Regulation of human brown adipose tissue activity

The rising prevalence of obesity globally poses significant morbidity and mortality, as obesity increases the risk of developing a number of diseases such as diabetes, hypertension and cardiovascular disease. While some more recent interventions to treat obesity have been efficacious, they can cause undesirable side effects, highlighting a need for novel treatment options. Adipose tissue comprises brown (BAT) and white adipose tissue (WAT). WAT mainly stores energy, while BAT increases energy expenditure primarily through cold-induced thermogenesis, which is mediated through a specialised thermogenic protein, called uncoupling protein 1 (UCP1). Due to its role in thermogenesis, BAT has gained significant interest as a target to treat obesity and associated cardiometabolic disease. 2-deoxy-2- [¹⁸F]fluoro-D-glucose (¹⁸F-FDG) positron emission tomography (PET) is the most commonly used technique to quantify human BAT mass and activity, exploiting the substantial glucose uptake by BAT as a surrogate marker for BAT thermogenesis. The prevalence of detectable BAT at room temperature using ¹⁸F-FDG PET is reduced in individuals with increased cardiovascular risk such as obesity, diabetes and hypertension. However, ¹⁸F-FDG uptake by BAT may be confounded by obesity-induced insulin resistance so it remains unclear whether BAT thermogenesis is decreased in obesity and cardiometabolic disease. Our understanding of the regulation of human BAT activation also remains limited. Using transcriptomics, we recently identified serotonin as a potential regulator of human BAT, by demonstrating that the gene SLC6A4, which encodes the serotonin reuptake transporter (SERT), was one of the most differentially expressed genes in human brown compared with white adipocytes. SERT inhibition, which increases serotonin receptor activation, decreased human brown adipocyte thermogenesis. However, it is unknown whether serotonin levels are altered in obesity or if reduction in peripheral serotonin activity can lead to a therapeutic benefit. We hypothesised that (1) UCP1 expression in human BAT, a marker of BAT thermogenic capacity, is inversely associated with cardiovascular risk factors, (2) circulating and adipose tissue serotonin levels are increased in obesity and (3) inhibition of peripheral serotonin synthesis stimulates human BAT activity. To assess hypothesis 1, we measured UCP1 mRNA expression in whole adipose tissue (n=53) and in differentiated pre-adipocytes (n=85) from paired BAT and WAT biopsy samples obtained from patients undergoing elective neck surgery. UCP1 expression in BAT (but not in WAT or in differentiated brown or white pre-adipocytes) was inversely associated with obesity, ageing, insulin resistance and hypertension. Age was the only independent predictor of high UCP1 expression in BAT and obesity reduced the frequency of high UCP1 expression only in individuals >40 years. To explore the effect of obesity in young adults in vivo, ¹⁸F-FDG PET-MR scans were performed in young obese and age-matched normal weight individuals (n=6 in each weight group, mean age ~22 years) following 2 hours of mild cold exposure. Consistent with the UCP1 data, young individuals with obesity had preserved ¹⁸F-FDG uptake by BAT, despite increased insulin resistance. To determine if obesity alters peripheral serotonin levels, we measured circulating and abdominal adipose tissue serotonin concentrations in healthy age-matched individuals with normal body weight and obesity (n=10 in each weight group) during warm and cold exposure. The majority of circulating serotonin is inactive due to being platelet-bound with only a small proportion circulating freely. Platelet serotonin concentrations increased during cold exposure in normal weight individuals. However, in obese volunteers, inactive platelet serotonin levels increased during warm conditions, which dropped during cold exposure, accompanied by an increase in adipose tissue serotonin levels. These variations in serotonin concentrations suggest a potential dysregulation in cold-induced serotonin response in obesity. To assess whether inhibition of peripheral serotonin synthesis altered BAT activity, we undertook a double-blind crossover study in 8 healthy normal weight subjects and 8 participants with obesity. These volunteers were given placebo and telotristat ethyl tablets (an inhibitor of peripheral serotonin synthesis) for 2 weeks in random order. Telotristat ethyl reduced ¹⁸F-FDG uptake by BAT, increased total cholesterol levels and suppressed the rise in noradrenaline and insulin levels following cold exposure and oral glucose load respectively. In conclusion, UCP1 expression in BAT is reduced with ageing, obesity and cardiometabolic disease, in keeping with BAT dysfunctio

