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Exploration of disease phenotype variation in equine trypanosomiasis
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The synthesis and development of radionuclide based tracers for the imaging of diseases
Get PDFThis PhD focused on the development of synthetic methods for the preparation of known and novel PET imaging agents targeting the central nervous system. The first project created a second-generation enantioselective synthesis of [18F]SynVesT-1, a PET imaging agent for the synaptic vesicle protein 2A (SV2A), along with its non-radiofluorinated standard. Additionally, a modification of this route allowed the synthesis of the novel radioligand, [3H]SynVesT-1, for SV2A autoradiography.
The next project focused on the synthesis of novel PET imaging agents for the monocarboxylate transporters-1 and -2. A small library of fluorinated and methoxylated 6 substituted thieno[2,3-d]pyrimidinedione-5-carboxamide analogues was synthesised via an eight-step route. The physicochemical properties of the developed compounds were evaluated using HPLC methodology, with all showing favourable characteristics.
The final project was dedicated to the development of novel fluorescent α-amino acids via derivatisation of tryptophan at C2-position through alkenylation (Horner-Wadsworth-Emmons and Witting) and arylation (Suzuki-Miyaura) reactions. The resulting amino acids showed excellent photophysical properties, solvatochromism and pH sensitivity
Modelling population dynamics to inform the evaluation of vector control tools in semi-field and field settings
Get PDFMalaria remains one of the most common life-threatening vector-borne diseases worldwide, with an estimated 263 million global cases and 597,000 deaths per year, 94% and 95% of which occur in sub-Saharan African countries, respectively. In sub-Saharan Africa, Tanzania accounts for approximately 3.3% and 4.3% of all malaria cases and deaths, placing it among the leading four countries responsible for just over half of global malaria deaths. Malaria is transmitted to humans through a bite by an infected female Anopheline mosquito. In Dar es Salaam, Tanzania, An. gambiae s.l. (i.e., An. gambiae s.s., An. arabiensis and An. merus) is the most important species in terms of malaria transmission, followed by An. funestus. Vector control remains the most effective strategy against malaria. The main malaria vector control interventions are insecticide-treated bed nets and indoor residual spraying; both were very successful but were not enough to eliminate transmission, so there is a continuous search for new tools and strategies for deployment.
Development of interventions typically starts in the laboratory and then moves to the semi-field system before going to the field; thus, we need robust ways to assess them at all these levels. Experiments for testing vector control interventions in semi-field systems serve as a cost-effective link between laboratory and field trials, enabling researchers to evaluate interventions or their combinations in controlled conditions. One way to achieve reliable outcomes is to design semi-field experiments with adequate statistical power. Evaluating power is crucial for determining necessary resources, including finances, time, and participants. However, power analysis is rarely done, possibly due to limitations in technical skills and the availability of tools such as software.
Furthermore, assessment of interventions in the field settings needs to not only determine the impact on population size but also regulatory processes (such as negative density dependence and positive density dependence known as Allee effect) that regulate populations. Negative density dependence is a regulatory process which typically operates in immature mosquitoes where growth rates decline at high densities, mainly caused by resource competition. Allee effect is another process operating in adult mosquitoes where population crash if density is low, mainly caused by mate limitation. Understanding the impacts on population dynamics and how low populations are regulated in the field settings could provide critical insights into how to improve vector control strategies. This is because at low densities, regulatory processes, particularly negative density dependence and Allee effects, have implications for vector suppression and elimination plans. However, the existence of Allee effects in the field settings with low mosquito population densities and their implications for vector control interventions is still unknown.
The main aim of this PhD thesis was to improve the evaluation of malaria vector control interventions. This was done through a combination of theoretical and statistical modelling approaches applied to both semi-field and field settings.There were three specific research aims: 1) how can vector control experimental designs be improved in semi-field systems? 2) what are the trade-offs between mosquito population regulatory mechanisms at low densities? and 3) do key mosquito population regulatory processes emerge from large-scale vector control?
To achieve aim 1, a simulation-based power analysis framework from a generalised linear mixed model was developed to assess how many chambers, sampling frequency and sampling size in semi-field systems would provide enough power to determine the impact of interaction between two tools, here pyriproxyfen autodissemination and the widespread insecticide-treated bed nets against malaria vector An. arabiensis across a range of commonly used semi-field experimental designs, such as single vs. combined interventions and short- vs. long-term experiments.
Results showed that the higher the effect sizes, the higher the power, but power also increased with the number of chambers, sampling frequency, and number of mosquitoes, while high variation between chambers reduced power. a generalisable power analysis framework was provided and can be used widely for other vector control tools, experimental scenarios and also other vectors.
