Permeability evolution across carbonate hosted normal fault zones

Acknowledgements: The authors would like to thank Total E&P and BG Group for project funding and support, and the Industry Technology Facilitator for facilitating the collaborative development (grant number 3322PSD). The authors would also like to express their gratitude to the Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Raymi Castilla (Total E&P), Fabrizio Agosta and Cathy Hollis are also thanked for their constructive comments and suggestions to improve the standard of this manuscript as are John Still and Colin Taylor (University of Aberdeen) for technical assistance in the laboratory. Piero Gianolla is thanked for his editorial handling of the manuscript.Peer reviewedPostprin

Impact of genetic and environmental risk factors for schizophrenia on cortical brain structure

It is now accepted that Schizophrenia, a neurodevelopmental disorder which affects around 1% of the population, is influenced by both genetic and environmental risk factors. Schizophrenia is evidenced as being heritable with twin-heritability estimates of around 80%. Recently, the disorder has been demonstrated to be polygenic in nature; many genetic variants with individually small effects contribute to the overall phenotypic variation. Furthermore, cannabis use, adverse events, urbanicity, obstetric complications and migration, are five environmental risk factors that have been evidenced as being associated with an increased risk of developing the disorder. Abnormalities in brain structure are also well evidenced in individuals with schizophrenia, in particular, reduced cortical thickness, volume and surface area have been linked to those with schizophrenia when compared to healthy controls. It has been posited that these cortical alterations may predate disorder onset, for example, disruptions in brain development may be a function of experiencing schizophrenia-associated genetic and environmental risk factors. However, the link between genes, environment and brain structure within schizophrenia remains unclear. In this thesis, we aimed to examine whether genetic and environmental risk factors for schizophrenia directly impact cortical brain structure. Methods and Results The current aims were assessed using measures of cortical thickness, volume and surface area, as defined by FreeSurfer, in three separate studies. Firstly, ANCOVA models were applied to a case-control sample, the Scottish Family Mental Health (SFMH) study, ncontrols/npatients = 41/58) to determine whether PolyGenic Risk Scores for Schizophrenia (PGRS-SCZ) are associated with lower cortical thickness both globally and within regions of interest (frontal and temporal lobes) as well as to examine whether the effects of experiencing an accumulation of the five environmental risk factors (outlined above) is associated with greater cortical thinning (Chapter Two). The results indicated that an increased PGRS-SCZ was related to lower, global cortical thickness in the whole sample and not a result of group differences. With regards to environmental effects, the more environmental risk factors experienced, the lower the cortical thickness, this was specific to the temporal lobe. Secondly, to further investigate the link between environmental risk factors of schizophrenia, we focused on birth weight as a proxy for obstetric complications (Chapter Three). Linear mixed effects regression (LME) models were used to assess whether birth weight was associated with cortical thickness, surface area and volume in a UK Biobank (UKB) sample (n = 1,680). We then applied Mendelian Randomisation (MR) to determine if birth weight-associated genetic variants were causally related to cortical structure. The results in this chapter suggested that higher weight at birth was associated with larger cortical volumes and surface area, both globally and in several cortical sub-regions. In contrast, a negative association was found between birth weight and cortical thickness in the lateral occipital parcel. MR analysis suggested a causal link of birth weight, as indexed by genetic variants, and insular lobe cortical volume as well as surface area globally, in the insular lobe and in middle temporal, medial orbitofrontal and inferior frontal gyrus parcels. Lastly, we tested whether the same association between PGRS-SCZ and cortical thickness (outlined in Chapter Two) could be replicated within a subset of UKB (Chapter Four). For this, we again utilised LME models using the second genetic data release of UKB (n = 2,864). We tested this globally, lobarly and within 27 bilateral cortical parcels for each of these parameters. We found a higher PGRS-SCZ to be associated with lower global cortical volume and thickness as well as insular lobe cortical thickness. To further test potential environmental influences (as outlined in Chapter Three) on these effects, we used a liner regression model to test for a relationship between PGRS-SCZ and birth weight as well as LME models to test for interactional effects. No relationship was found between PGRS-SCZ and birth weight nor were there any significant interactions found between PGRS-SCZ and birth weight on cortical structure Conclusion Together, these studies highlight the fact that both genetic and environmental risk factors for schizophrenia may, indeed, directly but differentially impact cortical brain structure. This information may help us to further understand the progression of the disorder but also, by identifying and addressing these risk factors early, we may be able to minimise the impact that the disorder can have on cortical brain structure; particularly in relation to potentially modifiable factors, such as birth weight. We also highlight the importance of using large samples and replications in order to examine such relationships

Understanding the impact of apathy in people with dementia on formal carers within residential settings

Abstract available at each chapter

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)

A Novel High-Throughput Assay for Islet Respiration Reveals Uncoupling of Rodent and Human Islets

The pancreatic beta cell is unique in its response to nutrient by increased fuel oxidation. Recent studies have demonstrated that oxygen consumption rate (OCR) may be a valuable predictor of islet quality and long term nutrient responsiveness. To date, high-throughput and user-friendly assays for islet respiration are lacking. The aim of this study was to develop such an assay and to examine bioenergetic efficiency of rodent and human islets.The XF24 respirometer platform was adapted to islets by the development of a 24-well plate specifically designed to confine islets. The islet plate generated data with low inter-well variability and enabled stable measurement of oxygen consumption for hours. The F1F0 ATP synthase blocker oligomycin was used to assess uncoupling while rotenone together with myxothiazol/antimycin was used to measure the level of non-mitochondrial respiration. The use of oligomycin in islets was validated by reversing its effect in the presence of the uncoupler FCCP. Respiratory leak averaged to 59% and 49% of basal OCR in islets from C57Bl6/J and FVB/N mice, respectively. In comparison, respiratory leak of INS-1 cells and C2C12 myotubes was measured to 38% and 23% respectively. Islets from a cohort of human donors showed a respiratory leak of 38%, significantly lower than mouse islets.The assay for islet respiration presented here provides a novel tool that can be used to study islet mitochondrial function in a relatively high-throughput manner. The data obtained in this study shows that rodent islets are less bioenergetically efficient than human islets as well as INS1 cells

Sex differences in the adult human brain:Evidence from 5216 UK Biobank participants

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Human-correlated genetic HCC models identify combination therapy for precision medicine [Pre-print]

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, is a leading cause of cancer related mortality worldwide. HCC occurs typically from a background of chronic liver disease, caused by a spectrum of predisposing conditions. Tumour development is driven by the expansion of clones that accumulated progressive driver mutations, with hepatocytes the most likely cell of origin. However, the landscape of driver mutations in HCC is independent of the underlying aetiologies. Despite an increasing range of systemic treatment options for advanced HCC outcomes remain heterogeneous and typically poor. Emerging data suggest that drug efficacies depend on disease aetiology and genetic alterations. Exploring subtypes in preclinical models with human relevance will therefore be essential to advance precision medicine in HCC. We generated over twenty-five new genetically-driven in vivo and in vitro HCC models. Our models represent multiple features of human HCC, including clonal origin, histopathological appearance, and metastasis to distant organs. We integrated transcriptomic data from the mouse models with human HCC data and identified four common human-mouse subtype clusters. The subtype clusters had distinct transcriptomic characteristics that aligned with histopathology. In a proof-of-principle analysis, we verified response to standard of care treatment and used a linked in vitro-in vivo pipeline to identify a promising therapeutic candidate, cladribine, that has not been linked to HCC treatment before. Cladribine acts in a highly effective subtype-specific manner in combination with standard of care therapy