Development and application of cell culture and genome editing techniques in Pacific whiteleg shrimp (Litopenaeus vannamei) and Atlantic salmon (Salmo salar)

[ A B S T R A C T : R e d a c t e d

Germline influences on processes that contribute to colorectal carcinogenesis

Colorectal cancer (CRC) is one of the most common causes of cancer-related death in the world with incidence rising particularly in younger individuals in the West. Understanding of the genetic causes underlying CRC has increased greatly in recent years as a result of work on familial CRC syndromes, which has identified rarer but more impactful genetic mutations, and CRC genome-wide association studies (GWAS), which have identified more common forms of DNA variation. The common variants from CRC GWAS are less impactful individually but when combined have a non-trivial effect on CRC risk. However, there are still many gaps of knowledge in terms of CRC genetics, with one notable example being the mechanisms through which variants are affecting CRC risk. This project aimed to contribute to this area by first expanding the existing GWAS meta-analysis dataset through the addition of 2,356 CRC patients and 14,162 CRC-free control patients from the 100,000 Genomes Project (100kGP). Inclusion of 100kGP data led to the identification of eight novel CRC risk loci but also called into question six previously identified loci. This modest net gain of CRC risk loci indicates that substantial expansion of GWAS cohorts (perhaps the addition of > 100,000 patients) may be needed for meaningful improvements in understanding common causes of CRC. Several risk loci identified by CRC GWAS highlight genomic regions where the target gene may not be affecting CRC predisposition through effects on the colorectal epithelium, but instead via an intermediate phenotype. The project explored two of these potential intermediate phenotypes: blood cell traits and the microbiome. For blood cell traits, genetic fine-mapping of a locus at 12q24.12 was first conducted to identify whether pan-haematopoietic regulator SH2B3 was the CRC causal risk gene, but these results were not conclusive. Work was then expanded to examine the phenotype generally, initially by using Mendelian randomisation (MR) to establish whether causal links existed between blood cell trait variation and CRC risk. A modified PCA-based GWAS and MR approach was then used to try and mitigate the high levels of horizontal pleiotropy that are apparent in haematopoietic genetics. These results showed indications of red blood cell and platelet variation affecting CRC risk but were not definitive and require further investigation. For the microbiome, fine-mapping was conducted on four risk loci, where the possible CRC causal genes (GALNT12, B3GNT8, FUT2, FUT3, and FUT6) play roles in oligosaccharide modification processes such as glycosylation and fucosylation in the colon, thereby potentially affecting susceptibility to microbial infections and subsequent CRC risk. The previous study of rare variants in GALNT12 specifically has raised the question as to whether it is a moderate CRC risk gene; this hypothesis was tested using the larger 100kGP cohort, which suggested that it is not a moderate risk gene, and then expanded to include the other four potential microbiome CRC genes. Once again, work was then extended from individual loci to the overall mechanism. First, MR was conducted using reported variants from existing microbiome association studies performed in disease-free individuals to test whether there are causal links between levels of bacterial taxa and CRC risk. This analysis suggested that variation in the Escherichia/Shigella, Fusobacterium, Streptococcus, and Bifidobacterium genera may be causal for CRC risk. A new complementary approach running GWAS in CRC patients specifically using the 100kGP cohort was performed, with relative abundance of bacterial genera and species, counts from toxin-producing bacterial strains, as well as global bacterial measures taken from the tumour directly used as phenotypes. Variants identified from these GWAS were then used in MR analyses to see whether causality between bacterial measures derived from CRC patients and CRC risk could be established. This analysis instead suggested causal associations for Oscillibacter and Blautia genera, Bacteroides fragilis and Ruminococcus faecis species, and bacterial count per human cell. In summary, this project has contributed to the understanding of the genetics of CRC carcinogenesis using methods that are, in large part, based on the intrinsic robustness of genetic data. The challenges encountered in this project are common in the field, namely (i) the weakness of most genetic associations with both CRC and its risk factors and (ii) confounding and pleiotropic effects of genes and other unobserved factors. My work provides insight into common genetic variation in CRC, as well as interesting clues for the role of blood cell levels and gut bacteria in CRC risk