For aim 2, a simulation model based on an age-structured population model was developed to quantify trade-offs between negative density dependence and the Allee effect and how these impact the outcomes of interventions.Results showed that while in isolation, these mechanisms are not able to drive the population into extinction, their co-existence can accelerate population extinction as populations become smaller. A combination of negative density dependence, the Allee effect, and sustained larvicidal intervention led to a decline in mosquito populations to levels from which they could not recover. Conversely, the combination of negative density dependence, the Allee effect, and short-term larvicidal applications did not decrease mosquito populations to lower levels enough to prevent a rebound. Understanding regulatory processes like Allee effects can support vector control by highlighting resilient and vulnerable aspects of the mosquito’s life cycle stages to interventions, and potentially accelerating malaria elimination.
To address aim 3, a population dynamics model was developed using the Bayesian state-space modelling approach. Initially, the model was fitted to simulated data to determine whether my framework would be able to quantify Allee effects if they exist in the wild. Results showed that the framework was indeed able to capture the life history traits, including negative density dependence and Allee effects. Subsequently, the model was fitted to female adult An. gambiae data from Dar es Salaam, Tanzania, to identify the presence of Allee effects in natural settings and quantify the impacts of a larvicide intervention. Results showed that there was no evidence of the Allee effect in the An. gambiae mosquito data from Dar es Salaam despite the larviciding having reduced the population by 60.92%. When planning for future malaria vector control strategies, it is essential to consider Allee effects, if they exist, fewer resources could result in better outcomes, similar to deploying more resources.
In conclusion, the methods and findings presented in this thesis will help future research to evaluate vector control interventions or their combinations in SFS and field settings. This thesis contributed to a general understanding of the trade-offs between negative density dependence and Allee effects and how they can contribute to vector control and accelerate malaria elimination. The Bayesian state-space modelling framework developed in this thesis will aid further research in identifying Allee effects in different settings with low mosquito population densities
Dissociation and sleep in dissociative seizures: an exploration
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Exploring metacognition and social connection as mechanisms of change in individuals with negative symptoms of psychosis
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Exploring the use of real-world data for studying clinical outcomes in people with rare endocrine conditions
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Towards a general theory within wastewater treatment: computational and experimental examples utilising fundamental laws to describe microbial community structure in wastewater treatment systems
Get PDFWastewater engineering needs novel, sustainable systems designed to cope with the pressures of climate change, urbanisation and increasing water scarcity. Modern molecular methods in microbiology are allowing us to interrogate the complex microbial communities underpinning biological wastewater treatment technologies, which affords the opportunity to design and control them. The application of theory is a fundamental tool to achieve this, however, current theories, whilst numerous, are partial and idiosyncratic. A concerted research effort is required to generate generic, widely accepted theory for wastewater treatment design. This thesis approaches the problem of defining fundamental rules on the structure and dynamics of wastewater microbial communities from two different perspectives.
The first asks the question if there was a generic theory on community assembly for a wastewater microbial community, is it possible to identify its parameters using the type of data that is routinely collected? To answer this an empirical approach is used where a model is assumed, in this case the simple neutral model. It is applied to generate a range of synthetic relative abundance time series with a range of different features, such as different sampling frequencies. The model is then calibrated using these data under various scenarios to assess parameter identifiability. The process of efficiently simulating, sampling and calibrating was achieved by developing an open-source user-friendly and adaptable computational framework. The results demonstrate fundamental difficulties in identifying neutral model parameters, even when using idealised time series. This is due to misrepresentation of the expected variance and correlated parameters. As such, there is a need to independently determine some of these parameters a priori. Reduced sampling periods and frequencies are also shown to impact model calibration, leading to systematic errors in the estimates of certain parameters. The research highlights the need for increasing information within relative abundance time series and demonstrates that this can be achieved by inducing a perturbation on a system. Thus, producing time series during periods of non-equilibrium is shown to be beneficial. Finally, it is demonstrated that for real data sets neutral model parameters must be considered as "effective" parameters as the estimates obtained will likely reflect a myriad of complex phenomena.
The second perspective is mechanistic. Growth kinetics, known to drive inter-species competition, are explored through energy and thermodynamics. This is achieved experimentally by culturing two species of methanotrophs, Methylomonas methanica S1 and Methylosinus trichosporium OB3b, within an isothermal calorimeter. Comparisons are made between the heat dissipated by the species and how they partition the available carbon between energy-yielding and biosynthetic reactions. The methodology developed for measuring heat dissipation is novel in its application to methanotrophic bacteria. These measurements identify that a significant amount of heat is dissipated during the growth of methanotrophic bacteria. Differences in growth are also observed with Methylosinus trichosporium producing more CO2 at the cost of a reduced biomass yield when compared to Methylomonas methanica. This difference in carbon partitioning is shown to be linearly related to the heat dissipated per unit of biomass, however, the impact this has on providing a competitive advantage is unclear. It is speculated that additional biochemical and physical phenomena need to be quantified in order to resolve the relative importance of thermodynamics on the different kinetics.
