signalling pathways in response to various genotoxic stresses, such as DNA damage and reactive oxygen species (ROS). It has been proposed that accumulation of oxidative stress due to loss of functional ATM contributes significantly to the pathogenesis and features of A-T, including neurodegeneration and immunodeficiency. However, despite the severity of the symptoms linked to A-T, lack of functional ATM protein is still compatible with life. We postulated that early adaptive mechanisms must be in place to allow cells to survive in the absence of ATM. Crucially, comprehension of these mechanisms would allow us to elucidate some of the molecular features of A-T, including genomic instability and predisposition to cancer.
To this aim, we adopted a quantitative proteomics approach to study changes occurring early on in normal fibroblasts upon depletion of ATM. We observed that ATM-depleted cells display progressive accumulation of oxidised proteins in the nuclear compartment. Furthermore, our study showed that ATM-depleted cells modulate proteolysis to counteract oxidative stress, which contributes to the survival at early stages after ATM loss. On the other hand, increased proteolysis in ATM-depleted fibroblasts had a negative impact on the frontline DNA repair system counteracting oxidative DNA damage: the DNA base excision repair (BER) pathway. ATM-depleted cells showed lower BER protein levels and severely impaired BER capacity. We propose that DNA repair deficiency caused by BER impairment could be one of the early mechanisms leading to accumulation of genomic instability in ATM-depleted cells.
These previously overlooked adaptation mechanisms give useful insight into the changes occurring very early on upon loss of ATM and provide a molecular explanation for some of the severe features of A-T.

Advisor: Dianov, G
Brown, T
Poletto, M
Dynamic longitudinal survival analysis

In recent times, a greater emphasis is being placed on understanding the underlying processes and mechanisms that drive and generate survival data. As Aalen and Gjessing (2001) note, events don’t happen out of the blue, there is a development preceding each event. When observing the time till occurrence of a death, ageing is one such underlying process or ‘development’. This project outlines potential methods for the analysis of longitudinal survival data, from an ageing perspective, and develops a novel dynamic model which incorporates understanding of the ageing process, illustrated through application to lifetime behavioural data available for a sample of fruit-flies.

Advisor: Steinsaltz, D
Predicting and improving perception performance for robotics applications

Perception systems are often the core component of a robotics framework as their ability to accurately interpret sensor data is essential for autonomy. The goal of this thesis is to estimate and improve the perception performance of a mobile robot across large areas of operation, particularly when there are no guarantees that the testing data distribution will match the training distribution. Such situations are prevalent for autonomous mobile robots operating outdoors under a variety of environmental conditions.
This thesis explores the adaptability of vision systems by training place-specific models which outperform generic ones. We show that it is possible to train such models in a self-supervised fashion using geometric scene constraints without relying on costly image annotations.
This thesis also explores the awareness that vision systems have of their own capability to make correct predictions at any given moment in time. We approach this problem from two different vantage points: firstly, through performance records which model perception performance as a function of location and appearance and, secondly, through intrinsic model uncertainty, or introspection as introduced by [Grimmett et al., 2016].
Performance records allow an autonomous agent to estimate the likelihood of making a mistake during future traversals of the same place. In a use-case scenario regarding offering or denying autonomy, we show that an agent is able to estimate when its confidence levels are low, deny autonomy, and reduce the number of perception mistakes made.
Introspection refers to the ability of a model to associate an appropriate assessment of confidence with any test case. We introduce an efficient way to obtain well-calibrated and reliable uncertainty scores from neural networks. Our method is more computationally efficient than Bayesian neural networks or model ensembles which, despite being well-calibrated, are more cumbersome to train and slower to test. Additionally, we believe that we are the first to propose more introspective detectors within a state of the art object detection framework such as Faster R-CNN.
This thesis proposes vision systems that are not only more accurate but also whose failures can be more reliably predicted. In doing so, we advocate practical solutions that often make use of tools specific to robotics such as additional sensing modalities or localisation maps pertaining to an autonomous vehicle, but we also touch upon machine learning techniques such as Bayesian deep learning.
While striving for high accuracy remains a crucial endeavour, given the safetycritical nature of robot perception, we believe that estimating reliability, introspection, and diagnosing failure are indispensable when operating in cluttered, complex, and ever-changing environments.