Investigating structural variants of BRCA1/2 as a novel biomarker of homologous recombination deficiency

Homologous recombination deficiency (HRD) represents a cancer vulnerability that has been successfully exploited through the use of PARP inhibitors by synthetic lethality. In high grade serous ovarian cancer (HGSOC), PARP inhibitors, such as olaparib, have revolutionised treatments outcomes for patients and are now routinely clinically used. PARP inhibitors are also approved for breast, pancreatic and prostate cancer, but their use is largely restricted to patients with a BRCA1/2 mutation. Though BRCA1/2 mutations are the archetypal event resulting in HRD, there is increasing evidence that there are patients with an HRD phenotype beyond those with a BRCA1/2 mutation. This therefore represents an opportunity to broaden the use of PARP inhibitors, including their use in other tumour types. Structural variants (SVs) are increasingly recognised as key cancer driver events. However, their importance has been underappreciated due to limited access to whole genome sequencing (WGS). Previously, SVs of BRCA1/2 were found to occur in ~15% of HGSOC cases, and were associated with reduced BRCA1/2 gene expression and higher genomic HRD scores. Furthermore, BRCA1/2 SVs have been shown to occur in a range of other tumour types, at a lower frequency. Despite the existing evidence supporting the importance of BRCA1/2 SVs in tumourigenesis, their functional impact has not been directly studied in vitro, including via functional homologous recombination (HR) assays. Moreover, the phenotype associated with this defect has not been explored in a range of different tumour types. Through in silico analysis, a provisional panel of candidate cell lines with BRCA1 or BRCA2 copy number loss were identified. These underwent detailed characterisation of existing genomic data, along with validation of copy number loss by quantitative PCR (qPCR). This resulted in a high confidence panel of candidate cell lines (n=11) from multiple tumour sites (ovary, breast, soft tissue sarcoma and bone sarcoma) with copy number loss of BRCA1 or BRCA2, which are likely to have BRCA1/2 SV deletions. These were investigated alongside known HR deficient comparator lines and an HR proficient cell line. The phenotype of these candidate cell lines was assessed, which included BRCA1/2 gene expression, BRCA1/2 protein expression and HR status by RAD51 immunofluorescence following irradiation. Drug sensitivity to chemotherapeutics and PARP inhibitors (olaparib, novel PARP1 selective PARP inhibitor AZD5305) was also performed via proliferation assay and colony formation assay. In the cell lines with BRCA1 SVs, two of the seven cell lines demonstrated a low BRCA1 gene expression (comparable to the BRCA1 mutant comparator), HR deficiency by RAD51 immunofluorescence and PARP inhibitor sensitivity. These were both Ewing’s sarcoma cell lines. There were a further two cell lines with BRCA1 SVs, originating from a breast and an ovarian tumour, that were functionally HR deficient, but did not demonstrate PARP inhibitor sensitivity. Four of the five cell lines with BRCA2 SVs had reduced BRCA2 gene expression (similar to that of a known BRCA2 mutant cell line). Furthermore, four of the five cell lines with BRCA2 SVs were functionally HR deficient and three of these cell lines were PARP inhibitor sensitive. These cell lines originated from varying tumour sites including ovary and two histological types of soft tissue sarcoma (leiomyosarcoma, rhabdomyosarcoma). These data suggest SVs, particularly in BRCA2, may represent a novel biomarker of HRD, which could be therapeutically exploitable with PARP inhibitors. Given that PARP inhibitors are not used routinely in sarcomas, this could represent a new therapeutic indication. This in vitro work therefore suggested that the accurate identification of BRCA1/2 SVs via copy number loss could have high clinical utility in identifying patients suitable for PARP inhibitors. With this in mind, the final chapter of this body of work aimed to identify a simple costeffective laboratory test to identify these defects. It was hypothesised that qPCR could be an efficient laboratory biomarker assay for detecting SVs. This work assessed the sensitivity and specificity of qPCR in detecting copy number variation of BRCA1/2, in two HGSOC clinical cohorts (cohort 1 n=355, cohort 2 n=89), in conjunction with matched next generation sequencing (cohort 1 panel sequencing, cohort 2 WGS). This work demonstrated qPCR had poor sensitivity for detecting BRCA1/2 SVs, with copy number variation at the reference probe erroneously leading to BRCA1/2 copy number loss detection. Overall, this suggests that next generation sequencing, such as WGS, remains the optimal method for accurately detecting these events

The four paws of robotics: designing a zoomorphic robot for animal welfare education

This doctoral thesis investigates the design of a zoomorphic robot for animal welfare education with children. Animal welfare education can cultivate positive attitudes and behaviours towards animals, thereby promoting positive, safe child-animal interactions and enabling children to experience the many benefits of human-animal relationships. Zoomorphic robots (robots that are animal-like in appearance and behaviour) are promising tools for animal welfare education because children engage with them somewhat like live animals and their interactivity could make interventions more engaging and effective. Since animal welfare education is a novel application domain, the thesis encompasses work to investigate children's perceptions of zoomorphic robots and how to design a zoomorphic robot that is suitable for animal welfare education. First, we aimed to better understand children's attitudes towards and beliefs about a zoomorphic robot, focusing on how small behaviours that implied the robot could feel emotions, like tail wagging, affected their opinions. The findings indicate that these subtle behaviours can influence children's beliefs about a zoomorphic robot. Subsequently, we invited end-users, namely animal welfare educators and schoolchildren, to co-design concepts for a zoomorphic robot for animal welfare education. We aimed to understand what children perceived as important features of pets and what animal welfare educators needed to teach children about safe, appropriate behaviour around pets. From this work, we identify several points of convergence and divergence in design requirements between the two groups, present guidelines for the design of educational pet robots that are applicable beyond animal welfare education, and challenge the widespread emphasis on cuteness in zoomorphic robots. Finally, we created a new design for a zoomorphic robot, implemented it by customising an existing platform, and developed an educational intervention focusing on dogs' emotions and welfare needs and responsible dog ownership. Evaluation in schools showed that the intervention improved children's knowledge and beliefs about dogs. While the zoomorphic robot did not significantly outperform a stuffed toy in terms of learning outcomes, children's experience of the intervention was better, highlighting the potential for robots to enrich animal welfare education in the future. This thesis contributes new insights into children's interactions with zoomorphic robots, design ideas for zoomorphic robots and educational robots, methodologies for eliciting these ideas from children and educators, and a prototyped and evaluated system that can support animal welfare education

Are anonymised datasets from clinical trials truly anonymous?

