Showing papers by "University of Newcastle published in 2018"

Analysis of shared heritability in common disorders of the brain

Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.

Abstract: High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future

Recent advances in functionalized micro and mesoporous carbon materials: synthesis and applications

Abstract: Functionalized nanoporous carbon materials have attracted the colossal interest of the materials science fraternity owing to their intriguing physical and chemical properties including a well-ordered porous structure, exemplary high specific surface areas, electronic and ionic conductivity, excellent accessibility to active sites, and enhanced mass transport and diffusion. These properties make them a special and unique choice for various applications in divergent fields such as energy storage batteries, supercapacitors, energy conversion fuel cells, adsorption/separation of bulky molecules, heterogeneous catalysts, catalyst supports, photocatalysis, carbon capture, gas storage, biomolecule detection, vapour sensing and drug delivery. Because of the anisotropic and synergistic effects arising from the heteroatom doping at the nanoscale, these novel materials show high potential especially in electrochemical applications such as batteries, supercapacitors and electrocatalysts for fuel cell applications and water electrolysis. In order to gain the optimal benefit, it is necessary to implement tailor made functionalities in the porous carbon surfaces as well as in the carbon skeleton through the comprehensive experimentation. These most appealing nanoporous carbon materials can be synthesized through the carbonization of high carbon containing molecular precursors by using soft or hard templating or non-templating pathways. This review encompasses the approaches and the wide range of methodologies that have been employed over the last five years in the preparation and functionalisation of nanoporous carbon materials via incorporation of metals, non-metal heteroatoms, multiple heteroatoms, and various surface functional groups that mostly dictate their place in a wide range of practical applications.

Neuronal Cell Death.

Abstract: Neuronal cell death occurs extensively during development and pathology, where it is especially important because of the limited capacity of adult neurons to proliferate or be replaced. The concept of cell death used to be simple as there were just two or three types, so we just had to work out which type was involved in our particular pathology and then block it. However, we now know that there are at least a dozen ways for neurons to die, that blocking a particular mechanism of cell death may not prevent the cell from dying, and that non-neuronal cells also contribute to neuronal death. We review here the mechanisms of neuronal death by intrinsic and extrinsic apoptosis, oncosis, necroptosis, parthanatos, ferroptosis, sarmoptosis, autophagic cell death, autosis, autolysis, paraptosis, pyroptosis, phagoptosis, and mitochondrial permeability transition. We next explore the mechanisms of neuronal death during development, and those induced by axotomy, aberrant cell-cycle reentry, glutamate (excitoxicity and oxytosis), loss of connected neurons, aggregated proteins and the unfolded protein response, oxidants, inflammation, and microglia. We then reassess which forms of cell death occur in stroke and Alzheimer's disease, two of the most important pathologies involving neuronal cell death. We also discuss why it has been so difficult to pinpoint the type of neuronal death involved, if and why the mechanism of neuronal death matters, the molecular overlap and interplay between death subroutines, and the therapeutic implications of these multiple overlapping forms of neuronal death.

Current Trends and Challenges in the Clinical Translation of Nanoparticulate Nanomedicines: Pathways for Translational Development and Commercialization

Abstract: The use of nanotechnology in medicine has the potential to have a major impact on human health for the prevention, diagnosis, and treatment of diseases. One particular aspect of the nanomedicine field which has received a great deal of attention is the design and development of nanoparticulate nanomedicines (NNMs) for drug delivery (i.e., drug-containing nanoparticles). NNMs are intended to deliver drugs via various mechanisms: solubilization, passive targeting, active targeting, and triggered release. The NNM approach aims to increase therapeutic efficacy, decrease the therapeutically effective dose, and/or reduce the risk of systemic side effects. In order to move a NNM from the bench to the bedside, several experimental challenges need to be addressed. This review will discuss the current trends and challenges in the clinical translation of NNMs as well as the potential pathways for translational development and commercialization. Key issues related to the clinical development of NNMs will be covered, including biological challenges, large-scale manufacturing, biocompatibility and safety, intellectual property (IP), government regulations, and overall cost-effectiveness in comparison to current therapies. These factors can impose significant hurdles limiting the appearance of NNMs on the market, irrelevant of whether they are therapeutically beneficial or not.

