VictorJuiz/thesis huggingface dataset:
Identification of immunological targets for HIV-1 vaccine and cure strategies 
Keywords: HIV
CD8 T cells

HIV-1 chronically infected individuals represent a large disease burden, making the development of a therapeutic vaccine for use in chronic infection a priority. However, therapeutic vaccination has not been successful to date. Most approaches have employed viral vectored vaccines encoding full length viral proteins, which aimed to boost pre-existing CD8&plus; T cell responses by mimicking natural HIV-1 infection. Simply boosting these pre-existing CD8&plus; T cell responses which have previously failed to control the virus may be insufficient. Although HIV-1 has a huge capacity to diversify, certain regions are less tolerant of mutations due to structural and functional constraints. We therefore hypothesised that it would be necessary to redirect the immune response to more vulnerable regions of the proteome, such as conserved regions.
HIVconsv is a rationally designed conserved region vaccine. Vaccination of 19 chronically HIV-1 infected HAART treated patients with MVA.HIVconsv was safe and well tolerated. There was a significant increase in the magnitude of HIVconsv-specific T cell response following vaccination (p = 0.001), as measured by IFN-γ Elispot assay, but changes observed in vaccinees did not reach statistical significance when compared with placebo recipients (p = 0.48).
The capacity of CD8&plus; T cells to inhibit HIV-1 replication in vitro is highly predictive of virus control in vivo and is thus a possible surrogate of vaccine efficacy. There was a trend towards increased CD8&plus; T cell mediated inhibition following vaccination with 2x108pfu MVA.HIVconsv (17% inhibition pre- vs 54% inhibition post-vaccination, p = 0.06). However, measurement of the latent HIV-1 reservoir by quantification of total HIV-1 DNA in circulating CD4&plus; T cells by droplet digital PCR showed no reduction in size upon vaccination, indicating CD8&plus; T cells induced by vaccination with MVA.HIVconsv were not of sufficient potency to impact the reservoir.
In a second cohort of HIV-1 infected individuals, antiviral inhibitory activity was measured in 36 HIV-1-infected STEP and Phambili trial participants. Sustained potent CD8&plus; T cell antiviral inhibitory responses were rare but were strongly correlated with IFN-γ responses to so-called ‘beneficial’ low entropy regions in HIV-1 Gag and Pol, that had been reported previously to be associated with HIV-1 control, (r = 0.69, p = 0.0001). This correlation was still significant after controlling for protective HLA alleles, whereas responses to conserved elements were only weakly correlated with viral inhibition (r = 0.41, p = 0.04).
These data indicate that immunogens that are based on the selection of regions within the viral proteome by conservation score alone may not induce the most effective HIV-1-specific T cell responses and they highlight the importance of systematically selecting specific regions associated with HIV-1 control, together with exclusion of immunodominant decoy epitopes.
In the name of oil
Keywords: Anglo-American relations
decolonisation
oil
Middle East
Cold War

Traditional historiographies of the Cold War Middle East read into Britain's postwar economic decline a corresponding demise of British regional influence. According to these accounts, the Suez Crisis served to teach Britain new limits to its military capabilities, occasioning a break from independent endeavours to project power in the region. However, the case studies presented in this thesis demonstrate that the Suez Crisis did not mark a precipitous turning point in Britain's political influence in the Middle East in the short- to medium-term. Britain's power in the region rested upon not only its material assets, but other less tangible bases as well. Most importantly, Britain's power in the Middle East during the period examined increasingly included its ability to influence the policies of United States – a country with great resources and an emerging presence in the region.
Bayesian methods for fine mapping in genetic association studies
Keywords: bayesian
genetics
random effects
mcmc
fine mapping
meta analysis
compound heterozygosity
statistics

