2,698 research outputs found

    Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

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    From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

    The Worldvolume Action of Kink Solitons in AdS Spacetime

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    A formalism is presented for computing the higher-order corrections to the worldvolume action of co-dimension one solitons. By modifying its potential, an explicit "kink" solution of a real scalar field in AdS spacetime is found. The formalism is then applied to explicitly compute the kink worldvolume action to quadratic order in two expansion parameters--associated with the hypersurface fluctuation length and the radius of AdS spacetime respectively. Two alternative methods are given for doing this. The results are expressed in terms of the trace of the extrinsic curvature and the intrinsic scalar curvature. In addition to conformal Galileon interactions, we find a non-Galileon term which is never sub-dominant. This method can be extended to any conformally flat bulk spacetime.Comment: 32 pages, 3 figures, typos corrected and additional comments adde

    Enhancing the relevance of Shared Socioeconomic Pathways for climate change impacts, adaptation and vulnerability research

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    This paper discusses the role and relevance of the shared socioeconomic pathways (SSPs) and the new scenarios that combine SSPs with representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social–environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of the SSPs and new scenarios that would improve their usefulness for IAV studies compared to earlier scenario sets: (i) enhancing their applicability while retaining coherence across spatial scales, and (ii) adding indicators of importance for projecting vulnerability. The paper therefore presents an agenda for future research, recommending that SSPs incorporate not only the standard variables of population and gross domestic product, but also indicators such as income distribution, spatial population, human health and governance

    An extracellular steric seeding mechanism for Eph-ephrin signaling platform assembly

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    Erythropoetin-producing hepatoma (Eph) receptors are cell-surface protein tyrosine kinases mediating cell-cell communication. Upon activation, they form signaling clusters. We report crystal structures of the full ectodomain of human EphA2 (eEphA2) both alone and in complex with the receptor-binding domain of the ligand ephrinA5 (ephrinA5 RBD). Unliganded eEphA2 forms linear arrays of staggered parallel receptors involving two patches of residues conserved across A-class Ephs. eEphA2-ephrinA5 RBD forms a more elaborate assembly, whose interfaces include the same conserved regions on eEphA2, but rearranged to accommodate ephrinA5 RBD. Cell-surface expression of mutant EphA2s showed that these interfaces are critical for localization at cell-cell contacts and activation-dependent degradation. Our results suggest a 'nucleation' mechanism whereby a limited number of ligand-receptor interactions 'seed' an arrangement of receptors which can propagate into extended signaling arrays

    An integrated general practice and pharmacy-based intervention to promote the use of appropriate preventive medications among individuals at high cardiovascular disease risk: protocol for a cluster randomized controlled trial

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    Background: Cardiovascular diseases (CVD) are responsible for significant morbidity, premature mortality, and economic burden. Despite established evidence that supports the use of preventive medications among patients at high CVD risk, treatment gaps remain. Building on prior evidence and a theoretical framework, a complex intervention has been designed to address these gaps among high-risk, under-treated patients in the Australian primary care setting. This intervention comprises a general practice quality improvement tool incorporating clinical decision support and audit/feedback capabilities; availability of a range of CVD polypills (fixed-dose combinations of two blood pressure lowering agents, a statin ± aspirin) for prescription when appropriate; and access to a pharmacy-based program to support long-term medication adherence and lifestyle modification. Methods: Following a systematic development process, the intervention will be evaluated in a pragmatic cluster randomized controlled trial including 70 general practices for a median period of 18 months. The 35 general practices in the intervention group will work with a nominated partner pharmacy, whereas those in the control group will provide usual care without access to the intervention tools. The primary outcome is the proportion of patients at high CVD risk who were inadequately treated at baseline who achieve target blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) levels at the study end. The outcomes will be analyzed using data from electronic medical records, utilizing a validated extraction tool. Detailed process and economic evaluations will also be performed. Discussion: The study intends to establish evidence about an intervention that combines technological innovation with team collaboration between patients, pharmacists, and general practitioners (GPs) for CVD prevention. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN1261600023342

