Ideal observer analysis for task normalization of pattern classifier performance applied to EEG and fMRI data

The application of multivariate techniques to neuroimaging and electrophysiological data has greatly enhanced the ability to detect where, when, and how functional neural information is processed during a variety of behavioral tasks. With the extension to single-trial analysis, neuroscientists are able to relate brain states to perceptual, cognitive, and motor processes. Using pattern classification methods, the neuroscientist can extract neural performance measures in a manner analogous to human behavioral performance, allowing for a consistent information content metric across measurement modalities. However, as with behavioral psychophysical performance, pattern classifier performances are a product of both the task-relevant information inherent in the brain and in the task/stimuli. Here, we argue for the use of an ideal observer framework with which the researcher can effectively normalize the observed neural performance given the task's inherent objective difficulty. We use data from a face versus car discrimination task and compare classifier performance applied to electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data with corresponding human behavior through the absolute and relative efficiency metrics. We show that confounding variables that can lead to erroneous interpretations of information content can be accounted for through comparisons to an ideal observer, allowing for more confident interpretation of the neural mechanisms involved in the task of interest. Finally, we discuss limitations of interpretation due to the transduction of indirect measures of neural activity, underlying assumptions in the optimality of the pattern classifiers, and dependence of efficiency results on signal contrast.     

Novel and Annotated Long Noncoding RNAs Associated with Ischemia in the Human Heart

Background: Long noncoding RNAs (lncRNAs) have been implicated in the pathogenesis of cardiovascular diseases. We aimed to identify novel lncRNAs associated with the early response to ischemia in the heart. Methods and Results: RNA sequencing data gathered from 81 paired left ventricle samples from patients undergoing cardiopulmonary bypass was collected before and after a period of ischemia. Novel lncRNAs were validated with Oxford Nanopore Technologies long-read sequencing. Gene modules associated with an early ischemic response were identified and the subcellular location of selected lncRNAs was determined with RNAscope. A total of 2446 mRNAs, 270 annotated lncRNAs and one novel lncRNA differed in response to ischemia (adjusted p < 0.001, absolute fold change >1.2). The novel lncRNA belonged to a gene module of highly correlated genes that also included 39 annotated lncRNAs. This module associated with ischemia (Pearson correlation coefficient = −0.69, p = 1 × 10⁻²³) and activation of cell death pathways (p < 6 × 10⁻⁹). A further nine novel cardiac lncRNAs were identified, of which, one overlapped five cis-eQTL eSNPs for the gene RWD Domain-Containing Sumoylation Enhancer (RWDD3) and was itself correlated with RWDD3 expression (Pearson correlation coefficient −0.2, p = 0.002). Conclusion: We have identified 10 novel lncRNAs, one of which was associated with myocardial ischemia and may have potential as a novel therapeutic target or early marker for myocardial dysfunction.     

Transcriptional Regulation of the Synaptic Vesicle Protein Synaptogyrin-3 (SYNGR3) Gene: The Effects of NURR1 on Its Expression

Synaptogyrin-3 (SYNGR3) is a synaptic vesicular membrane protein. Amongst four homologues (SYNGR1 to 4), SYNGR1 and 3 are especially abundant in the brain. SYNGR3 interacts with the dopamine transporter (DAT) to facilitate dopamine (DA) uptake and synaptic DA turnover in dopaminergic transmission. Perturbed SYNGR3 expression is observed in Parkinson’s disease (PD). The regulatory elements which affect SYNGR3 expression are unknown. Nuclear-receptor-related-1 protein (NURR1) can regulate dopaminergic neuronal differentiation and maintenance via binding to NGFI-B response elements (NBRE). We explored whether NURR1 can regulate SYNGR3 expression using an in silico analysis of the 5′-flanking region of the human SYNGR3 gene, reporter gene activity and an electrophoretic mobility shift assay (EMSA) of potential cis-acting sites. In silico analysis of two genomic DNA segments (1870 bp 5′-flanking region and 1870 + 159 bp of first exon) revealed one X Core Promoter Element 1 (XCPE1), two SP1, and three potential non-canonical NBRE response elements (ncNBRE) but no CAAT or TATA box. The longer segment exhibited gene promoter activity in luciferase reporter assays. Site-directed mutagenesis of XCPE1 decreased promoter activity in human neuroblastoma SH-SY5Y (↓43.2%) and human embryonic kidney HEK293 cells (↓39.7%). EMSA demonstrated NURR1 binding to these three ncNBRE. Site-directed mutagenesis of these ncNBRE reduced promoter activity by 11–17% in SH-SY5Y (neuronal) but not in HEK293 (non-neuronal) cells. C-DIM12 (Nurr1 activator) increased SYNGR3 protein expression in SH-SY5Y cells and its promoter activity using a real-time luciferase assay. As perturbed vesicular function is a feature of major neurodegenerative diseases, inducing SYNGR3 expression by NURR1 activators may be a potential therapeutic target to attenuate synaptic dysfunction in PD.     