Over the past several years genetic variation has been the centre of attention for different branches of genetics. The use of genome wide association studies (GWAS) has facilitated the discovery of a plethora of genetic variants which are associated with a vast range of diseases. These GWAS primarily examine a single variant, mostly a Single Nucleotide Polymorphism (SNP), at a time based on genotype data. Although this practice has proven to be powerful, low percentages of heritability prompt a call for the exploration of more complex structures of association.
As diseases are more likely to be caused by several variants, multi-SNP analyses are used to refine the signal leading to the development of fine mapping methodologies. Further biological information is accounted for by studying the diploid nature of the human genome which identifies phenomena, such as compound heterozygosity. We propose a flexible Bayesian fine mapping model for quantitative traits allowing for the analysis of haplotype data under a variety of genotype and haplotype models. A Metropolis-Hastings algorithm is employed to search the model space efficiently. Simulations show competitive performance over existing methods when compound heterozygous effects are present in the data.
An extension of a single cohort framework is meta-analysis where a collection of studies is used to increase confidence and boost power in noticeable associations. Traditional approaches include the fixed effects model where the assumption is that genetic effects are homogeneous amongst cohorts while the random effects model accounts for heterogeneity. We propose a Bayesian meta-analysis approach which implements both fixed and random effects with the addition of a parameter measuring the existence of effect in each cohort. Simulations and application to real samples explore the performance of the method under different conditions and show comparable evidence over established methodologies.
Biochemical determinants of nitric oxide synthesis in severe malaria
Keywords: Infectious Disease Pathogenesis
Vascular Homeostasis
Analytical Biochemsitry
Nitric Oxide
Tetrahydrobiopterin
Severe Malaria
Arginine Metabolism

Inhibition of nitric oxide (NO) signalling may contribute to the pathogenesis of severe malaria. This thesis examines the impact of Plasmodium infection on three key determinants of nitric oxide synthase (NOS) biochemistry: substrate availability, substrate/inhibitor homeostasis and cofactor availability. Arginine, the NOS substrate, is depleted in human patients with severe Plasmodium falciparum malaria and mice infected with P. berghei ANKA. Using heavy isotope tracer infusions to quantify arginine metabolism in infected mice, we found no evidence of increased catabolism by the enzyme arginase, widely assumed to be responsible for arginine depletion. Genetic knock-out of parasite arginase had no effect on arginine depletion in mice. Instead, our findings link arginine depletion to decreased rates of arginine and citrulline appearance in the plasma of infected mice. Asymmetric dimethylarginine (ADMA) competes with arginine for binding to the NOS catalytic site. We observed elevation of the ADMA/arginine ratio in Gambian children with severe malaria, favouring NOS inhibition. In mice infected with P. berghei ANKA, we found evidence of degradation of dimethylarginine dimethylaminohydrolase 1 (DDAH1), the enzyme primarily responsible for ADMA metabolism. We also observed reduced DDAH activity and accumulation of intracellular ADMA in hepatic tissue of infected mice, suggesting that DDAH dysfunction could contribute to disruption of ADMA/arginine homeostasis. Tetrahydrobiopterin (BH4) is an essential NOS cofactor. In P. berghei ANKA-infected mice, BH4 concentrations were decreased in plasma, erythrocytes and brain tissue, which could inhibit NO synthesis and promote NOS-dependent superoxide production. To reverse deficiencies of NOS substrate and cofactor availability, we infused P. berghei ANKA-infected mice with citrulline, an arginine precursor, and sepiapterin, a BH4 precursor. Restoration of systemic arginine and BH4 availability in infected mice improved whole blood nitrite concentrations, a biomarker of NO synthesis, but did not prevent onset of disease symptoms. These studies have identified biochemical disturbances that may contribute to severe malaria pathogenesis by inhibiting NO synthesis.
Importance sampling on the coalescent with recombination
Keywords: likelihood
infinite sites
probability
importance sampling
resampling
coalescent
Monte Carlo
two-locus

Performing inference on contemporary samples of homologous DNA sequence data is an important task. By assuming a stochastic model for ancestry, one can make full use of observed data by sampling from the distribution of genealogies conditional upon the sample configuration. A natural such model is Kingman's coalescent, with numerous extensions to account for additional biological phenomena. However, in this model the distribution of interest cannot be written down analytically, and so one solution is to utilize importance sampling.
In this context, importance sampling (IS) simulates genealogies from an artificial proposal distribution, and corrects for this by weighting each resulting genealogy. In this thesis I investigate in detail approaches for developing efficient proposal distributions on coalescent histories, with a particular focus on a two-locus model mutating under the infinite-sites assumption and in which the loci are separated by a region of recombination. This model was originally studied by Griffiths (1981), and is a useful simplification for considering the correlated ancestries of two linked loci. I show that my proposal distribution generally outperforms an existing IS method which could be recruited to this model.
Given today's sequencing technologies it is not difficult to find volumes of data for which even the most efficient proposal distributions might struggle. I therefore appropriate resampling mechanisms from the theory of sequential Monte Carlo in order to effect substantial improvements in IS applications. In particular, I propose a new resampling scheme and confirm that it ensures a significant gain in the accuracy of likelihood estimates. It outperforms an existing scheme which can actually diminish the quality of an IS simulation unless it is applied to coalescent models with care. Finally, I apply the methods developed here to an example dataset, and discuss a new measure for the way in which two gene trees are correlated.
Corporate water risk - and return
Keywords: water return
corporate sustainability
water risk