    Views of addiction neuroscientists and clinicians on the clinical impact of a ‘Brain Disease Model of Addiction’

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    Addiction is increasingly described as a "chronic and relapsing brain disease". The potential impact of the brain disease model on the treatment of addiction or addicted individuals' treatment behaviour remains uncertain. We conducted a qualitative study to examine: (i) the extent to which leading Australian addiction neuroscientists and clinicians accept the brain disease view of addiction; and (ii) their views on the likely impacts of this view on addicted individuals' beliefs and behaviour. Thirty-one Australian addiction neuroscientists and clinicians (10 females and 21 males; 16 with clinical experience and 15 with no clinical experience) took part in 1 h semi-structured interviews. Most addiction neuroscientists and clinicians did not uncritically support the use of brain disease model of addiction. Most were cautious about the potential for adverse impacts on individuals' recovery and motivation to enter treatment. While some recognised the possibility that the brain disease model of addiction may provide a rationale for addicted persons to seek treatment and motivate behaviour change, Australian addiction neuroscientist and clinicians do not assume that messages about "diseased brains" will always lead to increased treatment-seeking and reduced drug use. Research is needed on how neuroscience research could be used in ways that optimise positive outcomes for addicted persons

    To respond or not to respond - a personal perspective of intestinal tolerance

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    For many years, the intestine was one of the poor relations of the immunology world, being a realm inhabited mostly by specialists and those interested in unusual phenomena. However, this has changed dramatically in recent years with the realization of how important the microbiota is in shaping immune function throughout the body, and almost every major immunology institution now includes the intestine as an area of interest. One of the most important aspects of the intestinal immune system is how it discriminates carefully between harmless and harmful antigens, in particular, its ability to generate active tolerance to materials such as commensal bacteria and food proteins. This phenomenon has been recognized for more than 100 years, and it is essential for preventing inflammatory disease in the intestine, but its basis remains enigmatic. Here, I discuss the progress that has been made in understanding oral tolerance during my 40 years in the field and highlight the topics that will be the focus of future research

    Increased entropy of signal transduction in the cancer metastasis phenotype

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    Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

    The Effects of Cocaine on Different Redox Forms of Cysteine and Homocysteine, and on Labile, Reduced Sulfur in the Rat Plasma Following Active versus Passive Drug Injections

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    Received: 28 November 2012 / Revised: 19 April 2013 / Accepted: 6 May 2013 / Published online: 16 May 2013 The Author(s) 2013. This article is published with open access at Springerlink.comThe aim of the present studies was to evaluate cocaine-induced changes in the concentrations of different redox forms of cysteine (Cys) and homocysteine (Hcy), and products of anaerobic Cys metabolism, i.e., labile, reduced sulfur (LS) in the rat plasma. The above-mentioned parameters were determined after i.p. acute and subchronic cocaine treatment as well as following i.v. cocaine self-administration using the yoked procedure. Additionally, Cys, Hcy, and LS levels were measured during the 10-day extinction training in rats that underwent i.v. cocaine administration. Acute i.p. cocaine treatment increased the total and protein-bound Hcy contents, decreased LS, and did not change the concentrations of Cys fractions in the rat plasma. In turn, subchronic i.p. cocaine administration significantly increased free Hcy and lowered the total and protein-bound Cys concentrations while LS level was unchanged. Cocaine self-administration enhanced the total and protein-bound Hcy levels, decreased LS content, and did not affect the Cys fractions. On the other hand, yoked cocaine infusions did not alter the concentration of Hcy fractions while decreased the total and protein-bound Cys and LS content. This extinction training resulted in the lack of changes in the examined parameters in rats with a history of cocaine self-administration while in the yoked cocaine group an increase in the plasma free Cys fraction and LS was seen. Our results demonstrate for the first time that cocaine does evoke significant changes in homeostasis of thiol amino acids Cys and Hcy, and in some products of anaerobic Cys metabolism, which are dependent on the way of cocaine administration

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente
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