BACKGROUND: Funders, regulators and publishers are increasingly requesting that clinical trial researchers share their research data with others, once the primary analysis has been completed. Existing clinical trial data could significantly contribute to expanding medical and scientific knowledge by investigating questions beyond the original study scope, facilitating individual participant data (IPD) meta-analysis, verifying results, and exploring novel methodologies for data analysis. Anonymisation of IPD before sharing can offer a way to safeguard participants' privacy. While there are several recommendations and guidance available for attempting data anonymisation prior to sharing, completely anonymising data while keeping it usable remains challenging. Moreover, many anonymised datasets are already publicly available for secondary research. However, it remains unclear whether study participants could potentially be at risk of re-identification, and under what circumstances re-identification is more likely to occur. METHODS: In the first phase of this PhD research, a systematic scoping review was conducted to gather publications that reported recommendations on anonymisation for enabling data sharing from clinical trials, to understand what guidance was available to researchers and how publicly available anonymised datasets from clinical trials might have been compiled. Two reviewers, Aryelly Rodriguez with Chris Tuck or Alastair Murray independently assessed titles, abstracts, and full texts for eligibility. One reviewer extracted data from selected papers using thematic synthesis, which was then reviewed by a second reviewer for accuracy. Results were summarised through narrative analysis. Moving on to the second phase, I collected a broad selection of publicly available anonymised datasets that have been made available for research purposes extending beyond their original scope, to explore the characteristics of these anonymised datasets, assess the feasibility of applying re-identification risk scores to them, and determine how these scores could be useful. I estimated their re-identification risk scores with three equations designed for calculation of such scores based on the information in the entire dataset. These equations are commonly applied to routinely collected health records and only generate numerical values ranging from 0 (lowest risk) to 1 (maximum risk), without attempting to re-identify individuals within the datasets. Subsequently, I calculated the re-identification risk scores for each dataset, using the three equations. This analysis explored the characteristics of the datasets associated with increased or decreased risk scores, and compared the risk scores to evaluate their practicality for implementation. In the third and final phase of this PhD research, I used an online exploratory cross-sectional descriptive survey that consisted of both open-ended and closed questions to gather the UK researchers’ views regarding their experiences with the de-identification, anonymisation, release methods and re-identification risk estimation for clinical trials datasets. RESULTS: The systematic scoping review identified 59 eligible articles (from 43 studies) for inclusion. From these articles, three distinct themes emerged: anonymisation, de-identification and pseudonymisation. The articles also showed that the most commonly recommended anonymisation techniques are removal of direct participant identifiers, and the careful evaluation and modification of indirect identifiers to minimise the risk of identification. Anonymisation of datasets in conjunction with controlled access was the most recommended method for data sharing. For the next phase, I contacted data holders and followed their local procedures to access the anonymised datasets. I identified 86 potentially eligible datasets from 18 repositories and successfully secured 76 of them. After full evaluation, 70 datasets met the inclusion criteria and were included in the analysis, representing 14 out of the 18 repositories. Thirty-one datasets were shared with minimal restrictions (open access), while 39 were shared with varying levels of restrictions before access was granted (controlled access). Datasets had, on average, four identifiers and mean risk scores ranging from 0.47 to 0.91. The most common pieces of information present in the datasets that, when combined, may indirectly identify a participant were sex (80%) and age (72.9%). For the final phase, the exploratory survey had 38 responses to invitation from June 2022 to October 2022. Thirty-five participants (92%) used internal documentation, institutional standard operating procedures and/or published guidance to de-identify/anonymise clinical trials datasets. De-identification followed by anonymisation and then fulfilling data holders’ requirements before access was granted (controlled access) was the most common process for releasing the datasets as reported by 18 (47%) participants. Eleven participants (29%) had previous knowledge of re-identification risk estimation but had not used this. Experiences in the process of de-identifying/anonymising the datasets and maintaining such datasets were mostly negative, the main reported issues were lack of resources, guidance, and training. CONCLUSIONS: There is no single standardised set of recommendations on how to anonymise clinical trial datasets for sharing. However, the systematic scoping review showed a developing consensus on techniques used to achieve anonymisation. Researchers in clinical trials still consider that anonymisation techniques by themselves are insufficient to protect participant privacy, and they need to be paired with controlled access. The second phase of this research confirmed that clinical trial datasets are very rich in personal details and using re-identification risk scores as a measure of this richness is feasible. These scores could inform the anonymisation process of clinical trials datasets to release them for secondary research. We proposed a strategy for incorporating these scores into the decision-making process for releasing clinical trials datasets. Finally, the majority of responders to the survey reported using documented processes for de-identification and anonymisation. However, our survey results clearly indicate that there are still gaps in the areas of guidance, resources and training to fulfil sharing requests of de-identified/anonymised datasets, and that re-identification risk estimation is an underdeveloped area. This work will be of interest to the clinical trials research community, funders and publishers seeking to improve the process of anonymisation and foster data sharing