Of Mouse and Man: Cross-Species Characterization of Hypertensive Cardiac Remodeling

Hypertension is a major public health concern and poses a significant risk for sudden cardiac death (SCD). However, the characterisation of human tissues tends to be macroscopic, with little appreciation for the quantification of the pathological remodelling responsible for the advancement of the disease. While the components of hypertensive remodelling are well established, the timeline and comparative quantification of pathological changes in hypertension have not been shown before. Here, we sought to identify the phasing of cardiac remodelling with hypertension using post-mortem tissue from SCD patients with early and advanced hypertensive heart disease (HHD). In order to study and quantify the progression of phenotypic changes, human specimens were contrasted to a well-described angiotensin-II-mediated hypertensive mouse model. While cardiomyocyte hypertrophy is an early adaptive response in the mouse that stabilises in established hypertension and declines as the disease progresses, this finding did not translate to the human setting. In contrast, optimising fibrosis quantification methods and applying them to each setting identified perivascular fibrosis as the prevailing possible cause for overall disease progression. Indeed, assessing myocardial inflammation highlights CD45+ inflammatory cell infiltration that precedes fibrosis and is an early-phase event in response to elevated arterial pressures that may underscore perivascular remodelling. Along with aetiology insight, we highlight cross-species comparison for quantification of cardiac remodelling in human hypertension. As such, this platform could assist with the development of therapies specific to the disease phase rather than targeting global components of hypertension, such as blood pressure lowering.     

Nationwide buildings energy research enabled through an integrated data intensive

Modern workflow systems can enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve. However as a result of these new capabilities the science teams suddenly also face unprecedented data volumes that they are unable to analyze with their existing tools and methodologies in a timely fashion. In this paper we describe the ongoing development work to create an integrated data intensive scientific workflow and analysis environment that offers researchers the ability to easily create and execute complex simulation studies and provides them with different scalable methods to analyze the resulting data volumes. The capabilities of the new environment are demonstrated on a use case that focuses on building energy modeling. As part of the PNNL research initiative PRIMA (Platform for Regional Integrated Modeling and Analysis) the team performed an initial 3-year study of building energy demands for the US Eastern Interconnect domain. They are now planning to extend to predict the demand for the complete century. In the 3-year study the team simulated 2000 individual building types for 100 independent climate similar regions (600 000 individual runs) raising their data demands from a few MBs to 400 GB for the 3-year study.     

Des conducteurs ioniques pseudo-bidimensionnels: Li8MO6 (M = Zr,Sn), Li7LO6 (L = Nb,Ta) et Li6In2O6

The ionic conductivity of the pseudo-2D oxides Li₈MO₆ (M = Zr, Sn), Li₇LO₆ (L = Nb, Ta) and Li₆In₂O₆ has been measured and related to their structures. The ideal lattice consists of octahedral sheets [(Li₂M)O₆]_n, [(Li□L)O₆]_n or [(In₂□)O₆]_n of CdI₂-type, between which 6 Li⁺ ions are inserted with a tetrahedral environment. As expected from the structures the highest lithium mobility is observed for Li₇LO₆ phases and the smallest one for Li₈MO₆.     

Innovation Compass: A Self–audit Tool for the New Product Development Process

This paper presents a diagnostic tool referred to as the innovation ‘compass’. The innovation compass uses self–audit methodology to identify gaps between current and desired performance of individual organisations. The innovation compass aids organisations in identifying where problems lie within the organisation. This information can then be used in developing an action plan to improve their new product development performance. The compass acts as a support tool to the linear and mechanistic processes of managing new product development, such as the Stage Gate Model. The compass comprises of five core themes; structure, leadership, output, teams and context representing the fundamentals of the innovation process. A combined methodological approach was used, by means of both qualitative and quantitative techniques with organisations. The methodology adopted has allowed for benchmarking of these themes to occur, with additional depth added from the qualitative semi–structured interviews. This paper discusses the rationale for a tool such as the compass.     

Spam,Spam, Spam,Spam…

Many Monty Python fans remember fondly the infamous musical sketch celebrating the versatility of the meat product Spam. However, others of us are less favourably disposed to the modern day, information society version of ‘spam’: junk E-mail. For many users of the Internet, junk E-mail is becoming a significant nuisance that existing laws do not prevent, but regulations will soon be introduced to make it more difficult for people to send.     

US Software Law May Affect UK Companies

Under a recent controversial law approved at the federal level in the USA, some software vendors may have the right to remotely disable software if they believe that the software user is in breach of their licence. It is one of a number of rights included in the Uniform Computer Information Transactions Act (UCITA) which critics argue unfairly swings the law in favour of software vendors. If UCITA is ratified by the US States, companies who sell or purchase software under agreements subject to US law may feel its impact in England.     

Employing transaction aggregation strategy to detect credit card fraud

Credit card fraud costs consumers and the financial industry billions of dollars annually. However, there is a dearth of published literature on credit card fraud detection. In this study we employed transaction aggregation strategy to detect credit card fraud. We aggregated transactions to capture consumer buying behavior prior to each transaction and used these aggregations for model estimation to identify fraudulent transactions. We use real-life data of credit card transactions from an international credit card operation for transaction aggregation and model estimation.