Enabling Workflows in GridSolve: Request Sequencing and Service Trading

International audienceGridSolve employs a RPC-based client-agent-server model for solving computational problems. There are two deficiencies associated with GridSolve when a computational problem essentially forms a workflow consisting of a sequence of tasks with data dependencies between them. First, intermediate results are always passed through the client, resulting in unnecessary data transport. Second, since the execution of each individual task is a separate RPC session, it is difficult to enable any potential parallelism among tasks. This paper presents a request sequencing technique that addresses these deficiencies and enables workflow executions. Building on the request sequencing work, one way to generate workflows is by taking higher level service requests and decomposing them into a sequence of simpler service requests using a technique called service trading. A service trading component is added to GridSolve to take advantage of the new dynamic request sequencing. The features described here include automatic DAG construction and data dependency analysis, direct interserver data transfer, parallel task execution capabilities, and a service trading component

Why place matters in residential care: the mediating role of place attachment in the relation between adolescents’ rights and psychological well-being

Little evidence exists on the relationship between rights’ perceptions and well-being outcomes during the adolescence, and particularly in care, as well as on the mediating role of place attachment. Young people in residential care are psychologically and socially vulnerable, showing greater difficulties than their peers do in the family. Youth’s rights fulfilment in residential care may positively affect their psychological functioning together with positive attachments to this place. A sample of 365 adolescents in residential care settings (M = 14.71, SD = 1.81) completed a set of self-reported measures, specifically, the Rights perceptions scale, the Place attachment scale and Scales of psychological well-being. Results revealed significant mediating effects of place attachment (Global scale and subscales of Friends Bonding and Place Dependence) on the relationship between Participation and Protection rights in residential care and Psychological well-being (Positive Relations with others, Personal Growth and Self-Acceptance). The positive role of rights fulfilment in residential care, specifically participation opportunities, as well as the role of youth’s attachment to the care setting are discussed based on previous evidence and theoretical assumptions. A set of practical implications is described.info:eu-repo/semantics/acceptedVersio

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data

We introduce a wide and deep neural network for prediction of progression from patients with mild cognitive impairment to Alzheimer's disease. Information from anatomical shape and tabular clinical data (demographics, biomarkers) are fused in a single neural network. The network is invariant to shape transformations and avoids the need to identify point correspondences between shapes. To account for right censored time-to-event data, i.e., when it is only known that a patient did not develop Alzheimer's disease up to a particular time point, we employ a loss commonly used in survival analysis. Our network is trained end-to-end to combine information from a patient's hippocampus shape and clinical biomarkers. Our experiments on data from the Alzheimer's Disease Neuroimaging Initiative demonstrate that our proposed model is able to learn a shape descriptor that augments clinical biomarkers and outperforms a deep neural network on shape alone and a linear model on common clinical biomarkers.Comment: Data and Machine Learning Advances with Multiple Views Workshop, ECML-PKDD 201

Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias

Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and 18F-fluorodeoxyglucose (18F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and 18F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies

Two-Stage Clustering (TSC): A Pipeline for Selecting Operational Taxonomic Units for the High-Throughput Sequencing of PCR Amplicons

Clustering 16S/18S rRNA amplicon sequences into operational taxonomic units (OTUs) is a critical step for the bioinformatic analysis of microbial diversity. Here, we report a pipeline for selecting OTUs with a relatively low computational demand and a high degree of accuracy. This pipeline is referred to as two-stage clustering (TSC) because it divides tags into two groups according to their abundance and clusters them sequentially. The more abundant group is clustered using a hierarchical algorithm similar to that in ESPRIT, which has a high degree of accuracy but is computationally costly for large datasets. The rarer group, which includes the majority of tags, is then heuristically clustered to improve efficiency. To further improve the computational efficiency and accuracy, two preclustering steps are implemented. To maintain clustering accuracy, all tags are grouped into an OTU depending on their pairwise Needleman-Wunsch distance. This method not only improved the computational efficiency but also mitigated the spurious OTU estimation from ‘noise’ sequences. In addition, OTUs clustered using TSC showed comparable or improved performance in beta-diversity comparisons compared to existing OTU selection methods. This study suggests that the distribution of sequencing datasets is a useful property for improving the computational efficiency and increasing the clustering accuracy of the high-throughput sequencing of PCR amplicons. The software and user guide are freely available at http://hwzhoulab.smu.edu.cn/paperdata/

Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease

With the exception of APOE ε4 allele, the common genetic risk factors for sporadic Alzheimer's Disease (AD) are unknown., which can be considered potential “new” candidate loci to explore in the etiology of sporadic AD. These candidates included EFNA5, CAND1, MAGI2, ARSB, and PRUNE2, genes involved in the regulation of protein degradation, apoptosis, neuronal loss and neurodevelopment. Thus, we identified common genetic variants associated with the increased risk of developing AD in the ADNI cohort, and present publicly available genome-wide data. Supportive evidence based on case-control studies and biological plausibility by gene annotation is provided. Currently no available sample with both imaging and genetic data is available for replication.Using hippocampal atrophy as a quantitative phenotype in a genome-wide scan, we have identified candidate risk genes for sporadic Alzheimer's disease that merit further investigation

CSF tau is associated with impaired cortical plasticity, cognitive decline and astrocyte survival only in APOE4-positive Alzheimer's disease

In Alzheimer's disease (AD) patients, apopoliprotein (APOE) polymorphism is the main genetic factor associated with more aggressive clinical course. However, the interaction between cerebrospinal fluid (CSF) tau protein levels and APOE genotype has been scarcely investigated. A possible key mechanism invokes the dysfunction of synaptic plasticity. We investigated how CSF tau interacts with APOE genotype in AD patients. We firstly explored whether CSF tau levels and APOE genotype influence disease progression and long-term potentiation (LTP)-like cortical plasticity as measured by transcranial magnetic stimulation (TMS) in AD patients. Then, we incubated normal human astrocytes (NHAs) with CSF collected from sub-groups of AD patients to determine whether APOE genotype and CSF biomarkers influence astrocytes survival. LTP-like cortical plasticity differed between AD patients with apolipoprotein E4 (APOE4) and apolipoprotein E3 (APOE3) genotype. Higher CSF tau levels were associated with more impaired LTP-like cortical plasticity and faster disease progression in AD patients with APOE4 but not APOE3 genotype. Apoptotic activity was higher when cells were incubated with CSF from AD patients with APOE4 and high tau levels. CSF tau is detrimental on cortical plasticity, disease progression and astrocyte survival only when associated with APOE4 genotype. This is relevant for new therapeutic approaches targeting tau

Microbial Diversity of a Brazilian Coastal Region Influenced by an Upwelling System and Anthropogenic Activity

BACKGROUND: Upwelling systems are characterised by an intense primary biomass production in the surface (warmest) water after the outcrop of the bottom (coldest) water, which is rich in nutrients. Although it is known that the microbial assemblage plays an important role in the food chain of marine systems and that the upwelling systems that occur in southwest Brazil drive the complex dynamics of the food chain, little is known about the microbial composition present in this region. METHODOLOGY/PRINCIPAL FINDINGS: We carried out a molecular survey based on SSU rRNA gene from the three domains of the phylogenetic tree of life present in a tropical upwelling region (Arraial do Cabo, Rio de Janeiro, Brazil). The aim was to analyse the horizontal and vertical variations of the microbial composition in two geographically close areas influenced by anthropogenic activity (sewage disposal/port activity) and upwelling phenomena, respectively. A lower estimated diversity of microorganisms of the three domains of the phylogenetic tree of life was found in the water of the area influenced by anthropogenic activity compared to the area influenced by upwelling phenomena. We observed a heterogenic distribution of the relative abundance of taxonomic groups, especially in the Archaea and Eukarya domains. The bacterial community was dominated by Proteobacteria, Cyanobacteria and Bacteroidetes phyla, whereas the microeukaryotic community was dominated by Metazoa, Fungi, Alveolata and Stramenopile. The estimated archaeal diversity was the lowest of the three domains and was dominated by uncharacterised marine Crenarchaeota that were most closely related to Marine Group I. CONCLUSIONS/SIGNIFICANCE: The variety of conditions and the presence of different microbial assemblages indicated that the area of Arraial do Cabo can be used as a model for detailed studies that contemplate the correlation between pollution-indicating parameters and the depletion of microbial diversity in areas close to anthropogenic activity; functional roles and geochemical processes; phylogeny of the uncharacterised diversity; and seasonal variations of the microbial assemblages