Advisor: Posner, I
Molecular mechanisms underlying the development of Atrial Fibrillation

Atrial Fibrillation (AF) is the most common type of clinical arrhythmia, affecting roughly 1% of the population. While not fatal per se, it is associated with a signiFicant increase in the risk of stroke, accounting for around a quarter of all strokes. AF does not have a clear cause, but it appears to be a progressive remodelling of the atrial tissue characterised by extensive electrical and structural modiFications. Its main risk factors are age, hypertension, heart failure, obesity, diabetes mellitus and thyroid dysfunction. The overall goal of this project is to shed light on the molecular mechanisms that promote the development of AF.
The First part of the project focuses on the role of neuronal Nitric Oxide Synthase (nNOS) and dystrophin in AF. Previous studies reported that both proteins are reduced in the atrial tissues of patients with persistent AF. In addition, nNOS-/- mice showed an increased propensity to develop AF in response to pacing. Given that nNOS is physically associated with dystrophin at the membrane in atrial myocytes, I investigated whether a mouse lacking dystrophin (mdx) could be used as a model for AF development.
In the second part of the project, I investigated atrial samples from patients in sinus rhythm undergoing coronary revascularisation with the aim of identifying early changes linked to the development of post-operative AF (poAF). PoAF occurs in one-third of patients within a week of undergoing cardiac surgery. Although poAF is usually self-limiting, patients are more likely to develop persistent AF on follow-up. I adopted a whole-transcriptome approach, proFiling the mRNAs and microRNAs in samples of patients who developed poAF, and compared them to samples from patients who stayed in sinus rhythm postoperatively. Differences between the two groups may bring valuable insights on the atrial substrate that subtends the development of AF and uncover new therapeutic targets.

Advisor: Casadei, B
Characterization of a group of specialized cardiomyocytes and their interaction with sympathetic neurons in murine heart

Our group recently described a distinctive, novel class of Pnmt+ cell-derived cardiomyocytes (PdCMs), with a potential endocrine role. However, our understanding of this new cardiomyocyte population is still very limited. There are numerous issues to be addressed such as the evidence of their endocrine machinery, their interaction with autonomic system, and their physiological function in the heart corresponding to their unique location in the heart. In order to address these issues, by using wild type and Pnmtcre/ChR2 mice as model systems, I have conducted a series of immunohistochemical and electrophysiological experiments with the aims of: i) exploring the potential endocrine machinery of PdCMs (Chapter 3); ii) clarifying their interaction with sympathetic neuron innervation (Chapter 4), and iii) determining their physiological role in the atria (Chapter 5).
The key findings of this report include: i) firstly, a subtype of PdCMs containing vesicular structures was revealed by using immunostaining of vesicular monoamine transporter 2 (VMAT2) and myocyte marker α-actinin (aACT) as well as extra-neuronal monoamine transporter (EMT/ OCT3). This is the first time that such cellular vesicles have been found in cardiomyocytes. Although such vesicular structure requires further investigation, it opens a new frontier for exploring the cardiomyocyte endocrine function; ii) secondly, a synapse-like junction structure between these cardiomyocytes and sympathetic neuron innervation was identified by the staining of anti-Tyrosine Hydroxylase(TH) and anti-VMAT2; iii) finally, by using optogenetic stimulation combining with a high resolution optical imaging, the potential role as alternative pacemaker site of PdCMs was explored, which was induced by optogenetic pacing technique.
In conclusion, the results presented in my report have provided novel evidence to suggest the endocrine function and the pivotal role in neurocardiac crosstalk of PdCMs.

Advisor: Lei, M
Why do ABCC5 KO mice show a lean phenotype?

ABCC5 is an ATP-dependent membrane transporter that has been shown to transport glutamate conjugates in mammalian systems. Global loss of ABCC5 from mice causes a lean phenotype with enhanced enteroendocrine GLP-1 secretion. Here we develop a protocol for the live imaging of GLP-1 secretion in vitro using a model L-cell line. ABCC5 KO gut histology analysis shows no difference in gut villi length or surface area between WT and KO mice. Despite numerous studies showing enhanced brown adipose tissue (BAT) and white adipose tissue (WAT) thermogenic capacity in the presence of elevated GLP-1 levels, data presented here do not show increased non-shivering thermogenesis occurring in our KO animals. Analysis of fat pads from ABCC5 KO mice show that both their BAT and epididymal WAT depots have significantly lower mass than WT depots. Western blot and H&E; histological analysis suggests that inguinal WAT depots of ABCC5 KO mice may show a lack of browning. We theorise that the adipose physiology described is due to changes in glutamatergic signalling in the sympathetic nervous system innervating BAT and WAT. Finally, we conclude that the lean phenotype of ABCC5 KO mice cannot be attributed to an increased thermogenic capacity of BAT and WAT.

Keywords: endocrinology
ABCC5
brown
GLP-1
metabolism
beige
adipose
Advisor: de Wet, H
Austerity policies: towards local environmental empowerment or neoliberal conservation?

The United Kingdom’s government has been sharply reducing its size by exercising austerity on its departments since 2010, with the narrative that this will create opportunity for more localized scales to deliver services and be more empowered. Drawing on the Politics of Scale and Networks with an emphasis on conservation, this research uses semi-structured interviews with principal local authority conservation officers and local conservation charities to map the geographies of power that have resulted from central government’s measures, thus testing to what extent their localism narrative has come to pass. We find that some power was indeed transferred to the local scale, but only partially, specifically to established charities, while emerging charities were weakened. We also find evidence that suggests neoliberal motives for effecting the austerity. This research contributes to the scarce literature that delves into the effect of austerity on conservation capacity at localised scales and the debate against austerity.

Advisor: Ernwein, M