A design pattern for optimizations in data intensive applications using ABS and JAVA 8

Cloud environments have become a standard method for enterprises to offer their applications by means of web services, data management systems, or simply renting out computing resources. In our previous work, we presented how we can use a modeling language together with the new features of JAVA 8 to overcome certain drawbacks of data structures and synchronization mechanisms in parallel applications. We extend this solution into a design pattern that allows application-specific optimizations in a distributed setting. We validate this integration using our previous case study of the Prime Sieve of Eratosthenes and illustrate the performance improvements in terms of speed-up and memory consumption

Towards Type-Based Optimizations in Distributed Applications Using ABS and JAVA 8

In this paper we present an API to support modeling applications with Actors based on the paradigm of the Abstract Behavioural Specification (ABS) language. With the introduction of JAVA 8, we expose this API through a JAVA library to allow for a high-level actor-based methodology for programming distributed systems which supports the programming to interfaces discipline. We validate this solution through a case study where we obtain significant performance improvements as well as illustrating the ease with which simple high and low-level optimizations can be obtained by examining topologies and communication within an application. Using this API we show it is much easier to observe drawbacks of shared data-structures and communications methods in the design phase of a distributed application and apply the necessary corrections in order to obtain better results

A design pattern for optimizations in data intensive applications using ABS and JAVA 8

Cloud environments have become a standard method for enterprises to offer their applications by means of web services, data management systems, or simply renting out computing resources. In our previous work, we presented how we can use a modeling language together with the new features of JAVA 8 to overcome certain drawbacks of data structures and synchronization mechanisms in parallel applications. We extend this solution into a design pattern that allows application-specific optimizations in a distributed setting. We validate this integration using our previous case study of the Prime Sieve of Eratosthenes and illustrate the performance improvements in terms of speed-up and memory co

A Hybrid Spam Detection Method Based on Unstructured Datasets

This document is the accepted manuscript version of the following article: Shao, Y., Trovati, M., Shi, Q. et al. Soft Comput (2017) 21: 233. The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1959-z. © Springer-Verlag Berlin Heidelberg 2015.The identification of non-genuine or malicious messages poses a variety of challenges due to the continuous changes in the techniques utilised by cyber-criminals. In this article, we propose a hybrid detection method based on a combination of image and text spam recognition techniques. In particular, the former is based on sparse representation-based classification, which focuses on the global and local image features, and a dictionary learning technique to achieve a spam and a ham sub-dictionary. On the other hand, the textual analysis is based on semantic properties of documents to assess the level of maliciousness. More specifically, we are able to distinguish between meta-spam and real spam. Experimental results show the accuracy and potential of our approach.Peer reviewedFinal Accepted Versio

Neurochemical Changes in the Mouse Hippocampus Underlying the Antidepressant Effect of Genetic Deletion of P2X7 Receptors.

Recent investigations have revealed that the genetic deletion of P2X7 receptors (P2rx7) results in an antidepressant phenotype in mice. However, the link between the deficiency of P2rx7 and changes in behavior has not yet been explored. In the present study, we studied the effect of genetic deletion of P2rx7 on neurochemical changes in the hippocampus that might underlie the antidepressant phenotype. P2X7 receptor deficient mice (P2rx7-/-) displayed decreased immobility in the tail suspension test (TST) and an attenuated anhedonia response in the sucrose preference test (SPT) following bacterial endotoxin (LPS) challenge. The attenuated anhedonia was reproduced through systemic treatments with P2rx7 antagonists. The activation of P2rx7 resulted in the concentration-dependent release of [3H]glutamate in P2rx7+/+ but not P2rx7-/- mice, and the NR2B subunit mRNA and protein was upregulated in the hippocampus of P2rx7-/- mice. The brain-derived neurotrophic factor (BDNF) expression was higher in saline but not LPS-treated P2rx7-/- mice; the P2rx7 antagonist Brilliant blue G elevated and the P2rx7 agonist benzoylbenzoyl ATP (BzATP) reduced BDNF level. This effect was dependent on the activation of NMDA and non-NMDA receptors but not on Group I metabotropic glutamate receptors (mGluR1,5). An increased 5-bromo-2-deoxyuridine (BrdU) incorporation was also observed in the dentate gyrus derived from P2rx7-/- mice. Basal level of 5-HT was increased, whereas the 5HIAA/5-HT ratio was lower in the hippocampus of P2rx7-/- mice, which accompanied the increased uptake of [3H]5-HT and an elevated number of [3H]citalopram binding sites. The LPS-induced elevation of 5-HT level was absent in P2rx7-/- mice. In conclusion there are several potential mechanisms for the antidepressant phenotype of P2rx7-/- mice, such as the absence of P2rx7-mediated glutamate release, elevated basal BDNF production, enhanced neurogenesis and increased 5-HT bioavailability in the hippocampus

Lack of guidelines and translational knowledge is hindering the implementation of psychiatric genetic counseling and testing within Europe - A multi-professional survey study

Genetic research has identified a large number of genetic variants, both rare and common, underlying neurodevelopmental disorders (NDD) and major psychiatric disorders. Currently, these findings are being translated into clinical practice. However, there is a lack of knowledge and guidelines for psychiatric genetic testing (PsychGT) and genetic counseling (PsychGC). The European Union-funded COST action EnGagE (CA17130) network was started to investigate the current implementation status of PsychGT and PsychGC across 35 participating European countries. Here, we present the results of a pan-European online survey in which we gathered the opinions, knowledge, and practices of a self-selected sample of professionals involved/interested in the field. We received answers from 181 respondents. The three main occupational categories were genetic counselor (21.0%), clinical geneticist (24.9%), and researcher (25.4%). Of all 181 respondents, 106 provide GC for any psychiatric disorder or NDD, corresponding to 58.6% of the whole group ranging from 43.2% in Central Eastern Europe to 66.1% in Western Europe. Overall, 65.2% of the respondents reported that genetic testing is offered to individuals with NDD, and 26.5% indicated the same for individuals with major psychiatric disorders. Only 22.1% of the respondents indicated that they have guidelines for PsychGT. Pharmacogenetic testing actionable for psychiatric disorders was offered by 15%. Interestingly, when genetic tests are fully covered by national health insurance, more genetic testing is provided for individuals with NDD but not those with major psychiatric disorders. Our qualitative analyses of responses highlight the lack of guidelines and knowledge on utilizing and using genetic tests and education and training as the major obstacles to implementation. Indeed, the existence of psychiatric genetic training courses was confirmed by only 11.6% of respondents. The question on the relevance of up-to-date education and training in psychiatric genetics on everyday related practice was highly relevant. We provide evidence that PsychGC and PsychGT are already in use across European countries, but there is a lack of guidelines and education. Harmonization of practice and development of guidelines for genetic counseling, testing, and training professionals would improve equality and access to quality care for individuals with psychiatric disorders within Europe

Characterisation of age and polarity at onset in bipolar disorder

Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.publishedVersio

Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

BackgroundBipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder