Why Optimal States Recruit Fewer Reactions in Metabolic Networks

The metabolic network of a living cell involves several hundreds or thousands of interconnected biochemical reactions. Previous research has shown that under realistic conditions only a fraction of these reactions is concurrently active in any given cell. This is partially determined by nutrient availability, but is also strongly dependent on the metabolic function and network structure. Here, we establish rigorous bounds showing that the fraction of active reactions is smaller (rather than larger) in metabolic networks evolved or engineered to optimize a specific metabolic task, and we show that this is largely determined by the presence of thermodynamically irreversible reactions in the network. We also show that the inactivation of a certain number of reactions determined by irreversibility can generate a cascade of secondary reaction inactivations that propagates through the network. The mathematical results are complemented with numerical simulations of the metabolic networks of the bacterium Escherichia coli and of human cells, which show, counterintuitively, that even the maximization of the total reaction flux in the network leads to a reduced number of active reactions.Comment: Contribution to the special issue in honor of John Guckenheimer on the occasion of his 65th birthda

Rapid evolution of protein kinase PKR alters sensitivity to viral inhibitors.

Protein kinase PKR (also known as EIF2AK2) is activated during viral infection and phosphorylates the alpha subunit of eukaryotic translation initiation factor 2 (eIF2), leading to inhibition of translation and viral replication. We report fast evolution of the PKR kinase domain in vertebrates, coupled with positive selection of specific sites. Substitution of positively selected residues in human PKR with residues found in related species altered sensitivity to PKR inhibitors from different poxviruses. Species-specific differences in sensitivity to poxviral pseudosubstrate inhibitors were identified between human and mouse PKR, and these differences were traced to positively selected residues near the eIF2alpha binding site. Our findings indicate how an antiviral protein evolved to evade viral inhibition while maintaining its primary function. Moreover, the identified species-specific differences in the susceptibility to viral inhibitors have important implications for studying human infections in nonhuman model systems

Quantitative Kinetic Energy Estimated from Disdrometer Signal

The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas-Brazil. The equation in the form of exponential form suppressed the effects of large drops at low rainfall intensity observed at the beginning and end of the rainfall. The kinetic energy of the raindrop was underestimated in almost rain intensity ranges and was considered acceptable by the performance indicators such as coefficient of determination, average absolute error, percent relative error, mean absolute error, root mean square error, Willmott's concordance index and confidence index

Isoscalar meson spectroscopy from lattice QCD

We extract to high statistical precision an excited spectrum of single-particle isoscalar mesons using lattice QCD, including states of high spin and, for the first time, light exotic JPC isoscalars. The use of a novel quark field construction has enabled us to overcome the long-standing challenge of efficiently including quark-annihilation contributions. Hidden-flavor mixing angles are extracted and while most states are found to be close to ideally flavor mixed, there are examples of large mixing in the pseudoscalar and axial sectors in line with experiment. The exotic JPC isoscalar states appear at a mass scale comparable to the exotic isovector states.Comment: 4 pages, 4 figure

Exploring the Structure of Library and Information Science Web Space Based on Multivariate Analysis of Social Tags

Introduction. This study examines the structure of Web space in the field of library and information science using multivariate analysis of social tags from the Website, Delicious.com. A few studies have examined mathematical modelling of tags, mainly examining tagging in terms of tri-partite graphs, pattern tracing and descriptive statistics. This study is one of the few studies to employ multivariate analysis in investigating dimensions of Web spaces based on social tagging data. Method. This study examines the post data collected from a set of library and information science related Websites bookmarked on Delicious.com using a Web crawler. Post data consist of the URL, usernames, tags and comments assigned by users of Delicious.com. The collected tag data were analysed based on multivariate methods, such as multidimensional scaling and structural equation modelling. Analysis. Collected data were first analysed using multidimensional scaling to explore initial relationships amongst the selected Websites. Then, confirmatory factor analysis based on structural equation modelling was employed to examine the hierarchical structure of the library & information science Web space. Results. Social tag data exhibit different dimensions in the Web space of the library and information science field. In addition, social tags confirmed the hierarchical structure of the field by showing significantly stronger relationships between the sites with similar characteristics. That is, the structure of the tagging data shows similar connections to those present in the real world. Conclusions. This study suggests a new statistical approach in social tagging and Web space analysis studies. Tag information can be used to explain the hierarchical structure of a certain domain. Methodologically, this study suggests that structural equation modelling can be a compelling method to explore hierarchal structures of nodes on the Web space

STATISTICAL ANALYSIS SOFTWARE FOR MULTIPLICATIVE INTERACTION MODELS

In a two-way cross-classified experiment, one is almost always interested in whether the two factors interact or not. When there are no independent replications, there are no traditional tests for interaction. This research considers the problem of analyzing a two-way cross-classified experiment using multiplicative interaction models when there are no independent replications and interaction between the two factors may exist. The purpose of this research is to develop SAS® macros to provide user-friendly statistical software for the analysis of interaction in two-way experiments. The macros also provide many useful graphical displays including displays to help one determine the pattern of interaction when a pattern exists and to help one interpret the results of the analyses

Neutrino masses and mixing from S4 flavor twisting

We discuss a neutrino mass model based on the S4 discrete symmetry where the symmetry breaking is triggered by the boundary conditions of the bulk right-handed neutrino in the fifth spacial dimension. While the symmetry restricts bare mass parameters to flavor-diagonal forms, the viable mixing angles emerge from the wave functions of the Kaluza-Klein modes which carry symmetry breaking effect. The magnitudes of the lepton mixing angles, especially the reactor angle is related to the neutrino mass patterns and the model will be tested in future neutrino experiments, e.g., an early (late) discovery of the reactor angle favors the normal (inverted) hierarchy. The size of extra dimension has a connection to the possible mass spectrum; a small (large) volume corresponds to the normal (inverted) mass hierarchy.Comment: 22 pages, 3 figures; added references for section