S.cerevisiae Complex Function Prediction with Modular Multi-Relational Framework

Proceeding of: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Córdoba, Spain, June 1-4, 2010Determining the functions of genes is essential for understanding how the metabolisms work, and for trying to solve their malfunctions. Genes usually work in groups rather than isolated, so functions should be assigned to gene groups and not to individual genes. Moreover, the genetic knowledge has many relations and is very frequently changeable. Thus, a propositional ad-hoc approach is not appropriate to deal with the gene group function prediction domain. We propose the Modular Multi-Relational Framework (MMRF), which faces the problem from a relational and flexible point of view. The MMRF consists of several modules covering all involved domain tasks (grouping, representing and learning using computational prediction techniques). A specific application is described, including a relational representation language, where each module of MMRF is individually instantiated and refined for obtaining a prediction under specific given conditions.This research work has been supported by CICYT, TRA 2007-67374-C02-02 project and by the expert biological knowledge of the Structural Computational Biology Group in Spanish National Cancer Research Centre (CNIO). The authors would like to thank members of Tilde tool developer group in K.U.Leuven for providing their help and many useful suggestions.Publicad

Regulation of body weight and energy homeostasis by neuronal cell adhesion molecule 1

Susceptibility to obesity is linked to genes regulating neurotransmission, pancreatic beta-cell function and energy homeostasis. Genome-wide association studies have identified associations between body mass index and two loci near cell adhesion molecule 1 (CADM1) and cell adhesion molecule 2 (CADM2), which encode membrane proteins that mediate synaptic assembly. We found that these respective risk variants associate with increased CADM1 and CADM2 expression in the hypothalamus of human subjects. Expression of both genes was elevated in obese mice, and induction of Cadm1 in excitatory neurons facilitated weight gain while exacerbating energy expenditure. Loss of Cadm1 protected mice from obesity, and tract-tracing analysis revealed Cadm1-positive innervation of POMC neurons via afferent projections originating from beyond the arcuate nucleus. Reducing Cadm1 expression in the hypothalamus and hippocampus promoted a negative energy balance and weight loss. These data identify essential roles for Cadm1-mediated neuronal input in weight regulation and provide insight into the central pathways contributing to human obesity.</p

Infected erythrocyte-derived extracellular vesicles alter vascular function via regulatory Ago2-miRNA complexes in malaria

Malaria remains one of the greatest public health challenges worldwide, particularly in sub-Saharan Africa. The clinical outcome of individuals infected with Plasmodium falciparum parasites depends on many factors including host systemic inflammatory responses, parasite sequestration in tissues and vascular dysfunction. Production of pro-inflammatory cytokines and chemokines promotes endothelial activation as well as recruitment and infiltration of inflammatory cells, which in turn triggers further endothelial cell activation and parasite sequestration. Inflammatory responses are triggered in part by bioactive parasite products such as hemozoin and infected red blood cell-derived extracellular vesicles (iRBC-derived EVs). Here we demonstrate that such EVs contain functional miRNA-Argonaute 2 complexes that are derived from the host RBC. Moreover, we show that EVs are efficiently internalized by endothelial cells, where the miRNA-Argonaute 2 complexes modulate target gene expression and barrier properties. Altogether, these findings provide a mechanistic link between EVs and vascular dysfunction during malaria infection

Circulating microRNAs as novel biomarkers for diabetes mellitus.

Diabetes mellitus is characterized by insulin secretion from pancreatic β cells that is insufficient to maintain blood glucose homeostasis. Autoimmune destruction of β cells results in type 1 diabetes mellitus, whereas conditions that reduce insulin sensitivity and negatively affect β-cell activities result in type 2 diabetes mellitus. Without proper management, patients with diabetes mellitus develop serious complications that reduce their quality of life and life expectancy. Biomarkers for early detection of the disease and identification of individuals at risk of developing complications would greatly improve the care of these patients. Small non-coding RNAs called microRNAs (miRNAs) control gene expression and participate in many physiopathological processes. Hundreds of miRNAs are actively or passively released in the circulation and can be used to evaluate health status and disease progression. Both type 1 diabetes mellitus and type 2 diabetes mellitus are associated with distinct modifications in the profile of miRNAs in the blood, which are sometimes detectable several years before the disease manifests. Moreover, circulating levels of certain miRNAs seem to be predictive of long-term complications. Technical and scientific obstacles still exist that need to be overcome, but circulating miRNAs might soon become part of the diagnostic arsenal to identify individuals at risk of developing diabetes mellitus and its devastating complications

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning