Short perturbations of cosmic ray intensity and electric field in atmosphere

Short perturbations of cosmic ray intensity were found to be a common phenomenon. Its meteorological origin and correlation with electric field is established. The phenomenon can be explained by the electric field if the strength of this field at high altitudes is much bigger than the measured one at surface

Network enrichment analysis: extension of gene-set enrichment analysis to gene networks

<p>Abstract</p> <p>Background</p> <p>Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis.</p> <p>Results</p> <p>We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study.</p> <p>Conclusions</p> <p>The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.</p

Quantification in event semantics: Generalized quantifiers vs. sub-events

The goal of this paper is to evaluate two approaches to quantification in event semantics, namely the analysis of quantificational DPs in terms of generalized quantifiers and the analysis proposed in Schein (1993) according to which quantifiers over individuals contain an existential quantifier over sub-events in their scope. Both analyses capture the fact that the event quantifier always takes scope under quantifiers over individuals (the Event Type Principle in Landman (2000)), but the sub-events analysis has also been argued to be able to account for some further data, namely for adverbs qualifying ‘ensemble’ events and for mixed cumulative/distributive readings. This paper shows that the sub-events analysis also provides a better account of the Event Type Principle if a broader range of data is considered, including cases with non-existential quantifiers over events: unlike the generalized quantifiers analysis, it can successfully account for the interpretation of indefinites in bare habituals and sentences that contain overt adverbs of quantification

RhoA knockout fibroblasts lose tumor-inhibitory capacity in vitro and promote tumor growth in vivo

Fibroblasts are a main player in the tumor-inhibitory microenvironment. Upon tumor initiation and progression, fibroblasts can lose their tumor-inhibitory capacity and promote tumor growth. The molecular mechanisms that underlie this switch have not been defined completely. Previously, we identified four proteins over-expressed in cancer-associated fibroblasts and linked to Rho GTPase signaling. Here, we show that knocking out the Ras homolog family member A (RhoA) gene in normal fibroblasts decreased their tumor-inhibitory capacity, as judged by neighbor suppression in vitro and accompanied by promotion of tumor growth in vivo. This also induced PC3 cancer cell motility and increased colony size in 2D cultures. RhoA knockout in fibroblasts induced vimentin intermediate filament reorganization, accompanied by reduced contractile force and increased stiffness of cells. There was also loss of wide F-actin stress fibers and large focal adhesions. In addition, we observed a significant loss of a-smooth muscle actin, which indicates a difference between RhoA knockout fibroblasts and classic cancer-associated fibroblasts. In 3D collagen matrix, RhoA knockout reduced fibroblast branching and meshwork formation and resulted in more compactly clustered tumor-cell colonies in coculture with PC3 cells, which might boost tumor stem-like properties. Coculturing RhoA knockout fibroblasts and PC3 cells induced expression of proinflammatory genes in both. Inflammatory mediators may induce tumor cell stemness. Network enrichment analysis of transcriptomic changes, however, revealed that the Rho signaling pathway per se was significantly triggered only after coculturing with tumor cells. Taken together, our findings in vivo and in vitro indicate that Rho signaling governs the inhibitory effects by fibroblasts on tumor-cell growth.Peer reviewe

Using Erlang in Research and Education in a Technical University

This paper addresses the problem of using functional programming (FP) languages for research and education purposes. In order to identify problems associated with usage of FP languages, such as Erlang, an experiment consisting of two surveys was performed. The rst survey was anonymous, and aimed at establishing whether the participants prefer object-oriented or functional coding. The second one was a survey after students have nished an Erlang course. The results of these two surveys demonstrate that functional programming is underrated without apparent reasons. Possible steps to address this problem are suggested

Calcyon mRNA expression in the frontal-striatal circuitry and its relationship to vesicular processes and ADHD

<p>Abstract</p> <p>Background</p> <p>Calcyon is a single transmembrane protein predominantly expressed in the brain. Very recently, calcyon has been implicated in clathrin mediated endocytosis, a critical component of synaptic plasticity. At the genetic level, preliminary evidence supports an association between attention-deficit/hyperactivity disorder (ADHD) and polymorphisms in the calcyon gene. As little is known about the potential role of calcyon in ADHD, animal models may provide important insights into this issue.</p> <p>Methods</p> <p>We examined calcyon mRNA expression in the frontal-striatal circuitry of three-, five-, and ten-week-old Spontaneously Hypertensive Rats (SHR), the most commonly used animal model of ADHD, and Wistar-Kyoto (WKY; the strain from which SHR were derived). As a complement, we performed a co-expression network analysis using a database of mRNA gene expression profiles of multiple brain regions in order to explore potential functional links of calcyon to other genes.</p> <p>Results</p> <p>In all age groups, SHR expressed significantly more calcyon mRNA in the medial prefrontal and orbital frontal cortices than WKY rats. In contrast, in the motor cortex, dorsal striatum and nucleus accumbens, calcyon mRNA expression was only significantly elevated in SHR in younger animals. In both strains, calcyon mRNA levels decreased significantly with age in all regions studied. In the co-expression network analysis, we found a cluster of genes (many of them poorly studied so far) strongly connected to calcyon, which may help elucidate its role in the brain. The pair-wise relations of calcyon with other genes support its involvement in clathrin mediated endocytosis and, potentially, some other membrane/vesicular processes. Interestingly, no link was found between calcyon and the dopamine D1 receptor, which was previously shown to interact with the C-terminal of calcyon.</p> <p>Conclusion</p> <p>The results indicate an alteration in calcyon expression within the frontal-striatal circuitry of SHR, especially in areas involved in cognitive processes. These findings extend our understanding of the molecular alterations in SHR, a heuristically useful model of ADHD.</p

NEAT: An efficient network enrichment analysis test

Background: Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. Results: We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. Conclusions: NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat )

The Pathway Coexpression Network: Revealing pathway relationships.

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer's Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/

Transcriptomes and expression profiling of deep-sea corals from the Red Sea provide insight into the biology of azooxanthellate corals

Despite the importance of deep-sea corals, our current understanding of their ecology and evolutionis limited due to difficulties in sampling and studying deep-sea environments. Moreover, a recent reevaluation of habitat limitations has been suggested after characterization of deep-sea corals in the Red Sea, where they live at temperatures of above 20 °C at low oxygen concentrations. To gain further insight into the biology of deep-sea corals, we produced reference transcriptomes and studied gene expression of three deep-sea coral species from the Red Sea, i.e. Dendrophyllia sp., Eguchipsammia fistula, and Rhizotrochus typus. Our analyses suggest that deep-sea coral employ mitochondrial hypometabolism and anaerobic glycolysis to manage low oxygen conditions present in the Red Sea. Notably, we found expression of genes related to surface cilia motion that presumably enhance small particle transport rates in the oligotrophic deep-sea environment. This is the first study to characterize transcriptomes and in situ gene expression for deep-sea corals. Our work offers several mechanisms by which deep-sea corals might cope with the distinct environmental conditions present in the Red Sea. As such, our data provides direction for future research and further insight to organismal response of deep sea coral to environmental change and ocean warming.Tis work was supported by King Abdullah University of Science and Technology (KAUST), baseline funds to CRV and Center Competitive Funding (CCF) Program FCC/1/1973-18-01