Simple models with parameters and variables that are easily understood and manipulated by engineers have a long history of being successfully deployed in engineering design. In this thesis, two approaches have been explored to describe the assembly and kinetics of microbial communities. It is shown that identifying model parameters for even the simplest descriptions of community assembly, neutral models, is fraught with conceptual and practical difficulties. Notwithstanding this, their ability to capture phenomena is apparent, and the challenge for engineering design is mapping the calibrated parameters onto characteristics of engineered systems. A more mechanistic approach attempts to use energy and thermodynamics to explain kinetics using methanotroph species as an example. Energy based methods are the basis of many models used in engineering design because they can capture physical phenomena while eschewing much of the underlying complexities in physical or chemical processes. The thesis falls short of delivering a generic rule on the relationship between energy dissipated and kinetics. However, the empirical data generated are already being used in the design of technology for heat recovery from wastewater treatment. In general, the thesis demonstrates the merits of pursuing simplicity in models for generic application in environmental biotechnologies
Understanding the link between mutations in the enzyme PDE10A and hyperkinetic movement disorders
Get PDFThe regulation of cyclic nucleotide levels, particularly by Phosphodiesterase 10A (PDE10A), is critical for neurological function, and its dysregulation is implicated in hyperkinetic chorea-like disorders such as Huntington’s Disease (HD). While PDE10A inhibition has been explored as a therapeutic strategy, clinical trials have yielded limited success, suggesting a more complex pathology than previously understood. Recent studies on PDE10A mutants propose that a loss of PDE10A function, rather than compensatory downregulation, may contribute to these symptoms.
This investigation uses biochemical techniques to characterize five newly identified human PDE10A mutants (A530T, Asn838AlafsTer46, E890D, R182Ter, and D1023_N1024insY), four of which are pathogenic and one (E890D) is non-pathogenic. Using immunoblotting, RT-qPCR, and confocal microscopy in HEK293T cells, I assessed protein expression, mRNA levels, subcellular localization, and PDE enzyme activity. Our findings reveal that the pathogenicity of early termination mutants, R182Ter and Asn838AlafsTer46, is not fully clear, and caused either by a lack of key functional domains or due to NMD degrading the mRNA of these mutants. In contrast, other pathogenic mutants (A530T and D1023_N1024insY) exhibited normal expression and localization, but showed a profound loss of phosphodiesterase activity
The use of betaine as a novel senotherapy
Get PDFBackground: The global population demographic comprising those aged 65 years and over is increasing. Despite an increase in human life expectancy over the past 150 years, this has not been matched by a similar increase in health span (i.e. years of disease free living). Consequently, ageing populations present with more age-/lifestyle related diseases such as cardiovascular disease (CVD), chronic kidney disease (CKD) and cancer as part of a diseasome of ageing. Betaine is a key component of one-carbon metabolism required physiologically as an osmolyte, an antioxidant and a methyl donor for maintenance of the epigenetic landscape of ageing and mitochondrial function.
Objectives: The present study aims to assess how dysregulated ageing underpins the development of vascular ageing and the effects of betaine to mitigate this.
Methods: A series of experiments using real time cell analysis (RTCA), transcriptomics, immmunohistochemistry, immunocytochemistry and real-time PCR for a range of validated biomarkers of vascular ageing have been investigated in primary and induced pluripotent stem cell (iPSCs)-derived vascular smooth muscle cells (VSMCs) from human subjects. Betaine was then examined in in vivo models for its geroprotective effects on Drosophila melanogaster (D. melanogaster) and Caenorhabditis elegans (C. elegans).
Results: Our data indicate that betaine is a potent senotherapeutic able to extend primary VSMCs life span and diminish expression of biomarkers of cellular senescence (p16, p21, Nrf2, SerpineB2, cytoplasmic chromatin fragments), and the senescence-associated pro-inflammatory secretome (IL1β, IL6), as well as biomarkers of VMSCs damage (FOXO4, LMNA). In iPSCs-induced VSMCs, betaine has also displayed potential geroprotective effects by downregulating vascular calcification, extracellular vesicles and oxidative damage. Additionally, it increased total mitochondria content while protecting mitochondria membrane potential against DMSO treatment. Our vivo models (C. elegans, D. melanogaster) exhibited up to 20% lifespan extension after supplementation with betaine.
Conclusion: Our data indicate that betaine may be a powerful naturally occurring senotherapy and suitable for safe future clinical development
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