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Acute myeloid leukaemia (AML) is a highly heterogeneous disease in terms of genetics and at the clonal level. Despite improved understanding of the genetic landscape of AML, pathogenesis and cause of disease relapse remain poorly understood. To address these issues exome sequencing was carried out on 25 diagnostic and 12 relapse samples from 28 cytogenetic standard risk AML patients. More than 500 somatic mutations were identified, including recognised recurrent mutations, and novel variants with driver potential. Copy number variations were also investigated, identifying loss of heterozygosity of chromosome 13 involving the FLT3 locus as a common event acquired at disease relapse. The heterogeneity of disease relapse was also highlighted with the analysis of paired diagnostic and relapse samples. To further develop an understanding of AML clonal architecture and disease evolution, targeted deep sequencing was then carried out using a custom gene panel informed by exome sequencing results. Two cohorts were analysed including 223 diagnostic and 49 relapse samples from NPM1 mutant AML patients, followed by 43 unselected AML patients. In the NPM1 mutant cohort co-operating mutations were identified in 99% of patients, while at least one mutation was detected in 91% of the unselected cohort. Furthermore, quantification of variant allele frequencies allowed detailed analysis of mutational hierarchy and clonal evolution of relapse. The prevalence of mutations in candidate genes was also assessed, notably identifying mutations of MYC as recurring events in NPM1 mutant AML. Knowledge of AML genetics can also be applied post-treatment to track minimal residual disease (MRD) using molecular markers. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays were designed and optimised for rare fusion genes and NPM1 mutations. As a model, the NPM1 mutant RT-qPCR assays were used to track MRD in follow up samples from a large cohort of NPM1 mutant AML patients. These data identified a single MRD measurement in the blood following the second course of chemotherapy was the most informative outcome predictor, independent of mutational profile. It was also established that analysis of sequential samples could identify patients destined for relapse providing an opportunity for pre-emptive treatment. In the future a more personalised treatment approach, incorporating both mutational profiling and MRD monitoring, may improve patient outcome.

Background: Working memory (WM) refers to a system responsible for temporarily storing and manipulating information. It is recognised as having a key role in supporting children’s learning. Research has suggested that targeted interventions can lead to improvements in children’s WM capacity or strategies to increase its efficiency. Some interventions, largely computer-based but also practical, claim to address the needs of whole classes. There is relatively little research concerned with the implementation of such programmes as whole class interventions. Participants: Two Year 5 classes from separate schools received two WM interventions, MeeMo and Memory Booster. Six students from each class were selected to create two focus groups. Both class teachers also participated in the research. Methods: A mixed methods design was utilised, with an emphasis on qualitative data. Each class received a randomly allocated six week intervention implemented by the class teacher. Fidelity and dosage were monitored through the use of structured observations and an implementation diary completed by the class teachers. Two student focus groups and two semi-structured teacher interviews were conducted. The in-built monitoring provisions of each intervention were also investigated. Analysis/Findings: All qualitative data were transcribed verbatim and analysed using thematic analysis. Findings were presented as thematic maps, exploring the facilitators and barriers for implementation of each intervention. Quantitative data gathered through each interventions monitoring provision were analysed using descriptive statistics to inform discussion around the perceived outcomes. Conclusion/Implications: The study extends understanding of the context-specific implementation factors involved in using MeeMo and Memory Booster as whole class interventions and explores the utility of the monitoring provision of each intervention. A framework for effective implementation was developed and specific recommendations for both programme developers and school staff are provided.

This thesis is an investigation into the algebraic number-theoretical properties of certain polynomial invariants of graphs and matroids. The bulk of the work concerns chromatic polynomials of graphs, and was motivated by two conjectures proposed during a 2008 Newton Institute workshop on combinatorics and statistical mechanics. The first of these predicts that, given any algebraic integer, there is some natural number such that the sum of the two is the zero of a chromatic polynomial (chromatic root); the second that every positive integer multiple of a chromatic root is also a chromatic root. We compute general formulae for the chromatic polynomials of two large families of graphs, and use these to provide partial proofs of each of these conjectures. We also investigate certain correspondences between the abstract structure of graphs and the splitting fields of their chromatic polynomials. The final chapter concerns the much more general multivariate Tutte polynomials—or Potts model partition functions—of matroids. We give three separate proofs that the Galois group of every such polynomial is a direct product of symmetric groups, and conjecture that an analogous result holds for the classical bivariate Tutte polynomial.

