Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Ionotropic Receptors as a Driving Force behind Human Synapse Establishment

The origin of nervous systems is a main theme in biology and its mechanisms are largely underlied by synaptic neurotransmission. One problem to explain synapse establishment is that synaptic orthologs are present in multiple aneural organisms. We questioned how the interactions among these elements evolved and to what extent it relates to our understanding of the nervous systems complexity. We identified the human neurotransmission gene network based on genes present in GABAergic, glutamatergic, serotonergic, dopaminergic, and cholinergic systems. The network comprises 321 human genes, 83 of which act exclusively in the nervous system. We reconstructed the evolutionary scenario of synapse emergence by looking for synaptic orthologs in 476 eukaryotes. The Human–Cnidaria common ancestor displayed a massive emergence of neuroexclusive genes, mainly ionotropic receptors, which might have been crucial to the evolution of synapses. Very few synaptic genes had their origin after the Human–Cnidaria common ancestor. We also identified a higher abundance of synaptic proteins in vertebrates, which suggests an increase in the synaptic network complexity of those organisms.     

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.     

Characterization of polymorphic microsatellite markers for the Carnaby's cockatoo (Calyptorhynchus latirostris) and related black cockatoo species

Microsatellite loci were isolated from Carnaby's black cockatoo (Calyptorhynchus latirostris: Aves), a highly valued, endangered, and endemic species of bird from Western Australia. This study describes three dinucleotide and one tetranucleotide microsatellite loci for which the primers produced clear and polymorphic amplification patterns with between two and nine alleles and moderate levels of variability. Two additional dinucleotide markers which were monomorphic in the Carnaby's cockatoo were able to amplify and were polymorphic in two other species of black cockatoo, greatly increasing the utility of these markers.     

On the Stability of Clathrate Hydrates Encaging Polar Guest Molecules: Contrast in the Hydrogen Bonds of Methylamine and Methanol Hydrates

Abstract

The stability of clathrate hydrates encaging highly polar guests has been investigated in order to explain the experimental observation that some amines form clathrate hydrates but alcohols act as inhibitor to hydrate formation. We choose methylamine and methanol as guest species and examine the stable structure, at which the total potential energy has a minimum value. At the local minima of those two hydrates, the potential energies of water-water and guest-water, and their hydrogen bonded networks are compared. It is found that methanol does not retain the host lattice structure, while the host-network structure is kept in the presence of methylamine. It is shown that the difference in the magnitude of the partial charge on the hydrogen atom between the hydroxyl and amino groups plays a much more significant role on the stability of both clathrate hydrates than the difference in molecular geometry. This is supported from the result of a methylamine-like model that has the same partial charges on the atoms in the hydrophilic site as methanol.     

Characterization of tetranucleotide microsatellite loci and development and validation of multiplex reactions for the study of right whale species (genus Eubalaena)

A North Atlantic right whale (Eubalaena glacialis) genomic library was developed and screened with a (GATA)₈ probe to identify tetranucleotide microsatellite loci. Sixteen characterized loci were polymorphic in North Atlantic and/or South Atlantic (Eubalaena australis) right whales, 12 being polymorphic in E. glacialis, and 15 in E. australis. Fourteen of these were combined with 21 other previously identified loci for a suite of 35 loci which can be used to increase resolution of genetic analyses of these species. Multiplex reactions were developed for genotyping samples at these loci, providing a method that is rapid, reliable and cost‐effective.     

Adaptive Neural Network-Based ECG Data Compression According to the Morphology

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Constructing more informative plant–pollinator networks: visitation and pollen deposition networks in a heathland plant community

Interaction networks are widely used as tools to understand plant–pollinator communities, and to examine potential threats to plant diversity and food security if the ecosystem service provided by pollinating animals declines. However, most networks to date are based on recording visits to flowers, rather than recording clearly defined effective pollination events. Here we provide the first networks that explicitly incorporate measures of pollinator effectiveness (PE) from pollen deposition on stigmas per visit, and pollinator importance (PI) as the product of PE and visit frequency. These more informative networks, here produced for a low diversity heathland habitat, reveal that plant–pollinator interactions are more specialized than shown in most previous studies. At the studied site, the specialization index was lower for the visitation network than the PE network, which was in turn lower than for the PI network. Our study shows that collecting PE data is feasible for community-level studies in low diversity communities and that including information about PE can change the structure of interaction networks. This could have important consequences for our understanding of threats to pollination systems.