Deep code search

Abstract: To implement a program functionality, developers can reuse previously written code snippets by searching through a large-scale codebase. Over the years, many code search tools have been proposed to help developers. The existing approaches often treat source code as textual documents and utilize information retrieval models to retrieve relevant code snippets that match a given query. These approaches mainly rely on the textual similarity between source code and natural language query. They lack a deep understanding of the semantics of queries and source code. In this paper, we propose a novel deep neural network named CODEnn (Code-Description Embedding Neural Network). Instead of matching text similarity, CODEnn jointly embeds code snippets and natural language descriptions into a high-dimensional vector space, in such a way that code snippet and its corresponding description have similar vectors. Using the unified vector representation, code snippets related to a natural language query can be retrieved according to their vectors. Semantically related words can also be recognized and irrelevant/noisy keywords in queries can be handled. As a proof-of-concept application, we implement a code search tool named DeepCS using the proposed CODEnn model. We empirically evaluate DeepCS on a large scale codebase collected from GitHub. The experimental results show that our approach can effectively retrieve relevant code snippets and outperforms previous techniques.

Grasshopper optimization algorithm for multi-objective optimization problems

Abstract: This work proposes a new multi-objective algorithm inspired from the navigation of grass hopper swarms in nature. A mathematical model is first employed to model the interaction of individuals in the swam including attraction force, repulsion force, and comfort zone. A mechanism is then proposed to use the model in approximating the global optimum in a single-objective search space. Afterwards, an archive and target selection technique are integrated to the algorithm to estimate the Pareto optimal front for multi-objective problems. To benchmark the performance of the algorithm proposed, a set of diverse standard multi-objective test problems is utilized. The results are compared with the most well-regarded and recent algorithms in the literature of evolutionary multi-objective optimization using three performance indicators quantitatively and graphs qualitatively. The results show that the proposed algorithm is able to provide very competitive results in terms of accuracy of obtained Pareto optimal solutions and their distribution.

Widespread white matter microstructural differences in schizophrenia across 4322 individuals : results from the ENIGMA Schizophrenia DTI Working Group

Abstract: The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells.

Abstract: Parallel single-cell sequencing protocols represent powerful methods for investigating regulatory relationships, including epigenome-transcriptome interactions. Here, we report a single-cell method for parallel chromatin accessibility, DNA methylation and transcriptome profiling. scNMT-seq (single-cell nucleosome, methylation and transcription sequencing) uses a GpC methyltransferase to label open chromatin followed by bisulfite and RNA sequencing. We validate scNMT-seq by applying it to differentiating mouse embryonic stem cells, finding links between all three molecular layers and revealing dynamic coupling between epigenomic layers during differentiation.

Modern Trends in Hyperspectral Image Analysis: A Review

Abstract: Over the past three decades, significant developments have been made in hyperspectral imaging due to which it has emerged as an effective tool in numerous civil, environmental, and military applications. Modern sensor technologies are capable of covering large surfaces of earth with exceptional spatial, spectral, and temporal resolutions. Due to these features, hyperspectral imaging has been effectively used in numerous remote sensing applications requiring estimation of physical parameters of many complex surfaces and identification of visually similar materials having fine spectral signatures. In the recent years, ground based hyperspectral imaging has gained immense interest in the research on electronic imaging for food inspection, forensic science, medical surgery and diagnosis, and military applications. This review focuses on the fundamentals of hyperspectral image analysis and its modern applications such as food quality and safety assessment, medical diagnosis and image guided surgery, forensic document examination, defense and homeland security, remote sensing applications such as precision agriculture and water resource management and material identification and mapping of artworks. Moreover, recent research on the use of hyperspectral imaging for examination of forgery detection in questioned documents, aided by deep learning, is also presented. This review can be a useful baseline for future research in hyperspectral image analysis.

Soil-related sustainable development goals: Four concepts to make land degradation neutrality and restoration work

Abstract: In the effort to achieve the Sustainable Development Goals (SDGs) related to food, health, water, and climate, an increase in pressure on land is highly likely. To avoid further land degradation and promote land restoration, multifunctional use of land is needed within the boundaries of the soil-water system. In addition, awareness-raising, a change in stakeholders’ attitudes, and a change in economics are essential. The attainment of a balance between the economy, society, and the biosphere calls for a holistic approach. In this paper, we introduce four concepts that we consider to be conducive to realizing LDN in a more integrated way: systems thinking, connectivity, nature-based solutions, and regenerative economics. We illustrate the application of these concepts through three examples in agricultural settings. Systems thinking lies at the base of the three others, stressing feedback loops but also delayed responses. Their simultaneous use will result in more robust solutions, which are sustainable from an environmental, societal, and economic point of view. Solutions also need to take into account the level of scale (global, national, regional, local), stakeholders’ interests and culture, and the availability and boundaries of financial and natural capital. Furthermore, sustainable solutions need to embed short-term management in long-term landscape planning. In conclusion, paradigm shifts are needed. First, it is necessary to move from excessive exploitation in combination with environmental protection, to sustainable use and management of the soil-water system. To accomplish this, new business models in robust economic systems are needed based on environmental systems thinking; an approach that integrates environmental, social, and economic interests. Second, it is necessary to shift from a “system follows function” approach towards a “function follows system” one. Only by making the transition towards integrated solutions based on a socio-economical-ecological systems analysis, using concepts such as nature-based solutions, do we stand a chance to achieve Land Degradation Neutrality by 2030. To make these paradigm shifts, awareness-raising in relation to a different type of governance, economy and landscape and land-use planning and management is needed.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Abstract: General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Tailoring Adjuvant Endocrine Therapy for Premenopausal Breast Cancer.