Microzooplankton consume a significant fraction of phytoplankton and bacterioplankton production, remineralising macronutrients and providing a major trophic link to larger protozoan and metazoan consumers. Trace elements are essential for the growth of phytoplankton and bacteria and play a pivotal role in regulating primary productivity and microbial diversity in many areas of the ocean. To quantify the role of microzooplankton grazing in trace element biogeochemistry, we modified the dilution method to provide the first ever simultaneous measurements of microzooplankton grazing impacts on bacterioplankton and phytoplankton, and size fractionated biogenic particulate trace elements. In the Arctic Ocean we found microzooplankton obtained the majority of their nutrition (0.48 – 1.68 μg C L⁻¹ d⁻¹) from nanophytoplankton, on which they exerted a strong top down control (15 – 122% standing stock ingested). We subsequently applied our method in the North Atlantic Ocean. Microzooplankton grazing consumed a significant proportion of bacteria (97 – 165%) and particulate trace element standing stocks (0.4 fM d⁻¹ – 5 pM d⁻¹), thus playing a significant role in the flow of carbon and trace elements. Our results suggest the rate and quantity at which microzooplankton grazing mediates trace element biogeochemistry depends strongly on the structure and function of microbial assemblages. Iron enrichment assays supported the hypothesis that the high latitude North Atlantic is seasonally iron limited. Importantly, microzooplankton grazing had a significant effect in cropping expected iron stimulated biomass. Serendipitously we conducted assays in an area of ocean influenced by volcanic ash deposition from Eyjafjallajökull’s eruption. Our data are the first to quantify microzooplankton grazing in such an environment and revealed deposition of volcanic ash had significant short term local effects upon microbial ecology and carbon cycling. Results were analogous to iron enrichment assays and comparable to data from mesoscale iron enrichment experiments. Assays in a coastal environment showed microzooplankton played an important role in the control of bacterioplankton and cycling of carbon through the microbial food web. At all locations, ingestion rates of biogenic particulate trace elements suggest microzooplankton grazing has the potential to reduce the pressure of trace element deplete conditions at the microbial level by increasing residence times in the upper ocean through remineralisation. Our results provide important new parameterizations of trace element cycling that until now had been hypothesised but not observed. These data will allow us to better constrain biogeochemical models and those predicting the Ocean’s response to climate change and geoengineering. Likewise, the temporal and spatial nature of our data may allow the elucidation of inherent interannual and annual variability to enduring change at our study locations.

The Non-contact Atomic Force Microscope (NC-AFM) now offers the surface scientist the ability to resolve individual atoms on the surfaces of insulators. Atomically resolved NC-AFM images have now been demonstrated on insulating surfaces such as sodium chloride, calcium difluoride and nickel oxide, as well as many metallic and semi-conducting surfaces. However, in nearly all experiments the amount of information that can be extracted from these images alone is limited, and usually the identity of the resolved features is unknown. A great deal more information and understanding can be achieved if experimental data is combined with theoretical modelling of NC-AFM. A theoretical model was developed to reproduce the real NC-AFM tip-surface interactions and to simulate the behaviour of the oscillating cantilever under the influence of these interactions. A general study of the components of the tip-surface interaction has been performed, with special regard to the complex electrostatic interactions which are relevant to NC-AFM both at the microscopic and macroscopic scale. This study was used to produce a physical model of a NC-AFM tip which could be used in further modelling. In an attempt to characterize some of the important processes in NC-AFM, the model was first used to analyze the role of the tip, atomic relaxation and image forces in NC-AFM imaging. The model was then applied to NC-AFM imaging of the 1x1 reconstruction of the (110) surface of titanium dioxide, a classic benchmark in surface science. Theoretical scanlines of the surface compared well with experimental results, but it was found that image forces were important in imaging of TiO2. The model, including image forces, was then applied to two characteristic systems which have been atomically resolved in NC-AFM: (i) a thin film of NaCl on a copper substrate and (ii) the (111) surface of CaF2. In both cases the theoretical results compared well with experiment and extracted a lot more information about the tip, surface and tip-surface interactions than was previously available. In particular, for the first time in NC-AFM imaging of insulators, comparison of theory and experiment on the CaF2 surface allowed the sublattice imaged in experiments to be identified. Finally, the possibility of detecting the exchange force on a magnetic surface with a metal coated NC-AFM tip has been studied theoretically and compared with experimental results on the antiferromagnetic NiO (001) surface. The importance of theoretical modelling of NC-AFM in improving understanding of experimental results has been demonstrated. The model developed here has proved successful in simulating a wide variety of surfaces and interactions, and has greatly increased the amount of physical information available on the tip and surface structure, and tip-surface interactions compared to experiment alone.