Corporate water risk is a function of resource dependence, which exposes firms to uncertainty. Firms rationally seek to reduce this risk, and this shapes their disclosure strategies. However, the consequence is that corporate water risk disclosure is becoming increasingly unfit for purpose. As current approaches begin to acquire institutional legitimacy and the path-dependent label of best practice, a status quo is becoming embedded, reinforced through mimetic behaviour. The agency problem that this creates is unchecked; in part because of the legitimacy acquired by the disclosure strategies, but also because of temporal myopia exhibited by investors, which contributes to unpredictable decision-making. The status quo also results in sub-optimal resource allocation, a problem that is compounded by the large and growing global infrastructure deficit for water supply and services.
This thesis sets out a framework by which the disclosure of corporate water risk can be meaningfully evaluated by investors and other stakeholders; and proposes how the water infrastructure investment gap could be narrowed by the development and application of the corporate water return concept. The research builds on empirical foundations to offer new approaches that address the problems of the status quo. First, it empirically explores perceptions of best practice in terms of water risk disclosure, from the perspective of both listed firms and leading institutional investors (Chapters 3 and 4). Second, it proposes a methodology through which firms can disclose water risks in a systematic format; and advances corporate water return as a complementary concept to water risk, in order to catalyse corporate investment in water infrastructure (Chapters 5 and 6). Resource dependence theory, institutional theory, and stakeholder theory are combined to create a trio of integrative, explicative conceptual narratives that form the overarching thesis structure. The research also draws on other themes from economic geography, including proximity; strategic cognition; transaction costs; and real options theory.
Role of the haematopoietic transcription factor SCL in mesoderm development
Keywords: Cardic Development
SCL
Transcription Factors
Stem Cells
Haematopoesis
Mesoderm Development

During embryonic development, precursor cells commit to specific cell fates in response to environmental cues through the establishment of lineage-specific gene expression programmes. Transcription factors are important downstream effectors of signalling pathways that initiate and maintain cell fate decisions. The haematopoietic transcription factor SCL (TAL-1) is an essential regulator of embryonic blood development. However, the exact stage at which SCL is required, its mechanisms of action, and its genomic targets are poorly understood. Characterising how SCL functions during haematopoietic development will provide insights into how stem cells are specified.
Using the embryonic stem cell/embryoid body (ES/EB) system to model early mouse development, we describe a critical role for SCL in mesoderm patterning. SCL is first expressed in PDGFRα+ FLK1+ mesoderm populations which contain lateral, paraxial and cardiac precursors. Through loss- and gain-of-function studies, we show that SCL drives lateral mesoderm specification and activates the haematopoietic programme in a direct DNA-binding independent manner, while actively repressing alternative mesodermal fates, specifically cardiac development, in a DNA-binding dependent manner. At a molecular level, we have identified direct genomic targets of SCL in Flk-1+ mesoderm populations. These include haematopoietic and cardiac transcription factors, cardiac-specific structural proteins, signalling proteins and general transcriptional repressors; thereby strengthening the dual function of SCL in mesoderm patterning. Finally, we have shown that the cardiac transcription factor GATA4 acts in a reciprocal manner, specifying cardiac precursors while repressing a lateral mesoderm fate.
Collectively, this implicates SCL as a critical transcriptional regulator of cell fate decisions in early mesodermal precursors, employing distinct molecular mechanisms to impose a blood programme. Moreover, and extending earlier reports, we document the existence of an antagonistic cross-talk between haematopoietic and cardiac lineages during mesoderm patterning. In conclusion, this work offers a cellular and molecular platform to begin to dissect the network of genetic interactions involved in these developmental processes.
Modelling price dynamics through fundamental relationships in electricity and other energy markets
Keywords: stochastic
fundamental
multi-commodity
bid stack
electricity prices
PJM
carbon market
natural gas
structural
option pricing

