The Health and Well-Being of Individuals Before and After Coronary Artery Bypass Surgery

Introduction: Coronary artery bypass graft (CABG) surgery is an important intervention for individuals with established coronary heart disease (CHD). Although its place as one of a range of therapeutic options has been established, outcome assessment is based almost exclusively on biomedical measures such as mortality and morbidity. Much less is understood about benefits to general health and well-being, broader life circumstances and the expectations of those undergoing this procedure, particularly the manner in which these factors influence the favourability of the outcome. The objective of this thesis was to investigate these issues

The potential impact of climate change on Australia's soil organic carbon resources

BACKGROUND: Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO(2 )on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM). RESULTS: We estimate organic carbon storage in the topsoil (0–10 cm) of the Australian continent in 1990 to be 8.1 Gt. This equates to 19 and 34 Gt in the top 30 and 100 cm of soil, respectively. By the year 2100, under a low emissions scenario, topsoil organic carbon stores of the continent will have increased by 0.6% (49 Mt C). Under a high emissions scenario, the Australian continent becomes a source of CO(2 )with a net reduction of 6.4% (518 Mt) in topsoil carbon, when compared to no climate change. This is partially offset by the predicted increase in NPP of 20.3% CONCLUSION: Climate change impacts must be studied holistically, requiring integration of climate, plant, ecosystem and soil sciences. The SOCRATES terrestrial carbon cycling model provides realistic estimates of changes in SOC storage in response to climate change over the next century, and confirms the need for greater consideration of soils in assessing the full impact of climate change and the development of quantifiable mitigation strategies

Geo‐Hydromorphological Assessment of Europe’s Southernmost Blanket Bogs

Blanket bogs are a globally rare type of ombrotrophic peatland internationally recognised for long‐term terrestrial carbon storage, the potential to serve as carbon sinks, habitat provision and for their palaeoenvironmental archive. This habitat is protected in the European Union under the Habitats Directive (92/43/EEC), but a number of blanket bogs located in the Cantabrian Mountains (northern Spain), representing the southernmost known edge‐of‐range for this habitat in Europe, are currently not recognised and are at increased threat of loss. Using climatic data, topography, aerial photography and peat depth surveys, this study has identified ten new areas of blanket bog located between the administrative regions of Cantabria and Castilla y León. Peat depth data and topography were used to provide a detailed geomorphological description and hydromorphological classification (mesotope units) of these currently unrecognised areas of blanket bog. Maximum peat depth measured across the ten sites ranged from 1.61 m to 3.78 m covering a total area of 18.6 ha of blanket bog (> 40 cm peat depth). The volume of peat accumulated across the sites was determined to be more than 216,000 m3 and is estimated to hold 19.89 ± 3.51kt C. Twenty‐four individual hydrological mesotope units were described indicating a diverse assemblage of blanket bogs in this region. The peatlands identified in this research extend the known limit of blanket bogs in Europe farther south than previously recorded and combined with four other unprotected blanket bogs recently identified in the Cantabrian Mountains, these peatlands represent 10.5% of blanket bog currently recognised and protected in Spain. The range of anthropogenic pressures currently acting on peatlands in the Cantabrian Mountains indicates that without protection these important landforms and carbon stored may be lost. An urgent update of European peatland inventories is thus required to preserve these valuable carbon stores and potential carbon sinks

Consciousness in Artificial Intelligence: Insights from the Science of Consciousness

Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive "indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators

A disordered region controls cBAF activity via condensation and partner recruitment

Intrinsically disordered regions (IDRs) represent a large percentage of overall nuclear protein content. The prevailing dogma is that IDRs engage in non-specific interactions because they are poorly constrained by evolutionary selection. Here, we demonstrate that condensate formation and heterotypic interactions are distinct and separable features of an IDR within the ARID1A/B subunits of the mSWI/SNF chromatin remodeler, cBAF, and establish distinct sequence grammars underlying each contribution. Condensation is driven by uniformly distributed tyrosine residues, and partner interactions are mediated by non-random blocks rich in alanine, glycine, and glutamine residues. These features concentrate a specific cBAF protein-protein interaction network and are essential for chromatin localization and activity. Importantly, human disease-associated perturbations in ARID1B IDR sequence grammars disrupt cBAF function in cells. Together, these data identify IDR contributions to chromatin remodeling and explain how phase separation provides a mechanism through which both genomic localization and functional partner recruitment are achieved

SOX9 predicts progression towards cirrhosis in patients while its loss protects against liver fibrosis

Fibrosis and organ failure is a common endpoint for many chronic liver diseases. Much is known about the upstream inflammatory mechanisms provoking fibrosis and downstream potential for tissue remodeling. However, less is known about the transcriptional regulation in vivo governing fibrotic matrix deposition by liver myofibroblasts. This gap in understanding has hampered molecular predictions of disease severity and clinical progression and restricted targets for antifibrotic drug development. In this study we show the prevalence of SOX9 in biopsies from patients with chronic liver disease correlated with fibrosis severity and accurately predicted disease progression towards cirrhosis. Inactivation of Sox9 in mice protected against both parenchymal and biliary fibrosis, improved liver function and ameliorated chronic inflammation. SOX9 was downstream of mechanosignaling factor, YAP1. These data demonstrate a role for SOX9 in liver fibrosis and open the way for the transcription factor and its dependent pathways as new diagnostic, prognostic and therapeutic targets in patients with liver fibrosis

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively

A qualitative analysis exploring preferred methods of peer support to encourage adherence to a Mediterranean diet in a Northern European population at high risk of cardiovascular disease.

BACKGROUND: Epidemiological and randomised controlled trial evidence demonstrates that adherence to a Mediterranean diet (MD) can reduce cardiovascular disease (CVD) risk. However, methods used to support dietary change have been intensive and expensive. Peer support has been suggested as a possible cost-effective method to encourage adherence to a MD in at risk populations, although development of such a programme has not been explored. The purpose of this study was to use mixed-methods to determine the preferred peer support approach to encourage adherence to a MD. METHODS: Qualitative (focus groups) and quantitative methods (questionnaire and preference scoring sheet) were used to determine preferred methods of peer support. Sixty-seven high CVD risk participants took part in 12 focus groups (60% female, mean age 64 years) and completed a questionnaire and preference scoring sheet. Focus group data were transcribed and thematically analysed. RESULTS: The mean preference score (1 being most preferred and 5 being least preferred) for group support was 1.5, compared to 3.4 for peer mentorship, 4.0 for telephone peer support and 4.0 for internet peer support. Three key themes were identified from the transcripts: 1. Components of an effective peer support group: discussions around group peer support were predominantly positive. It was suggested that an effective group develops from people who consider themselves similar to each other meeting face-to-face, leading to the development of a group identity that embraces trust and honesty. 2. Catalysing Motivation: participants discussed that a group peer support model could facilitate interpersonal motivations including encouragement, competitiveness and accountability. 3. Stepping Stones of Change: participants conceptualised change as a process, and discussed that, throughout the process, different models of peer support might be more or less useful. CONCLUSION: A group-based approach was the preferred method of peer support to encourage a population at high risk of CVD to adhere to a MD. This finding should be recognised in the development of interventions to encourage adoption of a MD in a Northern European population