Dissecting the genomic and epigenomic alterations underlying glioblastoma

Glioblastoma (GBM) is the most common intrinsic primary brain tumour, characterised by structural complexity, tumoural heterogeneity and poor prognosis. GBM tumours reactivate neurodevelopmental programmes and they are driven by GBM stem-like cells (GSCs), displaying phenotypic similarities to neural stem cells (NSCs). Although much is known about the recurrent coding alterations and the role of GSCs in GBM, we still have a poor understanding of the contribution of non-coding alterations and complex structural variants (SVs) to GBM pathogenesis, as well as the role of key NSC transcription factors such as SOX2 and SOX9, in regulating self-renewal activity in GSCs and gliomagenesis. To study non-coding alterations and complex SVs, we compiled a large (n = 230) cohort of GBM tumours with whole genome sequencing data. We uncovered a lack of recurrent non-coding somatic small mutations (SSMs) apart from TERT promoter mutations. We identified loci under putative selection for SV recurrence, including those harbouring focal amplications and deletions, associated with complex SVs such as extrachromosomal DNA (ecDNA) and chromothripsis. We discovered underappreciated features of ecDNAs in GBM, including a high prevalence of ecDNAs generated via episomal exclusion, and uncovered the extent by which ecDNAs shape tumoural heterogeneity via seismic amplification and putative chromosomal re-integration. Notably, despite the relatively high SSM- and SV-derived neoantigen burdens, ecDNA+ samples exhibited higher transcriptional immune suppression compared to ecDNA- samples, an effect not seen in other complex SV types, suggesting that ecDNAs may modulate the tumour-immune microenvironment to evade immune clearance. Last, contrary to our expectations, ecDNA and chromothripsis were not associated with poor overall survival; rather, patients whose GBMs sustained high levels of overall complex SV burden were associated with significantly shorter overall survival, independent of other available prognostic factors. To complement these genomic analyses, we also explored transcriptional regulatory programs in GBM, particularly the role of SOX2 and SOX9 in regulating GSC self-renewal. We used chromatin immunoprecipitation followed by sequencing (ChIP-seq) data across 7 patient-derived GSCs. We found that SOX9 binds exclusively and at close proximity to SOX2, and co-bound SOX2/SOX9 sites are enriched with GSC-specific super-enhancers (SEs). We identified a dual-mode of SOX2/SOX9 co-binding that was regulatory element-dependent – as a monomer at promoters and a dimer at enhancers, reminiscent of SOX9 activity in cartilage development. Co-bound SOX2/SOX9 SEs target genes regulating NSC identity, including QKI, PTPRZ1 and CDK6. Intriguingly, SOX2/SOX9 co-binding also target their own and each other’s regulatory regions, suggesting the existence of an auto- and cross-regulatory feed-forward axis. Importantly, we observed no increased in mutational burden across SOX2/SOX9 co-binding sites, arguing against mutation-driven reactivation processes at these neurodevelopmental enhancers. These findings altogether suggest that SOX2 and SOX9 cooperate at shared enhancers and target genes, and their increased co-activity may contribute to the core programs of self-renewal displayed by GSCs. In summary, we present a thorough computational genomic analysis of the non-coding alterations and structural complexity shaping the GBM genome, revealing a complex interplay between ecDNA, immune evasion pathways and complex SV burden during gliomagenesis. Furthermore, we identify putative downstream targets of SOX2 and SOX9 that may underlie self-renewal activity in GSCs. It is hoped that these findings may lead to an increased understanding of GBM pathogenesis and ultimately result in new therapeutic avenues for GBM patients