Energy markets feature a wide range of unusual price behaviour along with a complicated dependence structure between electricity, natural gas, coal and carbon, as well as other variables. We approach this broad modelling challenge by firstly developing a structural framework to modelling spot electricity prices, through an analysis of the underlying supply and demand factors which drive power prices, and the relationship between them. We propose a stochastic model for fuel prices, power demand and generation capacity availability, as well as a parametric form for the bid stack function which maps these price drivers to the spot electricity price. Based on the intuition of cost-related bids from generators, the model describes mathematically how different fuel prices drive different portions of the bid stack (i.e., the merit order) and hence influence power prices at varying levels of demand. Using actual bid data, we find high correlations between the movements of bids and the corresponding fuel prices (coal and gas). We fit the model to the PJM and New England markets in the US, and assess the performance of the model, in terms of capturing key properties of simulated price trajectories, as well as comparing the model’s forward prices with observed data. We then discuss various mathematical techniques (explicit solutions, approximations, simulations and other numerical techniques) for calibrating to observed fuel and electricity forward curves, as well as for pricing of various single and multi-commodity options. The model reveals that natural gas prices are historically the primary driver of power prices over long horizons in both markets, with shorter term dynamics driven also by fluctuations in demand and reserve margin. However, the framework developed in this thesis is very flexible and able to adapt to different markets or changing conditions, as well as capturing automatically the possibility of changes in the merit order of fuels. In particular, it allows us to begin to understand price movements in the recently-formed carbon emissions markets, which add a new level of complexity to energy price modelling. Thus, the bid stack model can be viewed as more than just an original and elegant new approach to spot electricity prices, but also a convenient and intuitive tool for understanding risks and pricing contracts in the global energy markets, an important, rapidly-growing and fascinating area of research.
Enforcing corruption laws: the political economy of subnational prosecutions in Indonesia
Keywords: Indonesia
Corruption
Political Economy of Law Enforcement

This thesis focuses on subnational corruption law enforcement in a new democracy: Indonesia. It seeks to understand temporal and spatial variation in corruption prosecutions in the post-Suharto era, and answer three core research questions: Why has the number of corruption cases steadily increased over the past twenty years? Why is there significant subnational variation in the investigation and prosecution of corruption? And why are some cases of local corruption investigated and prosecuted while others are ignored? The argument developed in the thesis consists of three inter-linked components: that corruption generates complex collective action problems for law enforcement; that ostensibly public law enforcement regimes in Indonesia are informally privatised public law enforcement regimes; and that, in the context of these hybrid regimes, the availability of resources and the formation of coalitions is critical to understanding when individuals and groups mobilise corruption laws at the subnational level.
The project uses a mixed methods research strategy—combining qualitative case studies, formal game theoretic modelling, and quantitative regression analysis—to develop and provide evidence for the argument. The research strategy required twelve months of fieldwork in Indonesia. In total over one hundred interviews in Jakarta and Central Java were conducted, and a unique dataset of local corruption cases was coded for two additional provinces. The thesis's argument and methodological approach has implications for literature that spans the field of law and politics: the political economy of prosecution, theories of legal mobilisation, socio-legal studies, and studies of politics and power in contemporary Indonesia.
A bottom-up model of electricity reform for developing countries: a case study of Gujarat, India
Keywords: India
Gujarat
Electricity reform
distributed generation

In many developing countries, the electricity system is too weak to meet growing demand and the availability and reliability of generating capacity is inadequate. Protracted mismanagement, political interference, subsidised pricing, and corruption all undermine the ability of developing electricity supply industries to finance and deliver service or attract new private investment. Power sector reform is an acute need in developing countries where implementation of a top-down liberalisation approach has been pursued without adequately considering the social, political and economic conditions. The conventional response to low levels of electricity sector investment has been from the top-down: aim to create competitive electricity markets by encouraging new entry into the generation sector and by breaking up vertically integrated power companies. Using a case study from Gujarat, India, this thesis argues for an alternative approach—utilise distributed generation (DG) and captive power capacity (self-generation) of industry to reshape the generation and distribution sectors from the bottom-up. The thesis examines the economic viability of distributed generation in a rural setting and captive power for industrial use in Gujarat, India, taking into account the economic, technical and political factors that shape investment decisions. In India, 40 percent of the population still does not have an electricity connection, but an array of new energy technologies for small-scale electricity generation near the site of use may provide a new development path. The bottom-up model enables rapid addition of generation capacity to a system struggling to meet demand while increasing competition in the power market. The thesis concludes that more power from independent and industrial sources will best harness the financial and engineer resources of the Indian electricity supply industry (ESI) and ultimately benefit the economy. The solution proposed is not suggested as an optimal policy programme, but instead is advanced as the best of the feasible options available within current political and economic constraints.