Abstract: Background In the Suppression of Ovarian Function Trial (SOFT) and the Tamoxifen and Exemestane Trial (TEXT), the 5-year rates of recurrence of breast cancer were significantly lower among premenopausal women who received the aromatase inhibitor exemestane plus ovarian suppression than among those who received tamoxifen plus ovarian suppression. The addition of ovarian suppression to tamoxifen did not result in significantly lower recurrence rates than those with tamoxifen alone. Here, we report the updated results from the two trials. Methods Premenopausal women were randomly assigned to receive 5 years of tamoxifen, tamoxifen plus ovarian suppression, or exemestane plus ovarian suppression in SOFT and to receive tamoxifen plus ovarian suppression or exemestane plus ovarian suppression in TEXT. Randomization was stratified according to the receipt of chemotherapy. Results In SOFT, the 8-year disease-free survival rate was 78.9% with tamoxifen alone, 83.2% with tamoxifen plus ovarian suppression,...

A simple introduction to Markov Chain Monte-Carlo sampling.

Abstract: Markov Chain Monte–Carlo (MCMC) is an increasingly popular method for obtaining information about distributions, especially for estimating posterior distributions in Bayesian inference. This article provides a very basic introduction to MCMC sampling. It describes what MCMC is, and what it can be used for, with simple illustrative examples. Highlighted are some of the benefits and limitations of MCMC sampling, as well as different approaches to circumventing the limitations most likely to trouble cognitive scientists.

Thickness-Dependent Facet Junction Control of Layered BiOIO3 Single Crystals for Highly Efficient CO2 Photoreduction

Abstract: Thin layer fabrication and crystal facet engineering favor the prompt charge transfer from bulk to the surface of a material and spatial charge separation among different facets, tremendously benefitting photocatalytic activity. However, the thickness and surface facet composition are considered as two entwined characteristics of layered materials with well-defined and tunable shapes, which possess great promise to achieve the simultaneous manipulation of charge transfer and spatial separation. Herein, it is demonstrated that one solution for the aforementioned issue by controllably regulating the surface {010}/{100} facet junctions of a layered thickness-tunable bismuth-based material, BiOIO3. The attenuation in thickness of BiOIO3 nanoplates shortens the diffusion pathway of charge carriers, and more importantly the tuning of nanolayer thickness renders the ratio variation of the top {010} facet to the lateral {100} facet, which dominates the spatial separation of photogenerated electrons and holes. As a result, the highest CO evolution rate from CO2 reduction over BiOIO3 nanoplates with the optimal thickness and ratio of exposed facets reaches 5.42 μmol g−1 h−1, over 300% that of the bulk counterpart (1.77 μmol g−1 h−1). This work paves a new way for governing charge movement behaviors on the basis of the synergistic engineering of layer structure and exposing facets.

Green Innovation, Managerial Concern and Firm Performance: An Empirical Study

Abstract: Extant literature, while often suggesting a positive link between green innovation and firm performance, is inconclusive. Moreover, the possibly moderating role of management has not been sufficiently considered. Using a unique dataset sampling 188 manufacturing firms in China, we examine how managerial concern (for green issues) moderates the relationship between green innovation and firm performance. We find that green process innovation and green product innovation both significantly (positively) predict firm performance, when not considering managerial concern for the environment. Once managerial concern is included, we observe that it compounds the positive effect of green process innovation on firm performance – but not product innovation, which no longer explains significant unique variance in firm performance. The findings hold various implications for future research and business policy. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

Biological responses to the press and pulse of climate trends and extreme events

Abstract: The interaction of gradual climate trends and extreme weather events since the turn of the century has triggered complex and, in some cases, catastrophic ecological responses around the world. We illustrate this using Australian examples within a press–pulse framework. Despite the Australian biota being adapted to high natural climate variability, recent combinations of climatic presses and pulses have led to population collapses, loss of relictual communities and shifts into novel ecosystems. These changes have been sudden and unpredictable, and may represent permanent transitions to new ecosystem states without adaptive management interventions. The press–pulse framework helps illuminate biological responses to climate change, grounds debate about suitable management interventions and highlights possible consequences of (non-) intervention.