Quantifying climatic, lithological and tectonic drivers on topography

Mountain ranges and fluvial landforms are shaped by a competition of natural forcings: tectonic forcings provide the uplift that causes mountains to grow, and rivers erode them down by downcutting into the bedrock material. Climate forcings, such as precipitation, vegetation or temperature favour or hinder erosional processes, and the lithological composition controls how these forcings are recorded on the landscape. As geomorphologists, we are only able to work with current topography, through field observations or digital elevation models. Much of the existing work in geomorphology has focused on creating metrics that allow us to quantify the imprint of tectonic, climatic and lithological signals from landscapes. One of the first formulations relating erosion and uplift incorporates a direct relation with the channel steepness and the amount by which this steepening occurs. This thesis focuses on quantifying these factors to detect areas of river channels and hillslopes that show an active uplift, sudden changes in lithology or a change in erosion rates due to climatic differences, through deviations from their steady state behaviour. I start by exploring how a climate signal is recorded on the landscape, and whether it is possible to detect such a signal through a form of the stream power law that includes discharge instead of drainage area. I set up a range of numerical simulations with a rainfall gradient component from which I calculate the optimal concavity index (θ), the χ profiles and the disorder of each river basin. In a landscape with uniform lithology, it is possible to identify simulation runs with a rainfall gradient using the disorder metric. However, when heterogenous lithology is introduced, this signal becomes clouded. I test this method in eight natural landscapes with rainfall gradients and find that, similarly to the simulations with heterogenous lithology, it is not possible to distinguish between drainage-area-driven and discharge-driven incision using the disorder method. Nonetheless, I can quantify the distortion introduced on the channel steepness index (ksn) when using different erosion rules. The next research question explores the role of lithology in landscapes through its effects on drainage divide migration. Most drainage divides are located in the centre of mountain ranges. However, using a simple formulation of the stream power law, I find that a small difference in rock erodibility should theoretically lead to larger drainage divide asymmetries. I explore this discrepancy through a combination of analytical solutions and numerical simulations based on Hack's law and the stream power law. I quantify the difference in basin sizes expected due to a lithological step change offset from the centre of an initially symmetrical drainage divide. I expand on this with a set of numerical simulations, including a 3D lithology component where I study the role of rock erodibilities as well as the location and orientation of rock layers in the motion of the drainage divide. I find that the angle of the rock layers and the overall landscape erodibility largely control the position of the divide. I conclude this study with the comparison of the analytical and numerical solutions to the Sierra Alhamilla, an asymmetric mountain range with heterogenous lithology in south-eastern Spain. The final part of this thesis explores the interactions between fluvial and hillslope processes. Hillslopes have been found to record tectonic signals propagating up channel tributaries in the form of knickpoints, with a lag in the response time. I choose a landscape with active tectonics, the South Fork Eel River in California, USA, to explore this transient hilltop signal. The analysis toolkit to perform an exploration of hillslopes is based on different laws from fluvial incision, where the steady-state condition is defined based on the physical parameters of the hillslopes and soils, such as the hilltop curvature, hillslope length, relief, slope angle, and soil transport and density parameters. I extract these parameters from a 3 m digital elevation model of the study site and explore the hypothesised hillslope response lag with respect to the transient fluvial signal, recorded through changes in channel steepness, ksn. In summary, this thesis explores the signature of climatic, lithological and tectonic signals on landscapes. I discuss under what circumstances these signals can be detected, and propose new approaches to quantifying their effect on landscapes through a combination of analytical, numerical and topographic methods

Curvature statistics of turbulence

Turbulence is present in many different flow types across natural phenomena and industrial applications but still raises open questions due to its complexity and multi-scale nature which defers most direct analytical approaches. However, a statistical approach has proven itself as a powerful tool to help with the understanding and modelling of turbulence, overcoming some limitations of analytical approaches. Within this thesis, I analyse datasets of four different flow types, three of experimental nature and one of numerical nature to study the statistics of geometric quantities such as curvature and torsion, in particular concerning the effect of anisotropy. For the experimental datasets, the focus is on Lagrangian trajectories and for the numerical datasets on stream lines and, in case of a conducting fluid, magnetic field lines. These curves can be described as three-dimensional space curves and therefore curvature and torsion can give a full description of these. Curvature and torsion are particularly interesting measures of turbulence as a salient feature of turbulence is the presence of different spatial and temporal scales, which is captured by the different derivatives involved. The curvature vector is introduced as a new measure of the effect of anisotropies, originating from different mechanisms like a temperature gradient, mean flow or magnetic background field, on the geometry of Lagrangian trajectories and either stream lines or, in case of a conducting fluid, magnetic field lines. The first study includes Lagrangian experimental datasets of a turbulent von Kármán flow, Rayleigh-Bénard convection at two different Rayleigh numbers and the logarithmic layer of a turbulent zero-pressure-gradient boundary layer over a flat plate. The curvature and torsion statistics of von Kármán flow and Rayleigh-Bénard convection agree well with previously reported experimental and numerical results for the curvature and with numerical simulations of homogeneous and isotropic turbulence for the torsion. For the logarithmic region of the boundary layer, the form of the torsion probability density function (PDF) also agrees with these results. The curvature PDF retains the same heavy tail as curvature PDFs measured for the aforementioned flow types for small curvature events, however, high curvature events are suppressed by the mean flow. Studying the curvature vector and connecting it with velocity fluctuations shows the effect of anisotropy and allows a geometric interpretation of large-scale motion in terms of the structure of trajectories. In the second study, another type of anisotropy is introduced by a magnetic background field for a flow with electrically conducting fluid in magnetohydrodynamic turbulence. Utilising high resolution data obtained by direct numerical simulation of magnetohydrodynamic turbulence across a range of Reynolds numbers, the curvature PDFs of stream lines and magnetic field lines compare well with the PDFs derived based on Gaussian statistics for the Lagrangian trajectories. For the PDFs of the curvature vector components, the magnetic field lines tend to be less curved in the direction of the magnetic background field, which can be connected to the suppression of magnetic field fluctuations parallel to the magnetic background field and the partial two-dimensionalisation of the flow. The curvature vector PDFs of stream lines show that the effect of a magnetic background field on the geometry of stream lines is less profound compared to the effect on the magnetic field lines. The models mentioned above are based on Gaussian statistics. However, turbulence is more complex and intermittency plays a crucial role. As an improvement of these models, a model for the curvature PDF for von Kármán flow and Rayleigh-Bénard convection is derived, which takes spatio-temporal intermittency into account. Using a decomposition into Gaussian sub-ensembles, where within each the curvature PDF is known exactly, an exact model expression and a closed-form approximation for the curvature PDF can be derived. These PDFs agree qualitatively and quantitatively with the measured curvature PDFs of turbulent von Kármán flow and Rayleigh-Bénard convection

