Andromonoecy and fruit set in three genera of the Proteaceae

It has been suggested by some authors that the low fruit to flower ratio in some Proteaceae is due to andromonoecy, while others, looking particularly at Banksia , have not been able to find evidence for male flowers in the inflorescences. Stirlingia latifolia, Xylomelum occidentals and X. angustifolium are clearly andromonoecous, while no evidence for this condition could be found in Brabejum stellatifoliutn. Production of fertile fruit is related to andromonoecy in Xylomelum and S. latifolia but not in Brabejum. It is unlikely that all-encompassing solutions will be found to what initially seem to be widespread traits in the family, especially in regard to pollination biology, as the genera in the family occupy widely different environments and have very diverse ecological ranges.     

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.     

Emerging infectious diseases and animal social systems

Emerging infectious diseases threaten a wide diversity of animals, and important questions remain concerning disease emergence in socially structured populations. We developed a spatially explicit simulation model to investigate whether—and under what conditions—disease-related mortality can impact rates of pathogen spread in populations of polygynous groups. Specifically, we investigated whether pathogen-mediated dispersal (PMD) can occur when females disperse after the resident male dies from disease, thus carrying infections to new groups. We also examined the effects of incubation period and virulence, host mortality and rates of background dispersal, and we used the model to investigate the spread of the virus responsible for Ebola hemorrhagic fever, which currently is devastating African ape populations. Output was analyzed using regression trees, which enable exploration of hierarchical and non-linear relationships. Analyses revealed that the incidence of disease in single-male (polygynous) groups was significantly greater for those groups containing an average of more than six females, while the total number of infected hosts in the population was most sensitive to the number of females per group. Thus, as expected, PMD occurs in polygynous groups and its effects increase as harem size (the number of females) increases. Simulation output further indicated that population-level effects of Ebola are likely to differ among multi-male–multi-female chimpanzees and polygynous gorillas, with larger overall numbers of chimpanzees infected, but more gorilla groups becoming infected due to increased dispersal when the resident male dies. Collectively, our results highlight the importance of social system on the spread of disease in wild mammals.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

An Efficient Regression Type Estimator in Survey Sampling

For the estimation of population mean in simple random sampling, an efficient regression-type estimator is proposed which is more efficient than the conventional regression estimator and hence than mean per unit estimator, ratio and product estimators and many other estimators proposed by various authors. Some numerical examples are included for illustration.     

Ants resort to majority concession to reach democratic consensus in the presence of a persistent minority

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Some Common Themes for Enzymes and Verbs

Enzymes are remarkable molecules which make metabolism possible. Their processing powers are considerable for not only are they catalysts they also contribute to information processing, integration, coherence and memory in the cell. This complex of attributes suggests that a complementary perspective to enzyme nature and activity is needed related to what enzymes and verbs have in common. The value of this kind of thinking is that it shifts the focus from objects and mechanisms to processes and information. In order to support this idea a number of features which enzymes and verbs share are discussed including, context-dependence, occurrence, cases, voice, mood and glue/integrative capacities. The paper concludes with some reflections on the utility of a view of enzymes as verbs.