Introductory programming: a systematic literature review

Abstract: As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.

The pharmacokinetics and the pharmacodynamics of cannabinoids.

Abstract: There is increasing interest in the use of cannabinoids for disease and symptom management, but limited information available regarding their pharmacokinetics and pharmacodynamics to guide prescribers. Cannabis medicines contain a wide variety of chemical compounds, including the cannabinoids delta-9-tetrahydrocannabinol (THC), which is psychoactive, and the nonpsychoactive cannabidiol (CBD). Cannabis use is associated with both pathological and behavioural toxicity and, accordingly, is contraindicated in the context of significant psychiatric, cardiovascular, renal or hepatic illness. The pharmacokinetics of cannabinoids and the effects observed depend on the formulation and route of administration, which should be tailored to individual patient requirements. As both THC and CBD are hepatically metabolized, the potential exists for pharmacokinetic drug interactions via inhibition or induction of enzymes or transporters. An important example is the CBD-mediated inhibition of clobazam metabolism. Pharmacodynamic interactions may occur if cannabis is administered with other central nervous system depressant drugs, and cardiac toxicity may occur via additive hypertension and tachycardia with sympathomimetic agents. More vulnerable populations, such as older patients, may benefit from the potential symptomatic and palliative benefits of cannabinoids but are at increased risk of adverse effects. The limited availability of applicable pharmacokinetic and pharmacodynamic information highlights the need to initiate prescribing cannabis medicines using a 'start low and go slow' approach, carefully observing the patient for desired and adverse effects. Further clinical studies in the actual patient populations for whom prescribing may be considered are needed, to derive a better understanding of these drugs and enhance safe and optimal prescribing.

Identification of rare sequence variation underlying heritable pulmonary arterial hypertension.

Abstract: Pulmonary arterial hypertension (PAH) is a rare disorder with a poor prognosis. Deleterious variation within components of the transforming growth factor-β pathway, particularly the bone morphogenetic protein type 2 receptor (BMPR2), underlies most heritable forms of PAH. To identify the missing heritability we perform whole-genome sequencing in 1038 PAH index cases and 6385 PAH-negative control subjects. Case-control analyses reveal significant overrepresentation of rare variants in ATP13A3, AQP1 and SOX17, and provide independent validation of a critical role for GDF2 in PAH. We demonstrate familial segregation of mutations in SOX17 and AQP1 with PAH. Mutations in GDF2, encoding a BMPR2 ligand, lead to reduced secretion from transfected cells. In addition, we identify pathogenic mutations in the majority of previously reported PAH genes, and provide evidence for further putative genes. Taken together these findings contribute new insights into the molecular basis of PAH and indicate unexplored pathways for therapeutic intervention.

Engineering Catalytic Active Sites on Cobalt Oxide Surface for Enhanced Oxygen Electrocatalysis

Abstract: Tuning the catalytic active sites plays a crucial role in developing low cost and highly durable oxygen electrode catalysts with precious metal-competitive activity. In an attempt to engineer the active sites in Co3O4 spinel for oxygen electrocatalysis in alkaline electrolyte, herein, controllable synthesis of surface-tailored Co3O4 nanocrystals including nanocube (NC), nanotruncated octahedron (NTO), and nanopolyhedron (NP) anchored on nitrogen-doped reduced graphene oxide (N-rGO), through a facile and template-free hydrothermal strategy, is provided. The as-synthesized Co3O4 NC, NTO, and NP nanostructures are predominantly enclosed by {001}, {001} + {111}, and {112} crystal planes, which expose different surface atomic configurations of Co2+ and Co3+ active sites. Electrochemical results indicate that the unusual {112} plane enclosed Co3O4 NP on rGO with abundant Co3+ sites exhibit superior bifunctional activity for oxygen reduction and evolution reactions, as well as enhanced metal–air battery performance in comparison with other counterparts. Experimental and theoretical simulation studies demonstrate that the surface atomic arrangement of Co2+/Co3+ active sites, especially the existence of octahedrally coordinated Co3+ sites, optimizes the adsorption, activation, and desorption features of oxygen species. This work paves the way to obtain highly active, durable, and cost-effective electrocatalysts for practical clean energy devices through regulating the surface atomic configuration and catalytic active sites.