Predicting CO₂ migration in the shallow subsurface: the role of heterogeneity and mass transfer

Carbon capture and storage (CCS) is an important technology for the net-zero transition. The success of CCS relies on the security of storage, as unintended release of CO₂ from a storage site can impact water resources, release stored CO₂ to atmosphere and reduce the value of carbon credits associated with storage. Given the potential impacts, robust monitoring techniques are required, supported by a deep understanding of the complexities of CO₂ migration in the shallow subsurface. The objective of this research is to better understand the impacts of subsurface heterogeneity and multicomponent mass transfer on the fate and migration of CO₂ using numerical models. Simulations of a bench-scale CO₂ injection in saturated homogeneous sand were conducted using a coupled continuum-discrete approach using the Electrothermal Macroscopic Invasion Percolation (ET-MIP) model. ET-MIP was shown to accurately describe the experimental gas velocity, aqueous plume height and gas fingering behaviour, and demonstrated that multicomponent mass transfer impacts the persistence, distribution and development of the gas phase. A sensitivity study was conducted, and demonstrated that gas velocity and distribution were sensitive to the critical gas saturation and grid size. A binary tree algorithm was implemented for MIP including gas channel fragmentation and mobilization (MIP-FM) to improve performance of ET-MIP. The new algorithm showed a 76% decrease in overall run time when implemented in ET-MIP, and enables the use of ET-MIP in larger domains. Gas migration in realistic 3D sedimentary structures was simulated to understand the impact of cm-scale heterogeneities. Realistic sedimentary structures with cm-scale bedding and lamina were generated stochastically with varied entry pressure characteristics, and gas migration was simulated using MIP. The ensemble of gas migration results was analyzed and it was established that increased grain size contrast between the bedding and lamina (a function of both grain size and grain sorting of both materials) causes a transition from ganglia-dominated flow to pool-dominated flow and enhanced lateral migration from the source. These results highlight the challenges in gas migration monitoring, as small variations in heterogeneity can significantly alter gas migration pathways. Lastly, the effects of subscale heterogeneity, groundwater flow and gas composition on gas migration were investigated by simulating CO₂ and noble gas mixtures in heterogeneous domains with varied aqueous flow rates. Results showed that both heterogeneity and aqueous flow rate can influence the vertical migration of CO₂, as a significant portion of the CO₂ will dissolve. Additionally, dissolved noble gas ratios were shown to be sensitive to multicomponent mass transfer during injection and post-injection, as less soluble noble gases such as He will preferentially partition to the gaseous phase. The results of this thesis highlight the complexity of CO₂ migration in the shallow subsurface. Subscale heterogeneity can impact gas distribution, dissolution, and cause extensive lateral migration. Multicomponent mass transfer can impact the evolution of dissolved gas concentrations including noble gas ratios, and the persistence of gas in the subsurface. Ultimately, this research will help to improve monitoring and verification of CCS, through advancements in numerical modelling techniques and data interpretation. These findings extend beyond CCS, and can be applied to other fields of research including methane or hydrogen leakage and groundwater remediation techniques such as air-sparging or in-situ thermal remediation